1
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Ottoy J, Kang MS, Tan JXM, Boone L, Vos de Wael R, Park BY, Bezgin G, Lussier FZ, Pascoal TA, Rahmouni N, Stevenson J, Fernandez Arias J, Therriault J, Hong SJ, Stefanovic B, McLaurin J, Soucy JP, Gauthier S, Bernhardt BC, Black SE, Rosa-Neto P, Goubran M. Tau follows principal axes of functional and structural brain organization in Alzheimer's disease. Nat Commun 2024; 15:5031. [PMID: 38866759 PMCID: PMC11169286 DOI: 10.1038/s41467-024-49300-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 05/24/2024] [Indexed: 06/14/2024] Open
Abstract
Alzheimer's disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns ("gradient contraction") are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.
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Affiliation(s)
- Julie Ottoy
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Min Su Kang
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | - Lyndon Boone
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Bo-Yong Park
- Department of Data Science, Inha University, Incheon, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Gleb Bezgin
- Translational Neuroimaging laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
- Neuroinformatics for Personalized Medicine lab, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Firoza Z Lussier
- Translational Neuroimaging laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nesrine Rahmouni
- Translational Neuroimaging laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Jenna Stevenson
- Translational Neuroimaging laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Jaime Fernandez Arias
- Translational Neuroimaging laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Joseph Therriault
- Translational Neuroimaging laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Seok-Jun Hong
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Bojana Stefanovic
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - JoAnne McLaurin
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
- Biological Sciences Platform, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Jean-Paul Soucy
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Serge Gauthier
- Translational Neuroimaging laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Sandra E Black
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, ON, Canada
| | - Pedro Rosa-Neto
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
- Translational Neuroimaging laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Maged Goubran
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
- Physical Sciences Platform, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
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2
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Noh E, Namgung JY, Park Y, Jang Y, Lee MJ, Park BY. Shifts in structural connectome organization in the limbic and sensory systems of patients with episodic migraine. J Headache Pain 2024; 25:99. [PMID: 38862883 PMCID: PMC11165833 DOI: 10.1186/s10194-024-01806-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 06/06/2024] [Indexed: 06/13/2024] Open
Abstract
Migraine is a complex neurological condition characterized by recurrent headaches, which is often accompanied by various neurological symptoms. Magnetic resonance imaging (MRI) is a powerful tool for investigating whole-brain connectivity patterns; however, systematic assessment of structural connectome organization has rarely been performed. In the present study, we aimed to examine the changes in structural connectivity in patients with episodic migraines using diffusion MRI. First, we computed structural connectivity using diffusion MRI tractography, after which we applied dimensionality reduction techniques to the structural connectivity and generated three low-dimensional eigenvectors. We subsequently calculated the manifold eccentricity, defined as the Euclidean distance between each data point and the center of the data in the manifold space. We then compared the manifold eccentricity between patients with migraines and healthy controls, revealing significant between-group differences in the orbitofrontal cortex, temporal pole, and sensory/motor regions. Between-group differences in subcortico-cortical connectivity further revealed significant changes in the amygdala, accumbens, and caudate nuclei. Finally, supervised machine learning effectively classified patients with migraines and healthy controls using cortical and subcortical structural connectivity features, highlighting the importance of the orbitofrontal and sensory cortices, in addition to the caudate, in distinguishing between the groups. Our findings confirmed that episodic migraine is related to the structural connectome changes in the limbic and sensory systems, suggesting its potential utility as a diagnostic marker for migraine.
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Affiliation(s)
- Eunchan Noh
- College of Medicine, Inha University, Incheon, Republic of Korea
| | | | - Yeongjun Park
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Yurim Jang
- Department of Statistics and Data Science, Inha University, Incheon, Republic of Korea
| | - Mi Ji Lee
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Bo-Yong Park
- Department of Data Science, Inha University, Incheon, Republic of Korea.
- Department of Statistics and Data Science, Inha University, Incheon, Republic of Korea.
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea.
