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Cattarinussi G, Heidari-Foroozan M, Jafary H, Mohammadi E, Sambataro F, Ferro A, Barone Y, Delvecchio G. Resting-state functional magnetic resonance imaging alterations in first-degree relatives of individuals with bipolar disorder: A systematic review. J Affect Disord 2024; 365:321-331. [PMID: 39142577 DOI: 10.1016/j.jad.2024.08.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 07/25/2024] [Accepted: 08/11/2024] [Indexed: 08/16/2024]
Abstract
BACKGROUND Relatives of individuals with bipolar disorder (BD) are at higher risk of developing the disorder. Identifying brain alterations associated with familial vulnerability in BD can help discover endophenotypes, which are quantifiable biological traits more prevalent in unaffected relatives of BD (BD-RELs) than the general population. This review aimed at expanding our knowledge on endophenotypes of BD by providing an overview of resting-state functional magnetic resonance imaging (rs-fMRI) alterations in BD-RELs. METHODS A systematic search of PubMed, Scopus, and Web of Science was performed to identify all available rs-fMRI studies conducted in BD-RELs up to January 2024. A total of 18 studies were selected. Six included BD-RELs with no history of psychiatric disorders and 10 included BD-RELs that presented psychiatric disorders. Two investigations examined rs-fMRI alterations in BD-RELs with and without subthreshold symptoms for BD. RESULTS BD-RELs presented rs-fMRI alterations in the cortico-limbic network, fronto-thalamic-striatal circuit, fronto-occipital network, and, to a lesser extent, in the default mode network. This was true both for BD-RELs with no history of psychopathology and for BD-RELs that presented psychiatric disorders. The direct comparison of rs-fMRI alterations in BD-RELs with and without psychiatric symptoms displayed largely non-overlapping patterns of rs-fMRI abnormalities. LIMITATIONS Small sample sizes and the clinical heterogeneity of BD-RELs limit the generalizability of our findings. CONCLUSIONS The current literature suggests that first-degree BD-RELs exhibit rs-fMRI alterations in brain circuits involved in emotion regulation, cognition, reward processing, and psychosis susceptibility. Future studies are needed to validate these findings and to explore their potential as biomarkers for early detection and intervention.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), Padua Neuroscience Center, University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Mahsa Heidari-Foroozan
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hosein Jafary
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Esmaeil Mohammadi
- Department of Neurological Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Fabio Sambataro
- Department of Neuroscience (DNS), Padua Neuroscience Center, University of Padova, Padua, Italy; Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Adele Ferro
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Ylenia Barone
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
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Zhong YL, Liu H, Huang X. Altered dynamic large-scale brain networks and combined machine learning in primary angle-closure glaucoma. Neuroscience 2024; 558:11-21. [PMID: 39154845 DOI: 10.1016/j.neuroscience.2024.08.013] [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: 05/12/2024] [Revised: 07/16/2024] [Accepted: 08/08/2024] [Indexed: 08/20/2024]
Abstract
Primary angle-closure glaucoma (PACG) is a severe and irreversible blinding eye disease characterized by progressive retinal ganglion cell death. However, prior research has predominantly focused on static brain activity changes, neglecting the exploration of how PACG impacts the dynamic characteristics of functional brain networks. This study enrolled forty-four patients diagnosed with PACG and forty-four age, gender, and education level-matched healthy controls (HCs). The study employed Independent Component Analysis (ICA) techniques to extract resting-state networks (RSNs) from resting-state functional magnetic resonance imaging (rs-fMRI) data. Subsequently, the RSNs was utilized as the basis for examining and comparing the functional connectivity variations within and between the two groups of resting-state networks. To further explore, a combination of sliding time window and k-means cluster analyses identified seven stable and repetitive dynamic functional network connectivity (dFNC) states. This approach facilitated the comparison of dynamic functional network connectivity and temporal metrics between PACG patients and HCs for each state. Subsequently, a support vector machine (SVM) model leveraging functional connectivity (FC) and FNC was applied to differentiate PACG patients from HCs. Our study underscores the presence of modified functional connectivity within large-scale brain networks and abnormalities in dynamic temporal metrics among PACG patients. By elucidating the impact of changes in large-scale brain networks on disease evolution, researchers may enhance the development of targeted therapies and interventions to preserve vision and cognitive function in PACG.
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Affiliation(s)
- Yu-Lin Zhong
- Department of Ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi 330006, China
| | - Hao Liu
- School of Ophthalmology and Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, China
| | - Xin Huang
- Department of Ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi 330006, China.
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Mansour L. S, Seguin C, Winkler AM, Noble S, Zalesky A. Topological cluster statistic (TCS): Toward structural connectivity-guided fMRI cluster enhancement. Netw Neurosci 2024; 8:902-925. [PMID: 39355436 PMCID: PMC11424043 DOI: 10.1162/netn_a_00375] [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: 08/09/2023] [Accepted: 04/08/2024] [Indexed: 10/03/2024] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies most commonly use cluster-based inference to detect local changes in brain activity. Insufficient statistical power and disproportionate false-positive rates reportedly hinder optimal inference. We propose a structural connectivity-guided clustering framework, called topological cluster statistic (TCS), that enhances sensitivity by leveraging white matter anatomical connectivity information. TCS harnesses multimodal information from diffusion tractography and functional imaging to improve task fMRI activation inference. Compared to conventional approaches, TCS consistently improves power over a wide range of effects. This improvement results in a 10%-50% increase in local sensitivity with the greatest gains for medium-sized effects. TCS additionally enables inspection of underlying anatomical networks and thus uncovers knowledge regarding the anatomical underpinnings of brain activation. This novel approach is made available in the PALM software to facilitate usability. Given the increasing recognition that activation reflects widespread, coordinated processes, TCS provides a way to integrate the known structure underlying widespread activations into neuroimaging analyses moving forward.
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Affiliation(s)
- Sina Mansour L.
- Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Victoria, Australia
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States
| | - Anderson M. Winkler
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Stephanie Noble
- Department of Psychology, Department of Bioengineering, Center for Cognitive and Brain Health, Northeastern University, Boston MA, United States
| | - Andrew Zalesky
- Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Victoria, Australia
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4
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Andrade MÂ, Raposo A, Andrade A. Exploring the late maturation of an intrinsic episodic memory network: A resting-state fMRI study. Dev Cogn Neurosci 2024; 70:101453. [PMID: 39368283 DOI: 10.1016/j.dcn.2024.101453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 07/26/2024] [Accepted: 09/13/2024] [Indexed: 10/07/2024] Open
Abstract
Previous research suggests that episodic memory relies on functional neural networks,which are present even in the absence of an explicit task. The regions that integrate.these networks and the developmental changes in intrinsic functional connectivity.remain elusive. In the present study, we outlined an intrinsic episodic memory network.(iEMN) based on a systematic selection of functional connectivity studies, and.inspected network differences in resting-state fMRI between adolescents (13-17 years.old) and adults (23-27 years old) from the publicly available NKI-Rockland Sample.Through a review of brain regions commonly associated with episodic memory.networks, we identified a potential iEMN composed by 14 bilateral ROIs, distributed.across temporal, frontal and parietal lobes. Within this network, we found an increase.in resting-state connectivity from adolescents to adults between the right temporal pole.and two regions in the right lateral prefrontal cortex. We argue that the coordination of.these brain regions, connecting areas of semantic processing and areas of controlled.retrieval, arises as an important feature towards the full maturation of the episodic.memory system. The findings add to evidence suggesting that adolescence is a key.period in memory development and highlights the role of intrinsic functional.connectivity in such development.
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Affiliation(s)
| | - Ana Raposo
- CICPSI, Faculdade de Psicologia, Universidade de Lisboa, Portugal
| | - Alexandre Andrade
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Portugal
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Maiella M, Mencarelli L, Casula EP, Borghi I, Assogna M, di Lorenzo F, Bonnì S, Pezzopane V, Martorana A, Koch G. Breakdown of TMS evoked EEG signal propagation within the default mode network in Alzheimer's disease. Clin Neurophysiol 2024; 167:177-188. [PMID: 39332078 DOI: 10.1016/j.clinph.2024.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 09/09/2024] [Accepted: 09/13/2024] [Indexed: 09/29/2024]
Abstract
BACKGROUND The neural activity of the Default Mode Network (DMN) is disrupted in patients with In Alzheimer's disease (AD). OBJECTIVES We used a novel multimodal approach to track neural signal propagation within the DMN in AD patients. METHODS Twenty mild to moderate AD patients were recruited. We used transcranial magnetic stimulation (TMS) pulses to probe with a millisecond time resolution the propagation of evoked electroencephalography (EEG) signal following the neural activation of the Precuneus (PC), which is a key hub area of the DMN. Moreover, functional and structural magnetic resonance imaging (MRI) data were collected to reconstruct individual features of the DMN. RESULTS In AD patients a probe TMS pulse applied over the PC evokes an increased local activity unmasking underlying hyperexcitability. In contrast, the EEG evoked neural signal did not propagate efficiently within the DMN showing a remarkable breakdown of signal propagation. fMRI and structural tractography showed that impaired signal propagation was related to the same connectivity matrices derived from DMN BOLD signal and transferred by specific white matter bundles forming the cingulum. These features were not detectable stimulating other areas (left dorsolateral prefrontal cortex) or for different networks (fronto-parietal network). Finally, connectivity breakdown was associated with cognitive impairment, as measured with the Clinical Dementia Rating Scale sum of boxes (CDR-SB). CONCLUSIONS TMS-EEG in AD shows both local hyperexcitability and a lack of signal propagation within the DMN. These neurophysiological features also correlate with structural and cognitive attributes of the patients. SIGNIFICANCE Neuronavigated TMS-EEG may be used as a novel neurophysiological biomarker of DMN connectivity in AD patients.
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Affiliation(s)
- Michele Maiella
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Lucia Mencarelli
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Elias P Casula
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Ilaria Borghi
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Neuroscience and Rehabilitation, University of Ferrara, and Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara, Italy
| | - Martina Assogna
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Francesco di Lorenzo
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Sonia Bonnì
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Valentina Pezzopane
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Neuroscience and Rehabilitation, University of Ferrara, and Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara, Italy
| | | | - Giacomo Koch
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Neuroscience and Rehabilitation, University of Ferrara, and Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara, Italy.
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6
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Gili T, Avila B, Pasquini L, Holodny A, Phillips D, Boldi P, Gabrielli A, Caldarelli G, Zimmer M, Makse HA. Fibration symmetry-breaking supports functional transitions in a brain network engaged in language. ARXIV 2024:arXiv:2409.02674v1. [PMID: 39279833 PMCID: PMC11398549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
In his book 'A Beautiful Question', physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to the largest structures. While symmetry is a cornerstone of physics, it has not yet been found widespread applicability to describe biological systems, particularly the human brain. In this context, we study the human brain network engaged in language and explore the relationship between the structural connectivity (connectome or structural network) and the emergent synchronization of the mesoscopic regions of interest (functional network). We explain this relationship through a different kind of symmetry than physical symmetry, derived from the categorical notion of Grothendieck fibrations. This introduces a new understanding of the human brain by proposing a local symmetry theory of the connectome, which accounts for how the structure of the brain's network determines its coherent activity. Among the allowed patterns of structural connectivity, synchronization elicits different symmetry subsets according to the functional engagement of the brain. We show that the resting state is a particular realization of the cerebral synchronization pattern characterized by a fibration symmetry that is broken in the transition from rest to language. Our findings suggest that the brain's network symmetry at the local level determines its coherent function, and we can understand this relationship from theoretical principles.
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Affiliation(s)
- Tommaso Gili
- Networks Unit, IMT Scuola Alti Studi Lucca, Piazza San Francesco 15, 55100-Lucca, Italy
- Institute for Complex Systems (ISC), CNR, UoS Sapienza, Rome, 00185, Italy
| | - Bryant Avila
- Levich Institute and Physics Department, City College of New York, New York, NY 10031, USA
| | - Luca Pasquini
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital, La Sapienza University, Rome, 00189, Italy
| | - Andrei Holodny
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Department of Neurology and Neuroscience, Weill Medical College of Cornell University, New York, NY, 10021, USA
- Department of Radiology, Weill Medical College of Cornell University, New York, NY 10065, USA
| | - David Phillips
- Division of Mathematics, Computer and Information Systems, Office of Naval Research, Arlington, VA 22217, USA
- Department of Mechanical Engineering, University of New Mexico, Albuquerque, NM 87131, USA
| | - Paolo Boldi
- Department of Computer Science, University of Milan, Milano, Italy
| | - Andrea Gabrielli
- 'Enrico Fermi' Research Center (CREF), Via Panisperna 89A, 00184 - Rome, Italy
- Dipartimento di Ingegneria Civile, Informatica e delle Tecnologie Aeronautiche, Università degli Studi 'Roma Tre', Via Vito Volterra 62, 00146 - Rome, Italy
| | - Guido Caldarelli
- Institute for Complex Systems (ISC), CNR, UoS Sapienza, Rome, 00185, Italy
- Department of Molecular Science and Nanosystems and ECLT, Ca Foscari University of Venice, Venice, 30123, Italy
- London Institute for Mathematical Sciences, Royal Institution, 21 Albemarle St London W1S 4BS, UK
| | - Manuel Zimmer
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Hernán A Makse
- Levich Institute and Physics Department, City College of New York, New York, NY 10031, USA
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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7
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Kristensen TD, Ambrosen KS, Raghava JM, Syeda WT, Dhollander T, Lemvigh CK, Bojesen KB, Barber AD, Nielsen MØ, Rostrup E, Pantelis C, Fagerlund B, Glenthøj BY, Ebdrup BH. Structural and functional connectivity in relation to executive functions in antipsychotic-naïve patients with first episode schizophrenia and levels of glutamatergic metabolites. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:72. [PMID: 39217180 PMCID: PMC11366027 DOI: 10.1038/s41537-024-00487-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/23/2024] [Indexed: 09/04/2024]
Abstract
Patients with schizophrenia exhibit structural and functional dysconnectivity but the relationship to the well-documented cognitive impairments is less clear. This study investigates associations between structural and functional connectivity and executive functions in antipsychotic-naïve patients experiencing schizophrenia. Sixty-four patients with schizophrenia and 95 matched controls underwent cognitive testing, diffusion weighted imaging and resting state functional magnetic resonance imaging. In the primary analyses, groupwise interactions between structural connectivity as measured by fixel-based analyses and executive functions were investigated using multivariate linear regression analyses. For significant structural connections, secondary analyses examined whether functional connectivity and associations with executive functions also differed for the two groups. In group comparisons, patients exhibited cognitive impairments across all executive functions compared to controls (p < 0.001), but no group difference were observed in the fixel-based measures. Primary analyses revealed a groupwise interaction between planning abilities and fixel-based measures in the left anterior thalamic radiation (p = 0.004), as well as interactions between cognitive flexibility and fixel-based measures in the isthmus of corpus callosum and cingulum (p = 0.049). Secondary analyses revealed increased functional connectivity between grey matter regions connected by the left anterior thalamic radiation (left thalamus with pars opercularis p = 0.018, and pars orbitalis p = 0.003) in patients compared to controls. Moreover, a groupwise interaction was observed between cognitive flexibility and functional connectivity between contralateral regions connected by the isthmus (precuneus p = 0.028, postcentral p = 0.012), all p-values corrected for multiple comparisons. We conclude that structural and functional connectivity appear to associate with executive functions differently in antipsychotic-naïve patients with schizophrenia compared to controls.
