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Petersen M, Hoffstaedter F, Nägele FL, Mayer C, Schell M, Rimmele DL, Zyriax BC, Zeller T, Kühn S, Gallinat J, Fiehler J, Twerenbold R, Omidvarnia A, Patil KR, Eickhoff SB, Thomalla G, Cheng B. A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition. eLife 2024; 12:RP93246. [PMID: 38512127 PMCID: PMC10957178 DOI: 10.7554/elife.93246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2024] Open
Abstract
The link between metabolic syndrome (MetS) and neurodegenerative as well as cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, brain morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis, we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.
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Affiliation(s)
- Marvin Petersen
- Department of Neurology, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Felix Hoffstaedter
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center JülichJülichGermany
| | - Felix L Nägele
- Department of Neurology, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Carola Mayer
- Department of Neurology, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Maximilian Schell
- Department of Neurology, University Medical Center Hamburg-EppendorfHamburgGermany
| | - D Leander Rimmele
- Department of Neurology, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Birgit-Christiane Zyriax
- Midwifery Science-Health Services Research and Prevention, Institute for Health Services Research in Dermatology and Nursing (IVDP), University Medical Center Hamburg-EppendorfHamburgGermany
| | - Tanja Zeller
- Department of Cardiology, University Heart and Vascular CenterHamburgGermany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/LuebeckHamburgGermany
- University Center of Cardiovascular Science, University Heart and Vascular CenterHamburgGermany
| | - Simone Kühn
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Jürgen Gallinat
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Raphael Twerenbold
- Department of Cardiology, University Heart and Vascular CenterHamburgGermany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/LuebeckHamburgGermany
- University Center of Cardiovascular Science, University Heart and Vascular CenterHamburgGermany
- Epidemiological Study Center, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Amir Omidvarnia
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center JülichJülichGermany
| | - Kaustubh R Patil
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center JülichJülichGermany
| | - Simon B Eickhoff
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center JülichJülichGermany
| | - Goetz Thomalla
- Department of Neurology, University Medical Center Hamburg-EppendorfHamburgGermany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-EppendorfHamburgGermany
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Zhou ZX, Zuo XN. Population imaging cerebellar growth for personalized neuroscience. Nat Commun 2024; 15:2352. [PMID: 38499559 PMCID: PMC10948383 DOI: 10.1038/s41467-024-46545-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 02/22/2024] [Indexed: 03/20/2024] Open
Affiliation(s)
- Zi-Xuan Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, 100875, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, 100875, Beijing, China
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, 100875, Beijing, China.
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, No 19 Xinjiekouwai Street, Haidian District, 100875, Beijing, China.
- National Basic Science Data Center, No 04 Zhongguancun South 4th Street, Haidian District, 100190, Beijing, China.
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Chen P, Yang H, Zheng X, Jia H, Hao J, Xu X, Li C, He X, Chen R, Okubo TS, Cui Z. Group-common and individual-specific effects of structure-function coupling in human brain networks with graph neural networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.22.568257. [PMID: 38045396 PMCID: PMC10690242 DOI: 10.1101/2023.11.22.568257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
The human cerebral cortex is organized into functionally segregated but synchronized regions bridged by the structural connectivity of white matter pathways. While structure-function coupling has been implicated in cognitive development and neuropsychiatric disorders, studies yield inconsistent findings. The extent to which the structure-function coupling reflects reliable individual differences or primarily group-common characteristics remains unclear, at both the global and regional brain levels. By leveraging two independent, high-quality datasets, we found that the graph neural network accurately predicted unseen individuals' functional connectivity from structural connectivity, reflecting a strong structure-function coupling. This coupling was primarily driven by network topology and was substantially stronger than that of the linear models. Moreover, we observed that structure-function coupling was dominated by group-common effects, with subtle yet significant individual-specific effects. The regional group and individual effects of coupling were hierarchically organized across the cortex along a sensorimotor-association axis, with lower group and higher individual effects in association cortices. These findings emphasize the importance of considering both group and individual effects in understanding cortical structure-function coupling, suggesting insights into interpreting individual differences of the coupling and informing connectivity-guided therapeutics.
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54
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Xia J, Liu C, Li J, Meng Y, Yang S, Chen H, Liao W. Decomposing cortical activity through neuronal tracing connectome-eigenmodes in marmosets. Nat Commun 2024; 15:2289. [PMID: 38480767 PMCID: PMC10937940 DOI: 10.1038/s41467-024-46651-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 03/06/2024] [Indexed: 03/17/2024] Open
Abstract
Deciphering the complex relationship between neuroanatomical connections and functional activity in primate brains remains a daunting task, especially regarding the influence of monosynaptic connectivity on cortical activity. Here, we investigate the anatomical-functional relationship and decompose the neuronal-tracing connectome of marmoset brains into a series of eigenmodes using graph signal processing. These cellular connectome eigenmodes effectively constrain the cortical activity derived from resting-state functional MRI, and uncover a patterned cellular-functional decoupling. This pattern reveals a spatial gradient from coupled dorsal-posterior to decoupled ventral-anterior cortices, and recapitulates micro-structural profiles and macro-scale hierarchical cortical organization. Notably, these marmoset-derived eigenmodes may facilitate the inference of spontaneous cortical activity and functional connectivity of homologous areas in humans, highlighting the potential generalizing of the connectomic constraints across species. Collectively, our findings illuminate how neuronal-tracing connectome eigenmodes constrain cortical activity and improve our understanding of the brain's anatomical-functional relationship.
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Affiliation(s)
- Jie Xia
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
| | - Cirong Liu
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, P.R. China
| | - Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
| | - Yao Meng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China
| | - Siqi Yang
- School of Cybersecurity, Chengdu University of Information Technology, Chengdu, 610225, P.R. China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, P.R. China.
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Luppi AI, Uhrig L, Tasserie J, Signorelli CM, Stamatakis EA, Destexhe A, Jarraya B, Cofre R. Local orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain. Nat Commun 2024; 15:2171. [PMID: 38462641 PMCID: PMC10925605 DOI: 10.1038/s41467-024-46382-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 02/26/2024] [Indexed: 03/12/2024] Open
Abstract
A central challenge of neuroscience is to elucidate how brain function supports consciousness. Here, we combine the specificity of focal deep brain stimulation with fMRI coverage of the entire cortex, in awake and anaesthetised non-human primates. During propofol, sevoflurane, or ketamine anaesthesia, and subsequent restoration of responsiveness by electrical stimulation of the central thalamus, we investigate how loss of consciousness impacts distributed patterns of structure-function organisation across scales. We report that distributed brain activity under anaesthesia is increasingly constrained by brain structure across scales, coinciding with anaesthetic-induced collapse of multiple dimensions of hierarchical cortical organisation. These distributed signatures are observed across different anaesthetics, and they are reversed by electrical stimulation of the central thalamus, coinciding with recovery of behavioural markers of arousal. No such effects were observed upon stimulating the ventral lateral thalamus, demonstrating specificity. Overall, we identify consistent distributed signatures of consciousness that are orchestrated by specific thalamic nuclei.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
| | - Lynn Uhrig
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191, Gif-sur-Yvette, France
- Department of Anesthesiology and Critical Care, Necker Hospital, AP-HP, Université de Paris Cité, Paris, France
| | - Jordy Tasserie
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191, Gif-sur-Yvette, France
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Camilo M Signorelli
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191, Gif-sur-Yvette, France
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, 1070, Brussels, Belgium
- Department of Computer Science, University of Oxford, Oxford, 7 Parks Rd, Oxford, OX1 3QG, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Alain Destexhe
- Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France
| | - Bechir Jarraya
- Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191, Gif-sur-Yvette, France
- Department of Neurology, Hopital Foch, 92150, Suresnes, France
| | - Rodrigo Cofre
- Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France.
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56
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Schantell M, Taylor BK, Mansouri A, Arif Y, Coutant AT, Rice DL, Wang YP, Calhoun VD, Stephen JM, Wilson TW. Theta oscillatory dynamics serving cognitive control index psychosocial distress in youth. Neurobiol Stress 2024; 29:100599. [PMID: 38213830 PMCID: PMC10776433 DOI: 10.1016/j.ynstr.2023.100599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/09/2023] [Accepted: 12/10/2023] [Indexed: 01/13/2024] Open
Abstract
Background Psychosocial distress among youth is a major public health issue characterized by disruptions in cognitive control processing. Using the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, we quantified multidimensional neural oscillatory markers of psychosocial distress serving cognitive control in youth. Methods The sample consisted of 39 peri-adolescent participants who completed the NIH Toolbox Emotion Battery (NIHTB-EB) and the Eriksen flanker task during magnetoencephalography (MEG). A psychosocial distress index was computed with exploratory factor analysis using assessments from the NIHTB-EB. MEG data were analyzed in the time-frequency domain and peak voxels from oscillatory maps depicting the neural cognitive interference effect were extracted for voxel time series analyses to identify spontaneous and oscillatory aberrations in dynamics serving cognitive control as a function of psychosocial distress. Further, we quantified the relationship between psychosocial distress and dynamic functional connectivity between regions supporting cognitive control. Results The continuous psychosocial distress index was strongly associated with validated measures of pediatric psychopathology. Theta-band neural cognitive interference was identified in the left dorsolateral prefrontal cortex (dlPFC) and middle cingulate cortex (MCC). Time series analyses of these regions indicated that greater psychosocial distress was associated with elevated spontaneous activity in both the dlPFC and MCC and blunted theta oscillations in the MCC. Finally, we found that stronger phase coherence between the dlPFC and MCC was associated with greater psychosocial distress. Conclusions Greater psychosocial distress was marked by alterations in spontaneous and oscillatory theta activity serving cognitive control, along with hyperconnectivity between the dlPFC and MCC.
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Affiliation(s)
- Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Brittany K. Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Amirsalar Mansouri
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yasra Arif
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Anna T. Coutant
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Danielle L. Rice
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging & Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | | | - Tony W. Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
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Liu J, Guo H, Yang J, Xiao Y, Cai A, Zhao T, Womer FY, Zhao P, Zheng J, Zhang X, Wang J, Zhu R, Wang F. Visual cortex repetitive transcranial magnetic stimulation (rTMS) reversing neurodevelopmental impairments in adolescents with major psychiatric disorders (MPDs): A cross-species translational study. CNS Neurosci Ther 2024; 30:e14427. [PMID: 37721197 PMCID: PMC10915985 DOI: 10.1111/cns.14427] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 07/21/2023] [Accepted: 08/04/2023] [Indexed: 09/19/2023] Open
Abstract
AIMS Neurodevelopmental impairments are closely linked to the basis of adolescent major psychiatric disorders (MPDs). The visual cortex can regulate neuroplasticity throughout the brain during critical periods of neurodevelopment, which may provide a promising target for neuromodulation therapy. This cross-species translational study examined the effects of visual cortex repetitive transcranial magnetic stimulation (rTMS) on neurodevelopmental impairments in MPDs. METHODS Visual cortex rTMS was performed in both adolescent methylazoxymethanol acetate (MAM) rats and patients with MPDs. Functional magnetic resonance imaging (fMRI) and brain tissue proteomic data in rats and fMRI and clinical symptom data in patients were analyzed. RESULTS The regional homogeneity (ReHo) analysis of fMRI data revealed an increase in the frontal cortex and a decrease in the posterior cortex in the MAM rats, representing the abnormal neurodevelopmental pattern in MPDs. In regard to the effects of rTMS, similar neuroimaging changes, particularly reduced frontal ReHo, were found both in MAM rats and adolescent patients, suggesting that rTMS may reverse the abnormal neurodevelopmental pattern. Proteomic analysis revealed that rTMS modulated frontal synapse-associated proteins, which may be the underpinnings of rTMS efficacy. Furthermore, a positive relationship was observed between frontal ReHo and clinical symptoms after rTMS in patients. CONCLUSION Visual cortex rTMS was proven to be an effective treatment for adolescent MPDs, and the underlying neural and molecular mechanisms were uncovered. Our study provides translational evidence for therapeutics targeting the neurodevelopmental factor in MPDs.
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Affiliation(s)
- Juan Liu
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
| | - Huiling Guo
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
- School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjingJiangsuChina
| | - Jingyu Yang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
| | - Yao Xiao
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
| | - Aoling Cai
- School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjingJiangsuChina
- Changzhou Second People's Hospital, Changzhou Medical CenterNanjing Medical UniversityChangzhouJiangsuChina
| | - Tongtong Zhao
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
| | - Fay Y. Womer
- Department of Psychiatry and Behavioral SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Pengfei Zhao
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
| | - Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
| | - Xizhe Zhang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjingJiangsuChina
| | - Jie Wang
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of Sciences‐Wuhan National Laboratory for OptoelectronicsWuhanChina
- University of Chinese Academy of SciencesBeijingChina
| | - Rongxin Zhu
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain HospitalNanjing Medical UniversityNanjingJiangsuChina
- Functional Brain Imaging Institute of Nanjing Medical UniversityNanjingChina
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Norbom LB, Rokicki J, Eilertsen EM, Wiker T, Hanson J, Dahl A, Alnæs D, Fernández‐Cabello S, Beck D, Agartz I, Andreassen OA, Westlye LT, Tamnes CK. Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years. JCPP ADVANCES 2024; 4:e12220. [PMID: 38486948 PMCID: PMC10933599 DOI: 10.1002/jcv2.12220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 12/21/2023] [Indexed: 03/17/2024] Open
Abstract
Background A child's socioeconomic environment can shape central aspects of their life, including vulnerability to mental disorders. Negative environmental influences in youth may interfere with the extensive and dynamic brain development occurring at this time. Indeed, there are numerous yet diverging reports of associations between parental socioeconomic status (SES) and child cortical brain morphometry. Most of these studies have used single metric- or unimodal analyses of standard cortical morphometry that downplay the probable scenario where numerous biological pathways in sum account for SES-related cortical differences in youth. Methods To comprehensively capture such variability, using data from 9758 children aged 8.9-11.1 years from the ABCD Study®, we employed linked independent component analysis (LICA) and fused vertex-wise cortical thickness, surface area, curvature and grey-/white-matter contrast (GWC). LICA revealed 70 uni- and multimodal components. We then assessed the linear relationships between parental education, parental income and each of the cortical components, controlling for age, sex, genetic ancestry, and family relatedness. We also assessed whether cortical structure moderated the negative relationships between parental SES and child general psychopathology. Results Parental education and income were both associated with larger surface area and higher GWC globally, in addition to local increases in surface area and to a lesser extent bidirectional GWC and cortical thickness patterns. The negative relation between parental income and child psychopathology were attenuated in children with a multimodal pattern of larger frontal- and smaller occipital surface area, and lower medial occipital thickness and GWC. Conclusion Structural brain MRI is sensitive to SES diversity in childhood, with GWC emerging as a particularly relevant marker together with surface area. In low-income families, having a more developed cortex across MRI metrics, appears beneficial for mental health.