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3
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Park S, Haak KV, Oldham S, Cho H, Byeon K, Park BY, Thomson P, Chen H, Gao W, Xu T, Valk S, Milham MP, Bernhardt B, Di Martino A, Hong SJ. A shifting role of thalamocortical connectivity in the emergence of cortical functional organization. Nat Neurosci 2024:10.1038/s41593-024-01679-3. [PMID: 38858608 DOI: 10.1038/s41593-024-01679-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 05/13/2024] [Indexed: 06/12/2024]
Abstract
The cortical patterning principle has been a long-standing question in neuroscience, yet how this translates to macroscale functional specialization in the human brain remains largely unknown. Here we examine age-dependent differences in resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks during early life, using a primarily cross-sectional but also longitudinal approach. We show that thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically influenced axonal projection. This pattern changes in childhood, when connectivity is established with the salience network, while decoupling externally and internally oriented functional systems. A developmental simulation using generative network models corroborated these findings, demonstrating that thalamic connectivity contributes to developing key features of the mature brain, such as functional segregation and the sensory-association axis, especially across 12-18 years of age. Our study suggests that the thalamus plays an important role in functional specialization during development, with potential implications for studying conditions with compromised internal and external processing.
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Affiliation(s)
- Shinwon Park
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea
- Autism Center, Child Mind Institute, New York, NY, USA
| | - Koen V Haak
- Department of Cognitive Science and Artificial Intelligence, Tilburg School of Humanities and Digital Sciences, Tilburg University, Tilburg, The Netherlands
- Donders Centre for Cognitive Neuroimaging, Donders Institute, Radboud University, Radboud, The Netherlands
| | - Stuart Oldham
- Developmental Imaging, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Hanbyul Cho
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea
| | - Kyoungseob Byeon
- Center for Integrative Developing Brain, Child Mind Institute, New York, NY, USA
| | - Bo-Yong Park
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea
- Department of Data Science, Inha University, Incheon, South Korea
| | | | - Haitao Chen
- Department of Biomedical Sciences and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Bioengineering, University of California at Los Angeles, Los Angeles, CA, USA
| | - Wei Gao
- Department of Biomedical Sciences and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - Ting Xu
- Center for Integrative Developing Brain, Child Mind Institute, New York, NY, USA
| | - Sofie Valk
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7), Brain and Behavior, Forschungszentrum, Juelich, Germany
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Boris Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | | | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea.
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA.
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea.
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea.
- Department of MetaBioHealth, Sungkyunkwan University, Suwon, South Korea.
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4
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Nenning KH, Xu T, Tambini A, Franco AR, Margulies DS, Colcombe SJ, Milham MP. Fast connectivity gradient approximation: maintaining spatially fine-grained connectivity gradients while reducing computational costs. Commun Biol 2024; 7:697. [PMID: 38844612 PMCID: PMC11156950 DOI: 10.1038/s42003-024-06401-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 05/30/2024] [Indexed: 06/09/2024] Open
Abstract
Brain connectome analysis suffers from the high dimensionality of connectivity data, often forcing a reduced representation of the brain at a lower spatial resolution or parcellation. This is particularly true for graph-based representations, which are increasingly used to characterize connectivity gradients, capturing patterns of systematic spatial variation in the functional connectivity structure. However, maintaining a high spatial resolution is crucial for enabling fine-grained topographical analysis and preserving subtle individual differences that might otherwise be lost. Here we introduce a computationally efficient approach to establish spatially fine-grained connectivity gradients. At its core, it leverages a set of landmarks to approximate the underlying connectivity structure at the full spatial resolution without requiring a full-scale vertex-by-vertex connectivity matrix. We show that this approach reduces computational time and memory usage while preserving informative individual features and demonstrate its application in improving brain-behavior predictions. Overall, its efficiency can remove computational barriers and enable the widespread application of connectivity gradients to capture spatial signatures of the connectome. Importantly, maintaining a spatially fine-grained resolution facilitates to characterize the spatial transitions inherent in the core concept of gradients of brain organization.
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Affiliation(s)
- Karl-Heinz Nenning
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
| | - Ting Xu
- Child Mind Institute, New York, NY, USA
| | - Arielle Tambini
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- New York University, New York, NY, USA
| | - Alexandre R Franco
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Child Mind Institute, New York, NY, USA
- New York University, New York, NY, USA
| | | | - Stanley J Colcombe
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Child Mind Institute, New York, NY, USA
- New York University, New York, NY, USA
| | - Michael P Milham
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Child Mind Institute, New York, NY, USA
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5
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Arichi T. Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging. Cold Spring Harb Perspect Biol 2024; 16:a041496. [PMID: 38438187 PMCID: PMC11146311 DOI: 10.1101/cshperspect.a041496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.