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Affiliation(s)
- Tina D Kristensen
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark.
| | - Karen S Ambrosen
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - Jayachandra M Raghava
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Glostrup, Denmark
| | - Warda T Syeda
- Melbourne Brain Center Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC, Australia
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Cecilie K Lemvigh
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - Kirsten B Bojesen
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - Anita D Barber
- Department of Psychiatry, Zucker Hillside Hospital and Zucker School of Medicine at Hofstra/Northwell, Northwell, NY, USA
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Mette Ø Nielsen
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Egill Rostrup
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - Christos Pantelis
- Department of Psychiatry, University of Melbourne and Melbourne Health, Parkville, VIC, Australia
| | - Birgitte Fagerlund
- Child and Adolescent Psychiatry, Mental Health Centre, Copenhagen University Hospital, Hellerup, Copenhagen, Denmark
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Birte Y Glenthøj
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bjørn H Ebdrup
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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8
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Ma X, Li J, Yang Y, Qiu X, Sheng J, Han N, Wu C, Xu G, Jiang G, Tian J, Weng X, Wang J. Enhanced cerebral blood flow similarity of the somatomotor network in chronic insomnia: Transcriptomic decoding, gut microbial signatures and phenotypic roles. Neuroimage 2024; 297:120762. [PMID: 39089603 DOI: 10.1016/j.neuroimage.2024.120762] [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: 02/29/2024] [Revised: 07/24/2024] [Accepted: 07/26/2024] [Indexed: 08/04/2024] Open
Abstract
Chronic insomnia (CI) is a complex disease involving multiple factors including genetics, gut microbiota, and brain structure and function. However, there lacks a unified framework to elucidate how these factors interact in CI. By combining data of clinical assessment, sleep behavior recording, cognitive test, multimodal MRI (structural, functional, and perfusion), gene, and gut microbiota, this study demonstrated that enhanced cerebral blood flow (CBF) similarities of the somatomotor network (SMN) acted as a key mediator to link multiple factors in CI. Specifically, we first demonstrated that only CBF but not morphological or functional networks exhibited alterations in patients with CI, characterized by increases within the SMN and between the SMN and higher-order associative networks. Moreover, these findings were highly reproducible and the CBF similarity method was test-retest reliable. Further, we showed that transcriptional profiles explained 60.4 % variance of the pattern of the increased CBF similarities with the most correlated genes enriched in regulation of cellular and protein localization and material transport, and gut microbiota explained 69.7 % inter-individual variance in the increased CBF similarities with the most contributions from Negativicutes and Lactobacillales. Finally, we found that the increased CBF similarities were correlated with clinical variables, accounted for sleep behaviors and cognitive deficits, and contributed the most to the patient-control classification (accuracy = 84.4 %). Altogether, our findings have important implications for understanding the neuropathology of CI and may inform ways of developing new therapeutic strategies for the disease.
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Affiliation(s)
- Xiaofen Ma
- Department of Nuclear Medicine, Jinan University Affiliated Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Junle Li
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Yuping Yang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Xiaofan Qiu
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Jintao Sheng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Ningke Han
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Changwen Wu
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Guang Xu
- Department of Neurology, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Guihua Jiang
- Department of Nuclear Medicine, Jinan University Affiliated Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Junzhang Tian
- Department of Nuclear Medicine, Jinan University Affiliated Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Xuchu Weng
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China.
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9
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Radoman M, Phan KL, Ajilore OA, Gorka SM. Altered effective connectivity during threat anticipation in individuals with alcohol use disorder. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00211-8. [PMID: 39117274 DOI: 10.1016/j.bpsc.2024.07.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 07/18/2024] [Accepted: 07/30/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND A developing theory and recent research suggest that heightened reactivity to uncertain stressors or threats may be an important individual difference factor that facilitates excessive drinking as a means of avoidance-based coping and characterizes individuals with current and past alcohol use disorder (AUD). Neuroimaging studies of unpredictable threat processing have repeatedly demonstrated activation of the anterior insula (AIC), anteromedial (AM) thalamus and dorsal anterior cingulate cortex (dACC). The present study aimed to understand how these three regions function as a network during anticipation of unpredictable threat (and predictable threat). METHODS Participants were 43 young adults (aged 21-30) with AUD and 26 healthy controls. Functional magnetic resonance imaging and dynamic causal modeling were used to study inter-regional effective connectivities and predictable and unpredictable threat-related modulations thereof within this network. Parametric empirical Bayesian modeling was used to conduct between-group comparisons in effective connectivities. RESULTS During unpredictable threat trials, the increased projection from the right AM thalamus to the right AIC was significantly present only in the AUD group. This directional influence was stronger among individuals who on average consumed more drinks per week. As expected, we found no group differences in modulatory changes to effective connectivities during predictable threat trials. CONCLUSIONS To our knowledge, this is the first study to examine directional interactions between key frontolimbic regions during anticipation of unpredictable and predictable threat and demonstrate the importance of 'bottom-up' thalamic-insular projections during unpredictable threat processing in AUD. Prospective studies are warranted to determine whether this association may be causal.
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Affiliation(s)
- Milena Radoman
- Department of Radiology and Biomedical Imaging, Yale University, 2 Church Street South, New Haven, CT 06511, USA; Department of Psychiatry, University of Illinois at Chicago, 1601 W Taylor Street, Chicago, IL 60612, USA.
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, Ohio State University, 1670 Upham Drive, Columbus, OH 43205, USA
| | - Olusola A Ajilore
- Department of Psychiatry, University of Illinois at Chicago, 1601 W Taylor Street, Chicago, IL 60612, USA
| | - Stephanie M Gorka
- Department of Psychiatry and Behavioral Health, Ohio State University, 1670 Upham Drive, Columbus, OH 43205, USA
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10
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Bjork J, Kenley JK, Gardner C, Latham A, Smyser TA, Miller JP, Shimony JJ, Neil JJ, Warner B, Luby J, Barch DM, Rogers CE, Smyser CD, Lean RE. Associations between prenatal adversity and neonatal white matter microstructure on language outcomes at age 2 years. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.02.24311434. [PMID: 39211873 PMCID: PMC11361255 DOI: 10.1101/2024.08.02.24311434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Background Early life adversity is associated with microstructural alterations in white matter regions that subserve language. However, the mediating and moderating pathways between adversities experienced in utero and key neonatal white matter tracts including the corpus callosum (CC), superior longitudinal fasciculus (SLF), arcuate fasciculus (AF), inferior fronto- occipital fasciculus (IFOF), and uncinate on early language outcomes remains unknown. Methods This longitudinal study includes 160 neonates, oversampled for prenatal exposure to adversity, who underwent diffusion MRI (dMRI) in the first weeks of life. dMRI parameters were obtained using probabilistic tractography in FSL. Maternal Social Disadvantage and Psychosocial Stress was assessed throughout pregnancy. At age 2 years, the Bayley Scales of Infant and Toddler Development-III evaluated language outcomes. Linear regression, mediation, and moderation assessed associations between prenatal adversities and neonatal white matter on language outcomes. Results Prenatal exposure to Social Disadvantage (p<.001) and Maternal Psychosocial Stress (p<.001) were correlated with poorer language outcomes. When Social Disadvantage and maternal Psychosocial Stress were modeled simultaneously in relation to language outcomes, only Social Disadvantage was significant (p<.001). Independent of Social Disadvantage (p<.001), lower neonatal CC fractional anisotropy (FA) was related to poorer global (p=.02) and receptive (p=.02) language outcomes. CC FA did not mediate the association between Social Disadvantage and language outcomes (indirect effect 95% CIs -0.96-0.15), and there was no interaction between Social Disadvantage and CC FA on language outcomes (p>.05). Bilateral SLF/AF, IFOF, and uncinate were not significant (p>.05). Conclusions Prenatal exposure to Social Disadvantage and neonatal CC FA were independently related to language problems by age 2, with no evidence of mediating or moderating associations with language outcomes. These findings elucidate the early neural underpinnings of language development and suggest that the prenatal period may be an important time to provide poverty- reducing support to expectant mothers to promote offspring neurodevelopmental outcomes.
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11
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Zhang S, Zhao M, Sun J, Wen J, Li M, Wang C, Xu Q, Wang J, Sun X, Cheng L, Xue X, Wang X, Jia X. Alterations in degree centrality and functional connectivity in tension-type headache: a resting-state fMRI study. Brain Imaging Behav 2024; 18:819-829. [PMID: 38512647 DOI: 10.1007/s11682-024-00875-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] [Accepted: 03/08/2024] [Indexed: 03/23/2024]
Abstract
Previous studies have provided evidence of structural and functional changes in the brains of patients with tension-type headache (TTH). However, investigations of functional connectivity alterations in TTH have been inconclusive. The present study aimed to investigate abnormal intrinsic functional connectivity patterns in patients with TTH through the voxel-wise degree centrality (DC) method as well as functional connectivity (FC) analysis. A total of 33 patients with TTH and 30 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning and were enrolled in the final study. The voxel-wise DC method was performed to quantify abnormalities in the local functional connectivity hubs. Nodes with abnormal DC were used as seeds for further FC analysis to evaluate alterations in functional connectivity patterns. In addition, correlational analyses were performed between abnormal DC and FC values and clinical features. Compared with HCs, patients with TTH had higher DC values in the left middle temporal gyrus (MTG.L) and lower DC values in the left anterior cingulate and paracingulate gyri (ACG.L) (GRF, voxel-wise p < 0.05, cluster-wise p < 0.05, two-tailed). Seed-based FC analyses revealed that patients with TTH showed greater connections between ACG.L and the right cerebellum lobule IX (CR-IX.R), and smaller connections between ACG.L and ACG.L. The MTG.L showed increased FC with the ACG.L, and decreased FC with the right caudate nucleus (CAU.R) and left precuneus (PCUN.L) (GRF, voxel-wise p < 0.05, cluster-wise p < 0.05, two-tailed). Additionally, the DC value of the MTG.L was negatively correlated with the DASS-depression score (p = 0.046, r=-0.350). This preliminary study provides important insights into the pathophysiological mechanisms of TTH.
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Affiliation(s)
- Shuxian Zhang
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, 261031, China
| | - Mengqi Zhao
- School of Teacher Education, Zhejiang Normal University, Jinhua, 321004, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, 321004, China
| | - Jiazhang Sun
- Ophthalmologic Center, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, 261031, China
| | - Jianjie Wen
- School of Teacher Education, Zhejiang Normal University, Jinhua, 321004, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, 321004, China
| | - Mengting Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, 321004, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, 321004, China
| | - Chao Wang
- Basic Support Department, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, 261031, China
| | - Qinyan Xu
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, 261031, China
| | - Jili Wang
- School of Medical Imaging, Weifang Medical University, Weifang, Shandong Province, 261053, China
| | - Xihe Sun
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, 261031, China
- School of Medical Imaging, Weifang Medical University, Weifang, Shandong Province, 261053, China
| | - Lulu Cheng
- School of Foreign Studies, China University of Petroleum (East China), Qingdao, Shandong Province, 266580, China
| | - Xiaomeng Xue
- School of Foreign Studies, China University of Petroleum (East China), Qingdao, Shandong Province, 266580, China.
| | - Xizhen Wang
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, 261031, China.
| | - Xize Jia
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, 261031, China.
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12
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Ghaziri J, Fei P, Tucholka A, Obaid S, Boucher O, Rouleau I, Nguyen DK. Resting-State Functional Connectivity Profile of Insular Subregions. Brain Sci 2024; 14:742. [PMID: 39199437 PMCID: PMC11352390 DOI: 10.3390/brainsci14080742] [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: 06/20/2024] [Revised: 07/18/2024] [Accepted: 07/24/2024] [Indexed: 09/01/2024] Open
Abstract
The insula is often considered the fifth lobe of the brain and is increasingly recognized as one of the most connected regions in the brain, with widespread connections to cortical and subcortical structures. As a follow-up to our previous tractography work, we investigated the resting-state functional connectivity (rsFC) profiles of insular subregions and assessed their concordance with structural connectivity. We used the CONN toolbox to analyze the rsFC of the same 19 insular regions of interest (ROIs) we used in our prior tractography work and regrouped them into six subregions based on their connectivity pattern similarity. Our analysis of 50 healthy participants confirms the known broad connectivity of the insula and shows novel and specific whole-brain and intra-connectivity patterns of insular subregions. By examining such subregions, our findings provide a more detailed pattern of connectivity than prior studies that may prove useful for comparison between patients.
