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Herzberg MP, Nielsen AN, Luby J, Sylvester CM. Measuring neuroplasticity in human development: the potential to inform the type and timing of mental health interventions. Neuropsychopharmacology 2024; 50:124-136. [PMID: 39103496 PMCID: PMC11525577 DOI: 10.1038/s41386-024-01947-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/17/2024] [Accepted: 07/15/2024] [Indexed: 08/07/2024]
Abstract
Neuroplasticity during sensitive periods, the molecular and cellular process of enduring neural change in response to external stimuli during windows of high environmental sensitivity, is crucial for adaptation to expected environments and has implications for psychiatry. Animal research has characterized the developmental sequence and neurobiological mechanisms that govern neuroplasticity, yet gaps in our ability to measure neuroplasticity in humans limit the clinical translation of these principles. Here, we present a roadmap for the development and validation of neuroimaging and electrophysiology measures that index neuroplasticity to begin to address these gaps. We argue that validation of measures to track neuroplasticity in humans will elucidate the etiology of mental illness and inform the type and timing of mental health interventions to optimize effectiveness. We outline criteria for evaluating putative neuroimaging measures of plasticity in humans including links to neurobiological mechanisms shown to govern plasticity in animal models, developmental change that reflects heightened early life plasticity, and prediction of neural and/or behavior change. These criteria are applied to three putative measures of neuroplasticity using electroencephalography (gamma oscillations, aperiodic exponent of power/frequency) or functional magnetic resonance imaging (amplitude of low frequency fluctuations). We discuss the use of these markers in psychiatry, envision future uses for clinical and developmental translation, and suggest steps to address the limitations of the current putative neuroimaging measures of plasticity. With additional work, we expect these markers will significantly impact mental health and be used to characterize mechanisms, devise new interventions, and optimize developmental trajectories to reduce psychopathology risk.
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Affiliation(s)
- Max P Herzberg
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA.
| | - Ashley N Nielsen
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA.
| | - Joan Luby
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Taylor Family Institute for Innovative Psychiatric Research, Washington University in St. Louis, St. Louis, MO, USA
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2
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Furtado EJ, Camacho MC, Chin JH, Barch DM. Complex emotion processing and early life adversity in the Healthy Brain Network sample. Dev Cogn Neurosci 2024; 70:101469. [PMID: 39488929 DOI: 10.1016/j.dcn.2024.101469] [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: 07/18/2024] [Revised: 09/29/2024] [Accepted: 10/22/2024] [Indexed: 11/05/2024] Open
Abstract
OBJECTIVE Early life adversity (ELA) has shown to have negative impacts on mental health. One possible mechanism is through alterations in neural emotion processing. We sought to characterize how multiple indices of ELA were related to naturalistic neural socio-emotional processing. METHOD In 521 5-15-year-old participants from the Healthy Brain Network Biobank, we identified scenes that elicited activation of the Default Mode Network (DMN), Ventral Attention Network (VAN), Cingulo-Opercular Network (CON) and amygdala, all of which are networks shown to be associated with ELA. We used linear regression to examine associations between activation and ELA: negative parenting, social status, financial insecurity, neighborhood disadvantage, negative experiences, and parent psychopathology. RESULTS We found DMN, VAN, CON and amygdala activation during sad/emotional, bonding, action, conflict, sad, or fearful scenes. Greater inconsistent discipline was associated with greater VAN activation during sad or emotional scenes. CONCLUSION Findings suggest that the DMN, VAN, CON networks and the amygdala support socio-emotional processing consistent with prior literature. Individuals who experienced inconsistent discipline may have greater sensitivity to parent-child separation signals. Since no other ELA-activation associations were found, it is possible that unpredictability may be more strongly associated with complex neural emotion processing than socio-economic status or negative life events.
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Affiliation(s)
- Emily J Furtado
- the Institute of Child Development at University of Minnesota Twin Cities, Minneapolis, MN 55455, USA
| | - M Catalina Camacho
- Department of Psychiatry at Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Jenna H Chin
- Department of Psychology, University of Denver, Denver, CO 80208, USA
| | - Deanna M Barch
- Department of Psychological and Brain Sciences at Washington University in St. Louis, St. Louis, MO 63110, USA
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3
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Luckett PH, Olufawo MO, Park KY, Lamichhane B, Dierker D, Verastegui GT, Lee JJ, Yang P, Kim A, Butt OH, Chheda MG, Snyder AZ, Shimony JS, Leuthardt EC. Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning. J Neurooncol 2024; 169:175-185. [PMID: 38789843 PMCID: PMC11269343 DOI: 10.1007/s11060-024-04715-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024]
Abstract
PURPOSE High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care. METHODS Adult HGG patients (N = 102) from the neurosurgery brain tumor service at Washington University Medical Center were retrospectively recruited. All patients completed structural neuroimaging and resting state functional MRI prior to surgery. Demographics, measures of resting state network connectivity (FC), tumor location, and tumor volume were used to train a random forest classifier to predict functional outcomes based on Karnofsky Performance Status (KPS < 70, KPS ≥ 70). RESULTS The models achieved a nested cross-validation accuracy of 94.1% and an AUC of 0.97 in classifying KPS. The strongest predictors identified by the model included FC between somatomotor, visual, auditory, and reward networks. Based on location, the relation of the tumor to dorsal attention, cingulo-opercular, and basal ganglia networks were strong predictors of KPS. Age was also a strong predictor. However, tumor volume was only a moderate predictor. CONCLUSION The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumor's location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients.