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Affiliation(s)
- Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, New Hunt's House, Guy's Campus, London SE1 1UL, United Kingdom
- Children's Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London SE1 7EH, United Kingdom
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6
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Hu J, Chen G, Zeng Z, Ran H, Zhang R, Yu Q, Xie Y, He Y, Wang F, Li X, Huang K, Liu H, Zhang T. Systematically altered connectome gradient in benign childhood epilepsy with centrotemporal spikes: Potential effect on cognitive function. Neuroimage Clin 2024; 43:103628. [PMID: 38850833 PMCID: PMC11201345 DOI: 10.1016/j.nicl.2024.103628] [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: 02/25/2024] [Revised: 05/06/2024] [Accepted: 06/01/2024] [Indexed: 06/10/2024]
Abstract
OBJECTIVE Benign childhood epilepsy with centrotemporal spikes (BECTS) affects brain network hierarchy and cognitive function; however, itremainsunclearhowhierarchical changeaffectscognition in patients with BECTS. A major aim of this study was to examine changes in the macro-network function hierarchy in BECTS and its potential contribution to cognitive function. METHODS Overall, the study included 50 children with BECTS and 69 healthy controls. Connectome gradient analysis was used to determine the brain network hierarchy of each group. By comparing gradient scores at each voxel level and network between groups, we assessed changes in whole-brain voxel-level and network hierarchy. Functional connectivity was used to detect the functional reorganization of epilepsy caused by these abnormal brain regions based on these aberrant gradients. Lastly, we explored the relationships between the change gradient and functional connectivity values and clinical variables and further predicted the cognitive function associated with BECTS gradient changes. RESULTS In children with BECTS, the gradient was extended at different network and voxel levels. The gradient scores frontoparietal network was increased in the principal gradient of patients with BECTS. The left precentral gyrus (PCG) and right angular gyrus gradient scores were significantly increased in the principal gradient of children with BECTS. Moreover, in regions of the brain with abnormal principal gradients, functional connectivity was disrupted. The left PCG gradient score of children with BECTS was correlated with the verbal intelligence quotient (VIQ), and the disruption of functional connectivity in brain regions with abnormal principal gradients was closely related to cognitive function. VIQ was significantly predicted by the principal gradient map of patients. SIGNIFICANCE The results indicate connectome gradient disruption in children with BECTS and its relationship to cognitive function, thereby increasing our understanding of the functional connectome hierarchy and providing potential biomarkers for cognitive function of children with BECTS.
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Affiliation(s)
- Jie Hu
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China; Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Guiqin Chen
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China; Department of Radiology, The Second Affiliated Hospital of Guizhou University of TCM, Guiyang 550001, China
| | - Zhen Zeng
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Haifeng Ran
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Ruoxi Zhang
- Department of Radiology, The Second Affiliated Hospital of Guizhou University of TCM, Guiyang 550001, China
| | - Qiane Yu
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Yuxin Xie
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Yulun He
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Fuqin Wang
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Xuhong Li
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Kexing Huang
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China
| | - Heng Liu
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China.
| | - Tijiang Zhang
- Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Medical Imaging Center of Guizhou Province, Zunyi 563000, China.