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Affiliation(s)
- Jimmy Ghaziri
- Département de Psychologie, Université du Québec à Montréal, Montréal, QC H2X 3P2, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Montréal, QC H2X 0A9, Canada
| | - Phillip Fei
- Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, Chicoutimi, QC J4L 1C9, Canada
| | - Alan Tucholka
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, 08005 Barcelona, Spain
- Pixyl Medical, 38700 Grenoble, France
| | - Sami Obaid
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Montréal, QC H2X 0A9, Canada
| | - Olivier Boucher
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Montréal, QC H2X 0A9, Canada
- Service de Neurologie, Centre Hospitalier de l’Université de Montréal (CHUM), Montréal, QC H2X 0C1, Canada
| | - Isabelle Rouleau
- Département de Psychologie, Université du Québec à Montréal, Montréal, QC H2X 3P2, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Montréal, QC H2X 0A9, Canada
| | - Dang K. Nguyen
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Montréal, QC H2X 0A9, Canada
- Service de Neurologie, Centre Hospitalier de l’Université de Montréal (CHUM), Montréal, QC H2X 0C1, Canada
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13
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Huang S, Han J, Zheng H, Li M, Huang C, Kui X, Liu J. Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury: predictors of patient prognosis. Neural Regen Res 2024; 19:1553-1558. [PMID: 38051899 PMCID: PMC10883483 DOI: 10.4103/1673-5374.387971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/04/2023] [Indexed: 12/07/2023] Open
Abstract
Abstract
JOURNAL/nrgr/04.03/01300535-202407000-00035/figure1/v/2023-11-20T171125Z/r/image-tiff
Patients with mild traumatic brain injury have a diverse clinical presentation, and the underlying pathophysiology remains poorly understood. Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neurobiological markers after mild traumatic brain injury. This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury. Graph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function. However, most previous mild traumatic brain injury studies using graph theory have focused on specific populations, with limited exploration of simultaneous abnormalities in structural and functional connectivity. Given that mild traumatic brain injury is the most common type of traumatic brain injury encountered in clinical practice, further investigation of the patient characteristics and evolution of structural and functional connectivity is critical. In the present study, we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury. In this longitudinal study, we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 weeks of injury, as well as 36 healthy controls. Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis. In the acute phase, patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network. More than 3 months of follow-up data revealed signs of recovery in structural and functional connectivity, as well as cognitive function, in 22 out of the 46 patients. Furthermore, better cognitive function was associated with more efficient networks. Finally, our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal changes in connectivity in patients with mild traumatic brain injury. These findings highlight the importance of integrating structural and functional connectivity in understanding the occurrence and evolution of mild traumatic brain injury. Additionally, exploratory analysis based on subnetworks could serve a predictive function in the prognosis of patients with mild traumatic brain injury.
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Affiliation(s)
- Sihong Huang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Jungong Han
- Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, UK
| | - Hairong Zheng
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, China
| | - Mengjun Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Chuxin Huang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Xiaoyan Kui
- School of Computer Science and Engineering, Central South University, Changsha, Hunan Province, China
| | - Jun Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
- Department of Radiology, Quality Control Center of Hunan Province, Changsha, Hunan Province, China
- Clinical Research Center for Medical Imaging of Hunan Province, Changsha, Hunan Province, China
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Gili T, Avila B, Pasquini L, Holodny A, Phillips D, Boldi P, Gabrielli A, Caldarelli G, Zimmer M, Makse HA. Fibration symmetry-breaking supports functional transitions in a brain network engaged in language. RESEARCH SQUARE 2024:rs.3.rs-4409330. [PMID: 38883794 PMCID: PMC11177955 DOI: 10.21203/rs.3.rs-4409330/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
In his book 'A Beautiful Question' 1, physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to the largest structures 1-4. While symmetry is a cornerstone of physics, it has not yet been found widespread applicability to describe biological systems 5, particularly the human brain. In this context, we study the human brain network engaged in language and explore the relationship between the structural connectivity (connectome or structural network) and the emergent synchronization of the mesoscopic regions of interest (functional network). We explain this relationship through a different kind of symmetry than physical symmetry, derived from the categorical notion of Grothendieck fibrations 6. This introduces a new understanding of the human brain by proposing a local symmetry theory of the connectome, which accounts for how the structure of the brain's network determines its coherent activity. Among the allowed patterns of structural connectivity, synchronization elicits different symmetry subsets according to the functional engagement of the brain. We show that the resting state is a particular realization of the cerebral synchronization pattern characterized by a fibration symmetry that is broken 7 in the transition from rest to language. Our findings suggest that the brain's network symmetry at the local level determines its coherent function, and we can understand this relationship from theoretical principles.
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Affiliation(s)
- Tommaso Gili
- Networks Unit, IMT Scuola Alti Studi Lucca, Piazza San Francesco 15, 55100- Lucca, Italy
- Institute for Complex Systems (ISC), CNR, UoS Sapienza, Rome, 00185, Italy
| | - Bryant Avila
- Levich Institute and Physics Department, City College of New York, New York, NY 10031, USA
| | - Luca Pasquini
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital, La Sapienza University, Rome, 00189, Italy
| | - Andrei Holodny
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Department of Neurology and Neuroscience, Weill Medical College of Cornell University, New York, NY, 10021, USA
- Department of Radiology, Weill Medical College of Cornell University, New York, NY 10065, USA
| | - David Phillips
- Division of Mathematics, Computer and Information Systems, Office of Naval Research, Arlington, VA 22217, USA
- Department of Mechanical Engineering, University of New Mexico, Albuquerque, NM 87131, USA
| | - Paolo Boldi
- Department of Computer Science, University of Milan, Milano, Italy
| | - Andrea Gabrielli
- 'Enrico Fermi' Research Center (CREF), Via Panisperna 89A, 00184 - Rome, Italy
- Dipartimento di Ingegneria Civile, Informatica e delle Tecnologie Aeronautiche, Università degli Studi 'Roma Tre', Via Vito Volterra 62, 00146 - Rome, Italy
| | - Guido Caldarelli
- Institute for Complex Systems (ISC), CNR, UoS Sapienza, Rome, 00185, Italy
- Department of Molecular Science and Nanosystems and ECLT, Ca Foscari University of Venice, Venice, 30123, Italy
- London Institute for Mathematical Sciences, Royal Institution, 21 Albemarle St London W1S 4BS, UK
| | - Manuel Zimmer
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Hernán A Makse
- Levich Institute and Physics Department, City College of New York, New York, NY 10031, USA
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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15
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Toba MN, Malkinson TS, Howells H, Mackie MA, Spagna A. Same, Same but Different? A Multi-Method Review of the Processes Underlying Executive Control. Neuropsychol Rev 2024; 34:418-454. [PMID: 36967445 DOI: 10.1007/s11065-023-09577-4] [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: 02/17/2022] [Accepted: 09/26/2022] [Indexed: 03/29/2023]
Abstract
Attention, working memory, and executive control are commonly considered distinct cognitive functions with important reciprocal interactions. Yet, longstanding evidence from lesion studies has demonstrated both overlap and dissociation in their behavioural expression and anatomical underpinnings, suggesting that a lower dimensional framework could be employed to further identify processes supporting goal-directed behaviour. Here, we describe the anatomical and functional correspondence between attention, working memory, and executive control by providing an overview of cognitive models, as well as recent data from lesion studies, invasive and non-invasive multimodal neuroimaging and brain stimulation. We emphasize the benefits of considering converging evidence from multiple methodologies centred on the identification of brain mechanisms supporting goal-driven behaviour. We propose that expanding on this approach should enable the construction of a comprehensive anatomo-functional framework with testable new hypotheses, and aid clinical neuroscience to intervene on impairments of executive functions.
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Affiliation(s)
- Monica N Toba
- Laboratory of Functional Neurosciences (UR UPJV 4559), University Hospital of Amiens and University of Picardie Jules Verne, Amiens, France.
- CHU Amiens Picardie - Site Sud, Centre Universitaire de Recherche en Santé, Avenue René Laënnec, 80054, Amiens Cedex 1, France.
| | - Tal Seidel Malkinson
- Paris Brain Institute, ICM, Hôpital de La Pitié-Salpêtrière, Sorbonne Université, Inserm U 1127, CNRS UMR 7225, 75013, Paris, France
- Université de Lorraine, CRAN, F-54000, Nancy, France
| | - Henrietta Howells
- Laboratory of Motor Control, Department of Medical Biotechnologies and Translational Medicine, Humanitas Research Hospital, IRCCS, Università Degli Studi Di Milano, Milan, Italy
| | - Melissa-Ann Mackie
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Alfredo Spagna
- Department of Psychology, Columbia University, New York, NY, 10025, USA.
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16
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Zheng J, Cheng Y, Wu X, Li X, Fu Y, Yang Z. Rich-club organization of whole-brain spatio-temporal multilayer functional connectivity networks. Front Neurosci 2024; 18:1405734. [PMID: 38855440 PMCID: PMC11157044 DOI: 10.3389/fnins.2024.1405734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Accepted: 05/07/2024] [Indexed: 06/11/2024] Open
Abstract
Objective In this work, we propose a novel method for constructing whole-brain spatio-temporal multilayer functional connectivity networks (FCNs) and four innovative rich-club metrics. Methods Spatio-temporal multilayer FCNs achieve a high-order representation of the spatio-temporal dynamic characteristics of brain networks by combining the sliding time window method with graph theory and hypergraph theory. The four proposed rich-club scales are based on the dynamic changes in rich-club node identity, providing a parameterized description of the topological dynamic characteristics of brain networks from both temporal and spatial perspectives. The proposed method was validated in three independent differential analysis experiments: male-female gender difference analysis, analysis of abnormality in patients with autism spectrum disorders (ASD), and individual difference analysis. Results The proposed method yielded results consistent with previous relevant studies and revealed some innovative findings. For instance, the dynamic topological characteristics of specific white matter regions effectively reflected individual differences. The increased abnormality in internal functional connectivity within the basal ganglia may be a contributing factor to the occurrence of repetitive or restrictive behaviors in ASD patients. Conclusion The proposed methodology provides an efficacious approach for constructing whole-brain spatio-temporal multilayer FCNs and conducting analysis of their dynamic topological structures. The dynamic topological characteristics of spatio-temporal multilayer FCNs may offer new insights into physiological variations and pathological abnormalities in neuroscience.
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Affiliation(s)
- Jianhui Zheng
- College of Electronic Engineering, Chengdu University of Information Technology, Chengdu, China
| | - Yuhao Cheng
- Huaxi Molecular Imaging Research Laboratory, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Xi Wu
- Department of Computer Science, Chengdu University of Information Technology, Chengdu, China
| | - Xiaojie Li
- Department of Computer Science, Chengdu University of Information Technology, Chengdu, China
| | - Ying Fu
- Department of Computer Science, Chengdu University of Information Technology, Chengdu, China
| | - Zhipeng Yang
- College of Electronic Engineering, Chengdu University of Information Technology, Chengdu, China
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Peña-Casanova J, Sánchez-Benavides G, Sigg-Alonso J. Updating functional brain units: Insights far beyond Luria. Cortex 2024; 174:19-69. [PMID: 38492440 DOI: 10.1016/j.cortex.2024.02.004] [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: 09/28/2023] [Revised: 01/15/2024] [Accepted: 02/15/2024] [Indexed: 03/18/2024]
Abstract
This paper reviews Luria's model of the three functional units of the brain. To meet this objective, several issues were reviewed: the theory of functional systems and the contributions of phylogenesis and embryogenesis to the brain's functional organization. This review revealed several facts. In the first place, the relationship/integration of basic homeostatic needs with complex forms of behavior. Secondly, the multi-scale hierarchical and distributed organization of the brain and interactions between cells and systems. Thirdly, the phylogenetic role of exaptation, especially in basal ganglia and cerebellum expansion. Finally, the tripartite embryogenetic organization of the brain: rhinic, limbic/paralimbic, and supralimbic zones. Obviously, these principles of brain organization are in contradiction with attempts to establish separate functional brain units. The proposed new model is made up of two large integrated complexes: a primordial-limbic complex (Luria's Unit I) and a telencephalic-cortical complex (Luria's Units II and III). As a result, five functional units were delineated: Unit I. Primordial or preferential (brainstem), for life-support, behavioral modulation, and waking regulation; Unit II. Limbic and paralimbic systems, for emotions and hedonic evaluation (danger and relevance detection and contribution to reward/motivational processing) and the creation of cognitive maps (contextual memory, navigation, and generativity [imagination]); Unit III. Telencephalic-cortical, for sensorimotor and cognitive processing (gnosis, praxis, language, calculation, etc.), semantic and episodic (contextual) memory processing, and multimodal conscious agency; Unit IV. Basal ganglia systems, for behavior selection and reinforcement (reward-oriented behavior); Unit V. Cerebellar systems, for the prediction/anticipation (orthometric supervision) of the outcome of an action. The proposed brain units are nothing more than abstractions within the brain's simultaneous and distributed physiological processes. As function transcends anatomy, the model necessarily involves transition and overlap between structures. Beyond the classic approaches, this review includes information on recent systemic perspectives on functional brain organization. The limitations of this review are discussed.
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Affiliation(s)
- Jordi Peña-Casanova
- Integrative Pharmacology and Systems Neuroscience Research Group, Neuroscience Program, Hospital del Mar Medical Research Institute, Barcelona, Spain; Department of Psychiatry and Legal Medicine, Autonomous University of Barcelona, Bellaterra, Barcelona, Spain; Test Barcelona Services, Teià, Barcelona, Spain.
| | | | - Jorge Sigg-Alonso
- Department of Behavioral and Cognitive Neurobiology, Institute of Neurobiology, National Autonomous University of México (UNAM), Queretaro, Mexico
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Lv Z, Li J, Yao L, Guo X. Predicting resting-state brain functional connectivity from the structural connectome using the heat diffusion model: a multiple-timescale fusion method. J Neural Eng 2024; 21:026041. [PMID: 38565132 DOI: 10.1088/1741-2552/ad39a6] [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: 08/10/2023] [Accepted: 04/02/2024] [Indexed: 04/04/2024]
Abstract
Objective.Understanding the intricate relationship between structural connectivity (SC) and functional connectivity (FC) is pivotal for understanding the complexities of the human brain. To explore this relationship, the heat diffusion model (HDM) was utilized to predict FC from SC. However, previous studies using the HDM have typically predicted FC at a critical time scale in the heat kernel equation, overlooking the dynamic nature of the diffusion process and providing an incomplete representation of the predicted FC.Approach.In this study, we propose an alternative approach based on the HDM. First, we introduced a multiple-timescale fusion method to capture the dynamic features of the diffusion process. Additionally, to enhance the smoothness of the predicted FC values, we employed the Wavelet reconstruction method to maintain local consistency and remove noise. Moreover, to provide a more accurate representation of the relationship between SC and FC, we calculated the linear transformation between the smoothed FC and the empirical FC.Main results.We conducted extensive experiments in two independent datasets. By fusing different time scales in the diffusion process for predicting FC, the proposed method demonstrated higher predictive correlation compared with method considering only critical time points (Singlescale). Furthermore, compared with other existing methods, the proposed method achieved the highest predictive correlations of 0.6939±0.0079 and 0.7302±0.0117 on the two datasets respectively. We observed that the visual network at the network level and the parietal lobe at the lobe level exhibited the highest predictive correlations, indicating that the functional activity in these regions may be closely related to the direct diffusion of information between brain regions.Significance.The multiple-timescale fusion method proposed in this study provides insights into the dynamic aspects of the diffusion process, contributing to a deeper understanding of how brain structure gives rise to brain function.