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Affiliation(s)
- Patrick H Luckett
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA.
| | - Michael O Olufawo
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Ki Yun Park
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Bidhan Lamichhane
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
- Center for Health Sciences, Oklahoma State University, Tulsa, OK, USA
| | - Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - John J Lee
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Peter Yang
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Albert Kim
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Omar H Butt
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Milan G Chheda
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Abraham Z Snyder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric C Leuthardt
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biomedical Engineering, Washington University in Saint Louis, St. Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
- Department of Mechanical Engineering and Materials Science, Washington University in Saint Louis, St. Louis, MO, USA
- Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, MO, USA
- Brain Laser Center, Washington University School of Medicine, St. Louis, MO, USA
- National Center for Adaptive Neurotechnologies, Albany, NY, USA
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4
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Greenfield MS, Wang Y, Hamilton JP, Thunberg P, Msghina M. Emotional dysregulation and stimulant medication in adult ADHD. J Psychiatry Neurosci 2024; 49:E242-E251. [PMID: 39122408 PMCID: PMC11318975 DOI: 10.1503/jpn.240009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 05/21/2024] [Accepted: 05/25/2024] [Indexed: 08/12/2024] Open
Abstract
BACKGROUND Emotional dysregulation affects up to two-thirds of adult patients with attention-deficit/hyperactivity disorder (ADHD) and is increasingly seen as a core ADHD symptom that is clinically associated with greater functional impairment and psychiatric comorbidity. We sought to investigate emotional dysregulation in ADHD and explored its neural underpinnings. METHODS We studied emotion induction and regulation in a clinical cohort of adult patients with ADHD before and after a stimulant challenge. We compared patients with age- and gender-matched healthy controls using behavioural, structural, and functional measures. We hypothesized that patients would demonstrate aberrant emotion processing compared with healthy controls, and sought to find whether this could be normalized by stimulant medication. RESULTS Behaviourally, the ADHD group showed reduced emotion induction and regulation capacity. Brain imaging revealed abberant activation and deactivation patterns during emotion regulation, lower grey-matter volume in limbic and paralimbic areas, and greater grey-matter volume in visual and cerebellar areas, compared with healthy controls. The behavioural and functional deficits seen in emotion induction and regulation in the ADHD group were not normalized by stimulant medication. CONCLUSION Patients with ADHD may have impaired emotion induction and emotion regulation capacity, but these deficits are not reversed by stimulant medication. These results have important clinical implications when assessing which aspects of emotional dysregulation are relevant for patients and if and how traditional ADHD pharmacotherapy affects emotion induction and emotion regulation.
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Affiliation(s)
- Myrto Sklivanioti Greenfield
- From the Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden (Sklivanioti Greenfield, Msghina); the Department of Clinical Science, Intervention, and Technology, Karolinska Institute, Stockholm, Sweden (Wang); Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden (Wang); the Department of Biological and Medical Psychology, University of Bergen, Norway (Hamilton); the Department for Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); the Center for Experimental and Biomedical Imaging in Örebro, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); and the Department of Psychiatry, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Msghina)
| | - Yanlu Wang
- From the Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden (Sklivanioti Greenfield, Msghina); the Department of Clinical Science, Intervention, and Technology, Karolinska Institute, Stockholm, Sweden (Wang); Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden (Wang); the Department of Biological and Medical Psychology, University of Bergen, Norway (Hamilton); the Department for Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); the Center for Experimental and Biomedical Imaging in Örebro, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); and the Department of Psychiatry, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Msghina)
| | - J Paul Hamilton
- From the Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden (Sklivanioti Greenfield, Msghina); the Department of Clinical Science, Intervention, and Technology, Karolinska Institute, Stockholm, Sweden (Wang); Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden (Wang); the Department of Biological and Medical Psychology, University of Bergen, Norway (Hamilton); the Department for Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); the Center for Experimental and Biomedical Imaging in Örebro, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); and the Department of Psychiatry, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Msghina)
| | - Per Thunberg
- From the Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden (Sklivanioti Greenfield, Msghina); the Department of Clinical Science, Intervention, and Technology, Karolinska Institute, Stockholm, Sweden (Wang); Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden (Wang); the Department of Biological and Medical Psychology, University of Bergen, Norway (Hamilton); the Department for Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); the Center for Experimental and Biomedical Imaging in Örebro, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); and the Department of Psychiatry, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Msghina)
| | - Mussie Msghina
- From the Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden (Sklivanioti Greenfield, Msghina); the Department of Clinical Science, Intervention, and Technology, Karolinska Institute, Stockholm, Sweden (Wang); Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden (Wang); the Department of Biological and Medical Psychology, University of Bergen, Norway (Hamilton); the Department for Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); the Center for Experimental and Biomedical Imaging in Örebro, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Thunberg); and the Department of Psychiatry, Faculty of Medicine and Health, Örebro University, Örebro, Sweden (Msghina)
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5
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Rong D, Hu CP, Yang J, Guo Z, Liu W, Yu M. Consistent abnormal activity in the putamen by dopamine modulation in Parkinson's disease: A resting-state neuroimaging meta-analysis. Brain Res Bull 2024; 210:110933. [PMID: 38508469 DOI: 10.1016/j.brainresbull.2024.110933] [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: 11/09/2023] [Revised: 02/16/2024] [Accepted: 03/17/2024] [Indexed: 03/22/2024]
Abstract
OBJECTIVE This study aimed to elucidate brain areas mediated by oral anti-parkinsonian medicine that consistently show abnormal resting-state activation in PD and to reveal their functional connectivity profiles using meta-analytic approaches. METHODS Searches of the PubMed, Web of Science databases identified 78 neuroimaging studies including PD OFF state (PD-OFF) versus (vs.) PD ON state (PD-ON) or PD-ON versus healthy controls (HCs) or PD-OFF versus HCs data. Coordinate-based meta-analysis and functional meta-analytic connectivity modeling (MACM) were performed using the activation likelihood estimation algorithm. RESULTS Brain activation in PD-OFF vs. PD-ON was significantly changed in the right putamen and left inferior parietal lobule (IPL). Contrast analysis indicated that PD-OFF vs. HCs had more consistent activation in the right paracentral lobule, right middle frontal gyrus, right thalamus, left superior parietal lobule and right putamen, whereas PD-ON vs. HCs elicited more consistent activation in the bilateral middle temporal gyrus, left occipital gyrus, right inferior frontal gyrus and right caudate. MACM revealed coactivation of the right putamen in the direct contrast of PD-OFF vs. PD-ON. Subtraction analysis of significant coactivation clusters for PD-OFF vs. PD-ON with the medium of HCs showed effects in the sensorimotor, top-down control, and visual networks. By overlapping the MACM maps of the two analytical strategies, we demonstrated that the coactivated brain region focused on the right putamen. CONCLUSIONS The convergence of local brain regions and co-activation neural networks are involved the putamen, suggesting its potential as a specific imaging biomarker to monitor treatment efficacy. SYSTEMATIC REVIEW REGISTRATION [https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD CRD42022304150].