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Affiliation(s)
- Linn B. Norbom
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
| | - Jaroslav Rokicki
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Centre of Research and Education in Forensic PsychiatryOslo University HospitalOsloNorway
| | - Espen M. Eilertsen
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
| | - Thea Wiker
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Jamie Hanson
- Learning Research and Development Center University of PittsburghPennsylvaniaPittsburghUSA
- Department of PsychologyUniversity of PittsburghPennsylvaniaPittsburghUSA
| | - Andreas Dahl
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Dag Alnæs
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyPedagogy and LawKristiania University CollegeOsloNorway
| | | | - Dani Beck
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Ingrid Agartz
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- Centre for Psychiatry ResearchDepartment of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care ServicesStockholmSweden
| | - Ole A. Andreassen
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- NORMENTDivision of Mental Health and AddictionOslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Lars T. Westlye
- Department of PsychologyUniversity of OsloOsloNorway
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- NORMENTDivision of Mental Health and AddictionOslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Christian K. Tamnes
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
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Fan L, Li Y, Zhao X, Huang ZG, Liu T, Wang J. Dynamic nonreversibility view of intrinsic brain organization and brain dynamic analysis of repetitive transcranial magnitude stimulation. Cereb Cortex 2024; 34:bhae098. [PMID: 38494890 DOI: 10.1093/cercor/bhae098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/19/2024] Open
Abstract
Intrinsic neural activities are characterized as endless spontaneous fluctuation over multiple time scales. However, how the intrinsic brain organization changes over time under local perturbation remains an open question. By means of statistical physics, we proposed an approach to capture whole-brain dynamics based on estimating time-varying nonreversibility and k-means clustering of dynamic varying nonreversibility patterns. We first used synthetic fMRI to investigate the effects of window parameters on the temporal variability of varying nonreversibility. Second, using real test-retest fMRI data, we examined the reproducibility, reliability, biological, and physiological correlation of the varying nonreversibility substates. Finally, using repetitive transcranial magnetic stimulation-fMRI data, we investigated the modulation effects of repetitive transcranial magnetic stimulation on varying nonreversibility substate dynamics. The results show that: (i) as window length increased, the varying nonreversibility variance decreased, while the sliding step almost did not alter it; (ii) the global high varying nonreversibility states and low varying nonreversibility states were reproducible across multiple datasets and different window lengths; and (iii) there were increased low varying nonreversibility states and decreased high varying nonreversibility states when the left frontal lobe was stimulated, but not the occipital lobe. Taken together, these results provide a thermodynamic equilibrium perspective of intrinsic brain organization and reorganization under local perturbation.
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Affiliation(s)
- Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Xingjian Zhao
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Zi-Gang Huang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
- The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China
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60
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Ni Y, Zheng X, Betzel R, James TW. Increased Segregation in Functional Connectivity Networks When Watching Unpleasant Arousing Videos: A Generalized Psychophysiological Interaction Analysis. Brain Connect 2024; 14:92-106. [PMID: 38265003 DOI: 10.1089/brain.2023.0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024] Open
Abstract
Background: Properties of functional connectivity (FC), such as network integration and segregation, are shown to be associated with various human behaviors. For example, Godwin et al. and Sun et al. found increased integration with attention allocation, whereas Cohen and D'Esposito and Shine et al. observed increased segregation with simple motor tasks. The current study investigated how viewing video clips with different valence and arousal influenced integration-segregation properties in task-based FC networks. Methods: We analyzed an open dataset collected by Kim et al. We performed a generalized psychophysiological interaction (gPPI) analysis paired with network analysis and community detection to investigate changes in brain network dynamics when people watched four types of videos that differed by affective valence (unpleasant or pleasant) and arousal (arousing or calm). Results: Results showed that unpleasant arousing videos produced greater FC deviation from the baseline (task-induced FC deviation [tiFCd]) and perturbed the brain into a more segregated state than other kinds of video. Increased segregation was only observed in association systems, not sensorimotor systems. Discussion: Unpleasant arousing content perturbed the brain to a functionally distinct state from the other three types of affective videos. We suggest that the change in brain state was related to people disengaging from the unpleasant arousing content or, alternatively, staying alert while exposed to unpleasant arousing stimuli. The study also added to our understanding of how combining task-based gPPI analysis with community detection methods and network segregation measures can advance our knowledge of the links between behavior and brain state changes. Impact statement Network integration and segregation is an important property of the human brain. We address the question of how affective stimuli influence brain dynamics from a functional connectivity (FC) network integration-segregation perspective. By conducting a whole-brain generalized psychophysiological interaction (gPPI) analysis paired with community detection methods, we found that highly aversive video content induced significant FC changes and perturbed the brain to a more segregated state.
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Affiliation(s)
- Yuqian Ni
- The Media School, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Xia Zheng
- School of Communication and Journalism, Stony Brook University, Stony Brook, New York, USA
| | - Richard Betzel
- Department of Psychological and Brain Science, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Thomas W James
- Department of Psychological and Brain Science, Indiana University Bloomington, Bloomington, Indiana, USA
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Betzel R, Puxeddu MG, Seguin C, Bazinet V, Luppi A, Podschun A, Singleton SP, Faskowitz J, Parakkattu V, Misic B, Markett S, Kuceyeski A, Parkes L. Controlling the human connectome with spatially diffuse input signals. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.27.581006. [PMID: 38463980 PMCID: PMC10925126 DOI: 10.1101/2024.02.27.581006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
The human brain is never at "rest"; its activity is constantly fluctuating over time, transitioning from one brain state-a whole-brain pattern of activity-to another. Network control theory offers a framework for understanding the effort - energy - associated with these transitions. One branch of control theory that is especially useful in this context is "optimal control", in which input signals are used to selectively drive the brain into a target state. Typically, these inputs are introduced independently to the nodes of the network (each input signal is associated with exactly one node). Though convenient, this input strategy ignores the continuity of cerebral cortex - geometrically, each region is connected to its spatial neighbors, allowing control signals, both exogenous and endogenous, to spread from their foci to nearby regions. Additionally, the spatial specificity of brain stimulation techniques is limited, such that the effects of a perturbation are measurable in tissue surrounding the stimulation site. Here, we adapt the network control model so that input signals have a spatial extent that decays exponentially from the input site. We show that this more realistic strategy takes advantage of spatial dependencies in structural connectivity and activity to reduce the energy (effort) associated with brain state transitions. We further leverage these dependencies to explore near-optimal control strategies such that, on a per-transition basis, the number of input signals required for a given control task is reduced, in some cases by two orders of magnitude. This approximation yields network-wide maps of input site density, which we compare to an existing database of functional, metabolic, genetic, and neurochemical maps, finding a close correspondence. Ultimately, not only do we propose a more efficient framework that is also more adherent to well-established brain organizational principles, but we also posit neurobiologically grounded bases for optimal control.
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Affiliation(s)
- Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
- Cognitive Science Program, Indiana University, Bloomington IN 47401
- Program in Neuroscience, Indiana University, Bloomington IN 47401
| | - Maria Grazia Puxeddu
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
| | - Caio Seguin
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
| | - Vincent Bazinet
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Andrea Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | | | | | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
| | - Vibin Parakkattu
- Department of Psychological and Brain Sciences, Indiana University, Bloomington IN 47401
- Cognitive Science Program, Indiana University, Bloomington IN 47401
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | | | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY
- Department of Computational Biology, Cornell University, Ithaca, NY
| | - Linden Parkes
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
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62
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Wang Y, Wang Y, Wang H, Ma L, Eickhoff SB, Madsen KH, Chu C, Fan L. Spatio-molecular profiles shape the human cerebellar hierarchy along the sensorimotor-association axis. Cell Rep 2024; 43:113770. [PMID: 38363683 DOI: 10.1016/j.celrep.2024.113770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/27/2023] [Accepted: 01/25/2024] [Indexed: 02/18/2024] Open
Abstract
Cerebellar involvement in both motor and non-motor functions manifests in specific regions of the human cerebellum, revealing the functional heterogeneity within it. One compelling theory places the heterogeneity within the cerebellar functional hierarchy along the sensorimotor-association (SA) axis. Despite extensive neuroimaging studies, evidence for the cerebellar SA axis from different modalities and scales was lacking. Thus, we establish a significant link between the cerebellar SA axis and spatio-molecular profiles. Utilizing the gene set variation analysis, we find the intermediate biological principles the significant genes leveraged to scaffold the cerebellar SA axis. Interestingly, we find these spatio-molecular profiles notably associated with neuropsychiatric dysfunction and recent evolution. Furthermore, cerebello-cerebral interactions at genetic and functional connectivity levels mirror the cerebral cortex and cerebellum's SA axis. These findings can provide a deeper understanding of how the human cerebellar SA axis is shaped and its role in transitioning from sensorimotor to association functions.
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Affiliation(s)
- Yaping Wang
- Sino-Danish Center, University of Chinese Academy of Sciences, Beijing 100190, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yufan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Liang Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Kristoffer Hougaard Madsen
- Sino-Danish Center, University of Chinese Academy of Sciences, Beijing 100190, China; Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, 2650 Hvidovre, Denmark
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
| | - Lingzhong Fan
- Sino-Danish Center, University of Chinese Academy of Sciences, Beijing 100190, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Health and Life Sciences, University of Health and Rehabilitation Sciences, Qingdao 266000, China.
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63
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Boer OD, El Marroun H, Muetzel RL. Adolescent substance use initiation and long-term neurobiological outcomes: insights, challenges and opportunities. Mol Psychiatry 2024:10.1038/s41380-024-02471-2. [PMID: 38409597 DOI: 10.1038/s41380-024-02471-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 01/15/2024] [Accepted: 01/30/2024] [Indexed: 02/28/2024]
Abstract
The increased frequency of risk taking behavior combined with marked neuromaturation has positioned adolescence as a focal point of research into the neural causes and consequences of substance use. However, little work has provided a summary of the links between adolescent initiated substance use and longer-term brain outcomes. Here we review studies exploring the long-term effects of adolescent-initiated substance use with structural and microstructural neuroimaging. A quarter of all studies reviewed conducted repeated neuroimaging assessments. Long-term alcohol use, as well as tobacco use were consistently associated with smaller frontal cortices and altered white matter microstructure. This association was mostly observed in the ACC, insula and subcortical regions in alcohol users, and for the OFC in tobacco users. Long-term cannabis use was mostly related to altered frontal cortices and hippocampal volumes. Interestingly, cannabis users scanned more years after use initiation tended to show smaller measures of these regions, whereas those with fewer years since initiation showed larger measures. Long-term stimulant use tended to show a similar trend as cannabis in terms of years since initiation in measures of the putamen, insula and frontal cortex. Long-term opioid use was mostly associated with smaller subcortical and insular volumes. Of note, null findings were reported in all substance use categories, most often in cannabis use studies. In the context of the large variety in study designs, substance use assessment, methods, and sample characteristics, we provide recommendations on how to interpret these findings, and considerations for future studies.
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Affiliation(s)
- Olga D Boer
- Department of Psychology, Education and Child Studies - Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center - Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Hanan El Marroun
- Department of Psychology, Education and Child Studies - Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center - Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center - Sophia Children's Hospital, Rotterdam, The Netherlands.
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
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Seigfried FA, Britsch S. The Role of Bcl11 Transcription Factors in Neurodevelopmental Disorders. BIOLOGY 2024; 13:126. [PMID: 38392344 PMCID: PMC10886639 DOI: 10.3390/biology13020126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 02/05/2024] [Accepted: 02/10/2024] [Indexed: 02/24/2024]
Abstract
Neurodevelopmental disorders (NDDs) comprise a diverse group of diseases, including developmental delay, autism spectrum disorder (ASD), intellectual disability (ID), and attention-deficit/hyperactivity disorder (ADHD). NDDs are caused by aberrant brain development due to genetic and environmental factors. To establish specific and curative therapeutic approaches, it is indispensable to gain precise mechanistic insight into the cellular and molecular pathogenesis of NDDs. Mutations of BCL11A and BCL11B, two closely related, ultra-conserved zinc-finger transcription factors, were recently reported to be associated with NDDs, including developmental delay, ASD, and ID, as well as morphogenic defects such as cerebellar hypoplasia. In mice, Bcl11 transcription factors are well known to orchestrate various cellular processes during brain development, for example, neural progenitor cell proliferation, neuronal migration, and the differentiation as well as integration of neurons into functional circuits. Developmental defects observed in both, mice and humans display striking similarities, suggesting Bcl11 knockout mice provide excellent models for analyzing human disease. This review offers a comprehensive overview of the cellular and molecular functions of Bcl11a and b and links experimental research to the corresponding NDDs observed in humans. Moreover, it outlines trajectories for future translational research that may help to better understand the molecular basis of Bcl11-dependent NDDs as well as to conceive disease-specific therapeutic approaches.