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Affiliation(s)
- Zhengyuan Lv
- School of Artificial Intelligence, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Jingming Li
- School of Artificial Intelligence, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Li Yao
- School of Artificial Intelligence, Beijing Normal University, Beijing 100875, People's Republic of China
| | - Xiaojuan Guo
- School of Artificial Intelligence, Beijing Normal University, Beijing 100875, People's Republic of China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, People's Republic of China
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Saha R, Saha DK, Fu Z, Duda M, Silva RF, Calhoun VD. Analysis of Longitudinal Change Patterns in Developing Brain Using Functional and Structural Magnetic Resonance Imaging via Multimodal Fusion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.07.588473. [PMID: 38645216 PMCID: PMC11030394 DOI: 10.1101/2024.04.07.588473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Functional and structural magnetic resonance imaging (fMRI and sMRI) are complementary approaches that can be used to study longitudinal brain changes in adolescents. Each individual modality offers distinct insights into the brain. Each individual modality may overlook crucial aspects of brain analysis. By combining them, we can uncover hidden brain connections and gain a more comprehensive understanding. In previous work, we identified multivariate patterns of change in whole-brain function during adolescence. In this work, we focus on linking functional change patterns (FCPs) to brain structure. We introduce two approaches and applied them to data from the Adolescent Brain and Cognitive Development (ABCD) dataset. First, we evaluate voxelwise sMRI-FCP coupling to identify structural patterns linked to our previously identified FCPs. Our approach revealed multiple interesting patterns in functional network connectivity (FNC) and gray matter volume (GMV) data that were linked to subject level variation. FCP components 2 and 4 exhibit extensive associations between their loadings and voxel-wise GMV data. Secondly, we leveraged a symmetric multimodal fusion technique called multiset canonical correlation analysis (mCCA) + joint independent component analysis (jICA). Using this approach, we identify structured FCPs such as one showing increased connectivity between visual and sensorimotor domains and decreased connectivity between sensorimotor and cognitive control domains, linked to structural change patterns (SCPs) including alterations in the bilateral sensorimotor cortex. Interestingly, females exhibit stronger coupling between brain functional and structural changes than males, highlighting sex-related differences. The combined results from both asymmetric and symmetric multimodal fusion methods underscore the intricate sex-specific nuances in neural dynamics. By utilizing two complementary multimodal approaches, our study enhances our understanding of the dynamic nature of brain connectivity and structure during the adolescent period, shedding light on the nuanced processes underlying adolescent brain development.
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Affiliation(s)
- Rekha Saha
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Debbrata K. Saha
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Marlena Duda
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Rogers F. Silva
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
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20
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Papo D, Buldú JM. Does the brain behave like a (complex) network? I. Dynamics. Phys Life Rev 2024; 48:47-98. [PMID: 38145591 DOI: 10.1016/j.plrev.2023.12.006] [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: 12/08/2023] [Accepted: 12/10/2023] [Indexed: 12/27/2023]
Abstract
Graph theory is now becoming a standard tool in system-level neuroscience. However, endowing observed brain anatomy and dynamics with a complex network structure does not entail that the brain actually works as a network. Asking whether the brain behaves as a network means asking whether network properties count. From the viewpoint of neurophysiology and, possibly, of brain physics, the most substantial issues a network structure may be instrumental in addressing relate to the influence of network properties on brain dynamics and to whether these properties ultimately explain some aspects of brain function. Here, we address the dynamical implications of complex network, examining which aspects and scales of brain activity may be understood to genuinely behave as a network. To do so, we first define the meaning of networkness, and analyse some of its implications. We then examine ways in which brain anatomy and dynamics can be endowed with a network structure and discuss possible ways in which network structure may be shown to represent a genuine organisational principle of brain activity, rather than just a convenient description of its anatomy and dynamics.
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Affiliation(s)
- D Papo
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy; Center for Translational Neurophysiology, Fondazione Istituto Italiano di Tecnologia, Ferrara, Italy.
| | - J M Buldú
- Complex Systems Group & G.I.S.C., Universidad Rey Juan Carlos, Madrid, Spain
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21
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Jimenez-Marin A, Diez I, Erramuzpe A, Stramaglia S, Bonifazi P, Cortes JM. Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain. Sci Data 2024; 11:256. [PMID: 38424112 PMCID: PMC10904384 DOI: 10.1038/s41597-024-03060-2] [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: 08/10/2023] [Accepted: 02/12/2024] [Indexed: 03/02/2024] Open
Abstract
The human brain is an extremely complex network of structural and functional connections that operate at multiple spatial and temporal scales. Investigating the relationship between these multi-scale connections is critical to advancing our comprehension of brain function and disorders. However, accurately predicting structural connectivity from its functional counterpart remains a challenging pursuit. One of the major impediments is the lack of public repositories that integrate structural and functional networks at diverse resolutions, in conjunction with modular transcriptomic profiles, which are essential for comprehensive biological interpretation. To mitigate this limitation, our contribution encompasses the provision of an open-access dataset consisting of derivative matrices of functional and structural connectivity across multiple scales, accompanied by code that facilitates the investigation of their interrelations. We also provide additional resources focused on neuro-genetic associations of module-level network metrics, which present promising opportunities to further advance research in the field of network neuroscience, particularly concerning brain disorders.
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Affiliation(s)
- Antonio Jimenez-Marin
- Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain
- Biomedical Research Doctorate Program, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Ibai Diez
- Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, United States of America
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, United States of America
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, United States of America
| | - Asier Erramuzpe
- Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain
- IKERBASQUE Basque Foundation for Science, Bilbao, Spain
| | - Sebastiano Stramaglia
- Dipartamento Interateneo di Fisica, Universita Degli Studi di Bari Aldo Moro, INFN, Bari, Italy
| | - Paolo Bonifazi
- Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain
- IKERBASQUE Basque Foundation for Science, Bilbao, Spain
| | - Jesus M Cortes
- Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain.
- IKERBASQUE Basque Foundation for Science, Bilbao, Spain.
- Department of Cell Biology and Histology, University of the Basque Country (UPV/EHU), Leioa, Spain.
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22
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Dimitriadis SI, Castells-Sánchez A, Roig-Coll F, Dacosta-Aguayo R, Lamonja-Vicente N, Torán-Monserrat P, García-Molina A, Monte-Rubio G, Stillman C, Perera-Lluna A, Mataró M. Intrinsic functional brain connectivity changes following aerobic exercise, computerized cognitive training, and their combination in physically inactive healthy late-middle-aged adults: the Projecte Moviment. GeroScience 2024; 46:573-596. [PMID: 37872293 PMCID: PMC10828336 DOI: 10.1007/s11357-023-00946-8] [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: 06/13/2023] [Accepted: 09/13/2023] [Indexed: 10/25/2023] Open
Abstract
Lifestyle interventions have positive neuroprotective effects in aging. However, there are still open questions about how changes in resting-state functional connectivity (rsFC) contribute to cognitive improvements. The Projecte Moviment is a 12-week randomized controlled trial of a multimodal data acquisition protocol that investigated the effects of aerobic exercise (AE), computerized cognitive training (CCT), and their combination (COMB). An initial list of 109 participants was recruited from which a total of 82 participants (62% female; age = 58.38 ± 5.47) finished the intervention with a level of adherence > 80%. Only in the COMB group, we revealed an extended network of 33 connections that involved an increased and decreased rsFC within and between the aDMN/pDMN and a reduced rsFC between the bilateral supplementary motor areas and the right thalamus. No global and especially local rsFC changes due to any intervention mediated the cognitive benefits detected in the AE and COMB groups. Projecte Moviment provides evidence of the clinical relevance of lifestyle interventions and the potential benefits when combining them.
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Affiliation(s)
- Stavros I Dimitriadis
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain.
- Institut de Neurociències, University of Barcelona, Barcelona, Spain.
| | - Alba Castells-Sánchez
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, Barcelona, Spain
| | - Francesca Roig-Coll
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, Barcelona, Spain
| | - Rosalía Dacosta-Aguayo
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain
- Unitat de Suport a La Recerca Metropolitana Nord, Fundació Institut Universitari Per a La Recerca a L'Atenció Primària de Salut Jordi Gol I Gurina, Mataró, Spain
- Institut d'Investigació en Ciències de La Salut Germans Trias I Pujol (IGTP), Badalona, Spain
| | - Noemí Lamonja-Vicente
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, Barcelona, Spain
- Unitat de Suport a La Recerca Metropolitana Nord, Fundació Institut Universitari Per a La Recerca a L'Atenció Primària de Salut Jordi Gol I Gurina, Mataró, Spain
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | - Pere Torán-Monserrat
- Unitat de Suport a La Recerca Metropolitana Nord, Fundació Institut Universitari Per a La Recerca a L'Atenció Primària de Salut Jordi Gol I Gurina, Mataró, Spain
- Department of Medicine, Universitat de Girona, Girona, Spain
| | - Alberto García-Molina
- Institut d'Investigació en Ciències de La Salut Germans Trias I Pujol (IGTP), Badalona, Spain
- Institut Guttmann, Institut Universitari de Neurorehabilitació, Universitat Autònoma de Barcelona, Badalona, Spain
| | - Gemma Monte-Rubio
- Centre for Comparative Medicine and Bioimage (CMCiB), Germans Trias I Pujol Research Institute (IGTP), Badalona, Spain
| | - Chelsea Stillman
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alexandre Perera-Lluna
- B2SLab, Departament d'Enginyeria de Sistemes, CIBER-BBN, Automàtica I Informàtica Industrial, Universitat Politècnica de Catalunya, 08028, Barcelona, Spain
- Department of Biomedical Engineering, Institut de Recerca Pediàtrica Hospital Sant Joan de Déu, 08950, Esplugues de Llobregat, Barcelona, Spain
| | - Maria Mataró
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain.
- Institut de Neurociències, University of Barcelona, Barcelona, Spain.
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.
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23
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Liang X, Sun L, Liao X, Lei T, Xia M, Duan D, Zeng Z, Li Q, Xu Z, Men W, Wang Y, Tan S, Gao JH, Qin S, Tao S, Dong Q, Zhao T, He Y. Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence. Nat Commun 2024; 15:784. [PMID: 38278807 PMCID: PMC10817914 DOI: 10.1038/s41467-024-44863-6] [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: 05/15/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024] Open
Abstract
Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.
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Affiliation(s)
- Xinyuan Liang
- 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
| | - Lianglong Sun
- 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
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, 100875, China
| | - Tianyuan Lei
- 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
| | - Mingrui Xia
- 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
| | - Dingna Duan
- 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
| | - Zilong Zeng
- 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
| | - 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
| | - Zhilei Xu
- 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
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China
| | - Shaozheng Qin
- 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
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Tengda Zhao
- 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.
| | - Yong He
- 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.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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24
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Bonosi L, Torrente A, Brighina F, Tito Petralia CC, Merlino P, Avallone C, Gulino V, Costanzo R, Brunasso L, Iacopino DG, Maugeri R. Corticocortical Evoked Potentials in Eloquent Brain Tumor Surgery. A Systematic Review. World Neurosurg 2024; 181:38-51. [PMID: 37832637 DOI: 10.1016/j.wneu.2023.10.028] [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: 08/29/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 10/15/2023]
Abstract
Eloquent brain tumor surgery involves the delicate task of resecting tumors located in regions of the brain responsible for critical functions, such as language, motor control, and sensory perception. Preserving these functions is of paramount importance to maintain the patient's quality of life. Corticocortical evoked potentials (CCEPs) have emerged as a valuable intraoperative monitoring technique that aids in identifying and preserving eloquent cortical areas during surgery. This systematic review aimed to assess the utility of CCEPs in eloquent brain tumor surgery and determine their effectiveness in improving patient outcomes. A comprehensive literature search was conducted using electronic databases, including PubMed/Medline and Scopus. The search strategy identified 11 relevant articles for detailed analysis. The findings of the included studies consistently demonstrated the potential of CCEPs in guiding surgical decision making, minimizing the risk of postoperative neurological deficits, and mapping functional connectivity during surgery. However, further research and standardization are needed to fully establish the clinical benefits and refine the implementation of CCEPs in routine neurosurgical practice.
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Affiliation(s)
- Lapo Bonosi
- Department of Biomedicine Neurosciences and Advanced Diagnostics, Neurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in NeurologiSurgery, School of Medicine, University of Palermo, Palermo, Italy.
| | - Angelo Torrente
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo, Italy
| | - Filippo Brighina
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, Palermo, Italy
| | - Cateno Concetto Tito Petralia
- Department of Biomedicine Neurosciences and Advanced Diagnostics, Neurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in NeurologiSurgery, School of Medicine, University of Palermo, Palermo, Italy
| | - Pietro Merlino
- Department of Neuroscience, Psychology, Pharmacology and Child Health, Neurosurgery Clinic, Careggi University Hospital and University of Florence, Florence, Italy
| | - Chiara Avallone
- Department of Biomedicine Neurosciences and Advanced Diagnostics, Neurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in NeurologiSurgery, School of Medicine, University of Palermo, Palermo, Italy
| | - Vincenzo Gulino
- Department of Biomedicine Neurosciences and Advanced Diagnostics, Neurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in NeurologiSurgery, School of Medicine, University of Palermo, Palermo, Italy
| | - Roberta Costanzo
- Department of Biomedicine Neurosciences and Advanced Diagnostics, Neurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in NeurologiSurgery, School of Medicine, University of Palermo, Palermo, Italy
| | - Lara Brunasso
- Department of Biomedicine Neurosciences and Advanced Diagnostics, Neurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in NeurologiSurgery, School of Medicine, University of Palermo, Palermo, Italy
| | - Domenico Gerardo Iacopino
- Department of Biomedicine Neurosciences and Advanced Diagnostics, Neurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in NeurologiSurgery, School of Medicine, University of Palermo, Palermo, Italy
| | - Rosario Maugeri
- Department of Biomedicine Neurosciences and Advanced Diagnostics, Neurosurgical Clinic, AOUP "Paolo Giaccone", Post Graduate Residency Program in NeurologiSurgery, School of Medicine, University of Palermo, Palermo, Italy
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25
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Cui Z, Meng L, Zhang Q, Lou J, Lin Y, Sun Y. White and Gray Matter Abnormalities in Young Adult Females with Dependent Personality Disorder: A Diffusion-Tensor Imaging and Voxel-Based Morphometry Study. Brain Topogr 2024; 37:102-115. [PMID: 37831323 DOI: 10.1007/s10548-023-01013-3] [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: 02/27/2023] [Accepted: 09/30/2023] [Indexed: 10/14/2023]
Abstract
We applied diffusion-tensor imaging (DTI) including measurements of fractional anisotropy (FA), a parameter of neuronal fiber integrity, mean diffusivity (MD), a parameter of brain tissue integrity, as well as voxel-based morphometry (VBM), a measure of gray and white matter volume, to provide a basis to improve our understanding of the neurobiological basis of dependent personality disorder (DPD). DTI was performed on young girls with DPD (N = 17) and young female healthy controls (N = 17). Tract-based spatial statistics (TBSS) were used to examine microstructural characteristics. Gray matter volume differences between the two groups were investigated using voxel-based morphometry (VBM). The Pearson correlation analysis was utilized to examine the relationship between distinct brain areas of white matter and gray matter and the Dy score on the MMPI. The DPD had significantly higher fractional anisotropy (FA) values than the HC group in the right retrolenticular part of the internal capsule, right external capsule, the corpus callosum, right posterior thalamic radiation (include optic radiation), right cerebral peduncle (p < 0.05), which was strongly positively correlated with the Dy score of MMPI. The volume of gray matter in the right postcentral gyrus and left cuneus in DPD was significantly increased (p < 0.05), which was strongly positively correlated with the Dy score of MMPI (r1,2= 0.467,0.353; p1,2 = 0.005,0.04). Our results provide new insights into the changes in the brain structure in DPD, which suggests that alterations in the brain structure might implicate the pathophysiology of DPD. Possible visual and somatosensory association with motor nerve circuits in DPD.