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Affiliation(s)
- Danyan Rong
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, Jiangsu 210029, China
| | - Chuan-Peng Hu
- School of Psychology, Nanjing Normal University, No.122, Ninghai Road, Gulou District, Nanjing, Jiangsu 210024, China
| | - Jiaying Yang
- Department of Public Health, School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, No.138, Xianlin Road, Nanjing, Jiangsu 210023, China
| | - Zhiying Guo
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, Jiangsu 210029, China
| | - Weiguo Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, Jiangsu 210029, China.
| | - Miao Yu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, Jiangsu 210029, China.
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6
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Chauvin RJ, Newbold DJ, Nielsen AN, Miller RL, Krimmel SR, Metoki A, Wang A, Van AN, Montez DF, Marek S, Suljic V, Baden NJ, Ramirez-Perez N, Scheidter KM, Monk JS, Whiting FI, Adeyemo B, Snyder AZ, Kay BP, Raichle ME, Laumann TO, Gordon EM, Dosenbach NU. Disuse-driven plasticity in the human thalamus and putamen. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.07.566031. [PMID: 37987000 PMCID: PMC10659348 DOI: 10.1101/2023.11.07.566031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Motor adaptation in cortico-striato-thalamo-cortical loops has been studied mainly in animals using invasive electrophysiology. Here, we leverage functional neuroimaging in humans to study motor circuit plasticity in the human subcortex. We employed an experimental paradigm that combined two weeks of upper-extremity immobilization with daily resting-state and motor task fMRI before, during, and after the casting period. We previously showed that limb disuse leads to decreased functional connectivity (FC) of the contralateral somatomotor cortex (SM1) with the ipsilateral somatomotor cortex, increased FC with the cingulo-opercular network (CON) as well as the emergence of high amplitude, fMRI signal pulses localized in the contralateral SM1, supplementary motor area and the cerebellum. From our prior observations, it remains unclear whether the disuse plasticity affects the thalamus and striatum. We extended our analysis to include these subcortical regions and found that both exhibit strengthened cortical FC and spontaneous fMRI signal pulses induced by limb disuse. The dorsal posterior putamen and the central thalamus, mainly CM, VLP and VIM nuclei, showed disuse pulses and FC changes that lined up with fmri task activations from the Human connectome project motor system localizer, acquired before casting for each participant. Our findings provide a novel understanding of the role of the cortico-striato-thalamo-cortical loops in human motor plasticity and a potential link with the physiology of sleep regulation. Additionally, similarities with FC observation from Parkinson Disease (PD) questions a pathophysiological link with limb disuse.
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Affiliation(s)
- Roselyne J. Chauvin
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Dillan J. Newbold
- Department of Neurology, New York University Grossman School of Medicine, New York, New York 10016, USA
| | - Ashley N. Nielsen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Ryland L. Miller
- Basque Center on Cognition, Brain and Language, Donostia, Gipuzkoa, Spain
| | - Samuel R. Krimmel
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Anxu Wang
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, MO 63130
| | - Andrew N. Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Division of Computation and Data Science, Washington University School of Medicine, St. Louis, MO 63110
| | - David F. Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Vahdeta Suljic
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Noah J. Baden
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | | | - Kristen M. Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Julia S. Monk
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Forrest I. Whiting
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Abraham Z. Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Benjamin P. Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Marcus E. Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy O. Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Evan M. Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nico U.F. Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, MO 63130
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
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7
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Krimmel SR, Laumann TO, Chauvin RJ, Hershey T, Roland JL, Shimony JS, Willie JT, Norris SA, Marek S, Van AN, Monk J, Scheidter KM, Whiting F, Ramirez-Perez N, Metoki A, Wang A, Kay BP, Nahman-Averbuch H, Fair DA, Lynch CJ, Raichle ME, Gordon EM, Dosenbach NUF. The brainstem's red nucleus was evolutionarily upgraded to support goal-directed action. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.30.573730. [PMID: 38260662 PMCID: PMC10802246 DOI: 10.1101/2023.12.30.573730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The red nucleus is a large brainstem structure that coordinates limb movement for locomotion in quadrupedal animals (Basile et al., 2021). The humans red nucleus has a different pattern of anatomical connectivity compared to quadrupeds, suggesting a unique purpose (Hatschek, 1907). Previously the function of the human red nucleus remained unclear at least partly due to methodological limitations with brainstem functional neuroimaging (Sclocco et al., 2018). Here, we used our most advanced resting-state functional connectivity (RSFC) based precision functional mapping (PFM) in highly sampled individuals (n = 5) and large group-averaged datasets (combined N ~ 45,000), to precisely examine red nucleus functional connectivity. Notably, red nucleus functional connectivity to motor-effector networks (somatomotor hand, foot, and mouth) was minimal. Instead, red nucleus functional connectivity along the central sulcus was specific to regions of the recently discovered somato-cognitive action network (SCAN; (Gordon et al., 2023)). Outside of primary motor cortex, red nucleus connectivity was strongest to the cingulo-opercular (CON) and salience networks, involved in action/cognitive control (Dosenbach et al., 2007; Newbold et al., 2021) and reward/motivated behavior (Seeley, 2019), respectively. Functional connectivity to these two networks was organized into discrete dorsal-medial and ventral-lateral zones. Red nucleus functional connectivity to the thalamus recapitulated known structural connectivity of the dento-rubral thalamic tract (DRTT) and could prove clinically useful in functionally targeting the ventral intermediate (VIM) nucleus. In total, our results indicate that far from being a 'motor' structure, the red nucleus is better understood as a brainstem nucleus for implementing goal-directed behavior, integrating behavioral valence and action plans.