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Affiliation(s)
- Franziska Anna Seigfried
- Institute of Molecular and Cellular Anatomy, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany
| | - Stefan Britsch
- Institute of Molecular and Cellular Anatomy, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany
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65
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Voldsbekk I, Kjelkenes R, Frogner ER, Westlye LT, Alnæs D. Testing the sensitivity of diagnosis-derived patterns in functional brain networks to symptom burden in a Norwegian youth sample. Hum Brain Mapp 2024; 45:e26631. [PMID: 38379514 PMCID: PMC10879903 DOI: 10.1002/hbm.26631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 01/30/2024] [Accepted: 02/06/2024] [Indexed: 02/22/2024] Open
Abstract
Aberrant brain network development represents a putative aetiological component in mental disorders, which typically emerge during childhood and adolescence. Previous studies have identified resting-state functional connectivity (RSFC) patterns reflecting psychopathology, but the generalisability to other samples and politico-cultural contexts has not been established. We investigated whether a previously identified cross-diagnostic case-control and autism spectrum disorder (ASD)-specific pattern of RSFC (discovery sample; aged 5-21 from New York City, USA; n = 1666) could be validated in a Norwegian convenience-based youth sample (validation sample; aged 9-25 from Oslo, Norway; n = 531). As a test of generalisability, we investigated if these diagnosis-derived RSFC patterns were sensitive to levels of symptom burden in both samples, based on an independent measure of symptom burden. Both the cross-diagnostic and ASD-specific RSFC pattern were validated across samples. Connectivity patterns were significantly associated with thematically appropriate symptom dimensions in the discovery sample. In the validation sample, the ASD-specific RSFC pattern showed a weak, inverse relationship with symptoms of conduct problems, hyperactivity and prosociality, while the cross-diagnostic pattern was not significantly linked to symptoms. Diagnosis-derived connectivity patterns in a developmental clinical US sample were validated in a convenience sample of Norwegian youth, however, they were not associated with mental health symptoms.
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Affiliation(s)
- Irene Voldsbekk
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Rikka Kjelkenes
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Erik R. Frogner
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Lars T. Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
- KG Jebsen Centre for Neurodevelopmental DisordersUniversity of Oslo, Department of Neurology, Oslo University HospitalOsloNorway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University HospitalOsloNorway
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66
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Georgiadis F, Larivière S, Glahn D, Hong LE, Kochunov P, Mowry B, Loughland C, Pantelis C, Henskens FA, Green MJ, Cairns MJ, Michie PT, Rasser PE, Catts S, Tooney P, Scott RJ, Schall U, Carr V, Quidé Y, Krug A, Stein F, Nenadić I, Brosch K, Kircher T, Gur R, Gur R, Satterthwaite TD, Karuk A, Pomarol-Clotet E, Radua J, Fuentes-Claramonte P, Salvador R, Spalletta G, Voineskos A, Sim K, Crespo-Facorro B, Tordesillas Gutiérrez D, Ehrlich S, Crossley N, Grotegerd D, Repple J, Lencer R, Dannlowski U, Calhoun V, Rootes-Murdy K, Demro C, Ramsay IS, Sponheim SR, Schmidt A, Borgwardt S, Tomyshev A, Lebedeva I, Höschl C, Spaniel F, Preda A, Nguyen D, Uhlmann A, Stein DJ, Howells F, Temmingh HS, Diaz Zuluaga AM, López Jaramillo C, Iasevoli F, Ji E, Homan S, Omlor W, Homan P, Kaiser S, Seifritz E, Misic B, Valk SL, Thompson P, van Erp TGM, Turner JA, Bernhardt B, Kirschner M. Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study. Mol Psychiatry 2024:10.1038/s41380-024-02442-7. [PMID: 38336840 DOI: 10.1038/s41380-024-02442-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/08/2024] [Accepted: 01/18/2024] [Indexed: 02/12/2024]
Abstract
Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.
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Affiliation(s)
- Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland.
| | - Sara Larivière
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - David Glahn
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, US
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, US
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, Australia
| | - Carmel Loughland
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, USA
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton South, VIC, Australia
| | - Frans A Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - Melissa J Green
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
| | - Murray J Cairns
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Patricia T Michie
- School of Psychological Sciences, University of Newcastle, Newcastle, NSW, Australia
| | - Paul E Rasser
- School of Medicine and Public Health, College of Health, Medicine, and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia
| | - Stanley Catts
- Faculty of Medicine, University of Queensland, St Lucia, QLD, Australia
| | - Paul Tooney
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Rodney J Scott
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Vaughan Carr
- School of Clinical Medicine, Discipline of Psychiatry, UNSW Sydney, Sydney, NSW, Australia
| | - Yann Quidé
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW, Australia
| | - Axel Krug
- University Hospital Bonn, Department of Psychiatry and Psychotherapy, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Frederike Stein
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Igor Nenadić
- Department. of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry, University of Marburg, Rudolf Bultmann Str. 8, 35039, Marburg, Germany
| | - Raquel Gur
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ruben Gur
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation & CIBERSAM, ISCIII, Barcelona, Spain
| | | | - Aristotle Voineskos
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
| | | | - Diana Tordesillas Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain
| | - Stefan Ehrlich
- Division of Psychological & Social Medicine and Developmental Neurosciences, Technischen Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - Nicolas Crossley
- Department of Psychiatry, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Vince Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Kelly Rootes-Murdy
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Caroline Demro
- University of Minnesota Department of Psychology, Minneapolis, MN, USA
- Minneapolis VA Health Care System, Minneapolis, MN, USA
| | - Ian S Ramsay
- University of Minnesota Department of Psychiatry & Behavioral Sciences, Minneapolis, MN, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- University of Minnesota Department of Psychiatry & Behavioral Sciences, Minneapolis, MN, USA
| | - Andre Schmidt
- University of Basel, Department of Psychiatry, Basel, Switzerland
| | | | | | - Irina Lebedeva
- Mental Health Research Center, Moscow, Russian Federation
| | - Cyril Höschl
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Dana Nguyen
- Department of Pediatric Neurology, University of California Irvine, Irvine, CA, USA
| | - Anne Uhlmann
- Department of child and adolescent psychiatry, TU Dresden, Dresden, Germany
| | - Dan J Stein
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Fleur Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Henk S Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Ana M Diaz Zuluaga
- Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia
| | - Carlos López Jaramillo
- Research Group in Psychiatry, Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Colombia
| | - Felice Iasevoli
- University of Naples, Department of Neuroscience, Naples, Italy
| | - Ellen Ji
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Wolfgang Omlor
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Bratislav Misic
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - Sofie L Valk
- Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany
| | - Paul Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Theo G M van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, the Ohio State University, Columbus, OH, USA
| | - Boris Bernhardt
- McGill University, Montreal Neurological Institute, Montreal, QC, Canada
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland.
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland.
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Sanders AFP, Tirado B, Seider NA, Triplett RL, Lean RE, Neil JJ, Miller JP, Tillman R, Smyser TA, Barch DM, Luby JL, Rogers CE, Smyser CD, Warner BB, Chen E, Miller GE. Prenatal exposure to maternal disadvantage-related inflammatory biomarkers: associations with neonatal white matter microstructure. Transl Psychiatry 2024; 14:72. [PMID: 38307841 PMCID: PMC10837200 DOI: 10.1038/s41398-024-02782-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/11/2024] [Accepted: 01/15/2024] [Indexed: 02/04/2024] Open
Abstract
Prenatal exposure to heightened maternal inflammation has been associated with adverse neurodevelopmental outcomes, including atypical brain maturation and psychiatric illness. In mothers experiencing socioeconomic disadvantage, immune activation can be a product of the chronic stress inherent to such environmental hardship. While growing preclinical and clinical evidence has shown links between altered neonatal brain development and increased inflammatory states in utero, the potential mechanism by which socioeconomic disadvantage differentially impacts neural-immune crosstalk remains unclear. In the current study, we investigated associations between socioeconomic disadvantage, gestational inflammation, and neonatal white matter microstructure in 320 mother-infant dyads over-sampled for poverty. We analyzed maternal serum levels of four cytokines (IL-6, IL-8, IL-10, TNF-α) over the course of pregnancy in relation to offspring white matter microstructure and socioeconomic disadvantage. Higher average maternal IL-6 was associated with very low socioeconomic status (SES; INR < 200% poverty line) and lower neonatal corticospinal fractional anisotropy (FA) and lower uncinate axial diffusivity (AD). No other cytokine was associated with SES. Higher average maternal IL-10 was associated with lower FA and higher radial diffusivity (RD) in corpus callosum and corticospinal tracts, higher optic radiation RD, lower uncinate AD, and lower FA in inferior fronto-occipital fasciculus and anterior limb of internal capsule tracts. SES moderated the relationship between average maternal TNF-α levels during gestation and neonatal white matter diffusivity. When these interactions were decomposed, the patterns indicated that this association was significant and positive among very low SES neonates, whereby TNF-α was inversely and significantly associated with inferior cingulum AD. By contrast, among the more advantaged neonates (lower-to-higher SES [INR ≥ 200% poverty line]), TNF-α was positively and significantly associated with superior cingulum AD. Taken together, these findings suggest that the relationship between prenatal cytokine exposure and white matter microstructure differs as a function of SES. These patterns are consistent with a scenario where gestational inflammation's effects on white matter development diverge depending on the availability of foundational resources in utero.
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Affiliation(s)
- Ashley F P Sanders
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA.
| | - Brian Tirado
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Regina L Triplett
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Rachel E Lean
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jeffrey J Neil
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - J Philip Miller
- Division of Biostatistics, Institute for Informatics, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Rebecca Tillman
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Tara A Smyser
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, 63130, USA
| | - Joan L Luby
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Cynthia E Rogers
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Christopher D Smyser
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Barbara B Warner
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Newborn Medicine, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Edith Chen
- Institute for Policy Research, Northwestern University, Evanston, IL, 60208, USA
- Department of Psychology, Northwestern University, Evanston, IL, 60208, USA
| | - Gregory E Miller
- Institute for Policy Research, Northwestern University, Evanston, IL, 60208, USA
- Department of Psychology, Northwestern University, Evanston, IL, 60208, USA
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68
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Myers MJ, Labonte AK, Gordon EM, Laumann TO, Tu JC, Wheelock MD, Nielsen AN, Schwarzlose RF, Camacho MC, Alexopoulos D, Warner BB, Raghuraman N, Luby JL, Barch DM, Fair DA, Petersen SE, Rogers CE, Smyser CD, Sylvester CM. Functional parcellation of the neonatal cortical surface. Cereb Cortex 2024; 34:bhae047. [PMID: 38372292 PMCID: PMC10875653 DOI: 10.1093/cercor/bhae047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 02/20/2024] Open
Abstract
The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that existing parcellations, including surface-based parcels derived from older samples as well as volume-based neonatal parcels, are a poor fit for neonatal surface data. We next derive a set of 283 cortical surface parcels from a sample of n = 261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.
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Affiliation(s)
- Michael J Myers
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Alyssa K Labonte
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
- Neurosciences Graduate Program, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Evan M Gordon
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Timothy O Laumann
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Jiaxin C Tu
- Neurosciences Graduate Program, Washington University in St. Louis, St. Louis, MO 63110, United States
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Muriah D Wheelock
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Ashley N Nielsen
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Rebecca F Schwarzlose
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - M Catalina Camacho
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Barbara B Warner
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Nandini Raghuraman
- Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Joan L Luby
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States
- Institute of Child Development, University of Minnesota, Minneapolis, MN 55455, United States
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454, United States
| | - Steven E Petersen
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Cynthia E Rogers
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
| | - Christopher D Smyser
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
- Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, MO 63110, United States
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69
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Boen R, Kaufmann T, van der Meer D, Frei O, Agartz I, Ames D, Andersson M, Armstrong NJ, Artiges E, Atkins JR, Bauer J, Benedetti F, Boomsma DI, Brodaty H, Brosch K, Buckner RL, Cairns MJ, Calhoun V, Caspers S, Cichon S, Corvin AP, Crespo-Facorro B, Dannlowski U, David FS, de Geus EJC, de Zubicaray GI, Desrivières S, Doherty JL, Donohoe G, Ehrlich S, Eising E, Espeseth T, Fisher SE, Forstner AJ, Fortaner-Uyà L, Frouin V, Fukunaga M, Ge T, Glahn DC, Goltermann J, Grabe HJ, Green MJ, Groenewold NA, Grotegerd D, Grøntvedt GR, Hahn T, Hashimoto R, Hehir-Kwa JY, Henskens FA, Holmes AJ, Håberg AK, Haavik J, Jacquemont S, Jansen A, Jockwitz C, Jönsson EG, Kikuchi M, Kircher T, Kumar K, Le Hellard S, Leu C, Linden DE, Liu J, Loughnan R, Mather KA, McMahon KL, McRae AF, Medland SE, Meinert S, Moreau CA, Morris DW, Mowry BJ, Mühleisen TW, Nenadić I, Nöthen MM, Nyberg L, Ophoff RA, Owen MJ, Pantelis C, Paolini M, Paus T, Pausova Z, Persson K, Quidé Y, Marques TR, Sachdev PS, Sando SB, Schall U, Scott RJ, Selbæk G, Shumskaya E, Silva AI, Sisodiya SM, Stein F, Stein DJ, Straube B, Streit F, Strike LT, Teumer A, Teutenberg L, Thalamuthu A, Tooney PA, Tordesillas-Gutierrez D, Trollor JN, van 't Ent D, van den Bree MBM, van Haren NEM, Vázquez-Bourgon J, Völzke H, Wen W, Wittfeld K, Ching CRK, Westlye LT, Thompson PM, Bearden CE, Selmer KK, Alnæs D, Andreassen OA, Sønderby IE. Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers. Biol Psychiatry 2024; 95:147-160. [PMID: 37661008 PMCID: PMC7615370 DOI: 10.1016/j.biopsych.2023.08.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 07/25/2023] [Accepted: 08/21/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.