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Affiliation(s)
- Zhixia Cui
- Weifang Mental Health Center, Weifang, Shandong, China
| | | | - Qing Zhang
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China
| | - Jing Lou
- Beijing Normal University, Beijing, China
| | - Yuan Lin
- First Clinical Department, Dalian Medical University, Dalian, China
| | - Yueji Sun
- Department of Psychiatry and Behavioral Sciences, Dalian Medical University, Dalian, China.
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26
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Chong JSX, Tan YJ, Koh AJ, Ting SKS, Kandiah N, Ng ASL, Zhou JH. Plasma Neurofilament Light Relates to Divergent Default and Salience Network Connectivity in Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia. J Alzheimers Dis 2024; 99:965-980. [PMID: 38759005 PMCID: PMC11191491 DOI: 10.3233/jad-231251] [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] [Accepted: 03/27/2024] [Indexed: 05/19/2024]
Abstract
Background Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) show differential vulnerability to large-scale brain functional networks. Plasma neurofilament light (NfL), a promising biomarker of neurodegeneration, has been linked in AD patients to glucose metabolism changes in AD-related regions. However, it is unknown whether plasma NfL would be similarly associated with disease-specific functional connectivity changes in AD and bvFTD. Objective Our study examined the associations between plasma NfL and functional connectivity of the default mode and salience networks in patients with AD and bvFTD. Methods Plasma NfL and neuroimaging data from patients with bvFTD (n = 16) and AD or mild cognitive impairment (n = 38; AD + MCI) were analyzed. Seed-based functional connectivity maps of key regions within the default mode and salience networks were obtained and associated with plasma NfL in these patients. RESULTS We demonstrated divergent associations between NfL and functional connectivity in AD + MCI and bvFTD patients. Specifically, AD + MCI patients showed lower default mode network functional connectivity with higher plasma NfL, while bvFTD patients showed lower salience network functional connectivity with higher plasma NfL. Further, lower NfL-related default mode network connectivity in AD + MCI patients was associated with lower Montreal Cognitive Assessment scores and higher Clinical Dementia Rating sum-of-boxes scores, although NfL-related salience network connectivity in bvFTD patients was not associated with Neuropsychiatric Inventory Questionnaire scores. CONCLUSIONS Our findings indicate that plasma NfL is differentially associated with brain functional connectivity changes in AD and bvFTD.
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Affiliation(s)
- Joanna Su Xian Chong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Human Potential Translational Research Programme and Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Yi Jayne Tan
- Department of Neurology, National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
| | - Amelia Jialing Koh
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Human Potential Translational Research Programme and Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Simon Kang Seng Ting
- Department of Neurology, National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
| | - Nagaendran Kandiah
- Department of Neurology, National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
| | - Adeline Su Lyn Ng
- Department of Neurology, National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Human Potential Translational Research Programme and Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), NUS Graduate School, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- Neuroscience and Behavioural Disorders Programme, Duke-NUS Medical School, Singapore
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27
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Chang AJ, Roth RW, Gong R, Gross RE, Harmsen I, Parashos A, Revell A, Davis KA, Bonilha L, Gleichgerrcht E. Network coupling and surgical treatment response in temporal lobe epilepsy: A proof-of-concept study. Epilepsy Behav 2023; 149:109503. [PMID: 37931391 PMCID: PMC10842155 DOI: 10.1016/j.yebeh.2023.109503] [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: 07/17/2023] [Revised: 09/29/2023] [Accepted: 10/20/2023] [Indexed: 11/08/2023]
Abstract
OBJECTIVE This proof-of-concept study aimed to examine the overlap between structural and functional activity (coupling) related to surgical response. METHODS We studied intracranial rest and ictal stereoelectroencephalography (sEEG) recordings from 77 seizures in thirteen participants with temporal lobe epilepsy (TLE) who subsequently underwent resective/laser ablation surgery. We used the stereotactic coordinates of electrodes to construct functional (sEEG electrodes) and structural connectomes (diffusion tensor imaging). A Jaccard index was used to assess the similarity (coupling) between structural and functional connectivity at rest and at various intraictal timepoints. RESULTS We observed that patients who did not become seizure free after surgery had higher connectome coupling recruitment than responders at rest and during early and mid seizure (and visa versa). SIGNIFICANCE Structural networks provide a backbone for functional activity in TLE. The association between lack of seizure control after surgery and the strength of synchrony between these networks suggests that surgical intervention aimed to disrupt these networks may be ineffective in those that display strong synchrony. Our results, combined with findings of other groups, suggest a potential mechanism that explains why certain patients benefit from epilepsy surgery and why others do not. This insight has the potential to guide surgical planning (e.g., removal of high coupling nodes) following future research.
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Affiliation(s)
- Allen J Chang
- College of Graduate Studies, Neuroscience Institute, Medical University of South Carolina, Charleston, SC, USA
| | - Rebecca W Roth
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Ruxue Gong
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Robert E Gross
- Department of Neurosurgery, Emory University, Atlanta, GA, USA
| | - Irene Harmsen
- College of Graduate Studies, Neuroscience Institute, Medical University of South Carolina, Charleston, SC, USA
| | - Alexandra Parashos
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Andrew Revell
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Kathryn A Davis
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Leonardo Bonilha
- Department of Neurology, University of South Carolina, Columbia, SC, USA
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Mansour L S, Di Biase MA, Smith RE, Zalesky A, Seguin C. Connectomes for 40,000 UK Biobank participants: A multi-modal, multi-scale brain network resource. Neuroimage 2023; 283:120407. [PMID: 37839728 DOI: 10.1016/j.neuroimage.2023.120407] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 09/05/2023] [Accepted: 10/11/2023] [Indexed: 10/17/2023] Open
Abstract
We mapped functional and structural brain networks for more than 40,000 UK Biobank participants. Structural connectivity was estimated with tractography and diffusion MRI. Resting-state functional MRI was used to infer regional functional connectivity. We provide high-quality structural and functional connectomes for multiple parcellation granularities, several alternative measures of interregional connectivity, and a variety of common data pre-processing techniques, yielding more than one million connectomes in total and requiring more than 200,000 h of compute time. For a single subject, we provide 28 out-of-the-box versions of structural and functional brain networks, allowing users to select, e.g., the parcellation and connectivity measure that best suit their research goals. Furthermore, we provide code and intermediate data for the time-efficient reconstruction of more than 1000 different versions of a subject's connectome based on an array of methodological choices. All connectomes are available via the UK Biobank data-sharing platform and our connectome mapping pipelines are openly available. In this report, we describe our connectome resource in detail for users, outline key considerations in developing an efficient pipeline to map an unprecedented number of connectomes, and report on the quality control procedures that were completed to ensure connectome reliability and accuracy. We demonstrate that our structural and functional connectivity matrices meet a number of quality control checks and replicate previously established findings in network neuroscience. We envisage that our resource will enable new studies of the human connectome in health, disease, and aging at an unprecedented scale.
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Affiliation(s)
- Sina Mansour L
- Department of Biomedical Engineering, The University of Melbourne, VIC, Australia.
| | - Maria A Di Biase
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia; Department of Anatomy and Physiology, School of Biomedical Sciences, The University of Melbourne, Parkville, Victoria, Australia; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, MA, USA
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Andrew Zalesky
- Department of Biomedical Engineering, The University of Melbourne, VIC, Australia; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
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29
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Sasaki T, Makris N, Shenton ME, Savadjiev P, Rathi Y, Eckbo R, Bouix S, Yeterian E, Dickerson BC, Kubicki M. Structural connectivity of cytoarchitectonically distinct human left temporal pole subregions: a diffusion MRI tractography study. Front Neuroanat 2023; 17:1240545. [PMID: 38090110 PMCID: PMC10713846 DOI: 10.3389/fnana.2023.1240545] [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: 06/15/2023] [Accepted: 10/09/2023] [Indexed: 02/01/2024] Open
Abstract
The temporal pole (TP) is considered one of the major paralimbic cortical regions, and is involved in a variety of functions such as sensory perception, emotion, semantic processing, and social cognition. Based on differences in cytoarchitecture, the TP can be further subdivided into smaller regions (dorsal, ventrolateral and ventromedial), each forming key nodes of distinct functional networks. However, the brain structural connectivity profile of TP subregions is not fully clarified. Using diffusion MRI data in a set of 31 healthy subjects, we aimed to elucidate the comprehensive structural connectivity of three cytoarchitectonically distinct TP subregions. Diffusion tensor imaging (DTI) analysis suggested that major association fiber pathways such as the inferior longitudinal, middle longitudinal, arcuate, and uncinate fasciculi provide structural connectivity to the TP. Further analysis suggested partially overlapping yet still distinct structural connectivity patterns across the TP subregions. Specifically, the dorsal subregion is strongly connected with wide areas in the parietal lobe, the ventrolateral subregion with areas including constituents of the default-semantic network, and the ventromedial subregion with limbic and paralimbic areas. Our results suggest the involvement of the TP in a set of extensive but distinct networks of cortical regions, consistent with its functional roles.
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Affiliation(s)
- Takeshi Sasaki
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Center for Morphometric Analysis, Department of Psychiatry, Neurology, and Radiology Services, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
- Department of Psychiatry and Behavioral Sciences, Tokyo Medical and Dental University Graduate School, Tokyo, Japan
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Center for Morphometric Analysis, Department of Psychiatry, Neurology, and Radiology Services, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Peter Savadjiev
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Software Engineering and Information Technology, École de Technologie Supérieure, Montréal, QC, Canada
| | - Edward Yeterian
- Department of Psychology, Colby College, Waterville, ME, United States
| | - Bradford C. Dickerson
- Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Center for Morphometric Analysis, Department of Psychiatry, Neurology, and Radiology Services, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
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30
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Aganj I, Mora J, Frau-Pascual A, Fischl B. Exploratory Correlation of The Human Structural Connectome with Non-MRI Variables in Alzheimer's Disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.30.547308. [PMID: 37461543 PMCID: PMC10350016 DOI: 10.1101/2023.06.30.547308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/24/2023]
Abstract
INTRODUCTION Discovery of the associations between brain structural connectivity and clinical and demographic variables can help to better understand the vulnerability and resilience of the brain architecture to neurodegenerative diseases and to discover biomarkers. METHODS We used four diffusion-MRI databases, three related to Alzheimer's disease, to exploratorily correlate structural connections between 85 brain regions with non-MRI variables, while stringently correcting the significance values for multiple testing and ruling out spurious correlations via careful visual inspection. We repeated the analysis with brain connectivity augmented with multi-synaptic neural pathways. RESULTS We found 85 and 101 significant relationships with direct and augmented connectivity, respectively, which were generally stronger for the latter. Age was consistently linked to decreased connectivity, and healthier clinical scores were generally linked to increased connectivity. DISCUSSION Our findings help to elucidate which structural brain networks are affected in Alzheimer's disease and aging and highlight the importance of including indirect connections.
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Affiliation(s)
- Iman Aganj
- Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, 149 13 St., Suite 2301, Boston, MA 02129, USA
- Radiology Department, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | - Jocelyn Mora
- Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, 149 13 St., Suite 2301, Boston, MA 02129, USA
| | - Aina Frau-Pascual
- Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, 149 13 St., Suite 2301, Boston, MA 02129, USA
- Radiology Department, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, 149 13 St., Suite 2301, Boston, MA 02129, USA
- Radiology Department, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
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31
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Huang X, Du Y, Guo D, Xie F, Zhou C. Structural-functional coupling abnormalities in temporal lobe epilepsy. Front Neurosci 2023; 17:1272514. [PMID: 37928725 PMCID: PMC10620528 DOI: 10.3389/fnins.2023.1272514] [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: 08/04/2023] [Accepted: 10/04/2023] [Indexed: 11/07/2023] Open
Abstract
Background Nowadays, researchers are using advanced multimodal neuroimaging techniques to construct the brain network connectome to elucidate the complex relationship among the networks of brain functions and structure. The objective of this study was to evaluate the coupling of structural connectivity (SC) and functional connectivity (FC) in the entire brain of healthy controls (HCs), and to investigate modifications in SC-FC coupling in individuals suffering from temporal lobe epilepsy (TLE). Methods We evaluated 65 patients with TLE matched for age and gender with 48 healthy controls. The SC-FC coupling between regions was determined, based on which whole-brain nodes were clustered. Differences in the coupling among the three groups of nodes were compared. To further validate the results obtained, the within-cluster coupling indices of the three groups were compared to determine the inter-group differences. Results Nodes were divided into five clusters. Cluster 1 was primarily located in the limbic system (n = 9/27), whereas cluster 5 was mainly within the visual network (n = 12/29). By comparing average cluster SC-FC coupling in each cluster of the three groups, we identified marked discrepancies within the three cohorts in Cluster 3 (p = 0.001), Cluster 4 (p < 0.001), and Cluster 5 (p < 0.001). Post-hoc analysis revealed that the SC-FC coupling strengths in LTLE and RTLE were significantly lower than that in HCs in Cluster 3 (PL = 0.001/PR = 0.003), Cluster 4 (PL = 0.001/PR < 0.001), and Cluster 5 (PL < 0.001/PR < 0.001). We also observed that the within-cluster SC-FC coupling in cluster 5 of left- and right TLE was significantly lower than in HCs (PL = 0.0001, PR = 0.0005). Conclusion The SC and FC are inconsistently coupled across the brain with spatial heterogeneity. In the fifth cluster with the highest degree of coupling in HCs, the average SC-FC coupling index of individuals with TLE was notably less than that of HCs, manifesting that brain regions with high coupling may be more delicate and prone to pathological disruption.