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Affiliation(s)
- Samuel R Krimmel
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tamara Hershey
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
| | - Jarod L Roland
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jon T Willie
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, New York, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri
| | - Scott A Norris
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
| | - Julia Monk
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Kristen M Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Forrest Whiting
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Nadeshka Ramirez-Perez
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Anxu Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Division of Computation and Data Science, Washington University, St. Louis, Missouri, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Hadas Nahman-Averbuch
- Washington University Pain Center, Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota, USA
- Institute of Child Development, University of Minnesota, Minneapolis, Minnesota, USA
| | - Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, New York, USA
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
- Program in Occupational Therapy, Washington University, St. Louis, Missouri, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri, USA
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8
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Fricchione G. Brain evolution and the meaning of catatonia - An update. Schizophr Res 2024; 263:139-150. [PMID: 36754715 DOI: 10.1016/j.schres.2023.01.026] [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: 10/31/2022] [Revised: 01/16/2023] [Accepted: 01/18/2023] [Indexed: 02/10/2023]
Abstract
Back in 2004, in a chapter titled "Brain Evolution and the Meaning of Catatonia", a case was made that the syndrome's core meaning is embedded in millions of years of vertebrate brain evolution. (Fricchione, 2004) In this update, advances over the last almost 20 years, in catatonia theory and research in particular, and pertinent neuropsychiatry in general, will be applied to this question of meaning. The approach will rely heavily on a number of thought leaders, including Nicos Tinbergen, Paul MacLean, John Bowlby, M. Marsel Mesulam, Bruce McEwen and Karl Friston. Their guidance will be supplemented with a selected survey of 21sty century neuropsychiatry, neurophysiology, molecular biology, neuroimaging and neurotherapeutics as applied to the catatonic syndrome. In an attempt to address the question of the meaning of the catatonic syndrome in human life, we will employ two conceptual networks representing the intersubjectivity of the quantitative conceptual network of physical terms and the subjectivity of the qualitative conceptual network of mental and spiritual terms. In the process, a common referent providing extensional identity may emerge (Goodman, 1991). The goal of this exercise is to enhance our attunement with the experience of patients suffering with catatonia. A deeper understanding of catatonia's origins in brain evolution and of the challenges of individual epigenetic development in the setting of environmental events coupled with appreciation of what has been described as the most painful mammalian condition, that of separation, has the potential to foster greater efforts on the part of clinicians to diagnose and treat patients who present with catatonia. In addition, in this ancient and extreme tactic, evolved to provide safety from extreme survival threat, one can speculate what is at the core of human fear and the challenge it presents to all of us. And when the biology, psychology and sociology of catatonia are examined, the nature of solutions to the challenge may emerge.
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Affiliation(s)
- Gregory Fricchione
- Benson-Henry Institute for Mind Body Medicine Division of Psychiatry and Medicine Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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9
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Gao Y, Wu X, Yan Y, Li M, Qin F, Ma M, Yuan X, Yang W, Qiu J. The unity and diversity of verbal and visuospatial creativity: Dynamic changes in hemispheric lateralisation. Hum Brain Mapp 2023; 44:6031-6042. [PMID: 37772359 PMCID: PMC10619400 DOI: 10.1002/hbm.26494] [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: 03/09/2023] [Revised: 09/02/2023] [Accepted: 09/14/2023] [Indexed: 09/30/2023] Open
Abstract
The investigation of similarities and differences in the mechanisms of verbal and visuospatial creative thinking has long been a controversial topic. Prior studies found that visuospatial creativity was primarily supported by the right hemisphere, whereas verbal creativity relied on the interaction between both hemispheres. However, creative thinking also involves abundant dynamic features that may have been ignored in the previous static view. Recently, a new method has been developed that measures hemispheric laterality from a dynamic perspective, providing new insight into the exploration of creative thinking. In the present study, dynamic lateralisation index was calculated with resting-state fMRI data. We combined the dynamic lateralisation index with sparse canonical correlation analysis to examine similarities and differences in the mechanisms of verbal and visuospatial creativity. Our results showed that the laterality reversal of the default mode network, fronto-parietal network, cingulo-opercular network and visual network contributed significantly to both verbal and visuospatial creativity and consequently could be considered the common neural mechanisms shared by these creative modes. In addition, we found that verbal creativity relied more on the language network, while visuospatial creativity relied more on the somatomotor network, which can be considered a difference in their mechanism. Collectively, these findings indicated that verbal and visuospatial creativity may have similar mechanisms to support the basic creative thinking process and different mechanisms to adapt to the specific task conditions. These findings may have significant implications for our understanding of the neural mechanisms of different types of creative thinking.