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Affiliation(s)
- Rune Boen
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Germany; German Center for Mental Health (DZPG), partner site Tübingen, Tübingen, Germany
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Research, Diakonhjemmet Hospital, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - David Ames
- University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, Victoria, Australia; National Ageing Research Institute, Parkville, Victoria, Australia
| | - Micael Andersson
- Department of Integrative Medical Biology and Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Curtin University, Perth, Western Australia, Australia
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale U1299, École Normale Supérieure Paris-Saclay, Université Paris Saclay, Gif-sur-Yvette, France; Établissement public de santé (EPS) Barthélemy Durand, Etampes, France
| | - Joshua R Atkins
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia; Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jochen Bauer
- University Clinic for Radiology, University of Münster, Münster, Germany
| | - Francesco Benedetti
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Randy L Buckner
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University/Georgia Institute of Technology/Emory University, Atlanta, Georgia
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sven Cichon
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland; University Hospital Basel, Institute of Medical Genetics and Pathology, Basel, Switzerland
| | - Aiden P Corvin
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Benedicto Crespo-Facorro
- Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/Centro superior de investigaciones científicas (CSIC), Sevilla, Spain; Centro de Investigación Biomédica en Red Salud Mental, Sevilla, Spain; Department of Psychiatry, University of Sevilla, Sevilla, Spain
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Friederike S David
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Greig I de Zubicaray
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Sylvane Desrivières
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Joanne L Doherty
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Gary Donohoe
- School of Psychology and Center for Neuroimaging, Cognition and Genomics, University of Galway, Galway, Ireland
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Else Eising
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Thomas Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway; Department of Psychology, Oslo New University College, Oslo, Norway
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Andreas J Forstner
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Lidia Fortaner-Uyà
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Vincent Frouin
- Neurospin, Commissariat a l'Energie Atomique (CEA), Université Paris-Saclay, Gif-sur-Yvette, France
| | - Masaki Fukunaga
- Section of Brain Function Information, National Institute for Physiological Sciences, Okazaki, Japan
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - David C Glahn
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Melissa J Green
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia; Neuroscience Research Australia, Sydney, New South Wales, Australia
| | - Nynke A Groenewold
- Department of Psychiatry and Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Gøril Rolfseng Grøntvedt
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Jayne Y Hehir-Kwa
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Frans A Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia; Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, New South Wales, Australia
| | - Avram J Holmes
- Department of Psychiatry, Rutgers University, New Brunswick, New Jersey; Brain Health Institute, Rutgers University, Piscataway, New Jersey
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Radiology and Nuclear Medicine, St. Olav's Hospital, Trondheim, Norway
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway; Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Sebastien Jacquemont
- Sainte Justine Hospital Research Center, Montreal, Quebec, Canada; Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany; Core-Facility Brainimaging and Department of Psychiatry, Faculty of Medicine, Philipps-University Marburg, Marburg, Germany
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Erik G Jönsson
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Masataka Kikuchi
- Department of Genome Informatics, Graduate School of Medicine, Osaka University, Osaka, Japan; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Kuldeep Kumar
- Sainte Justine Hospital Research Center, Montreal, Quebec, Canada
| | - Stephanie Le Hellard
- Norwegian Centre for Mental Disorders Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Costin Leu
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Department of Neurology, McGovern Medical School, UTHealth Houston, Houston, Texas
| | - David E Linden
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, United Kingdom; School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Jingyu Liu
- Department of Computer Science and Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, Georgia
| | - Robert Loughnan
- Department of Cognitive Science and Population Neuroscience and Genetics Lab, University of California San Diego, La Jolla, California
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Sarah E Medland
- Psychiatric Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Brisbane, Queensland, Australia; University of Queensland, Brisbane, Queensland, Australia; Queensland University of Technology, Brisbane, Queensland, Australia
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany; Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Clara A Moreau
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Derek W Morris
- Centre for Neuroimaging, Cognition and Genomics, School of Biological and Chemical Sciences, University of Galway, Galway, Ireland
| | - Bryan J Mowry
- Queensland Brain Institute and Queensland Centre for Mental Health Research, University of Queensland, Brisbane, Queensland, Australia
| | - Thomas W Mühleisen
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Lars Nyberg
- Departments of Radiation Sciences, Integrative Medical Biology and Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Roel A Ophoff
- Department of Psychiatry, Erasmus University Medical Center, Rotterdam, the Netherlands; Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California Los Angeles, Los Angeles, California
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Carlton South, Victoria, Australia; Western Centre for Health Research and Education, Sunshine Hospital, St Albans, Victoria, Australia
| | - Marco Paolini
- Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy
| | - Tomas Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Sainte Justine Hospital Research Center, University of Montreal, Montreal, Quebec, Canada; Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Karin Persson
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| | - Yann Quidé
- Neuroscience Research Australia, Sydney, New South Wales, Australia; School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Tiago Reis Marques
- Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Sigrid B Sando
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Hunter Medical Research Institute, Newcastle, New South Wales, Australia; Division of Molecular Medicine, New South Wales Health Pathology, Newcastle, New South Wales, Australia
| | - Geir Selbæk
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Elena Shumskaya
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands; Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ana I Silva
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, United Kingdom
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Dan J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lachlan T Strike
- Psychiatric Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Brisbane, Queensland, Australia; School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Brisbane, Australia
| | - Alexander Teumer
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research, Greifswald, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Paul A Tooney
- School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia; Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Diana Tordesillas-Gutierrez
- Instituto de Física de Cantabria UC-CSIC, Santander, Spain; Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute, Instituto de Investigación Sanitaria Valdecilla, Santander, Spain
| | - Julian N Trollor
- Department of Developmental Disability Neuropsychiatry and Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Dennis van 't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Marianne B M van den Bree
- Institute of Psychological Medicine and Clinical Neurosciences and Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Neeltje E M van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, the Netherlands; Department of Psychiatry, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Javier Vázquez-Bourgon
- Centro de Investigación Biomédica en Red Salud Mental, Sevilla, Spain; Department of Psychiatry, University Hospital Maqués de Valdecilla, Instituto de Investigación Sanitaria Valdecilla, Santander, Spain; Departamento de Medicina y Psiquiatría, Universidad de Cantabria, Santander, Spain
| | - Henry Völzke
- German Centre for Cardiovascular Research, Greifswald, Germany; Greifswald University Hospital, Greifswald, Germany
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California Los Angeles, Los Angeles, California
| | - Kaja K Selmer
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital and the University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Kristiania University College, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ida E Sønderby
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
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Luppi AI, Girn M, Rosas FE, Timmermann C, Roseman L, Erritzoe D, Nutt DJ, Stamatakis EA, Spreng RN, Xing L, Huttner WB, Carhart-Harris RL. A role for the serotonin 2A receptor in the expansion and functioning of human transmodal cortex. Brain 2024; 147:56-80. [PMID: 37703310 DOI: 10.1093/brain/awad311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 08/14/2023] [Accepted: 08/18/2023] [Indexed: 09/15/2023] Open
Abstract
Integrating independent but converging lines of research on brain function and neurodevelopment across scales, this article proposes that serotonin 2A receptor (5-HT2AR) signalling is an evolutionary and developmental driver and potent modulator of the macroscale functional organization of the human cerebral cortex. A wealth of evidence indicates that the anatomical and functional organization of the cortex follows a unimodal-to-transmodal gradient. Situated at the apex of this processing hierarchy-where it plays a central role in the integrative processes underpinning complex, human-defining cognition-the transmodal cortex has disproportionately expanded across human development and evolution. Notably, the adult human transmodal cortex is especially rich in 5-HT2AR expression and recent evidence suggests that, during early brain development, 5-HT2AR signalling on neural progenitor cells stimulates their proliferation-a critical process for evolutionarily-relevant cortical expansion. Drawing on multimodal neuroimaging and cross-species investigations, we argue that, by contributing to the expansion of the human cortex and being prevalent at the apex of its hierarchy in the adult brain, 5-HT2AR signalling plays a major role in both human cortical expansion and functioning. Owing to its unique excitatory and downstream cellular effects, neuronal 5-HT2AR agonism promotes neuroplasticity, learning and cognitive and psychological flexibility in a context-(hyper)sensitive manner with therapeutic potential. Overall, we delineate a dual role of 5-HT2ARs in enabling both the expansion and modulation of the human transmodal cortex.
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Affiliation(s)
- Andrea I Luppi
- Department of Clinical Neurosciences and Division of Anaesthesia, University of Cambridge, Cambridge, CB2 0QQ, UK
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, CB2 1SB, UK
- The Alan Turing Institute, London, NW1 2DB, UK
| | - Manesh Girn
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, H3A 2B4, Canada
- Psychedelics Division-Neuroscape, Department of Neurology, University of California SanFrancisco, San Francisco, CA 94158, USA
| | - Fernando E Rosas
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
- Data Science Institute, Imperial College London, London, SW7 2AZ, UK
- Centre for Complexity Science, Imperial College London, London, SW7 2AZ, UK
| | - Christopher Timmermann
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Leor Roseman
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - David Erritzoe
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - David J Nutt
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Emmanuel A Stamatakis
- Department of Clinical Neurosciences and Division of Anaesthesia, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - R Nathan Spreng
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, H3A 2B4, Canada
| | - Lei Xing
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, 01307, Germany
| | - Wieland B Huttner
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, 01307, Germany
| | - Robin L Carhart-Harris
- Psychedelics Division-Neuroscape, Department of Neurology, University of California SanFrancisco, San Francisco, CA 94158, USA
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
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71
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Park BY, Benkarim O, Weber CF, Kebets V, Fett S, Yoo S, Martino AD, Milham MP, Misic B, Valk SL, Hong SJ, Bernhardt BC. Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism. Neuroimage 2024; 285:120481. [PMID: 38043839 DOI: 10.1016/j.neuroimage.2023.120481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 11/29/2023] [Accepted: 12/01/2023] [Indexed: 12/05/2023] Open
Abstract
Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms.
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Affiliation(s)
- Bo-Yong Park
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Department of Data Science, Inha University, Incheon, South Korea; Department of Statistics and Data Science, Inha University, Incheon, South Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea.
| | - Oualid Benkarim
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Clara F Weber
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Valeria Kebets
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Serena Fett
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Seulki Yoo
- Convergence Research Institute, Sungkyunkwan University, Suwon, South Korea
| | - Adriana Di Martino
- Center for the Developing Brain, Child Mind Institute, New York, United States
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, United States
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Sofie L Valk
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Seok-Jun Hong
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea; Center for the Developing Brain, Child Mind Institute, New York, United States; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
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72
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Lynch KM, Cabeen RP, Toga AW. Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI. Hum Brain Mapp 2024; 45:e26528. [PMID: 37994234 PMCID: PMC10789199 DOI: 10.1002/hbm.26528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 10/10/2023] [Accepted: 10/19/2023] [Indexed: 11/24/2023] Open
Abstract
Neocortical maturation is a dynamic process that proceeds in a hierarchical manner; however, the spatiotemporal organization of cortical microstructure with diffusion MRI has yet to be fully defined. This study characterized cortical microstructural maturation using diffusion MRI (fwe-diffusion tensor imaging [DTI] and neurite orientation dispersion and density imaging [NODDI] multicompartment modeling) in a cohort of 637 children and adolescents between 8 and 21 years of age. We found spatially heterogeneous developmental patterns broadly demarcated into functional domains where NODDI metrics increased, and fwe-DTI metrics decreased with age. By applying nonlinear growth models in a vertex-wise analysis, we observed a general posterior-to-anterior pattern of maturation, where the fwe-DTI measures mean diffusivity and radial diffusivity reached peak maturation earlier than the NODDI metrics neurite density index. Using non-negative matrix factorization, we found occipito-parietal cortical regions that correspond to lower order sensory domains mature earlier than fronto-temporal higher order association domains. Our findings corroborate previous histological and neuroimaging studies that show spatially varying patterns of cortical maturation that may reflect unique developmental processes of cytoarchitectonically determined regional patterns of change.
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Affiliation(s)
- Kirsten M. Lynch
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| | - Ryan P. Cabeen
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
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73
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Zheng C, Zhao W, Yang Z, Guo S. Functional connectome hierarchy dysfunction in Alzheimer's disease and its relationship with cognition and gene expression profiling. J Neurosci Res 2024; 102:e25280. [PMID: 38284860 DOI: 10.1002/jnr.25280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 10/21/2023] [Accepted: 11/16/2023] [Indexed: 01/30/2024]
Abstract
Numerous researches have shown that the human brain organizes as a continuum axis crossing from sensory motor to transmodal cortex. Functional network alterations were commonly found in Alzheimer's disease (AD). Whether the hierarchy of AD brain networks has changed and how these changes related to gene expression profiling and cognition is unclear. Using resting-state functional magnetic resonance imaging data from 233 subjects (185 AD patients and 48 healthy controls), we studied the changes in the functional network gradients in AD. Moreover, we investigated the relationships between gradient alterations and cognition, and gene expression profiling, respectively. We found that the second gradient organizes as a continuum axis crossing from the sensory motor to the transmodal cortex. Compared to the healthy controls, the secondary gradient scores of the visual and somatomotor network (SOM) increased significantly in AD, and the secondary gradient scores of default mode and frontoparietal network decreased significantly in AD. The secondary gradient scores of SOM and salience network (SAL) significantly positively correlated with memory function in AD. The secondary gradient in SAL also significantly positively correlated with language function. The AD-related second gradient alterations were spatially associated with the gene expression and the relevant genes enriched in neurobiology-related pathways, specially expressed in various tissues, cell types, and developmental stages. These findings suggested the changes in the functional network gradients in AD and deepened our understanding of the correlation between macroscopic gradient structure and microscopic gene expression profiling in AD.
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Affiliation(s)
- Chuchu Zheng
- School of Mathematics and Statistics, Hunan Normal University, Changsha, China
- Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, China
| | - Wei Zhao
- School of Mathematics and Statistics, Hunan Normal University, Changsha, China
- Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, China
| | - Zeyu Yang
- School of Mathematics and Statistics, Hunan Normal University, Changsha, China
- Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, China
| | - Shuixia Guo
- School of Mathematics and Statistics, Hunan Normal University, Changsha, China
- Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, China
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74
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Bagautdinova J, Bourque J, Sydnor VJ, Cieslak M, Alexander-Bloch AF, Bertolero MA, Cook PA, Gur RE, Gur RC, Hu F, Larsen B, Moore TM, Radhakrishnan H, Roalf DR, Shinohara RT, Tapera TM, Zhao C, Sotiras A, Davatzikos C, Satterthwaite TD. Development of white matter fiber covariance networks supports executive function in youth. Cell Rep 2023; 42:113487. [PMID: 37995188 PMCID: PMC10795769 DOI: 10.1016/j.celrep.2023.113487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 10/05/2023] [Accepted: 11/09/2023] [Indexed: 11/25/2023] Open
Abstract
During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks aligned with known major tracts, while also capturing distinct patterns of spatial covariance across distributed white matter locations. Most networks showed age-related increases in fiber network properties, which were also related to developmental changes in executive function. This study delineates data-driven patterns of white matter development that support cognition.