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7
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Chen Z, Xu T, Liu X, Becker B, Li W, Xia L, Zhao W, Zhang R, Huo Z, Hu B, Tang Y, Xiao Z, Feng Z, Chen J, Feng T. Cortical gradient perturbation in attention deficit hyperactivity disorder correlates with neurotransmitter-, cell type-specific and chromosome- transcriptomic signatures. Psychiatry Clin Neurosci 2024; 78:309-321. [PMID: 38334172 DOI: 10.1111/pcn.13649] [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: 10/03/2023] [Revised: 01/16/2024] [Accepted: 01/18/2024] [Indexed: 02/10/2024]
Abstract
AIMS This study aimed to illuminate the neuropathological landscape of attention deficit hyperactivity disorder (ADHD) by a multiscale macro-micro-molecular perspective from in vivo neuroimaging data. METHODS The "ADHD-200 initiative" repository provided multi-site high-quality resting-state functional connectivity (rsfc-) neuroimaging for ADHD children and matched typically developing (TD) cohort. Diffusion mapping embedding model to derive the functional connectome gradient detecting biologically plausible neural pattern was built, and the multivariate partial least square method to uncover the enrichment of neurotransmitomic, cellular and chromosomal gradient-transcriptional signatures of AHBA enrichment and meta-analytic decoding. RESULTS Compared to TD, ADHD children presented connectopic cortical gradient perturbations in almost all the cognition-involved brain macroscale networks (all pBH <0.001), but not in the brain global topology. As an intermediate phenotypic variant, such gradient perturbation was spatially enriched into distributions of GABAA/BZ and 5-HT2A receptors (all pBH <0.01) and co-varied with genetic transcriptional expressions (e.g. DYDC2, ATOH7, all pBH <0.01), associated with phenotypic variants in episodic memory and emotional regulations. Enrichment models demonstrated such gradient-transcriptional variants indicated the risk of both cell-specific and chromosome- dysfunctions, especially in enriched expression of oligodendrocyte precursors and endothelial cells (all pperm <0.05) as well enrichment into chromosome 18, 19 and X (pperm <0.05). CONCLUSIONS Our findings bridged brain macroscale neuropathological patterns to microscale/cellular biological architectures for ADHD children, demonstrating the neurobiologically pathological mechanism of ADHD into the genetic and molecular variants in GABA and 5-HT systems as well brain-derived enrichment of specific cellular/chromosomal expressions.
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Affiliation(s)
- Zhiyi Chen
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Ting Xu
- Department of Psychology, The University of Hong Kong, Hong Kong, China
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Xuerong Liu
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
| | - Benjamin Becker
- Department of Psychology, The University of Hong Kong, Hong Kong, China
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Wei Li
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
| | - Lei Xia
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
| | - Wenqi Zhao
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
| | - Rong Zhang
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Zhenzhen Huo
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Bowen Hu
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Yancheng Tang
- School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Zhibing Xiao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zhengzhi Feng
- Experimental Research Center of Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Ji Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
- Department of Psychiatry, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Tingyong Feng
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
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8
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Vohryzek J, Cabral J, Timmermann C, Atasoy S, Roseman L, Nutt DJ, Carhart-Harris RL, Deco G, Kringelbach ML. The flattening of spacetime hierarchy of the N,N-dimethyltryptamine brain state is characterized by harmonic decomposition of spacetime (HADES) framework. Natl Sci Rev 2024; 11:nwae124. [PMID: 38778818 PMCID: PMC11110867 DOI: 10.1093/nsr/nwae124] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 02/15/2024] [Accepted: 03/11/2024] [Indexed: 05/25/2024] Open
Abstract
The human brain is a complex system, whose activity exhibits flexible and continuous reorganization across space and time. The decomposition of whole-brain recordings into harmonic modes has revealed a repertoire of gradient-like activity patterns associated with distinct brain functions. However, the way these activity patterns are expressed over time with their changes in various brain states remains unclear. Here, we investigate healthy participants taking the serotonergic psychedelic N,N-dimethyltryptamine (DMT) with the Harmonic Decomposition of Spacetime (HADES) framework that can characterize how different harmonic modes defined in space are expressed over time. HADES demonstrates significant decreases in contributions across most low-frequency harmonic modes in the DMT-induced brain state. When normalizing the contributions by condition (DMT and non-DMT), we detect a decrease specifically in the second functional harmonic, which represents the uni- to transmodal functional hierarchy of the brain, supporting the leading hypothesis that functional hierarchy is changed in psychedelics. Moreover, HADES' dynamic spacetime measures of fractional occupancy, life time and latent space provide a precise description of the significant changes of the spacetime hierarchical organization of brain activity in the psychedelic state.