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Affiliation(s)
- Yixin Gao
- Key Laboratory of Cognition and Personality (SWU)Ministry of EducationChongqingChina
- Faculty of PsychologySouthwest University (SWU)ChongqingChina
| | - Xinran Wu
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
| | - Yuchi Yan
- Key Laboratory of Cognition and Personality (SWU)Ministry of EducationChongqingChina
- Faculty of PsychologySouthwest University (SWU)ChongqingChina
| | - Min Li
- Key Laboratory of Cognition and Personality (SWU)Ministry of EducationChongqingChina
- Faculty of PsychologySouthwest University (SWU)ChongqingChina
| | - Facai Qin
- Key Laboratory of Cognition and Personality (SWU)Ministry of EducationChongqingChina
- Faculty of PsychologySouthwest University (SWU)ChongqingChina
| | - Mujie Ma
- Key Laboratory of Cognition and Personality (SWU)Ministry of EducationChongqingChina
- Faculty of PsychologySouthwest University (SWU)ChongqingChina
| | - Xiaoning Yuan
- Key Laboratory of Cognition and Personality (SWU)Ministry of EducationChongqingChina
- Faculty of PsychologySouthwest University (SWU)ChongqingChina
| | - Wenjing Yang
- Key Laboratory of Cognition and Personality (SWU)Ministry of EducationChongqingChina
- Faculty of PsychologySouthwest University (SWU)ChongqingChina
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU)Ministry of EducationChongqingChina
- Faculty of PsychologySouthwest University (SWU)ChongqingChina
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10
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D'Andrea CB, Laumann TO, Newbold DJ, Nelson SM, Nielsen AN, Chauvin R, Marek S, Greene DJ, Dosenbach NUF, Gordon EM. Substructure of the brain's Cingulo-Opercular network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.10.561772. [PMID: 37873065 PMCID: PMC10592749 DOI: 10.1101/2023.10.10.561772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.
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Affiliation(s)
- Carolina Badke D'Andrea
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Cognitive Science, University of California San Diego, La Jolla, California 92093, USA
- Medical Scientist Training Program, Washington University School of Medicine, St. Louis, MO 63310, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Dillan J Newbold
- Department of Neurology, New York University Medical Center, New York, New York 10016, USA
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota 55455, USA
| | - Ashley N Nielsen
- Department of Neurology, New York University Medical Center, New York, New York 10016, USA
| | - Roselyne Chauvin
- Department of Neurology, New York University Medical Center, New York, New York 10016, USA
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, California 92093, USA
| | - Nico U F Dosenbach
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
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11
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Badke D’Andrea C, Marek S, Van AN, Miller RL, Earl EA, Stewart SB, Dosenbach NUF, Schlaggar BL, Laumann TO, Fair DA, Gordon EM, Greene DJ. Thalamo-cortical and cerebello-cortical functional connectivity in development. Cereb Cortex 2023; 33:9250-9262. [PMID: 37293735 PMCID: PMC10492576 DOI: 10.1093/cercor/bhad198] [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] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 05/09/2023] [Accepted: 05/17/2023] [Indexed: 06/10/2023] Open
Abstract
The thalamus is a critical relay center for neural pathways involving sensory, motor, and cognitive functions, including cortico-striato-thalamo-cortical and cortico-ponto-cerebello-thalamo-cortical loops. Despite the importance of these circuits, their development has been understudied. One way to investigate these pathways in human development in vivo is with functional connectivity MRI, yet few studies have examined thalamo-cortical and cerebello-cortical functional connectivity in development. Here, we used resting-state functional connectivity to measure functional connectivity in the thalamus and cerebellum with previously defined cortical functional networks in 2 separate data sets of children (7-12 years old) and adults (19-40 years old). In both data sets, we found stronger functional connectivity between the ventral thalamus and the somatomotor face cortical functional network in children compared with adults, extending previous cortico-striatal functional connectivity findings. In addition, there was more cortical network integration (i.e. strongest functional connectivity with multiple networks) in the thalamus in children than in adults. We found no developmental differences in cerebello-cortical functional connectivity. Together, these results suggest different maturation patterns in cortico-striato-thalamo-cortical and cortico-ponto-cerebellar-thalamo-cortical pathways.
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Affiliation(s)
- Carolina Badke D’Andrea
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, United States
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Ryland L Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Eric A Earl
- Data Science and Sharing Team, National Institute of Mental Health, NIH, DHHS, Bethesda, MD 20899, United States
| | - Stephanie B Stewart
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, CO 80045, United States
| | - Nico U F Dosenbach
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States
| | | | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Damien A Fair
- Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN 55455, United States
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55455, United States
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, United States
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12
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Demeter DV, Gordon EM, Nugiel T, Garza A, Larguinho TL, Church JA. Resting-state cortical hubs in youth organize into four categories. Cell Rep 2023; 42:112521. [PMID: 37200192 PMCID: PMC10281712 DOI: 10.1016/j.celrep.2023.112521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 02/13/2023] [Accepted: 05/02/2023] [Indexed: 05/20/2023] Open
Abstract
During childhood, neural systems supporting high-level cognitive processes undergo periods of rapid growth and refinement, which rely on the successful coordination of activation across the brain. Some coordination occurs via cortical hubs-brain regions that coactivate with functional networks other than their own. Adult cortical hubs map into three distinct profiles, but less is known about hub categories during development, when critical improvement in cognition occurs. We identify four distinct hub categories in a large youth sample (n = 567, ages 8.5-17.2), each exhibiting more diverse connectivity profiles than adults. Youth hubs integrating control-sensory processing split into two distinct categories (visual control and auditory/motor control), whereas adult hubs unite under one. This split suggests a need for segregating sensory stimuli while functional networks are experiencing rapid development. Functional coactivation strength for youth control-processing hubs are associated with task performance, suggesting a specialized role in routing sensory information to and from the brain's control system.
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Affiliation(s)
- Damion V Demeter
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, USA.