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Affiliation(s)
- Joëlle Bagautdinova
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Josiane Bourque
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Maxwell A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Philip A Cook
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Fengling Hu
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hamsanandini Radhakrishnan
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russel T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tinashe M Tapera
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chenying Zhao
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aristeidis Sotiras
- Department of Radiology and Institute for Informatics, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63130, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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75
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Petersen M, Hoffstaedter F, Nägele FL, Mayer C, Schell M, Rimmele DL, Zyriax BC, Zeller T, Kühn S, Gallinat J, Fiehler J, Twerenbold R, Omidvarnia A, Patil KR, Eickhoff SB, Thomalla G, Cheng B. A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.22.529531. [PMID: 36865285 PMCID: PMC9980040 DOI: 10.1101/2023.02.22.529531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, cortical morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.
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Affiliation(s)
- Marvin Petersen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Felix Hoffstaedter
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Moorenstraße 5, 40225 Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Ju lich, Wilhelm-Johnen-Straße, 52425 Ju lich, Germany
| | - Felix L. Nägele
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Carola Mayer
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Maximilian Schell
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - D. Leander Rimmele
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Birgit-Christiane Zyriax
- Midwifery Science-Health Services Research and Prevention, Institute for Health Services Research in Dermatology and Nursing (IVDP), University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Tanja Zeller
- Department of Cardiology, University Heart and Vascular Center, Martinistraße 52, 20251 Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Martinistraße 52, 20251 Hamburg, Germany
- University Center of Cardiovascular Science, University Heart and Vascular Center, Martinistraße 52, 20251 Hamburg, Germany
| | - Simone Kühn
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Jürgen Gallinat
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Raphael Twerenbold
- Department of Cardiology, University Heart and Vascular Center, Martinistraße 52, 20251 Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Martinistraße 52, 20251 Hamburg, Germany
- University Center of Cardiovascular Science, University Heart and Vascular Center, Martinistraße 52, 20251 Hamburg, Germany
- Epidemiological Study Center, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Amir Omidvarnia
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Moorenstraße 5, 40225 Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Ju lich, Wilhelm-Johnen-Straße, 52425 Ju lich, Germany
| | - Kaustubh R. Patil
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Moorenstraße 5, 40225 Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Ju lich, Wilhelm-Johnen-Straße, 52425 Ju lich, Germany
| | - Simon B. Eickhoff
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Moorenstraße 5, 40225 Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Ju lich, Wilhelm-Johnen-Straße, 52425 Ju lich, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251 Hamburg, Germany
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76
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He LW, Guo XJ, Zhao C, Rao JS. Rehabilitation Training after Spinal Cord Injury Affects Brain Structure and Function: From Mechanisms to Methods. Biomedicines 2023; 12:41. [PMID: 38255148 PMCID: PMC10813763 DOI: 10.3390/biomedicines12010041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 12/03/2023] [Accepted: 12/12/2023] [Indexed: 01/24/2024] Open
Abstract
Spinal cord injury (SCI) is a serious neurological insult that disrupts the ascending and descending neural pathways between the peripheral nerves and the brain, leading to not only functional deficits in the injured area and below the level of the lesion but also morphological, structural, and functional reorganization of the brain. These changes introduce new challenges and uncertainties into the treatment of SCI. Rehabilitation training, a clinical intervention designed to promote functional recovery after spinal cord and brain injuries, has been reported to promote activation and functional reorganization of the cerebral cortex through multiple physiological mechanisms. In this review, we evaluate the potential mechanisms of exercise that affect the brain structure and function, as well as the rehabilitation training process for the brain after SCI. Additionally, we compare and discuss the principles, effects, and future directions of several rehabilitation training methods that facilitate cerebral cortex activation and recovery after SCI. Understanding the regulatory role of rehabilitation training at the supraspinal center is of great significance for clinicians to develop SCI treatment strategies and optimize rehabilitation plans.
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Affiliation(s)
- Le-Wei He
- Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China; (L.-W.H.); (X.-J.G.)
| | - Xiao-Jun Guo
- Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China; (L.-W.H.); (X.-J.G.)
| | - Can Zhao
- Institute of Rehabilitation Engineering, China Rehabilitation Science Institute, Beijing 100068, China
| | - Jia-Sheng Rao
- Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China; (L.-W.H.); (X.-J.G.)
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77
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Snyder WE, Vértes PE, Kyriakopoulou V, Wagstyl K, Williams LZJ, Moraczewski D, Thomas AG, Karolis VR, Seidlitz J, Rivière D, Robinson EC, Mangin JF, Raznahan A, Bullmore ET. A bipolar taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.19.572454. [PMID: 38168226 PMCID: PMC10760196 DOI: 10.1101/2023.12.19.572454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (N=34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bipolar distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex; complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (N=228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.
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Affiliation(s)
- William E Snyder
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Logan Z J Williams
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Dustin Moraczewski
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, Maryland, USA
| | - Adam G Thomas
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, Maryland, USA
| | - Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Jakob Seidlitz
- Lifespan Brain Institute, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Denis Rivière
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, 91191, France
| | - Emma C Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Jean-Francois Mangin
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, 91191, France
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
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78
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Keller AS, Pines AR, Shanmugan S, Sydnor VJ, Cui Z, Bertolero MA, Barzilay R, Alexander-Bloch AF, Byington N, Chen A, Conan GM, Davatzikos C, Feczko E, Hendrickson TJ, Houghton A, Larsen B, Li H, Miranda-Dominguez O, Roalf DR, Perrone A, Shetty A, Shinohara RT, Fan Y, Fair DA, Satterthwaite TD. Personalized functional brain network topography is associated with individual differences in youth cognition. Nat Commun 2023; 14:8411. [PMID: 38110396 PMCID: PMC10728159 DOI: 10.1038/s41467-023-44087-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 11/29/2023] [Indexed: 12/20/2023] Open
Abstract
Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain's functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) that account for interindividual heterogeneity in functional brain network topography in 9-10 year olds from the Adolescent Brain Cognitive Development℠ Study. Across matched discovery (n = 3525) and replication (n = 3447) samples, the total cortical representation of fronto-parietal PFNs positively correlates with general cognition. Cross-validated ridge regressions trained on PFN topography predict cognition in unseen data across domains, with prediction accuracy increasing along the cortex's sensorimotor-association organizational axis. These results establish that functional network topography heterogeneity is associated with individual differences in cognition before the critical transition into adolescence.
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Affiliation(s)
- Arielle S Keller
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Adam R Pines
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sheila Shanmugan
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Maxwell A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ran Barzilay
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Nora Byington
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Andrew Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Gregory M Conan
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Eric Feczko
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Timothy J Hendrickson
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
- University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Audrey Houghton
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Hongming Li
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Oscar Miranda-Dominguez
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Anders Perrone
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Alisha Shetty
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yong Fan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
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79
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Knodt AR, Elliott ML, Whitman ET, Winn A, Addae A, Ireland D, Poulton R, Ramrakha S, Caspi A, Moffitt TE, Hariri AR. Test-retest reliability and predictive utility of a macroscale principal functional connectivity gradient. Hum Brain Mapp 2023; 44:6399-6417. [PMID: 37851700 PMCID: PMC10681655 DOI: 10.1002/hbm.26517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 09/23/2023] [Accepted: 09/30/2023] [Indexed: 10/20/2023] Open
Abstract
Mapping individual differences in brain function has been hampered by poor reliability as well as limited interpretability. Leveraging patterns of brain-wide functional connectivity (FC) offers some promise in this endeavor. In particular, a macroscale principal FC gradient that recapitulates a hierarchical organization spanning molecular, cellular, and circuit level features along a sensory-to-association cortical axis has emerged as both a parsimonious and interpretable measure of individual differences in behavior. However, the measurement reliabilities of this FC gradient have not been fully evaluated. Here, we assess the reliabilities of both global and regional principal FC gradient measures using test-retest data from the young adult Human Connectome Project (HCP-YA) and the Dunedin Study. Analyses revealed that the reliabilities of principal FC gradient measures were (1) consistently higher than those for traditional edge-wise FC measures, (2) higher for FC measures derived from general FC (GFC) in comparison with resting-state FC, and (3) higher for longer scan lengths. We additionally examined the relative utility of these principal FC gradient measures in predicting cognition and aging in both datasets as well as the HCP-aging dataset. These analyses revealed that regional FC gradient measures and global gradient range were significantly associated with aging in all three datasets, and moderately associated with cognition in the HCP-YA and Dunedin Study datasets, reflecting contractions and expansions of the cortical hierarchy, respectively. Collectively, these results demonstrate that measures of the principal FC gradient, especially derived using GFC, effectively capture a reliable feature of the human brain subject to interpretable and biologically meaningful individual variation, offering some advantages over traditional edge-wise FC measures in the search for brain-behavior associations.
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Affiliation(s)
- Annchen R. Knodt
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - Maxwell L. Elliott
- Department of Psychology, Center for Brain ScienceHarvard UniversityCambridgeMassachusettsUSA
| | - Ethan T. Whitman
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - Alex Winn
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - Angela Addae
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Avshalom Caspi
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
- Institute of Psychiatry, Psychology, and NeuroscienceKing's College LondonLondonUK
| | - Terrie E. Moffitt
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
- Institute of Psychiatry, Psychology, and NeuroscienceKing's College LondonLondonUK
| | - Ahmad R. Hariri
- Department of Psychology and NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
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80
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Persson Waye K, Löve J, Lercher P, Dzhambov AM, Klatte M, Schreckenberg D, Belke C, Leist L, Ristovska G, Jeram S, Kanninen KM, Selander J, Arat A, Lachmann T, Clark C, Botteldooren D, White K, Julvez J, Foraster M, Kaprio J, Bolte G, Psyllidis A, Gulliver J, Boshuizen H, Bozzon A, Fels J, Hornikx M, van den Hazel P, Weber M, Brambilla M, Braat-Eggen E, Van Kamp I, Vincens N. Adopting a child perspective for exposome research on mental health and cognitive development - Conceptualisation and opportunities. ENVIRONMENTAL RESEARCH 2023; 239:117279. [PMID: 37778607 DOI: 10.1016/j.envres.2023.117279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 09/27/2023] [Accepted: 09/29/2023] [Indexed: 10/03/2023]
Abstract
Mental disorders among children and adolescents pose a significant global challenge. The exposome framework covering the totality of internal, social and physical exposures over a lifetime provides opportunities to better understand the causes of and processes related to mental health, and cognitive functioning. The paper presents a conceptual framework on exposome, mental health, and cognitive development in children and adolescents, with potential mediating pathways, providing a possibility for interventions along the life course. The paper underscores the significance of adopting a child perspective to the exposome, acknowledging children's specific vulnerability, including differential exposures, susceptibility of effects and capacity to respond; their susceptibility during development and growth, highlighting neurodevelopmental processes from conception to young adulthood that are highly sensitive to external exposures. Further, critical periods when exposures may have significant effects on a child's development and future health are addressed. The paper stresses that children's behaviour, physiology, activity pattern and place for activities make them differently vulnerable to environmental pollutants, and calls for child-specific assessment methods, currently lacking within today's health frameworks. The importance of understanding the interplay between structure and agency is emphasized, where agency is guided by social structures and practices and vice-versa. An intersectional approach that acknowledges the interplay of social and physical exposures as well as a global and rural perspective on exposome is further pointed out. To advance the exposome field, interdisciplinary efforts that involve multiple scientific disciplines are crucial. By adopting a child perspective and incorporating an exposome approach, we can gain a comprehensive understanding of how exposures impact children's mental health and cognitive development leading to better outcomes.