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Affiliation(s)
- Jakub Vohryzek
- Centre for Eudaimonia and Human Flourishing, Linacre College, Department of Psychiatry, University of Oxford, Oxford OX3 9BX, UK
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus 8000, Denmark
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08005, Spain
| | - Joana Cabral
- Centre for Eudaimonia and Human Flourishing, Linacre College, Department of Psychiatry, University of Oxford, Oxford OX3 9BX, UK
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga 4710-057, Portugal
- ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães 4710-057, Portugal
| | - Christopher Timmermann
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK
| | - Selen Atasoy
- Centre for Eudaimonia and Human Flourishing, Linacre College, Department of Psychiatry, University of Oxford, Oxford OX3 9BX, UK
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Leor Roseman
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK
| | - David J Nutt
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK
| | - Robin L Carhart-Harris
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK
- Departments of Neurology and Psychiatry, University of California San Francisco, San Francisco 94143, USA
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08005, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, Department of Psychiatry, University of Oxford, Oxford OX3 9BX, UK
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus 8000, Denmark
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9
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Meinke C, Lueken U, Walter H, Hilbert K. Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 160:105640. [PMID: 38548002 DOI: 10.1016/j.neubiorev.2024.105640] [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: 06/29/2023] [Revised: 02/29/2024] [Accepted: 03/21/2024] [Indexed: 04/07/2024]
Abstract
Predicting treatment outcome in internalizing mental disorders prior to treatment initiation is pivotal for precision mental healthcare. In this regard, resting-state functional connectivity (rs-FC) and machine learning have often shown promising prediction accuracies. This systematic review and meta-analysis evaluates these studies, considering their risk of bias through the Prediction Model Study Risk of Bias Assessment Tool (PROBAST). We examined the predictive performance of features derived from rs-FC, identified features with the highest predictive value, and assessed the employed machine learning pipelines. We searched the electronic databases Scopus, PubMed and PsycINFO on the 12th of December 2022, which resulted in 13 included studies. The mean balanced accuracy for predicting treatment outcome was 77% (95% CI: [72%- 83%]). rs-FC of the dorsolateral prefrontal cortex had high predictive value in most studies. However, a high risk of bias was identified in all studies, compromising interpretability. Methodological recommendations are provided based on a comprehensive exploration of the studies' machine learning pipelines, and potential fruitful developments are discussed.
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Affiliation(s)
- Charlotte Meinke
- Department of Psychology, Humboldt-Universität zu Berlin, Germany.
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Germany; German Center for Mental Health (DZPG), partner site Berlin/Potsdam, Germany.
| | - Henrik Walter
- Charité Universtätsmedizin Berlin, corporate member of FU Berlin and Humboldt Universität zu Berlin, Department of Psychiatrie and Psychotherapy, CCM, Germany.
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Germany; Department of Psychology, Health and Medical University Erfurt, Germany.
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10
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Janet R, Smallwood J, Hutcherson CA, Plassmann H, Mckeown B, Tusche A. Body mass index-dependent shifts along large-scale gradients in human cortical organization explain dietary regulatory success. Proc Natl Acad Sci U S A 2024; 121:e2314224121. [PMID: 38648482 PMCID: PMC11067012 DOI: 10.1073/pnas.2314224121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 03/14/2024] [Indexed: 04/25/2024] Open
Abstract
Making healthy dietary choices is essential for keeping weight within a normal range. Yet many people struggle with dietary self-control despite good intentions. What distinguishes neural processing in those who succeed or fail to implement healthy eating goals? Does this vary by weight status? To examine these questions, we utilized an analytical framework of gradients that characterize systematic spatial patterns of large-scale neural activity, which have the advantage of considering the entire suite of processes subserving self-control and potential regulatory tactics at the whole-brain level. Using an established laboratory food task capturing brain responses in natural and regulatory conditions (N = 123), we demonstrate that regulatory changes of dietary brain states in the gradient space predict individual differences in dietary success. Better regulators required smaller shifts in brain states to achieve larger goal-consistent changes in dietary behaviors, pointing toward efficient network organization. This pattern was most pronounced in individuals with lower weight status (low-BMI, body mass index) but absent in high-BMI individuals. Consistent with prior work, regulatory goals increased activity in frontoparietal brain circuits. However, this shift in brain states alone did not predict variance in dietary success. Instead, regulatory success emerged from combined changes along multiple gradients, showcasing the interplay of different large-scale brain networks subserving dietary control and possible regulatory strategies. Our results provide insights into how the brain might solve the problem of dietary control: Dietary success may be easier for people who adopt modes of large-scale brain activation that do not require significant reconfigurations across contexts and goals.