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Tehila Nugiel
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - AnnaCarolina Garza
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712, USA
| | - Tyler L Larguinho
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712, USA
| | - Jessica A Church
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712, USA
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13
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Hua M, Shi D, Xu W, Zhu L, Hao X, Zhu B, Shu Q, Lozoff B, Geng F, Shao J. Differentiation between fetal and postnatal iron deficiency in altering brain substrates of cognitive control in pre-adolescence. BMC Med 2023; 21:167. [PMID: 37143078 PMCID: PMC10161450 DOI: 10.1186/s12916-023-02850-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 03/27/2023] [Indexed: 05/06/2023] Open
Abstract
BACKGROUND Early iron deficiency (ID) is a common risk factor for poorer neurodevelopment, limiting children's potential and contributing to global burden. However, it is unclear how early ID alters the substrate of brain functions supporting high-order cognitive abilities and whether the timing of early ID matters in terms of long-term brain development. This study aimed to examine the effects of ID during fetal or early postnatal periods on brain activities supporting proactive and reactive cognitive control in pre-adolescent children. METHODS Participants were part of a longitudinal cohort enrolled at birth in southeastern China between December 2008 and November 2011. Between July 2019 and October 2021, 115 children aged 8-11 years were invited to participate in this neuroimaging study. Final analyses included 71 children: 20 with fetal ID, 24 with ID at 9 months (postnatal ID), and 27 iron-sufficient at birth and 9 months. Participants performed a computer-based behavioral task in a Magnetic Resonance Imaging scanner to measure proactive and reactive cognitive control. Outcome measures included accuracy, reaction times, and brain activity. Linear mixed modeling and the 3dlme command in Analysis of Functional NeuroImages (AFNI) were separately used to analyze behavioral performance and neuroimaging data. RESULTS Faster responses in proactive vs. reactive conditions indicated that all groups could use proactive or reactive cognitive control according to contextual demands. However, the fetal ID group was lower in general accuracy than the other 2 groups. Per the demands of cues and targets, the iron-sufficient group showed greater activation of wide brain regions in proactive vs. reactive conditions. In contrast, such condition differences were reversed in the postnatal ID group. Condition differences in brain activation, shown in postnatal ID and iron-sufficient groups, were not found in the fetal ID group. This group specifically showed greater activation of brain regions in the reward pathway in proactive vs. reactive conditions. CONCLUSIONS Early ID was associated with altered brain functions supporting proactive and reactive cognitive control in childhood. Alterations differed between fetal and postnatal ID groups. The findings imply that iron supplement alone is insufficient to prevent persisting brain alterations associated with early ID. Intervention strategies in addition to the iron supplement should consider ID timing.
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Affiliation(s)
- Mengdi Hua
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Donglin Shi
- Department of Curriculum and Learning Sciences, Zhejiang University, Hangzhou, China
| | - Wenwen Xu
- Department of Curriculum and Learning Sciences, Zhejiang University, Hangzhou, China
| | - Liuyan Zhu
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoxin Hao
- Department of Curriculum and Learning Sciences, Zhejiang University, Hangzhou, China
| | - Bingquan Zhu
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qiang Shu
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- National Clinical Research Center for Child Health, Hangzhou, China
| | - Betsy Lozoff
- Department of Pediatrics, University of Michigan, Ann Arbor, MI, USA
| | - Fengji Geng
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Department of Curriculum and Learning Sciences, Zhejiang University, Hangzhou, China.
- National Clinical Research Center for Child Health, Hangzhou, China.
| | - Jie Shao
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- National Clinical Research Center for Child Health, Hangzhou, China.
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14
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Gordon EM, Chauvin RJ, Van AN, Rajesh A, Nielsen A, Newbold DJ, Lynch CJ, Seider NA, Krimmel SR, Scheidter KM, Monk J, Miller RL, Metoki A, Montez DF, Zheng A, Elbau I, Madison T, Nishino T, Myers MJ, Kaplan S, Badke D'Andrea C, Demeter DV, Feigelis M, Ramirez JSB, Xu T, Barch DM, Smyser CD, Rogers CE, Zimmermann J, Botteron KN, Pruett JR, Willie JT, Brunner P, Shimony JS, Kay BP, Marek S, Norris SA, Gratton C, Sylvester CM, Power JD, Liston C, Greene DJ, Roland JL, Petersen SE, Raichle ME, Laumann TO, Fair DA, Dosenbach NUF. A somato-cognitive action network alternates with effector regions in motor cortex. Nature 2023; 617:351-359. [PMID: 37076628 PMCID: PMC10172144 DOI: 10.1038/s41586-023-05964-2] [Citation(s) in RCA: 139] [Impact Index Per Article: 139.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/16/2023] [Indexed: 04/21/2023]
Abstract
Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations1,2, despite evidence for concentric functional zones3 and maps of complex actions4. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action5 and physiological control6, arousal7, errors8 and pain9. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions4 and connectivity to internal organs10 such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.
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Affiliation(s)
- Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA.
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
| | - Aishwarya Rajesh
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Ashley Nielsen
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, New York University Langone Medical Center, New York, NY, USA
| | - Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Samuel R Krimmel
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Kristen M Scheidter
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Julia Monk
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Ryland L Miller
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Immanuel Elbau
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Thomas Madison
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Tomoyuki Nishino
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Michael J Myers
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Sydney Kaplan
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Carolina Badke D'Andrea
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Damion V Demeter
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Matthew Feigelis
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Julian S B Ramirez
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Deanna M Barch
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Christopher D Smyser
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Cynthia E Rogers
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Kelly N Botteron
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - John R Pruett
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Jon T Willie
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Peter Brunner
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Scott A Norris
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Caterina Gratton
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Jonathan D Power
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Jarod L Roland
- Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, USA
| | - Steven E Petersen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Marcus E Raichle
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, 55455, United States
| | - Nico U F Dosenbach
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA.
- Department of Biomedical Engineering, Washington University in St. Louis, St Louis, MO, USA.
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA.
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA.
- Program in Occupational Therapy, Washington University in St. Louis, St Louis, MO, USA.