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Affiliation(s)
- Xiaoting Huang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yangsa Du
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Danni Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Fangfang Xie
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Chunyao Zhou
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
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32
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Boot EM, Omes QPM, Maaijwee N, Schaapsmeerders P, Arntz RM, Rutten-Jacobs LCA, Kessels RPC, de Leeuw FE, Tuladhar AM. Functional brain connectivity in young adults with post-stroke epilepsy. Brain Commun 2023; 5:fcad277. [PMID: 37953839 PMCID: PMC10639092 DOI: 10.1093/braincomms/fcad277] [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: 08/02/2022] [Revised: 08/07/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
Approximately 1 in 10 young stroke patients (18-50 years) will develop post-stroke epilepsy, which is associated with cognitive impairment. While previous studies have shown altered brain connectivity in patients with epilepsy, little is however known about the changes in functional brain connectivity in young stroke patients with post-stroke epilepsy and their relationship with cognitive impairment. Therefore, we aimed to investigate whether young ischaemic stroke patients have altered functional networks and whether this alteration is related to cognitive impairment. We included 164 participants with a first-ever cerebral infarction at young age (18-50 years), along with 77 age- and sex-matched controls, from the Follow-Up of Transient Ischemic Attack and Stroke patients and Unelucidated Risk Factor Evaluation study. All participants underwent neuropsychological testing and resting-state functional MRI to generate functional connectivity networks. At follow-up (10.5 years after the index event), 23 participants developed post-stroke epilepsy. Graph theoretical analysis revealed functional network reorganization in participants with post-stroke epilepsy, in whom a weaker (i.e. network strength), less-integrated (i.e. global efficiency) and less-segregated (i.e. clustering coefficient and local efficiency) functional network was observed compared with the participants without post-stroke epilepsy group and the controls (P < 0.05). Regional analysis showed a trend towards decreased clustering coefficient, local efficiency and nodal efficiency in contralesional brain regions, including the caudal anterior cingulate cortex, posterior cingulate cortex, precuneus, superior frontal gyrus and insula in participants with post-stroke epilepsy compared with those without post-stroke epilepsy. Furthermore, participants with post-stroke epilepsy more often had impairment in the processing speed domain than the group without post-stroke epilepsy, in whom the network properties of the precuneus were positively associated with processing speed performance. Our findings suggest that post-stroke epilepsy is associated with functional reorganization of the brain network after stroke that is characterized by a weaker, less-integrated and less-segregated brain network in young ischaemic stroke patients compared with patients without post-stroke epilepsy. The contralesional brain regions, which are mostly considered as hub regions, might be particularly involved in the altered functional network and may contribute to cognitive impairment in post-stroke epilepsy patients. Overall, our findings provide additional evidence for a potential role of disrupted functional network as underlying pathophysiological mechanism for cognitive impairment in patients with post-stroke epilepsy.
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Affiliation(s)
- Esther M Boot
- Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Radboud University Medical Centre, Nijmegen 6525GA, The Netherlands
| | - Quinty P M Omes
- Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Radboud University Medical Centre, Nijmegen 6525GA, The Netherlands
| | - Noortje Maaijwee
- Department of Neurology and Neurorehabilitation, Luzerner Kantonsspital Neurocentre, Luzern 16, Switzerland
| | | | - Renate M Arntz
- Department of Neurology, Medisch Spectrum Twente, Enschede 7500 KA, The Netherlands
| | | | - Roy P C Kessels
- Donders Institute for Brain, Cognition and Behaviour, Department of Psychology, Radboud University, Nijmegen 6525 GD, The Netherlands
- Department of Medical Psychology and Radboudumc Alzheimer Centre, Radboud University Medical Centre, Nijmegen 6525 GA, The Netherlands
- Vincent van Gogh Institute for Psychiatry, Venray 5803 AC, The Netherlands
| | - Frank-Erik de Leeuw
- Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Radboud University Medical Centre, Nijmegen 6525GA, The Netherlands
| | - Anil M Tuladhar
- Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Radboud University Medical Centre, Nijmegen 6525GA, The Netherlands
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33
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Babiloni C, Lopez S, Noce G, Ferri R, Panerai S, Catania V, Soricelli A, Salvatore M, Nobili F, Arnaldi D, Famà F, Massa F, Buttinelli C, Giubilei F, Stocchi F, Vacca L, Marizzoni M, D'Antonio F, Bruno G, De Lena C, Güntekin B, Yıldırım E, Hanoğlu L, Yener G, Yerlikaya D, Taylor JP, Schumacher J, McKeith I, Bonanni L, Pantano P, Piervincenzi C, Petsas N, Frisoni GB, Del Percio C, Carducci F. Relationship between default mode network and resting-state electroencephalographic alpha rhythms in cognitively unimpaired seniors and patients with dementia due to Alzheimer's disease. Cereb Cortex 2023; 33:10514-10527. [PMID: 37615301 PMCID: PMC10588004 DOI: 10.1093/cercor/bhad300] [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: 09/15/2022] [Revised: 07/26/2023] [Accepted: 07/27/2023] [Indexed: 08/25/2023] Open
Abstract
Here we tested the hypothesis of a relationship between the cortical default mode network (DMN) structural integrity and the resting-state electroencephalographic (rsEEG) rhythms in patients with Alzheimer's disease with dementia (ADD). Clinical and instrumental datasets in 45 ADD patients and 40 normal elderly (Nold) persons originated from the PDWAVES Consortium (www.pdwaves.eu). Individual rsEEG delta, theta, alpha, and fixed beta and gamma bands were considered. Freeware platforms served to derive (1) the (gray matter) volume of the DMN, dorsal attention (DAN), and sensorimotor (SMN) cortical networks and (2) the rsEEG cortical eLORETA source activities. We found a significant positive association between the DMN gray matter volume, the rsEEG alpha source activity estimated in the posterior DMN nodes (parietal and posterior cingulate cortex), and the global cognitive status in the Nold and ADD participants. Compared with the Nold, the ADD group showed lower DMN gray matter, lower rsEEG alpha source activity in those nodes, and lower global cognitive status. This effect was not observed in the DAN and SMN. These results suggest that the DMN structural integrity and the rsEEG alpha source activities in the DMN posterior hubs may be related and predict the global cognitive status in ADD and Nold persons.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology “Vittorio Erspamer,” Sapienza University of Rome, Rome, Italy
- Hospital San Raffaele Cassino, Cassino (FR), Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology “Vittorio Erspamer,” Sapienza University of Rome, Rome, Italy
| | | | | | | | | | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy
- Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Flavio Nobili
- Clinica neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Italy
| | - Dario Arnaldi
- Clinica neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy
- Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Italy
| | - Francesco Famà
- Clinica neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Federico Massa
- Clinica neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | | | | | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Fabrizia D'Antonio
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Giuseppe Bruno
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Carlo De Lena
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, International School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Ebru Yıldırım
- Program of Electroneurophysiology, Vocational School, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Görsev Yener
- Izmir School of Economics, Faculty of Medicine, Izmir, Turkey
| | - Deniz Yerlikaya
- Health Sciences Institute, Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - John Paul Taylor
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, United Kingdom
| | - Julia Schumacher
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, United Kingdom
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Ian McKeith
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, United Kingdom
| | - Laura Bonanni
- Department of Medicine and Aging Sciences, University “G. d'Annunzio” of Chieti-Pescara, Chieti, Italy
| | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
- IRCCS Neuromed, Pozzilli (IS), Italy
| | | | - Nikolaos Petsas
- Scuola di Specializzazione in Statistica Medica e Biometria, Dipartimento di Sanità Pubblica e Malattie Infettive, Sapienza University of Rome, Rome, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Claudio Del Percio
- Department of Physiology and Pharmacology “Vittorio Erspamer,” Sapienza University of Rome, Rome, Italy
| | - Filippo Carducci
- Department of Physiology and Pharmacology “Vittorio Erspamer,” Sapienza University of Rome, Rome, Italy
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Jin H, Verma P, Jiang F, Nagarajan SS, Raj A. Bayesian inference of a spectral graph model for brain oscillations. Neuroimage 2023; 279:120278. [PMID: 37516373 PMCID: PMC10840584 DOI: 10.1016/j.neuroimage.2023.120278] [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: 02/13/2023] [Revised: 05/22/2023] [Accepted: 07/12/2023] [Indexed: 07/31/2023] Open
Abstract
The relationship between brain functional connectivity and structural connectivity has caught extensive attention of the neuroscience community, commonly inferred using mathematical modeling. Among many modeling approaches, spectral graph model (SGM) is distinctive as it has a closed-form solution of the wide-band frequency spectra of brain oscillations, requiring only global biophysically interpretable parameters. While SGM is parsimonious in parameters, the determination of SGM parameters is non-trivial. Prior works on SGM determine the parameters through a computational intensive annealing algorithm, which only provides a point estimate with no confidence intervals for parameter estimates. To fill this gap, we incorporate the simulation-based inference (SBI) algorithm and develop a Bayesian procedure for inferring the posterior distribution of the SGM parameters. Furthermore, using SBI dramatically reduces the computational burden for inferring the SGM parameters. We evaluate the proposed SBI-SGM framework on the resting-state magnetoencephalography recordings from healthy subjects and show that the proposed procedure has similar performance to the annealing algorithm in recovering power spectra and the spatial distribution of the alpha frequency band. In addition, we also analyze the correlations among the parameters and their uncertainty with the posterior distribution which cannot be done with annealing inference. These analyses provide a richer understanding of the interactions among biophysical parameters of the SGM. In general, the use of simulation-based Bayesian inference enables robust and efficient computations of generative model parameter uncertainties and may pave the way for the use of generative models in clinical translation applications.
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Affiliation(s)
- Huaqing Jin
- Department of Radiology and Biomedical Imaging University of California San Francisco, San Francisco, CA, USA
| | - Parul Verma
- Department of Radiology and Biomedical Imaging University of California San Francisco, San Francisco, CA, USA
| | - Fei Jiang
- Department of Epidemiology and Biostatistics University of California San Francisco, San Francisco, CA, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging University of California San Francisco, San Francisco, CA, USA.
| | - Ashish Raj
- Department of Radiology and Biomedical Imaging University of California San Francisco, San Francisco, CA, USA.
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35
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Ali DG, Bahrani AA, El Khouli RH, Gold BT, Jiang Y, Zachariou V, Wilcock DM, Jicha GA. White matter hyperintensities influence distal cortical β-amyloid accumulation in default mode network pathways. Brain Behav 2023; 13:e3209. [PMID: 37534614 PMCID: PMC10570488 DOI: 10.1002/brb3.3209] [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: 02/16/2023] [Revised: 07/19/2023] [Accepted: 07/22/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND AND PURPOSE Cerebral small vessel disease (SVD) has been suggested to contribute to the pathogenesis of Alzheimer's disease (AD). Yet, the role of SVD in potentially contributing to AD pathology is unclear. The main objective of this study was to test the hypothesis that WMHs influence amyloid β (Aβ) levels within connected default mode network (DMN) tracts and cortical regions in cognitively unimpaired older adults. METHODS Regional standard uptake value ratios (SUVr) from Aβ-PET and white matter hyperintensity (WMH) volumes from three-dimensional magnetic resonance imaging FLAIR images were analyzed across a sample of 72 clinically unimpaired (mini-mental state examination ≥26), older adults (mean age 74.96 and standard deviation 8.13) from the Alzheimer's Disease Neuroimaging Initiative (ADNI3). The association of WMH volumes in major fiber tracts projecting from cortical DMN regions and Aβ-PET SUVr in the connected cortical DMN regions was analyzed using linear regression models adjusted for age, sex, ApoE, and total brain volumes. RESULTS The regression analyses demonstrate that increased WMH volumes in the superior longitudinal fasciculus were associated with increased regional SUVr in the inferior parietal lobule (p = .011). CONCLUSION The findings suggest that the relation between Aβ in parietal cortex is associated with SVD in downstream white matter (WM) pathways in preclinical AD. The biological relationships and interplay between Aβ and WM microstructure alterations that precede overt WMH development across the continuum of AD progression warrant further study.
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Affiliation(s)
- Doaa G. Ali
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Ahmed A. Bahrani
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Riham H. El Khouli
- Department of Radiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Brian T. Gold
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Yang Jiang
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Valentinos Zachariou
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Donna M. Wilcock
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Physiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Gregory A. Jicha
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
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Aganj I, Mora J, Frau‐Pascual A, Fischl B. Exploratory correlation of the human structural connectome with non-MRI variables in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12511. [PMID: 38111597 PMCID: PMC10725839 DOI: 10.1002/dad2.12511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 11/08/2023] [Accepted: 11/20/2023] [Indexed: 12/20/2023]
Abstract
Introduction Discovery of the associations between brain structural connectivity and clinical and demographic variables can help to better understand the vulnerability and resilience of the brain architecture to neurodegenerative diseases and to discover biomarkers. Methods We used four diffusion-MRI databases, three related to Alzheimer's disease (AD), to exploratorily correlate structural connections between 85 brain regions with non-MRI variables, while stringently correcting the significance values for multiple testing and ruling out spurious correlations via careful visual inspection. We repeated the analysis with brain connectivity augmented with multi-synaptic neural pathways. Results We found 85 and 101 significant relationships with direct and augmented connectivity, respectively, which were generally stronger for the latter. Age was consistently linked to decreased connectivity, and healthier clinical scores were generally linked to increased connectivity. Discussion Our findings help to elucidate which structural brain networks are affected in AD and aging and highlight the importance of including indirect connections.