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Affiliation(s)
- Rémi Janet
- Department of Psychology, Queen’s University, Kingston, ONK7L 3N6, Canada
| | - Jonathan Smallwood
- Department of Psychology, Queen’s University, Kingston, ONK7L 3N6, Canada
| | - Cendri A. Hutcherson
- Department of Psychology, University of Toronto, Toronto, ONM5S 2E5, Canada
- Department of Marketing, Rotman School of Management, University of Toronto, Toronto, ONM5S 3E6, Canada
| | - Hilke Plassmann
- Marketing Area, INSEAD, FontainebleauF-77300, France
- Control-Interoception-Attention Team, Paris Brain Institute (ICM), Sorbonne University, Paris75013, France
| | - Bronte Mckeown
- Department of Psychology, Queen’s University, Kingston, ONK7L 3N6, Canada
| | - Anita Tusche
- Department of Psychology, Queen’s University, Kingston, ONK7L 3N6, Canada
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA91125
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11
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Chen X, Wei Z, Wolbers T. Repetition Suppression Reveals Cue-Specific Spatial Representations for Landmarks and Self-Motion Cues in the Human Retrosplenial Cortex. eNeuro 2024; 11:ENEURO.0294-23.2024. [PMID: 38519127 PMCID: PMC11007318 DOI: 10.1523/eneuro.0294-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 03/08/2024] [Accepted: 03/11/2024] [Indexed: 03/24/2024] Open
Abstract
The efficient use of various spatial cues within a setting is crucial for successful navigation. Two fundamental forms of spatial navigation, landmark-based and self-motion-based, engage distinct cognitive mechanisms. The question of whether these modes invoke shared or separate spatial representations in the brain remains unresolved. While nonhuman animal studies have yielded inconsistent results, human investigation is limited. In our previous work (Chen et al., 2019), we introduced a novel spatial navigation paradigm utilizing ultra-high field fMRI to explore neural coding of positional information. We found that different entorhinal subregions in the right hemisphere encode positional information for landmarks and self-motion cues. The present study tested the generalizability of our previous finding with a modified navigation paradigm. Although we did not replicate our previous finding in the entorhinal cortex, we identified adaptation-based allocentric positional codes for both cue types in the retrosplenial cortex (RSC), which were not confounded by the path to the spatial location. Crucially, the multi-voxel patterns of these spatial codes differed between the cue types, suggesting cue-specific positional coding. The parahippocampal cortex exhibited positional coding for self-motion cues, which was not dissociable from path length. Finally, the brain regions involved in successful navigation differed from our previous study, indicating overall distinct neural mechanisms recruited in our two studies. Taken together, the current findings demonstrate cue-specific allocentric positional coding in the human RSC in the same navigation task for the first time and that spatial representations in the brain are contingent on specific experimental conditions.
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Affiliation(s)
- Xiaoli Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, P.R. China
| | - Ziwei Wei
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, P.R. China
| | - Thomas Wolbers
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg 39106, Germany
- Center for Behavioral Brain Sciences (CBBS), Otto-von-Guericke University, Magdeburg 39106, Germany
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12
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Pedersen R, Johansson J, Nordin K, Rieckmann A, Wåhlin A, Nyberg L, Bäckman L, Salami A. Dopamine D1-Receptor Organization Contributes to Functional Brain Architecture. J Neurosci 2024; 44:e0621232024. [PMID: 38302439 PMCID: PMC10941071 DOI: 10.1523/jneurosci.0621-23.2024] [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: 04/03/2023] [Revised: 12/01/2023] [Accepted: 01/21/2024] [Indexed: 02/03/2024] Open
Abstract
Recent work has recognized a gradient-like organization in cortical function, spanning from primary sensory to transmodal cortices. It has been suggested that this axis is aligned with regional differences in neurotransmitter expression. Given the abundance of dopamine D1-receptors (D1DR), and its importance for modulation and neural gain, we tested the hypothesis that D1DR organization is aligned with functional architecture, and that inter-regional relationships in D1DR co-expression modulate functional cross talk. Using the world's largest dopamine D1DR-PET and MRI database (N = 180%, 50% female), we demonstrate that D1DR organization follows a unimodal-transmodal hierarchy, expressing a high spatial correspondence to the principal gradient of functional connectivity. We also demonstrate that individual differences in D1DR density between unimodal and transmodal regions are associated with functional differentiation of the apices in the cortical hierarchy. Finally, we show that spatial co-expression of D1DR primarily modulates couplings within, but not between, functional networks. Together, our results show that D1DR co-expression provides a biomolecular layer to the functional organization of the brain.