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15
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Nielsen AN, Kaplan S, Meyer D, Alexopoulos D, Kenley JK, Smyser TA, Wakschlag LS, Norton ES, Raghuraman N, Warner BB, Shimony JS, Luby JL, Neil JJ, Petersen SE, Barch DM, Rogers CE, Sylvester CM, Smyser CD. Maturation of large-scale brain systems over the first month of life. Cereb Cortex 2023; 33:2788-2803. [PMID: 35750056 PMCID: PMC10016041 DOI: 10.1093/cercor/bhac242] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 04/29/2022] [Accepted: 05/23/2022] [Indexed: 01/14/2023] Open
Abstract
The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.
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Affiliation(s)
- Ashley N Nielsen
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Sydney Kaplan
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Dominique Meyer
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Jeanette K Kenley
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Tara A Smyser
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Lauren S Wakschlag
- Institute for Innovations and Developmental Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Medical Social Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Feinberg School of Medicine, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
| | - Elizabeth S Norton
- Institute for Innovations and Developmental Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Medical Social Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Communication Sciences and Disorders, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
| | - Nandini Raghuraman
- Department of Obstetrics and Gynecology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Barbara B Warner
- Department of Pediatrics, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joshua S Shimony
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joan L Luby
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Jeffery J Neil
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Cynthia E Rogers
- Department of Communication Sciences and Disorders, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Christopher D Smyser
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Pediatrics, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
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16
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Wang X, Zwosta K, Wolfensteller U, Ruge H. Changes in global functional network properties predict individual differences in habit formation. Hum Brain Mapp 2023; 44:1565-1578. [PMID: 36413054 PMCID: PMC9921330 DOI: 10.1002/hbm.26158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 11/08/2022] [Accepted: 11/11/2022] [Indexed: 11/23/2022] Open
Abstract
Prior evidence suggests that sensorimotor regions play a crucial role in habit formation. Yet, whether and how their global functional network properties might contribute to a more comprehensive characterization of habit formation still remains unclear. Capitalizing on advances in Elastic Net regression and predictive modeling, we examined whether learning-related functional connectivity alterations distributed across the whole brain could predict individual habit strength. Using the leave-one-subject-out cross-validation strategy, we found that the habit strength score of the novel unseen subjects could be successfully predicted. We further characterized the contribution of both, individual large-scale networks and individual brain regions by calculating their predictive weights. This highlighted the pivotal role of functional connectivity changes involving the sensorimotor network and the cingulo-opercular network in subject-specific habit strength prediction. These results contribute to the understanding the neural basis of human habit formation by demonstrating the importance of global functional network properties especially also for predicting the observable behavioral expression of habits.
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Affiliation(s)
- Xiaoyu Wang
- Fakultät Psychologie, Technische Universität Dresden, Dresden, Germany
| | - Katharina Zwosta
- Fakultät Psychologie, Technische Universität Dresden, Dresden, Germany
| | - Uta Wolfensteller
- Fakultät Psychologie, Technische Universität Dresden, Dresden, Germany
| | - Hannes Ruge
- Fakultät Psychologie, Technische Universität Dresden, Dresden, Germany
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17
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Perez DC, Dworetsky A, Braga RM, Beeman M, Gratton C. Hemispheric Asymmetries of Individual Differences in Functional Connectivity. J Cogn Neurosci 2023; 35:200-225. [PMID: 36378901 PMCID: PMC10029817 DOI: 10.1162/jocn_a_01945] [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] [Indexed: 11/16/2022]
Abstract
Resting-state fMRI studies have revealed that individuals exhibit stable, functionally meaningful divergences in large-scale network organization. The locations with strongest deviations (called network "variants") have a characteristic spatial distribution, with qualitative evidence from prior reports suggesting that this distribution differs across hemispheres. Hemispheric asymmetries can inform us on constraints guiding the development of these idiosyncratic regions. Here, we used data from the Human Connectome Project to systematically investigate hemispheric differences in network variants. Variants were significantly larger in the right hemisphere, particularly along the frontal operculum and medial frontal cortex. Variants in the left hemisphere appeared most commonly around the TPJ. We investigated how variant asymmetries vary by functional network and how they compare with typical network distributions. For some networks, variants seemingly increase group-average network asymmetries (e.g., the group-average language network is slightly bigger in the left hemisphere and variants also appeared more frequently in that hemisphere). For other networks, variants counter the group-average network asymmetries (e.g., the default mode network is slightly bigger in the left hemisphere, but variants were more frequent in the right hemisphere). Intriguingly, left- and right-handers differed in their network variant asymmetries for the cingulo-opercular and frontoparietal networks, suggesting that variant asymmetries are connected to lateralized traits. These findings demonstrate that idiosyncratic aspects of brain organization differ systematically across the hemispheres. We discuss how these asymmetries in brain organization may inform us on developmental constraints of network variants and how they may relate to functions differentially linked to the two hemispheres.
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Affiliation(s)
| | | | | | | | - Caterina Gratton
- Northwestern University, Evanston, IL
- Florida State University, Tallahassee
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18
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Mapping correlated neurological deficits after stroke to distributed brain networks. Brain Struct Funct 2022; 227:3173-3187. [PMID: 35881254 DOI: 10.1007/s00429-022-02525-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 06/12/2022] [Indexed: 11/02/2022]
Abstract
Understanding the relationships between brain organization and behavior is a central goal of neuroscience. Traditional teaching emphasizes that the human cerebrum includes many distinct areas for which damage or dysfunction would lead to a unique and specific behavioral syndrome. This teaching implies that brain areas correspond to encapsulated modules that are specialized for specific cognitive operations. However, empirically, local damage from stroke more often produces one of a small number of clusters of deficits and disrupts brain-wide connectivity in a small number of predictable ways (relative to the vast complexity of behavior and brain connectivity). Behaviors that involve shared operations show correlated deficits following a stroke, consistent with a low-dimensional behavioral space. Because of the networked organization of the brain, local damage from a stroke can result in widespread functional abnormalities, matching the low dimensionality of behavioral deficit. In alignment with this, neurological disease, psychiatric disease, and altered brain states produce behavioral changes that are highly correlated across a range of behaviors. We discuss how known structural and functional network priors in addition to graph theoretical concepts such as modularity and entropy have provided inroads to understanding this more complex relationship between brain and behavior. This model for brain disease has important implications for normal brain-behavior relationships and the treatment of neurological and psychiatric diseases.