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Affiliation(s)
- Iman Aganj
- Athinoula A. Martinos Center for Biomedical ImagingRadiology DepartmentMassachusetts General HospitalBostonMassachusettsUSA
- Radiology DepartmentHarvard Medical SchoolBostonMassachusettsUSA
| | - Jocelyn Mora
- Athinoula A. Martinos Center for Biomedical ImagingRadiology DepartmentMassachusetts General HospitalBostonMassachusettsUSA
| | - Aina Frau‐Pascual
- Athinoula A. Martinos Center for Biomedical ImagingRadiology DepartmentMassachusetts General HospitalBostonMassachusettsUSA
- Radiology DepartmentHarvard Medical SchoolBostonMassachusettsUSA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical ImagingRadiology DepartmentMassachusetts General HospitalBostonMassachusettsUSA
- Radiology DepartmentHarvard Medical SchoolBostonMassachusettsUSA
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Milisav F, Bazinet V, Iturria-Medina Y, Misic B. Resolving inter-regional communication capacity in the human connectome. Netw Neurosci 2023; 7:1051-1079. [PMID: 37781139 PMCID: PMC10473316 DOI: 10.1162/netn_a_00318] [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: 10/11/2022] [Accepted: 04/03/2023] [Indexed: 10/03/2023] Open
Abstract
Applications of graph theory to the connectome have inspired several models of how neural signaling unfolds atop its structure. Analytic measures derived from these communication models have mainly been used to extract global characteristics of brain networks, obscuring potentially informative inter-regional relationships. Here we develop a simple standardization method to investigate polysynaptic communication pathways between pairs of cortical regions. This procedure allows us to determine which pairs of nodes are topologically closer and which are further than expected on the basis of their degree. We find that communication pathways delineate canonical functional systems. Relating nodal communication capacity to meta-analytic probabilistic patterns of functional specialization, we also show that areas that are most closely integrated within the network are associated with higher order cognitive functions. We find that these regions' proclivity towards functional integration could naturally arise from the brain's anatomical configuration through evenly distributed connections among multiple specialized communities. Throughout, we consider two increasingly constrained null models to disentangle the effects of the network's topology from those passively endowed by spatial embedding. Altogether, the present findings uncover relationships between polysynaptic communication pathways and the brain's functional organization across multiple topological levels of analysis and demonstrate that network integration facilitates cognitive integration.
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Affiliation(s)
- Filip Milisav
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Vincent Bazinet
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Yasser Iturria-Medina
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
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Shokri-Kojori E, Tomasi D, Demiral SB, Wang GJ, Volkow ND. An autonomic mode of brain activity. Prog Neurobiol 2023; 229:102510. [PMID: 37516341 PMCID: PMC10591458 DOI: 10.1016/j.pneurobio.2023.102510] [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: 02/07/2023] [Revised: 05/11/2023] [Accepted: 07/18/2023] [Indexed: 07/31/2023]
Abstract
The relevance of interactions between autonomic and central nervous systems remains unclear for human brain function and health, particularly when both systems are challenged under sleep deprivation (SD). We measured brain activity (with fMRI), pulse and respiratory signals, and baseline brain amyloid beta burden (with PET) in healthy participants. We found that SD relative to rested wakefulness (RW) resulted in a significant increase in synchronized low frequency (LF, < 0.1 Hz) activity in an autonomically-related network (AN), including dorsal attention, visual, and sensorimotor regions, which we previously found to have consistent temporal coupling with LF pulse signal changes (regulated by sympathetic tone). SD resulted in a significant phase coherence between the LF component of the pulse signal and a medial network with peak effects in the midbrain reticular formation, and between LF component of the respiratory variations (regulated by respiratory motor output) and a cerebellar network. The LF power of AN during SD was significantly and independently correlated with pulse-medial network and respiratory-cerebellar network phase coherences (total adjusted R2 = 0.78). Higher LF power of AN during SD (but not RW) was associated with lower amyloid beta burden (Cohen's d = 0.8). In sum, SD triggered an autonomic mode of synchronized brain activity that was associated with distinct autonomic-central interactions. Findings highlight the direct relevance of global cortical synchronization to brain clearance mechanisms.
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Affiliation(s)
- Ehsan Shokri-Kojori
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
| | - Dardo Tomasi
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Sukru B Demiral
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Gene-Jack Wang
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Nora D Volkow
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
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Mayorova L, Portnova G, Skorokhodov I. Cortical Response Variation with Social and Non-Social Affective Touch Processing in the Glabrous and Hairy Skin of the Leg: A Pilot fMRI Study. SENSORS (BASEL, SWITZERLAND) 2023; 23:7881. [PMID: 37765936 PMCID: PMC10538157 DOI: 10.3390/s23187881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/12/2023] [Accepted: 08/21/2023] [Indexed: 09/29/2023]
Abstract
Despite the crucial role of touch in social development and its importance for social interactions, there has been very little functional magnetic resonance imaging (fMRI) research on brain mechanisms underlying social touch processing. Moreover, there has been very little research on the perception of social touch in the lower extremities in humans, even though this information could expand our understanding of the mechanisms of the c-tactile system. Here, variations in the neural response to stimulation by social and non-social affective leg touch were investigated using fMRI. Participants were subjected to slow a (at 3-5 cm/s) stroking social touch (hand, skin-to-skin) and a non-social touch (peacock feather) to the hairy skin of the shin and to the glabrous skin of the foot sole. Stimulation of the glabrous skin of the foot sole, regardless of the type of stimulus, elicited a much more widespread cortical response, including structures such as the medial segment of precentral gyri, left precentral gyrus, bilateral putamen, anterior insula, left postcentral gyrus, right thalamus, and pallidum. Stimulation of the hairy skin of the shin elicited a relatively greater response in the left middle cingulate gyrus, left angular gyrus, left frontal eye field, bilateral anterior prefrontal cortex, and left frontal pole. Activation of brain structures, some of which belong to the "social brain"-the pre- and postcentral gyri bilaterally, superior and middle occipital gyri bilaterally, left middle and superior temporal gyri, right anterior cingulate gyrus and caudate, left middle and inferior frontal gyri, and left lateral ventricle area, was associated with the perception of non-social stimuli in the leg. The left medial segment of pre- and postcentral gyri, left postcentral gyrus and precuneus, bilateral parietal operculum, right planum temporale, left central operculum, and left thalamus proper showed greater activation for social tactile touch. There are regions in the cerebral cortex that responded specifically to hand and feather touch in the foot sole region. These areas included the posterior insula, precentral gyrus; putamen, pallidum and anterior insula; superior parietal cortex; transverse temporal gyrus and parietal operculum, supramarginal gyrus and planum temporale. Subjective assessment of stimulus ticklishness was related to activation of the left cuneal region. Our results make some contribution to understanding the physiology of the perception of social and non-social tactile stimuli and the CT system, including its evolution, and they have clinical impact in terms of environmental enrichment.
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Affiliation(s)
- Larisa Mayorova
- Laboratory of Physiology of Sensory Systems, Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Science, 117485 Moscow, Russia
- Laboratory for the Study of Tactile Communication, Pushkin State Russian Language Institute, 117485 Moscow, Russia
| | - Galina Portnova
- Laboratory for the Study of Tactile Communication, Pushkin State Russian Language Institute, 117485 Moscow, Russia
- Laboratory of Human Higher Nervous Activity, Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Science, 117485 Moscow, Russia
| | - Ivan Skorokhodov
- Laboratory for the Study of Tactile Communication, Pushkin State Russian Language Institute, 117485 Moscow, Russia
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Hansen JY, Shafiei G, Voigt K, Liang EX, Cox SML, Leyton M, Jamadar SD, Misic B. Integrating multimodal and multiscale connectivity blueprints of the human cerebral cortex in health and disease. PLoS Biol 2023; 21:e3002314. [PMID: 37747886 PMCID: PMC10553842 DOI: 10.1371/journal.pbio.3002314] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 10/05/2023] [Accepted: 08/28/2023] [Indexed: 09/27/2023] Open
Abstract
The brain is composed of disparate neural populations that communicate and interact with one another. Although fiber bundles, similarities in molecular architecture, and synchronized neural activity all reflect how brain regions potentially interact with one another, a comprehensive study of how all these interregional relationships jointly reflect brain structure and function remains missing. Here, we systematically integrate 7 multimodal, multiscale types of interregional similarity ("connectivity modes") derived from gene expression, neurotransmitter receptor density, cellular morphology, glucose metabolism, haemodynamic activity, and electrophysiology in humans. We first show that for all connectivity modes, feature similarity decreases with distance and increases when regions are structurally connected. Next, we show that connectivity modes exhibit unique and diverse connection patterns, hub profiles, spatial gradients, and modular organization. Throughout, we observe a consistent primacy of molecular connectivity modes-namely correlated gene expression and receptor similarity-that map onto multiple phenomena, including the rich club and patterns of abnormal cortical thickness across 13 neurological, psychiatric, and neurodevelopmental disorders. Finally, to construct a single multimodal wiring map of the human cortex, we fuse all 7 connectivity modes and show that the fused network maps onto major organizational features of the cortex including structural connectivity, intrinsic functional networks, and cytoarchitectonic classes. Altogether, this work contributes to the integrative study of interregional relationships in the human cerebral cortex.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Katharina Voigt
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Emma X. Liang
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | | | - Marco Leyton
- Montréal Neurological Institute, McGill University, Montréal, Canada
- Department of Psychiatry, McGill University, Montréal, Canada
| | - Sharna D. Jamadar
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Canada
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Cormie MA, Kaya B, Hadjis GE, Mouseli P, Moayedi M. Insula-cingulate structural and functional connectivity: an ultra-high field MRI study. Cereb Cortex 2023; 33:9787-9801. [PMID: 37429832 PMCID: PMC10656949 DOI: 10.1093/cercor/bhad244] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 06/16/2023] [Accepted: 06/17/2023] [Indexed: 07/12/2023] Open
Abstract
The insula and the cingulate are key brain regions with many heterogenous functions. Both regions are consistently shown to play integral roles in the processing of affective, cognitive, and interoceptive stimuli. The anterior insula (aINS) and the anterior mid-cingulate cortex (aMCC) are two key hubs of the salience network (SN). Beyond the aINS and aMCC, previous 3 Tesla (T) magnetic resonance imaging studies have suggested both structural connectivity (SC) and functional connectivity (FC) between other insular and cingulate subregions. Here, we investigate the SC and FC between insula and cingulate subregions using ultra-high field 7T diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI). DTI revealed strong SC between posterior INS (pINS) and posterior MCC (pMCC), and rs-fMRI revealed strong FC between the aINS and aMCC that was not supported by SC, indicating the likelihood of a mediating structure. Finally, the insular pole had the strongest SC to all cingulate subregions, with a slight preference for the pMCC, indicative of a potential relay node of the insula. Together these finding shed new light on the understanding of insula-cingulate functioning, both within the SN and other cortical processes, through a lens of its SC and FC.
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Affiliation(s)
- Matthew A Cormie
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, ON, Canada
- University of Toronto Centre for the Study of Pain, Toronto, ON, Canada
| | - Batu Kaya
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, ON, Canada
- University of Toronto Centre for the Study of Pain, Toronto, ON, Canada
| | - Georgia E Hadjis
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, ON, Canada
- University of Toronto Centre for the Study of Pain, Toronto, ON, Canada
| | - Pedram Mouseli
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, ON, Canada
- University of Toronto Centre for the Study of Pain, Toronto, ON, Canada
| | - Massieh Moayedi
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, ON, Canada
- University of Toronto Centre for the Study of Pain, Toronto, ON, Canada
- Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Department of Dentistry, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
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42
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León JJ, Fernández-Martin P, González-Rodríguez A, Rodríguez-Herrera R, García-Pinteño J, Pérez-Fernández C, Sánchez-Kuhn A, Amaya-Pascasio L, Soto-Ontoso M, Martínez-Sánchez P, Sánchez-Santed F, Flores P. Decision-making and frontoparietal resting-state functional connectivity among impulsive-compulsive diagnoses. Insights from a Bayesian approach. Addict Behav 2023; 143:107683. [PMID: 36963236 DOI: 10.1016/j.addbeh.2023.107683] [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: 10/14/2022] [Revised: 02/20/2023] [Accepted: 02/24/2023] [Indexed: 03/13/2023]
Abstract
The Iowa Gambling Task (IGT) is one of the most widely used paradigms for assessing decision-making. An impairment in this process may be linked to several psychopathological disorders, such as obsessive-compulsive disorder (OCD), substance abuse disorder (SUD) or attention-deficit/hyperactivity disorder (ADHD), which could make it a good candidate for being consider a transdiagnostic domain. Resting-state functional connectivity (rsFC) has been proposed as a promising biomarker of decision-making. In this study, we aimed to identify idiosyncratic decision-making profiles among healthy people and impulsive-compulsive spectrum patients during the IGT, and to investigate the role of frontoparietal network (FPN) rsFC as a possible biomarker of different decision-making patterns. Using functional near-infrared spectroscopy (fNIRS), rsFC of 114 adults (34 controls; 25 OCD; 41 SUD; 14 ADHD) was obtained. Then, they completed the IGT. Hybrid clustering methods based on individual deck choices yielded three decision-makers subgroups. Cluster 1 (n = 27) showed a long-term advantageous strategy. Cluster 2 (n = 25) presented a maladaptive decision-making strategy. Cluster 3 (n = 62) did not develop a preference for any deck during the task. Interestingly, the proportion of participants in each cluster was not different between diagnostic groups. A Bayesian general linear model showed no credible differences in the IGT performance between diagnostic groups nor credible evidence to support the role of FPN rsFC as a biomarker of decision-making under the IGT context. This study highlights the importance of exploring in depth the behavioral and neurophysiological variables that may drive decision-making in clinical and healthy populations.
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Affiliation(s)
- J J León
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - P Fernández-Martin
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - A González-Rodríguez
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - R Rodríguez-Herrera
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - J García-Pinteño
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - C Pérez-Fernández
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - A Sánchez-Kuhn
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - L Amaya-Pascasio
- Department of Neurology and Stroke Centre. Torrecárdenas University Hospital, Spain.
| | - M Soto-Ontoso
- Mental Health Departament. Torrecárdenas University Hospital, Spain.
| | - P Martínez-Sánchez
- Department of Neurology and Stroke Centre. Torrecárdenas University Hospital, Spain.
| | - F Sánchez-Santed
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
| | - P Flores
- Department of Psychology, Faculty of Psychology, University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain; Health Research Centre (CEINSA), University of Almeria, Carretera de Sacramento S/N, 04120, La Cañada de San Urbano, Almeria, Spain.