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Affiliation(s)
- Kerstin Persson Waye
- School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
| | - Jesper Löve
- School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Peter Lercher
- Institute of Highway Engineering and Transport Planning, Graz University of Technology, Graz, Austria
| | - Angel M Dzhambov
- Institute of Highway Engineering and Transport Planning, Graz University of Technology, Graz, Austria; Department of Hygiene, Faculty of Public Health, Medical University of Plovdiv, Plovdiv, Bulgaria; Research Group "Health and Quality of Life in a Green and Sustainable Environment", SRIPD, Medical University of Plovdiv, Plovdiv, Bulgaria; Environmental Health Division, Research Institute at Medical University of Plovdiv, Medical University of Plovdiv, Bulgaria
| | - Maria Klatte
- Cognitive and Developmental Psychology, University of Kaiserslautern-Landau, Kaiserslautern, Germany
| | - Dirk Schreckenberg
- Centre for Applied Psychology, Environmental and Social Research (Zeus GmbH), Hagen, Germany
| | - Christin Belke
- Centre for Applied Psychology, Environmental and Social Research (Zeus GmbH), Hagen, Germany
| | - Larisa Leist
- Cognitive and Developmental Psychology, University of Kaiserslautern-Landau, Kaiserslautern, Germany
| | - Gordana Ristovska
- Institute of Public Health of the Republic of North Macedonia, Skopje, Macedonia
| | - Sonja Jeram
- National Institute of Public Health, Ljubljana, Slovenia
| | - Katja M Kanninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jenny Selander
- Unit of Occupational Medicine, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Arzu Arat
- Unit of Occupational Medicine, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Thomas Lachmann
- Cognitive and Developmental Psychology, University of Kaiserslautern-Landau, Kaiserslautern, Germany; Centro de Investigación Nebrija en Cognición (CINC), Universidad Nebrija, Madrid, Spain
| | - Charlotte Clark
- Population Health Research Institute, St George's, University of London, London, United Kingdom
| | - Dick Botteldooren
- Department of Information Technology, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium
| | - Kim White
- National Institute for Public Health and the Environment, Netherlands
| | - Jordi Julvez
- Institut D'Investigació Sanitària Pere Virgili (IISPV), Clinical and Epidemiological Neuroscience Group (NeuroÈpia), Reus, Spain
| | | | - Jaakko Kaprio
- Institute for Molecular Medicine Finland and Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Gabriele Bolte
- Institute of Public Health and Nursing Research, University of Bremen, Bremen, Germany
| | - Achilleas Psyllidis
- Department of Sustainable Design Engineering, Delft University of Technology, Delft, the Netherlands
| | - John Gulliver
- Population Health Research Institute, St George's, University of London, London, United Kingdom; Centre for Environmental Health and Sustainability & School of Geography, Geology and the Environment, University of Leicester, Leicester, United Kingdom
| | - Hendriek Boshuizen
- Department for Statistics, Datascience and Mathematical Modelling, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Alessandro Bozzon
- Department of Sustainable Design Engineering, Delft University of Technology, Delft, the Netherlands
| | - Janina Fels
- Institute for Hearing Technology and Acoustics, RWTH Aachen University, Aachen, Germany
| | - Maarten Hornikx
- Department of the Built Environment, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Peter van den Hazel
- International Network on Children's Health, Environment and Safety, Ellecom, the Netherlands
| | | | - Marco Brambilla
- Data Science Laboratory, Politecnico di Milano, Milan, Italy
| | | | - Irene Van Kamp
- National Institute for Public Health and the Environment, Netherlands
| | - Natalia Vincens
- School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
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81
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Lewis L, Corcoran M, Cho KIK, Kwak Y, Hayes RA, Larsen B, Jalbrzikowski M. Age-associated alterations in thalamocortical structural connectivity in youths with a psychosis-spectrum disorder. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:86. [PMID: 38081873 PMCID: PMC10713597 DOI: 10.1038/s41537-023-00411-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/30/2023] [Indexed: 12/23/2023]
Abstract
Psychotic symptoms typically emerge in adolescence. Age-associated thalamocortical connectivity differences in psychosis remain unclear. We analyzed diffusion-weighted imaging data from 1254 participants 8-23 years old (typically developing (TD):N = 626, psychosis-spectrum (PS): N = 329, other psychopathology (OP): N = 299) from the Philadelphia Neurodevelopmental Cohort. We modeled thalamocortical tracts using deterministic fiber tractography, extracted Q-Space Diffeomorphic Reconstruction (QSDR) and diffusion tensor imaging (DTI) measures, and then used generalized additive models to determine group and age-associated thalamocortical connectivity differences. Compared to other groups, PS exhibited thalamocortical reductions in QSDR global fractional anisotropy (GFA, p-values range = 3.0 × 10-6-0.05) and DTI fractional anisotropy (FA, p-values range = 4.2 × 10-4-0.03). Compared to TD, PS exhibited shallower thalamus-prefrontal age-associated increases in GFA and FA during mid-childhood, but steeper age-associated increases during adolescence. TD and OP exhibited decreases in thalamus-frontal mean and radial diffusivities during adolescence; PS did not. Altered developmental trajectories of thalamocortical connectivity may contribute to the disruptions observed in adults with psychosis.
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Affiliation(s)
- Lydia Lewis
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Mary Corcoran
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Kang Ik K Cho
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - YooBin Kwak
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Rebecca A Hayes
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Bart Larsen
- Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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82
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Bazinet V, Hansen JY, Misic B. Towards a biologically annotated brain connectome. Nat Rev Neurosci 2023; 24:747-760. [PMID: 37848663 DOI: 10.1038/s41583-023-00752-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/20/2023] [Indexed: 10/19/2023]
Abstract
The brain is a network of interleaved neural circuits. In modern connectomics, brain connectivity is typically encoded as a network of nodes and edges, abstracting away the rich biological detail of local neuronal populations. Yet biological annotations for network nodes - such as gene expression, cytoarchitecture, neurotransmitter receptors or intrinsic dynamics - can be readily measured and overlaid on network models. Here we review how connectomes can be represented and analysed as annotated networks. Annotated connectomes allow us to reconceptualize architectural features of networks and to relate the connection patterns of brain regions to their underlying biology. Emerging work demonstrates that annotated connectomes help to make more veridical models of brain network formation, neural dynamics and disease propagation. Finally, annotations can be used to infer entirely new inter-regional relationships and to construct new types of network that complement existing connectome representations. In summary, biologically annotated connectomes offer a compelling way to study neural wiring in concert with local biological features.
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Affiliation(s)
- Vincent Bazinet
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada.
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83
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Holmes A, Levi PT, Chen YC, Chopra S, Aquino KM, Pang JC, Fornito A. Disruptions of Hierarchical Cortical Organization in Early Psychosis and Schizophrenia. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1240-1250. [PMID: 37683727 DOI: 10.1016/j.bpsc.2023.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/27/2023] [Accepted: 08/14/2023] [Indexed: 09/10/2023]
Abstract
BACKGROUND The cerebral cortex is organized hierarchically along an axis that spans unimodal sensorimotor to transmodal association areas. This hierarchy is often characterized using low-dimensional embeddings, termed gradients, of interregional functional coupling estimates measured with resting-state functional magnetic resonance imaging. Such analyses may offer insights into the pathophysiology of schizophrenia, which has been frequently linked to dysfunctional interactions between association and sensorimotor areas. METHODS To examine disruptions of hierarchical cortical function across distinct stages of psychosis, we applied diffusion map embedding to 2 independent functional magnetic resonance imaging datasets: one comprising 114 patients with early psychosis and 48 control participants, and the other comprising 50 patients with established schizophrenia and 121 control participants. Then, we analyzed the primary sensorimotor-to-association and secondary visual-to-sensorimotor gradients of each participant in both datasets. RESULTS There were no significant differences in regional gradient scores between patients with early psychosis and control participants. Patients with established schizophrenia showed significant differences in the secondary, but not primary, gradient compared with control participants. Gradient differences in schizophrenia were characterized by lower within-network dispersion in the dorsal attention (false discovery rate [FDR]-corrected p [pFDR] < .001), visual (pFDR = .003), frontoparietal (pFDR = .018), and limbic (pFDR = .020) networks and lower between-network dispersion between the visual network and other networks (pFDR < .001). CONCLUSIONS These findings indicate that differences in cortical hierarchical function occur along the secondary visual-to-sensorimotor axis rather than the primary sensorimotor-to-association axis as previously thought. The absence of differences in early psychosis suggests that visual-sensorimotor abnormalities may emerge as the illness progresses.
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Affiliation(s)
- Alexander Holmes
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia.
| | - Priscila T Levi
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
| | - Yu-Chi Chen
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia; Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Sidhant Chopra
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Kevin M Aquino
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - James C Pang
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
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84
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Cattarinussi G, Grimaldi DA, Sambataro F. Spontaneous Brain Activity Alterations in First-Episode Psychosis: A Meta-analysis of Functional Magnetic Resonance Imaging Studies. Schizophr Bull 2023; 49:1494-1507. [PMID: 38029279 PMCID: PMC10686347 DOI: 10.1093/schbul/sbad044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
BACKGROUND AND HYPOTHESIS Several studies have shown that spontaneous brain activity, including the total and fractional amplitude of low-frequency fluctuations (LFF) and regional homogeneity (ReHo), is altered in psychosis. Nonetheless, neuroimaging results show a high heterogeneity. For this reason, we gathered the extant literature on spontaneous brain activity in first-episode psychosis (FEP), where the effects of long-term treatment and chronic disease are minimal. STUDY DESIGN A systematic research was conducted on PubMed, Scopus, and Web of Science to identify studies exploring spontaneous brain activity and local connectivity in FEP estimated using functional magnetic resonance imaging. 20 LFF and 15 ReHo studies were included. Coordinate-Based Activation Likelihood Estimation Meta-Analyses stratified by brain measures, age (adolescent vs adult), and drug-naïve status were performed to identify spatially-convergent alterations in spontaneous brain activity in FEP. STUDY RESULTS We found a significant increase in LFF in FEP compared to healthy controls (HC) in the right striatum and in ReHo in the left striatum. When pooling together all studies on LFF and ReHo, spontaneous brain activity was increased in the bilateral striatum and superior and middle frontal gyri and decreased in the right precentral gyrus and the right inferior frontal gyrus compared to HC. These results were also replicated in the adult and drug-naïve samples. CONCLUSIONS Abnormalities in the frontostriatal circuit are present in early psychosis independently of treatment status. Our findings support the view that altered frontostriatal can represent a core neural alteration of the disorder and could be a target of treatment.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
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85
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Hansen JY, Cauzzo S, Singh K, García-Gomar MG, Shine JM, Bianciardi M, Misic B. Integrating brainstem and cortical functional architectures. RESEARCH SQUARE 2023:rs.3.rs-3569352. [PMID: 38076888 PMCID: PMC10705693 DOI: 10.21203/rs.3.rs-3569352/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
The brainstem is a fundamental component of the central nervous system yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. Here we use high-resolution 7 Tesla fMRI to derive a functional connectome encompassing cortex as well as 58 brainstem nuclei spanning the midbrain, pons and medulla. We identify a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as multiple emergent phenomena including neurophysiological oscillatory rhythms, patterns of cognitive functional specialization, and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicate all findings using 3 Tesla data from the same participants. Collectively, we find that multiple organizational features of cortical activity can be traced back to the brainstem.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Parkinson’s Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - James M. Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard University, Boston, MA, USA
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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86
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Kim JZ, Larsen B, Parkes L. Shaping dynamical neural computations using spatiotemporal constraints. ARXIV 2023:arXiv:2311.15572v1. [PMID: 38076517 PMCID: PMC10705584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
Dynamics play a critical role in computation. The principled evolution of states over time enables both biological and artificial networks to represent and integrate information to make decisions. In the past few decades, significant multidisciplinary progress has been made in bridging the gap between how we understand biological versus artificial computation, including how insights gained from one can translate to the other. Research has revealed that neurobiology is a key determinant of brain network architecture, which gives rise to spatiotemporally constrained patterns of activity that underlie computation. Here, we discuss how neural systems use dynamics for computation, and claim that the biological constraints that shape brain networks may be leveraged to improve the implementation of artificial neural networks. To formalize this discussion, we consider a natural artificial analog of the brain that has been used extensively to model neural computation: the recurrent neural network (RNN). In both the brain and the RNN, we emphasize the common computational substrate atop which dynamics occur-the connectivity between neurons-and we explore the unique computational advantages offered by biophysical constraints such as resource efficiency, spatial embedding, and neurodevelopment.
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Affiliation(s)
- Jason Z. Kim
- Department of Physics, Cornell University, Ithaca, NY 14853, USA
| | - Bart Larsen
- Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota
| | - Linden Parkes
- Department of Psychiatry, Rutgers University, Piscataway, NJ 08854, USA
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87
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Schinz D, Schmitz-Koep B, Tahedl M, Teckenberg T, Schultz V, Schulz J, Zimmer C, Sorg C, Gaser C, Hedderich DM. Lower cortical thickness and increased brain aging in adults with cocaine use disorder. Front Psychiatry 2023; 14:1266770. [PMID: 38025412 PMCID: PMC10679447 DOI: 10.3389/fpsyt.2023.1266770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Background Cocaine use disorder (CUD) is a global health issue with severe behavioral and cognitive sequelae. While previous evidence suggests a variety of structural and age-related brain changes in CUD, the impact on both, cortical thickness and brain age measures remains unclear. Methods Derived from a publicly available data set (SUDMEX_CONN), 74 CUD patients and 62 matched healthy controls underwent brain MRI and behavioral-clinical assessment. We determined cortical thickness by surface-based morphometry using CAT12 and Brain Age Gap Estimate (BrainAGE) via relevance vector regression. Associations between structural brain changes and behavioral-clinical variables of patients with CUD were investigated by correlation analyses. Results We found significantly lower cortical thickness in bilateral prefrontal cortices, posterior cingulate cortices, and the temporoparietal junction and significantly increased BrainAGE in patients with CUD [mean (SD) = 1.97 (±3.53)] compared to healthy controls (p < 0.001, Cohen's d = 0.58). Increased BrainAGE was associated with longer cocaine abuse duration. Conclusion Results demonstrate structural brain abnormalities in CUD, particularly lower cortical thickness in association cortices and dose-dependent, increased brain age.
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Affiliation(s)
- David Schinz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen- (FAU), Nürnberg, Germany
| | - Benita Schmitz-Koep
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Marlene Tahedl
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Timo Teckenberg
- Digital Management & Transformation, SRH Fernhochschule - The Mobile University, Riedlingen, Germany
| | - Vivian Schultz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julia Schulz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Sorg
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Psychiatry, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena-Magdeburg-Halle, Germany
| | - Dennis M. Hedderich
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
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88
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Luppi AI, Golkowski D, Ranft A, Ilg R, Jordan D, Bzdok D, Owen AM, Naci L, Stamatakis EA, Amico E, Misic B. General anaesthesia reduces the uniqueness of brain connectivity across individuals and across species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.08.566332. [PMID: 38014199 PMCID: PMC10680788 DOI: 10.1101/2023.11.08.566332] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The human brain is characterised by idiosyncratic patterns of spontaneous thought, rendering each brain uniquely identifiable from its neural activity. However, deep general anaesthesia suppresses subjective experience. Does it also suppress what makes each brain unique? Here we used functional MRI under the effects of the general anaesthetics sevoflurane and propofol to determine whether anaesthetic-induced unconsciousness diminishes the uniqueness of the human brain: both with respect to the brains of other individuals, and the brains of another species. We report that under anaesthesia individual brains become less self-similar and less distinguishable from each other. Loss of distinctiveness is highly organised: it co-localises with the archetypal sensory-association axis, correlating with genetic and morphometric markers of phylogenetic differences between humans and other primates. This effect is more evident at greater anaesthetic depths, reproducible across sevoflurane and propofol, and reversed upon recovery. Providing convergent evidence, we show that under anaesthesia the functional connectivity of the human brain becomes more similar to the macaque brain. Finally, anaesthesia diminishes the match between spontaneous brain activity and meta-analytic brain patterns aggregated from the NeuroSynth engine. Collectively, the present results reveal that anaesthetised human brains are not only less distinguishable from each other, but also less distinguishable from the brains of other primates, with specifically human-expanded regions being the most affected by anaesthesia.