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19
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Rawls E, Kummerfeld E, Mueller BA, Ma S, Zilverstand A. The resting-state causal human connectome is characterized by hub connectivity of executive and attentional networks. Neuroimage 2022; 255:119211. [PMID: 35430360 PMCID: PMC9177236 DOI: 10.1016/j.neuroimage.2022.119211] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 04/08/2022] [Accepted: 04/12/2022] [Indexed: 01/17/2023] Open
Abstract
We demonstrate a data-driven approach for calculating a "causal connectome" of directed connectivity from resting-state fMRI data using a greedy adjacency search and pairwise non-Gaussian edge orientations. We used this approach to construct n = 442 causal connectomes. These connectomes were very sparse in comparison to typical Pearson correlation-based graphs (roughly 2.25% edge density) yet were fully connected in nearly all cases. Prominent highly connected hubs of the causal connectome were situated in attentional (dorsal attention) and executive (frontoparietal and cingulo-opercular) networks. These hub networks had distinctly different connectivity profiles: attentional networks shared incoming connections with sensory regions and outgoing connections with higher cognitive networks, while executive networks primarily connected to other higher cognitive networks and had a high degree of bidirected connectivity. Virtual lesion analyses accentuated these findings, demonstrating that attentional and executive hub networks are points of critical vulnerability in the human causal connectome. These data highlight the central role of attention and executive control networks in the human cortical connectome and set the stage for future applications of data-driven causal connectivity analysis in psychiatry.
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Affiliation(s)
- Eric Rawls
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, USA.
| | | | - Bryon A Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, USA
| | - Sisi Ma
- Institute for Health Informatics, University of Minnesota, USA
| | - Anna Zilverstand
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, USA; Medical Discovery Team on Addiction, University of Minnesota, USA
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20
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Seider NA, Adeyemo B, Miller R, Newbold DJ, Hampton JM, Scheidter KM, Rutlin J, Laumann TO, Roland JL, Montez DF, Van AN, Zheng A, Marek S, Kay BP, Bretthorst GL, Schlaggar BL, Greene DJ, Wang Y, Petersen SE, Barch DM, Gordon EM, Snyder AZ, Shimony JS, Dosenbach NUF. Accuracy and reliability of diffusion imaging models. Neuroimage 2022; 254:119138. [PMID: 35339687 PMCID: PMC9841915 DOI: 10.1016/j.neuroimage.2022.119138] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 03/01/2022] [Accepted: 03/22/2022] [Indexed: 01/19/2023] Open
Abstract
Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.
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Affiliation(s)
- Nicole A Seider
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Ryland Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neurology, New York University Langone Medical Center, New York, NY 10016, United States of America
| | - Jacqueline M Hampton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Kristen M Scheidter
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Jerrel Rutlin
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Jarod L Roland
- Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO 63110 United States of America
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO 63110, United States of America
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - G Larry Bretthorst
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Chemistry, Washington University in St Louis, St. Louis, MO 63110, United States of America
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD 21205, United States of America; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States of America; Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States of America
| | - Deanna J Greene
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, United States of America
| | - Yong Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO 63110, United States of America
| | - Steven E Petersen
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO 63110, United States of America; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychological and Brain Sciences, Washington University in St. Louis, MO 63110, United States of America
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Psychological and Brain Sciences, Washington University in St. Louis, MO 63110, United States of America
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Abraham Z Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States of America
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO 63110, United States of America; Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States of America; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States of America
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21
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Kawagoe T. Overview of (f)MRI Studies of Cognitive Aging for Non-Experts: Looking through the Lens of Neuroimaging. Life (Basel) 2022; 12:416. [PMID: 35330167 PMCID: PMC8953678 DOI: 10.3390/life12030416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/21/2022] [Accepted: 03/11/2022] [Indexed: 11/20/2022] Open
Abstract
This special issue concerning Brain Functional and Structural Connectivity and Cognition aims to expand our understanding of brain connectivity. Herein, I review related topics including the principle and concepts of functional MRI, brain activation, and functional/structural connectivity in aging for uninitiated readers. Visuospatial attention, one of the well-studied functions in aging, is discussed from the perspective of neuroimaging.
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Affiliation(s)
- Toshikazu Kawagoe
- Liberal Arts Education Centre, Kyushu Campus, Tokai University, Toroku 9-1-1, Kumamoto-City 862-8652, Kumamoto, Japan
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22
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Zheng A, Montez DF, Marek S, Gilmore AW, Newbold DJ, Laumann TO, Kay BP, Seider NA, Van AN, Hampton JM, Alexopoulos D, Schlaggar BL, Sylvester CM, Greene DJ, Shimony JS, Nelson SM, Wig GS, Gratton C, McDermott KB, Raichle ME, Gordon EM, Dosenbach NUF. Parallel hippocampal-parietal circuits for self- and goal-oriented processing. Proc Natl Acad Sci U S A 2021; 118:e2101743118. [PMID: 34404728 PMCID: PMC8403906 DOI: 10.1073/pnas.2101743118] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing.
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Affiliation(s)
- Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110;
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Adrian W Gilmore
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Jacqueline M Hampton
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD 21205
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | - Chad M Sylvester
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Deanna J Greene
- Department of Cognitive Science, University of California, San Diego, CA 92093
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414
| | - Gagan S Wig
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL 60208
- Department of Neurology, Northwestern University, Evanston, IL 60208
| | - Kathleen B McDermott
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110;
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110
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23
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