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Ibáñez-Berganza M, Lucibello C, Santucci F, Gili T, Gabrielli A. Noise cleaning the precision matrix of short time series. Phys Rev E 2023; 108:024313. [PMID: 37723818 DOI: 10.1103/physreve.108.024313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 08/02/2023] [Indexed: 09/20/2023]
Abstract
We present a comparison between various algorithms of inference of covariance and precision matrices in small data sets of real vectors of the typical length and dimension of human brain activity time series retrieved by functional magnetic resonance imaging (fMRI). Assuming a Gaussian model underlying the neural activity, the problem consists of denoising the empirically observed matrices to obtain a better estimator of the (unknown) true precision and covariance matrices. We consider several standard noise-cleaning algorithms and compare them on two types of data sets. The first type consists of synthetic time series sampled from a generative Gaussian model of which we can vary the fraction of dimensions per sample q and the strength of off-diagonal correlations. The second type consists of time series of fMRI brain activity of human subjects at rest. The reliability of each algorithm is assessed in terms of test-set likelihood and, in the case of synthetic data, of the distance from the true precision matrix. We observe that the so-called optimal rotationally invariant estimator, based on random matrix theory, leads to a significantly lower distance from the true precision matrix in synthetic data and higher test likelihood in natural fMRI data. We propose a variant of the optimal rotationally invariant estimator in which one of its parameters is optimzed by cross-validation. In the severe undersampling regime (large q) typical of fMRI series, it outperforms all the other estimators. We furthermore propose a simple algorithm based on an iterative likelihood gradient ascent, leading to very accurate estimations in weakly correlated synthetic data sets.
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Affiliation(s)
- Miguel Ibáñez-Berganza
- Networks Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco 19, 50100 Lucca, Italy and Istituto Italiano di Tecnologia. Largo Barsanti e Matteucci, 53, 80125 Napoli, Italy
| | - Carlo Lucibello
- AI Lab, Institute for Data Science and Analytics, Bocconi University, 20136 Milano, Italy
| | - Francesca Santucci
- Networks Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco 19, 50100 Lucca, Italy
| | - Tommaso Gili
- Networks Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco 19, 50100 Lucca, Italy
| | - Andrea Gabrielli
- Dipartimento di Ingegneria Civile, Informatica e delle Tecnologie Aeronautiche, Universitá degli Studi Roma Tre, Via Vito Volterra 62, 00146 Rome, Italy and Centro Ricerche Enrico Fermi, Via Panisperna 89a, 00184 Rome, Italy
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Nozais V, Forkel SJ, Petit L, Talozzi L, Corbetta M, Thiebaut de Schotten M, Joliot M. Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain. Commun Biol 2023; 6:726. [PMID: 37452124 PMCID: PMC10349117 DOI: 10.1038/s42003-023-05107-3] [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: 08/24/2022] [Accepted: 07/06/2023] [Indexed: 07/18/2023] Open
Abstract
Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.
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Affiliation(s)
- Victor Nozais
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France.
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France.
| | - Stephanie J Forkel
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Donders Institute for Brain Cognition Behaviour, Radboud University, Nijmegen, the Netherlands
- Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Departments of Neurosurgery, Technical University of Munich School of Medicine, Munich, Germany
| | - Laurent Petit
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France
| | - Lia Talozzi
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Maurizio Corbetta
- Department of Neuroscience, Venetian Institute of Molecular Medicine and Padova Neuroscience Center, University of Padua, Padova, PD, 32122, Italy
| | - Michel Thiebaut de Schotten
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
| | - Marc Joliot
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France.
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45
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Bolton TAW, Van De Ville D, Amico E, Preti MG, Liégeois R. The arrow-of-time in neuroimaging time series identifies causal triggers of brain function. Hum Brain Mapp 2023; 44:4077-4087. [PMID: 37209360 PMCID: PMC10258533 DOI: 10.1002/hbm.26331] [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: 11/15/2022] [Revised: 03/07/2023] [Accepted: 04/18/2023] [Indexed: 05/22/2023] Open
Abstract
Moving from association to causal analysis of neuroimaging data is crucial to advance our understanding of brain function. The arrow-of-time (AoT), that is, the known asymmetric nature of the passage of time, is the bedrock of causal structures shaping physical phenomena. However, almost all current time series metrics do not exploit this asymmetry, probably due to the difficulty to account for it in modeling frameworks. Here, we introduce an AoT-sensitive metric that captures the intensity of causal effects in multivariate time series, and apply it to high-resolution functional neuroimaging data. We find that causal effects underlying brain function are more distinctively localized in space and time than functional activity or connectivity, thereby allowing us to trace neural pathways recruited in different conditions. Overall, we provide a mapping of the causal brain that challenges the association paradigm of brain function.
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Affiliation(s)
- Thomas A. W. Bolton
- Connectomics Laboratory, Department of RadiologyCentre Hospitalier Universitaire VaudoisLausanneSwitzerland
- Department of Clinical NeurosciencesCentre Hospitalier Universitaire VaudoisLausanneSwitzerland
| | - Dimitri Van De Ville
- Neuro‐X InstituteÉcole Polytechnique Fédérale de LausanneLausanneSwitzerland
- Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
| | - Enrico Amico
- Neuro‐X InstituteÉcole Polytechnique Fédérale de LausanneLausanneSwitzerland
- Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
| | - Maria G. Preti
- Neuro‐X InstituteÉcole Polytechnique Fédérale de LausanneLausanneSwitzerland
- Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
- CIBM Center for Biomedical ImagingVaudSwitzerland
| | - Raphaël Liégeois
- Neuro‐X InstituteÉcole Polytechnique Fédérale de LausanneLausanneSwitzerland
- Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
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Wu D, Li X. Graph propagation network captures individual specificity of the relationship between functional and structural connectivity. Hum Brain Mapp 2023; 44:3885-3896. [PMID: 37186004 PMCID: PMC10203799 DOI: 10.1002/hbm.26320] [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: 01/08/2023] [Revised: 04/06/2023] [Accepted: 04/12/2023] [Indexed: 05/17/2023] Open
Abstract
Functional connectivity (FC) network characterizes the functional interactions between brain regions and is considered to root in the underlying structural connectivity (SC) network. If this is the case, individual variations in SC should cause corresponding individual variations in FC. However, divergences exist in the correspondence between direct SC and FC and researchers still cannot capture individual differences in FC via direct SC. As brain regions may interact through multi-hop indirect SC pathways, we conceived that one can capture the individual specific SC-FC relationship via incorporating indirect SC pathways appropriately. In this study, we designed graph propagation network (GPN) that models the information propagation between brain regions based on the SC network. Effects of interactions through multi-hop SC pathways naturally emerge from the multilayer information propagation in GPN. We predicted the individual differences in FC network based on SC network via multilayer GPN and results indicate that multilayer GPN incorporating effects of multi-hop indirect SCs greatly enhances the ability to predict individual FC network. Furthermore, the SC-FC relationship evaluated via the prediction accuracy is negatively correlated with the functional gradient, suggesting that the SC-FC relationship gradually uncouples along the functional hierarchy spanning from unimodal to transmodal cortex. We also revealed important intermediate brain regions along multi-hop SC pathways involving in the individual SC-FC relationship. These results suggest that multilayer GPN can serve as a method to establish individual SC-FC relationship at the macroneuroimaging level.
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Affiliation(s)
- Dongya Wu
- School of Information Science and TechnologyNorthwest UniversityXi'anChina
| | - Xin Li
- School of MathematicsNorthwest UniversityXi'anChina
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Frank LE, Zeithamova D. Evaluating methods for measuring background connectivity in slow event-related functional magnetic resonance imaging designs. Brain Behav 2023; 13:e3015. [PMID: 37062880 PMCID: PMC10275534 DOI: 10.1002/brb3.3015] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/10/2023] [Accepted: 03/20/2023] [Indexed: 04/18/2023] Open
Abstract
INTRODUCTION Resting-state functional magnetic resonance imaging (fMRI) is widely used for measuring functional interactions between brain regions, significantly contributing to our understanding of large-scale brain networks and brain-behavior relationships. Furthermore, idiosyncratic patterns of resting-state connections can be leveraged to identify individuals and predict individual differences in clinical symptoms, cognitive abilities, and other individual factors. Idiosyncratic connectivity patterns are thought to persist across task states, suggesting task-based fMRI can be similarly leveraged for individual differences analyses. METHOD Here, we tested the degree to which functional interactions occurring in the background of a task during slow event-related fMRI parallel or differ from those captured during resting-state fMRI. We compared two approaches for removing task-evoked activity from task-based fMRI: (1) applying a low-pass filter to remove task-related frequencies in the signal, or (2) extracting residuals from a general linear model (GLM) that accounts for task-evoked responses. RESULT We found that the organization of large-scale cortical networks and individual's idiosyncratic connectivity patterns are preserved during task-based fMRI. In contrast, individual differences in connection strength can vary more substantially between rest and task. Compared to low-pass filtering, background connectivity obtained from GLM residuals produced idiosyncratic connectivity patterns and individual differences in connection strength that more resembled rest. However, all background connectivity measures were highly similar when derived from the low-pass-filtered signal or GLM residuals, indicating that both methods are suitable for measuring background connectivity. CONCLUSION Together, our results highlight new avenues for the analysis of task-based fMRI datasets and the utility of each background connectivity method.
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Affiliation(s)
- Lea E. Frank
- Department of PsychologyUniversity of OregonEugeneOregonUSA
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48
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Li Z, Dong Q, Hu B, Wu H. Every individual makes a difference: A trinity derived from linking individual brain morphometry, connectivity and mentalising ability. Hum Brain Mapp 2023; 44:3343-3358. [PMID: 37051692 PMCID: PMC10171537 DOI: 10.1002/hbm.26285] [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: 04/19/2022] [Revised: 02/01/2023] [Accepted: 03/08/2023] [Indexed: 04/14/2023] Open
Abstract
Mentalising ability, indexed as the ability to understand others' beliefs, feelings, intentions, thoughts and traits, is a pivotal and fundamental component of human social cognition. However, considering the multifaceted nature of mentalising ability, little research has focused on characterising individual differences in different mentalising components. And even less research has been devoted to investigating how the variance in the structural and functional patterns of the amygdala and hippocampus, two vital subcortical regions of the "social brain", are related to inter-individual variability in mentalising ability. Here, as a first step toward filling these gaps, we exploited inter-subject representational similarity analysis (IS-RSA) to assess relationships between amygdala and hippocampal morphometry (surface-based multivariate morphometry statistics, MMS), connectivity (resting-state functional connectivity, rs-FC) and mentalising ability (interactive mentalisation questionnaire [IMQ] scores) across the participants ( N = 24 $$ N=24 $$ ). In IS-RSA, we proposed a novel pipeline, that is, computing patching and pooling operations-based surface distance (CPP-SD), to obtain a decent representation for high-dimensional MMS data. On this basis, we found significant correlations (i.e., second-order isomorphisms) between these three distinct modalities, indicating that a trinity existed in idiosyncratic patterns of brain morphometry, connectivity and mentalising ability. Notably, a region-related mentalising specificity emerged from these associations: self-self and self-other mentalisation are more related to the hippocampus, while other-self mentalisation shows a closer link with the amygdala. Furthermore, by utilising the dyadic regression analysis, we observed significant interactions such that subject pairs with similar morphometry had even greater mentalising similarity if they were also similar in rs-FC. Altogether, we demonstrated the feasibility and illustrated the promise of using IS-RSA to study individual differences, deepening our understanding of how individual brains give rise to their mentalising abilities.
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Affiliation(s)
- Zhaoning Li
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, China
| | - Qunxi Dong
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Bin Hu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Haiyan Wu
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, China
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Katsumi Y, Zhang J, Chen D, Kamona N, Bunce JG, Hutchinson JB, Yarossi M, Tunik E, Dickerson BC, Quigley KS, Barrett LF. Correspondence of functional connectivity gradients across human isocortex, cerebellum, and hippocampus. Commun Biol 2023; 6:401. [PMID: 37046050 PMCID: PMC10097701 DOI: 10.1038/s42003-023-04796-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/03/2023] [Indexed: 04/14/2023] Open
Abstract
Gradient mapping is an important technique to summarize high dimensional biological features as low dimensional manifold representations in exploring brain structure-function relationships at various levels of the cerebral cortex. While recent studies have characterized the major gradients of functional connectivity in several brain structures using this technique, very few have systematically examined the correspondence of such gradients across structures under a common systems-level framework. Using resting-state functional magnetic resonance imaging, here we show that the organizing principles of the isocortex, and those of the cerebellum and hippocampus in relation to the isocortex, can be described using two common functional gradients. We suggest that the similarity in functional connectivity gradients across these structures can be meaningfully interpreted within a common computational framework based on the principles of predictive processing. The present results, and the specific hypotheses that they suggest, represent an important step toward an integrative account of brain function.
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Affiliation(s)
- Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
| | - Jiahe Zhang
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Danlei Chen
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Nada Kamona
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Jamie G Bunce
- Department of Biology, Northeastern University, Boston, MA, 02115, USA
| | | | - Mathew Yarossi
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, 02115, USA
- Department of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, Boston, MA, 02115, USA
| | - Eugene Tunik
- Department of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, Boston, MA, 02115, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Karen S Quigley
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
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50
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Tissink E, Werme J, de Lange SC, Savage JE, Wei Y, de Leeuw CA, Nagel M, Posthuma D, van den Heuvel MP. The Genetic Architectures of Functional and Structural Connectivity Properties within Cerebral Resting-State Networks. eNeuro 2023; 10:ENEURO.0242-22.2023. [PMID: 36882310 PMCID: PMC10089056 DOI: 10.1523/eneuro.0242-22.2023] [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: 06/23/2022] [Revised: 12/12/2022] [Accepted: 01/08/2023] [Indexed: 03/09/2023] Open
Abstract
Functional connectivity within resting-state networks (RSN-FC) is vital for cognitive functioning. RSN-FC is heritable and partially translates to the anatomic architecture of white matter, but the genetic component of structural connections of RSNs (RSN-SC) and their potential genetic overlap with RSN-FC remain unknown. Here, we perform genome-wide association studies (N discovery = 24,336; N replication = 3412) and annotation on RSN-SC and RSN-FC. We identify genes for visual network-SC that are involved in axon guidance and synaptic functioning. Genetic variation in RSN-FC impacts biological processes relevant to brain disorders that previously were only phenotypically associated with RSN-FC alterations. Correlations of the genetic components of RSNs are mostly observed within the functional domain, whereas less overlap is observed within the structural domain and between the functional and structural domains. This study advances the understanding of the complex functional organization of the brain and its structural underpinnings from a genetics viewpoint.
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Affiliation(s)
- Elleke Tissink
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Josefin Werme
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Siemon C de Lange
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam 1105 BA, The Netherlands
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Yongbin Wei
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Christiaan A de Leeuw
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Mats Nagel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
- Department of Clinical Genetics, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam University Medical Centre, Amsterdam 1081 HZ, The Netherlands
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
- Department of Clinical Genetics, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam University Medical Centre, Amsterdam 1081 HZ, The Netherlands
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