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89
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Michael C, Taxali A, Angstadt M, Kardan O, Weigard A, Molloy MF, McCurry KL, Hyde LW, Heitzeg MM, Sripada C. Socioeconomic resources in youth are linked to divergent patterns of network integration and segregation across the brain's transmodal axis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.08.565517. [PMID: 38014302 PMCID: PMC10680554 DOI: 10.1101/2023.11.08.565517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Socioeconomic resources (SER) calibrate the developing brain to the current context, which can confer or attenuate risk for psychopathology across the lifespan. Recent multivariate work indicates that SER levels powerfully influence intrinsic functional connectivity patterns across the entire brain. Nevertheless, the neurobiological meaning of these widespread alterations remains poorly understood, despite its translational promise for early risk identification, targeted intervention, and policy reform. In the present study, we leverage the resources of graph theory to precisely characterize multivariate and univariate associations between household SER and the functional integration and segregation (i.e., participation coefficient, within-module degree) of brain regions across major cognitive, affective, and sensorimotor systems during the resting state in 5,821 youth (ages 9-10 years) from the Adolescent Brain Cognitive Development (ABCD) Study. First, we establish that decomposing the brain into profiles of integration and segregation captures more than half of the multivariate association between SER and functional connectivity with greater parsimony (100-fold reduction in number of features) and interpretability. Second, we show that the topological effects of SER are not uniform across the brain; rather, higher SER levels are related to greater integration of somatomotor and subcortical systems, but greater segregation of default mode, orbitofrontal, and cerebellar systems. Finally, we demonstrate that the effects of SER are spatially patterned along the unimodal-transmodal gradient of brain organization. These findings provide critical interpretive context for the established and widespread effects of SER on brain organization, indicating that SER levels differentially configure the intrinsic functional architecture of developing unimodal and transmodal systems. This study highlights both sensorimotor and higher-order networks that may serve as neural markers of environmental stress and opportunity, and which may guide efforts to scaffold healthy neurobehavioral development among disadvantaged communities of youth.
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90
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Myers MJ, Labonte AK, Gordon EM, Laumann TO, Tu JC, Wheelock MD, Nielsen AN, Schwarzlose R, Camacho MC, Warner BB, Raghuraman N, Luby JL, Barch DM, Fair DA, Petersen SE, Rogers CE, Smyser CD, Sylvester CM. Functional parcellation of the neonatal brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.10.566629. [PMID: 37986902 PMCID: PMC10659431 DOI: 10.1101/2023.11.10.566629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that adult- and older infant-derived parcels are a poor fit with neonatal data, emphasizing the need for neonatal-specific parcels. We next derive a set of 283 cortical surface parcels from a sample of n=261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.
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Affiliation(s)
- Michael J Myers
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Alyssa K Labonte
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
- Neurosciences Graduate Program, Washington University in St. Louis, St. Louis, MO USA
| | - Evan M Gordon
- Department of Radiology, Washington University in St. Louis, St. Louis, MO USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Jiaxin Cindy Tu
- Neurosciences Graduate Program, Washington University in St. Louis, St. Louis, MO USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO USA
| | - Muriah D Wheelock
- Department of Radiology, Washington University in St. Louis, St. Louis, MO USA
| | - Ashley N Nielsen
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Rebecca Schwarzlose
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - M Catalina Camacho
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Barbara B Warner
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
| | - Nandini Raghuraman
- Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, USA
| | - Joan L Luby
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Steven E Petersen
- Department of Radiology, Washington University in St. Louis, St. Louis, MO USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Cynthia E Rogers
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Christopher D Smyser
- Department of Radiology, Washington University in St. Louis, St. Louis, MO USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO USA
- Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, MO, USA
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91
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Schmitz‐Koep B, Menegaux A, Zimmermann J, Thalhammer M, Neubauer A, Wendt J, Schinz D, Daamen M, Boecker H, Zimmer C, Priller J, Wolke D, Bartmann P, Sorg C, Hedderich DM. Altered gray-to-white matter tissue contrast in preterm-born adults. CNS Neurosci Ther 2023; 29:3199-3211. [PMID: 37365964 PMCID: PMC10580354 DOI: 10.1111/cns.14320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 06/01/2023] [Accepted: 06/10/2023] [Indexed: 06/28/2023] Open
Abstract
AIMS To investigate cortical organization in brain magnetic resonance imaging (MRI) of preterm-born adults using percent contrast of gray-to-white matter signal intensities (GWPC), which is an in vivo proxy measure for cortical microstructure. METHODS Using structural MRI, we analyzed GWPC at different percentile fractions across the cortex (0%, 10%, 20%, 30%, 40%, 50%, and 60%) in a large and prospectively collected cohort of 86 very preterm-born (<32 weeks of gestation and/or birth weight <1500 g, VP/VLBW) adults and 103 full-term controls at 26 years of age. Cognitive performance was assessed by full-scale intelligence quotient (IQ) using the Wechsler Adult Intelligence Scale. RESULTS GWPC was significantly decreased in VP/VLBW adults in frontal, parietal, and temporal associative cortices, predominantly in the right hemisphere. Differences were pronounced at 20%, 30%, and 40%, hence, in middle cortical layers. GWPC was significantly increased in right paracentral lobule in VP/VLBW adults. GWPC in frontal and temporal cortices was positively correlated with birth weight, and negatively with duration of ventilation (p < 0.05). Furthermore, GWPC in right paracentral lobule was negatively correlated with IQ (p < 0.05). CONCLUSIONS Widespread aberrant gray-to-white matter contrast suggests lastingly altered cortical microstructure after preterm birth, mainly in middle cortical layers, with differential effects on associative and primary cortices.
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Affiliation(s)
- Benita Schmitz‐Koep
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Aurore Menegaux
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Juliana Zimmermann
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Melissa Thalhammer
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Antonia Neubauer
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Jil Wendt
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - David Schinz
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Marcel Daamen
- Department of Diagnostic and Interventional RadiologyUniversity Hospital Bonn, Clinical Functional Imaging GroupBonnGermany
- Department of Neonatology and Pediatric Intensive CareUniversity Hospital BonnBonnGermany
| | - Henning Boecker
- Department of Diagnostic and Interventional RadiologyUniversity Hospital Bonn, Clinical Functional Imaging GroupBonnGermany
| | - Claus Zimmer
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
| | - Josef Priller
- Department of PsychiatryTechnical University of Munich, School of MedicineMunichGermany
| | - Dieter Wolke
- Department of PsychologyUniversity of WarwickCoventryUK
- Warwick Medical SchoolUniversity of WarwickCoventryUK
| | - Peter Bartmann
- Department of Neonatology and Pediatric Intensive CareUniversity Hospital BonnBonnGermany
| | - Christian Sorg
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
- Department of PsychiatryTechnical University of Munich, School of MedicineMunichGermany
| | - Dennis M. Hedderich
- Department of Diagnostic and Interventional NeuroradiologyTechnical University of Munich; School of MedicineMunichGermany
- Technical University of Munich, School of Medicine, TUM‐NIC Neuroimaging CenterMunichGermany
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92
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Pfarr JK, Meller T, Brosch K, Stein F, Thomas-Odenthal F, Evermann U, Wroblewski A, Ringwald KG, Hahn T, Meinert S, Winter A, Thiel K, Flinkenflügel K, Jansen A, Krug A, Dannlowski U, Kircher T, Gaser C, Nenadić I. Data-driven multivariate identification of gyrification patterns in a transdiagnostic patient cohort: A cluster analysis approach. Neuroimage 2023; 281:120349. [PMID: 37683808 DOI: 10.1016/j.neuroimage.2023.120349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 07/14/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023] Open
Abstract
BACKGROUND Multivariate data-driven statistical approaches offer the opportunity to study multi-dimensional interdependences between a large set of biological parameters, such as high-dimensional brain imaging data. For gyrification, a putative marker of early neurodevelopment, direct comparisons of patterns among multiple psychiatric disorders and investigations of potential heterogeneity of gyrification within one disorder and a transdiagnostic characterization of neuroanatomical features are lacking. METHODS In this study we used a data-driven, multivariate statistical approach to analyze cortical gyrification in a large cohort of N = 1028 patients with major psychiatric disorders (Major depressive disorder: n = 783, bipolar disorder: n = 129, schizoaffective disorder: n = 44, schizophrenia: n = 72) to identify cluster patterns of gyrification beyond diagnostic categories. RESULTS Cluster analysis applied on gyrification data of 68 brain regions (DK-40 atlas) identified three clusters showing difference in overall (global) gyrification and minor regional variation (regions). Newly, data-driven subgroups are further discriminative in cognition and transdiagnostic disease risk factors. CONCLUSIONS Results indicate that gyrification is associated with transdiagnostic risk factors rather than diagnostic categories and further imply a more global role of gyrification related to mental health than a disorder specific one. Our findings support previous studies highlighting the importance of association cortices involved in psychopathology. Explorative, data-driven approaches like ours can help to elucidate if the brain imaging data on hand and its a priori applied grouping actually has the potential to find meaningful effects or if previous hypotheses about the phenotype as well as its grouping have to be revisited.
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Affiliation(s)
- Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Department of Psychology, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany.
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
| | - Ulrika Evermann
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
| | - Adrian Wroblewski
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
| | - Kai G Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Germany; Institute for Translational Neuroscience, University of Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Germany
| | | | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany; Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Germany
| | - Axel Krug
- Department of Psychiatry und Psychotherapy, University Hospital Bonn, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
| | - Christian Gaser
- Department of Neurology, Jena University Hospital, Germany; Department of Psychiatry and Psychotherapy, Jena University Hospital, Germany; German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Jena-Magdeburg-Halle, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; Center for Mind, Brain and Behavior, Philipps-University Marburg, Germany
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93
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Linguiti S, Vogel JW, Sydnor VJ, Pines A, Wellman N, Basbaum A, Eickhoff CR, Eickhoff SB, Edwards RR, Larsen B, McKinstry-Wu A, Scott JC, Roalf DR, Sharma V, Strain EC, Corder G, Dworkin RH, Satterthwaite TD. Functional imaging studies of acute administration of classic psychedelics, ketamine, and MDMA: Methodological limitations and convergent results. Neurosci Biobehav Rev 2023; 154:105421. [PMID: 37802267 DOI: 10.1016/j.neubiorev.2023.105421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 10/02/2023] [Indexed: 10/08/2023]
Abstract
Functional magnetic resonance imaging (fMRI) is increasingly used to non-invasively study the acute impact of psychedelics on the human brain. While fMRI is a promising tool for measuring brain function in response to psychedelics, it also has known methodological challenges. We conducted a systematic review of fMRI studies examining acute responses to experimentally administered psychedelics in order to identify convergent findings and characterize heterogeneity in the literature. We reviewed 91 full-text papers; these studies were notable for substantial heterogeneity in design, task, dosage, drug timing, and statistical approach. Data recycling was common, with 51 unique samples across 91 studies. Fifty-seven studies (54%) did not meet contemporary standards for Type I error correction or control of motion artifact. Psilocybin and LSD were consistently reported to moderate the connectivity architecture of the sensorimotor-association cortical axis. Studies also consistently reported that ketamine administration increased activation in the dorsomedial prefrontal cortex. Moving forward, use of best practices such as pre-registration, standardized image processing and statistical testing, and data sharing will be important in this rapidly developing field.
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Affiliation(s)
- Sophia Linguiti
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Jacob W Vogel
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; Department of Clinical Sciences, Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; Department of Psychiatry, Stanford University, Stanford, CA, United States
| | - Nick Wellman
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Allan Basbaum
- Department of Anatomy, University of California, San Francisco, United States
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine, (INM-1, INM-7), Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, (INM-1, INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Robert R Edwards
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Andrew McKinstry-Wu
- Department of Anesthesiology and Critical Care, Neuroscience of Unconsciousness and Reanimation Research Alliance (NEURRAL), University of Pennsylvania, Philadelphia, United States
| | - J Cobb Scott
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; VISN4 Mental Illness Research, Education, and Clinical Center at the Corporal Michael J. Crescenz VA (Veterans Affairs) Medical Center, Philadelphia, PA, United States
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Vaishnavi Sharma
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Eric C Strain
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, 5510 Nathan Shock Drive, Baltimore, MD, United States
| | - Gregory Corder
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Robert H Dworkin
- Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.
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94
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Hansen JY, Cauzzo S, Singh K, García-Gomar MG, Shine JM, Bianciardi M, Misic B. Integrating brainstem and cortical functional architectures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564245. [PMID: 37961347 PMCID: PMC10634864 DOI: 10.1101/2023.10.26.564245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The brainstem is a fundamental component of the central nervous system yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. Here we use high-resolution 7 Tesla fMRI to derive a functional connectome encompassing cortex as well as 58 brainstem nuclei spanning the midbrain, pons and medulla. We identify a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as multiple emergent phenomena including neurophysiological oscillatory rhythms, patterns of cognitive functional specialization, and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicate all findings using 3 Tesla data from the same participants. Collectively, we find that multiple organizational features of cortical activity can be traced back to the brainstem.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Parkinson’s Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - James M. Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard University, Boston, MA, USA
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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95
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Baracchini G, Zhou Y, da Silva Castanheira J, Hansen JY, Rieck J, Turner GR, Grady CL, Misic B, Nomi J, Uddin LQ, Spreng RN. The biological role of local and global fMRI BOLD signal variability in human brain organization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.22.563476. [PMID: 37961684 PMCID: PMC10634715 DOI: 10.1101/2023.10.22.563476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Variability drives the organization and behavior of complex systems, including the human brain. Understanding the variability of brain signals is thus necessary to broaden our window into brain function and behavior. Few empirical investigations of macroscale brain signal variability have yet been undertaken, given the difficulty in separating biological sources of variance from artefactual noise. Here, we characterize the temporal variability of the most predominant macroscale brain signal, the fMRI BOLD signal, and systematically investigate its statistical, topographical and neurobiological properties. We contrast fMRI acquisition protocols, and integrate across histology, microstructure, transcriptomics, neurotransmitter receptor and metabolic data, fMRI static connectivity, and empirical and simulated magnetoencephalography data. We show that BOLD signal variability represents a spatially heterogeneous, central property of multi-scale multi-modal brain organization, distinct from noise. Our work establishes the biological relevance of BOLD signal variability and provides a lens on brain stochasticity across spatial and temporal scales.
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Affiliation(s)
- Giulia Baracchini
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Yigu Zhou
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jason da Silva Castanheira
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Justine Y. Hansen
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | | | - Gary R. Turner
- Department of Psychology, York University, Toronto, ON, Canada
| | - Cheryl L. Grady
- Rotman Research Institute at Baycrest, and Department of Psychiatry and Psychology, University of Toronto, Toronto, ON, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jason Nomi
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, USA
| | - Lucina Q. Uddin
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, USA
| | - R. Nathan Spreng
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
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96
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Kraft D, Alnæs D, Kaufmann T. Domain adapted brain network fusion captures variance related to pubertal brain development and mental health. Nat Commun 2023; 14:6698. [PMID: 37872174 PMCID: PMC10593774 DOI: 10.1038/s41467-023-41839-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 09/15/2023] [Indexed: 10/25/2023] Open
Abstract
Puberty demarks a period of profound brain dynamics that orchestrates changes to a multitude of neuroimaging-derived phenotypes. This complexity poses a dimensionality problem when attempting to chart an individual's brain development over time. Here, we illustrate that shifts in subject similarity of brain imaging data relate to pubertal maturation in the longitudinal ABCD study. Given that puberty depicts a critical window for emerging mental health issues, we additionally show that our model is capable of capturing variance in the adolescent brain related to psychopathology in a population-based and a clinical cohort. These results suggest that low-dimensional reference spaces based on subject similarities render useful to chart variance in brain development in youths.
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Affiliation(s)
- Dominik Kraft
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany.
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Tobias Kaufmann
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany.
- Norwegian Centre for Mental Disorders Research, University of Oslo and Oslo University Hospital, Oslo, Norway.
- German Center for Mental Health (DZPG), partner site Tübingen, Tübingen, Germany.
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97
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Wang D, Fan Q, Xiao X, He H, Yang Y, Li Y. Structural Fingerprinting of the Frontal Aslant Tract: Predicting Cognitive Control Capacity and Obsessive-Compulsive Symptoms. J Neurosci 2023; 43:7016-7027. [PMID: 37696666 PMCID: PMC10586535 DOI: 10.1523/jneurosci.0628-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/29/2023] [Accepted: 08/18/2023] [Indexed: 09/13/2023] Open
Abstract
White matter of the human brain is influenced by common genetic variations and shaped by neural activity-dependent experiences. Variations in microstructure of cerebral white matter across individuals and even across fiber tracts might underlie differences in cognitive capacity and vulnerabilities to mental disorders. The frontoparietal and cingulo-opercular networks of the brain constitute the central system supporting cognitive functions, and functional connectivity of these networks has been used to distinguish individuals known as "functional fingerprinting." The frontal aslant tract (FAT) that passes through the two networks has been implicated in executive functions. However, whether FAT can be used as a "structural fingerprint" to distinguish individuals and predict an individual's cognitive function and dysfunction is unknown. Here we investigated the fingerprinting property of FAT microstructural profiles using three independent diffusion MRI datasets with repeated scans on human participants including both females and males. We found that diffusion and geometric profiles of FAT can be used to distinguish individuals with a high accuracy. Next, we demonstrated that fractional anisotropy in different FAT segments predicted distinct cognitive functions, including working memory, inhibitory control, and relational reasoning. Finally, we assessed the contribution of altered FAT microstructural profiles to cognitive dysfunction in unmedicated patients with obsessive-compulsive disorders. We found that the altered microstructure in FAT was associated with the severity of obsessive-compulsive symptoms. Collectively, our findings suggest that the microstructural profiles of FAT can identify individuals with a high accuracy and may serve as an imaging marker for predicting an individual's cognitive capacity and disease severity.SIGNIFICANCE STATEMENT The frontoparietal network and cingulo-opercular network of the brain constitute a dual-network architecture for human cognitive functions, and functional connectivity of these two networks can be used as a "functional fingerprint" to distinguish individuals. However, the structural underpinnings of these networks subserving individual heterogeneities in their functional connectivity and cognitive ability remain unknown. We show here that the frontal aslant tract (FAT) that passes through the two networks distinguishes individuals with a high accuracy. Further, we demonstrate that the diffusion profiles of FAT predict distinct cognitive functions in healthy subjects and are associated with the clinical symptoms in patients with obsessive-compulsive disorders. Our findings suggest that the FAT may serve as a unique structural fingerprint underlying individual cognitive capability.
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Affiliation(s)
- Danni Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, People's Republic of China
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland 21224
| | - Qing Fan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, People's Republic of China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, People's Republic of China
| | - Xiang Xiao
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland 21224
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou 310027, People's Republic of China
- School of Physics, Zhejiang University, Hangzhou 310027, People's Republic of China
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland 21224
| | - Yao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, People's Republic of China
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98
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Liao Z, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Paillère Martinot ML, Artiges E, Nees F, Papadopoulos Orfanos D, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Paus T. Hemispheric asymmetry in cortical thinning reflects intrinsic organization of the neurotransmitter systems and homotopic functional connectivity. Proc Natl Acad Sci U S A 2023; 120:e2306990120. [PMID: 37831741 PMCID: PMC10589642 DOI: 10.1073/pnas.2306990120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 09/07/2023] [Indexed: 10/15/2023] Open
Abstract
Hemispheric lateralization and its origins have been of great interest in neuroscience for over a century. The left-right asymmetry in cortical thickness may stem from differential maturation of the cerebral cortex in the two hemispheres. Here, we investigated the spatial pattern of hemispheric differences in cortical thinning during adolescence, and its relationship with the density of neurotransmitter receptors and homotopic functional connectivity. Using longitudinal data from IMAGEN study (N = 532), we found that many cortical regions in the frontal and temporal lobes thinned more in the right hemisphere than in the left. Conversely, several regions in the occipital and parietal lobes thinned less in the right (vs. left) hemisphere. We then revealed that regions thinning more in the right (vs. left) hemispheres had higher density of neurotransmitter receptors and transporters in the right (vs. left) side. Moreover, the hemispheric differences in cortical thinning were predicted by homotopic functional connectivity. Specifically, regions with stronger homotopic functional connectivity showed a more symmetrical rate of cortical thinning between the left and right hemispheres, compared with regions with weaker homotopic functional connectivity. Based on these findings, we suggest that the typical patterns of hemispheric differences in cortical thinning may reflect the intrinsic organization of the neurotransmitter systems and related patterns of homotopic functional connectivity.
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Affiliation(s)
- Zhijie Liao
- Research Centre of Sainte-Justine University Hospital, Montreal, QCH3T 1C5, Canada
- Department of Psychiatry and Addictology, University of Montreal, Montreal, QCH3T 1J4, Canada
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
| | - Arun L. W. Bokde
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, Social, Genetic & Developmental Psychiatry Centre, King’s College London, LondonSE5 8AF, United Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim69117, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim68131, Germany
| | - Antoine Grigis
- NeuroSpin, Energies and Atomic Energy Commission, Université Paris-Saclay, Paris F-91191, France
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT05405
- Department of Psychology, University of Vermont, Burlington, VT05405
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, NottinghamNG7 2RD, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin10117, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin38116, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Developmental trajectories & psychiatry” Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Paris75006, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Developmental trajectories & psychiatry” Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Paris75006, France
- Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, AP-HP.Sorbonne Université, Paris75006, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Developmental trajectories & psychiatry” Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Paris75006, France
- Etablissement Public de Santé Barthélemy Durand, Paris91700, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim69117, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel24118, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen37075, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
| | - Juliane H. Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden01087, Germany
| | - Michael N. Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden01087, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin10117, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, DublinD02 PN40, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, Institute for Science and Technology of Brain-inspired Intelligence, Fudan University, Shanghai200437, Peoples Republic of China
- Centre for Population Neuroscience and Precision Medicine, Charite Universitätsmedizin Berlin, Berlin10117, Germany
| | - Tomáš Paus
- Research Centre of Sainte-Justine University Hospital, Montreal, QCH3T 1C5, Canada
- Department of Psychiatry and Addictology, University of Montreal, Montreal, QCH3T 1J4, Canada
- Department of Neuroscience, University of Montreal, Montreal, QCH3T 1J4, Canada
| | - IMAGEN Consortium
- Research Centre of Sainte-Justine University Hospital, Montreal, QCH3T 1C5, Canada
- Department of Psychiatry and Addictology, University of Montreal, Montreal, QCH3T 1J4, Canada
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim68159, Germany
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, DublinD02 PN40, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, DublinD02 PN40, Ireland
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, Social, Genetic & Developmental Psychiatry Centre, King’s College London, LondonSE5 8AF, United Kingdom
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim69117, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim68131, Germany
- NeuroSpin, Energies and Atomic Energy Commission, Université Paris-Saclay, Paris F-91191, France
- Department of Psychiatry, University of Vermont, Burlington, VT05405
- Department of Psychology, University of Vermont, Burlington, VT05405
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, NottinghamNG7 2RD, United Kingdom
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Berlin10117, Germany
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin38116, Germany
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 “Developmental trajectories & psychiatry” Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Paris75006, France
- Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, AP-HP.Sorbonne Université, Paris75006, France
- Etablissement Public de Santé Barthélemy Durand, Paris91700, France
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel24118, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen37075, Germany
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden01087, Germany
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, DublinD02 PN40, Ireland
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, Institute for Science and Technology of Brain-inspired Intelligence, Fudan University, Shanghai200437, Peoples Republic of China
- Centre for Population Neuroscience and Precision Medicine, Charite Universitätsmedizin Berlin, Berlin10117, Germany
- Department of Neuroscience, University of Montreal, Montreal, QCH3T 1J4, Canada
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99
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Huang Y, Zhang T, Zhang S, Zhang W, Yang L, Zhu D, Liu T, Jiang X, Han J, Guo L. Genetic Influence on Gyral Peaks. Neuroimage 2023; 280:120344. [PMID: 37619794 DOI: 10.1016/j.neuroimage.2023.120344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 08/21/2023] [Indexed: 08/26/2023] Open
Abstract
Genetic mechanisms have been hypothesized to be a major determinant in the formation of cortical folding. Although there is an increasing number of studies examining the heritability of cortical folding, most of them focus on sulcal pits rather than gyral peaks. Gyral peaks, which reflect the highest local foci on gyri and are consistent across individuals, remain unstudied in terms of heritability. To address this knowledge gap, we used high-resolution data from the Human Connectome Project (HCP) to perform classical twin analysis and estimate the heritability of gyral peaks across various brain regions. Our results showed that the heritability of gyral peaks was heterogeneous across different cortical regions, but relatively symmetric between hemispheres. We also found that pits and peaks are different in a variety of anatomic and functional measures. Further, we explored the relationship between the levels of heritability and the formation of cortical folding by utilizing the evolutionary timeline of gyrification. Our findings indicate that the heritability estimates of both gyral peaks and sulcal pits decrease linearly with the evolution timeline of gyrification. This suggests that the cortical folds which formed earlier during gyrification are subject to stronger genetic influences than the later ones. Moreover, the pits and peaks coupled by their time of appearance are also positively correlated in respect of their heritability estimates. These results fill the knowledge gap regarding genetic influences on gyral peaks and significantly advance our understanding of how genetic factors shape the formation of cortical folding. The comparison between peaks and pits suggests that peaks are not a simple morphological mirror of pits but could help complete the understanding of folding patterns.
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Affiliation(s)
- Ying Huang
- School of Automation, Northwestern Polytechnical University, Xi'an 710129, China; School of Information and Technology, Northwest University, Xi'an 710127, China
| | - Tuo Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an 710129, China.
| | - Songyao Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
| | - Weihan Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
| | - Li Yang
- School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
| | - Dajiang Zhu
- Computer Science & Engineering, University of Texas at Arlington, TX 76010, USA
| | - Tianming Liu
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA 30602, USA
| | - Xi Jiang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China
| | - Junwei Han
- School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
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100
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He Y, Li Q, Fu Z, Zeng D, Han Y, Li S. Functional gradients reveal altered functional segregation in patients with amnestic mild cognitive impairment and Alzheimer's disease. Cereb Cortex 2023; 33:10836-10847. [PMID: 37718155 DOI: 10.1093/cercor/bhad328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/26/2023] [Accepted: 08/23/2023] [Indexed: 09/19/2023] Open
Abstract
Alzheimer's disease and amnestic mild cognitive impairment are associated with disrupted functional organization in brain networks, involved with alteration of functional segregation. Connectome gradients are a new tool representing brain functional topological organization to smoothly capture the human macroscale hierarchy. Here, we examined altered topological organization in amnestic mild cognitive impairment and Alzheimer's disease by connectome gradient mapping. We further quantified functional segregation by gradient dispersion. Then, we systematically compared the alterations observed in amnestic mild cognitive impairment and Alzheimer's disease patients with those in normal controls in a two-dimensional functional gradient space from both the whole-brain level and module level. Compared with normal controls, the first gradient, which described the neocortical hierarchy from unimodal to transmodal regions, showed a more distributed and significant suppression in Alzheimer's disease than amnestic mild cognitive impairment patients. Furthermore, gradient dispersion showed significant decreases in Alzheimer's disease at both the global level and module level, whereas this alteration was limited only to limbic areas in amnestic mild cognitive impairment. Notably, we demonstrated that suppressed gradient dispersion in amnestic mild cognitive impairment and Alzheimer's disease was associated with cognitive scores. These findings provide new evidence for altered brain hierarchy in amnestic mild cognitive impairment and Alzheimer's disease, which strengthens our understanding of the progressive mechanism of cognitive decline.
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Affiliation(s)
- Yirong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Zhenrong Fu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing 100083, China
| | - Debin Zeng
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing 100083, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- Biomedical Engineering Institute, Hainan University, Haikou 570228, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing 100050, China
- National Clinical Research Center for Geriatric Disorders, Beijing 100053, China
| | - Shuyu Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
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