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Affiliation(s)
- Robin Pedersen
- Department of Integrative Medical Biology, Umeå University, Umeå S-90197, Sweden
- Wallenberg Center for Molecular Medicine (WCMM), Umeå University, Umeå S-90197, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90197, Sweden
| | - Jarkko Johansson
- Department of Integrative Medical Biology, Umeå University, Umeå S-90197, Sweden
- Wallenberg Center for Molecular Medicine (WCMM), Umeå University, Umeå S-90197, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90197, Sweden
| | - Kristin Nordin
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90197, Sweden
- Aging Research Center, Karolinska Institutet & Stockholm University, Stockholm S-17165, Sweden
| | - Anna Rieckmann
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90197, Sweden
- Department of Radiation Sciences, Umeå University, Umeå S-90197, Sweden
- Max-Planck-Institut für Sozialrecht und Sozialpolitik, Munich 80799, Germany
| | - Anders Wåhlin
- Department of Integrative Medical Biology, Umeå University, Umeå S-90197, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90197, Sweden
| | - Lars Nyberg
- Department of Integrative Medical Biology, Umeå University, Umeå S-90197, Sweden
- Wallenberg Center for Molecular Medicine (WCMM), Umeå University, Umeå S-90197, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90197, Sweden
- Department of Radiation Sciences, Umeå University, Umeå S-90197, Sweden
| | - Lars Bäckman
- Aging Research Center, Karolinska Institutet & Stockholm University, Stockholm S-17165, Sweden
| | - Alireza Salami
- Department of Integrative Medical Biology, Umeå University, Umeå S-90197, Sweden
- Wallenberg Center for Molecular Medicine (WCMM), Umeå University, Umeå S-90197, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå S-90197, Sweden
- Aging Research Center, Karolinska Institutet & Stockholm University, Stockholm S-17165, Sweden
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13
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Yoo S, Jang Y, Hong SJ, Park H, Valk SL, Bernhardt BC, Park BY. Whole-brain structural connectome asymmetry in autism. Neuroimage 2024; 288:120534. [PMID: 38340881 DOI: 10.1016/j.neuroimage.2024.120534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/28/2024] [Accepted: 02/07/2024] [Indexed: 02/12/2024] Open
Abstract
Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.
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Affiliation(s)
- Seulki Yoo
- Convergence Research Institute, Sungkyunkwan University, Suwon, Republic of Korea
| | - Yurim Jang
- Artificial Intelligence Convergence Research Center, Inha University, Incheon, Republic of Korea
| | - Seok-Jun Hong
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Hyunjin Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Sofie L Valk
- Forschungszentrum Julich, Germany; Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany; Systems Neuroscience, Heinrich Heine University, Duesseldorf, Germany
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Bo-Yong Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; Department of Data Science, Inha University, Incheon, Republic of Korea; Department of Statistics and Data Science, Inha University, Incheon, Republic of Korea.
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14
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Busch EL, Rapuano KM, Anderson KM, Rosenberg MD, Watts R, Casey BJ, Haxby JV, Feilong M. Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during Development. J Neurosci 2024; 44:e0735232023. [PMID: 38148152 PMCID: PMC10866091 DOI: 10.1523/jneurosci.0735-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 10/09/2023] [Accepted: 11/16/2023] [Indexed: 12/28/2023] Open
Abstract
The functional connectome supports information transmission through the brain at various spatial scales, from exchange between broad cortical regions to finer-scale, vertex-wise connections that underlie specific information processing mechanisms. In adults, while both the coarse- and fine-scale functional connectomes predict cognition, the fine scale can predict up to twice the variance as the coarse-scale functional connectome. Yet, past brain-wide association studies, particularly using large developmental samples, focus on the coarse connectome to understand the neural underpinnings of individual differences in cognition. Using a large cohort of children (age 9-10 years; n = 1,115 individuals; both sexes; 50% female, including 170 monozygotic and 219 dizygotic twin pairs and 337 unrelated individuals), we examine the reliability, heritability, and behavioral relevance of resting-state functional connectivity computed at different spatial scales. We use connectivity hyperalignment to improve access to reliable fine-scale (vertex-wise) connectivity information and compare the fine-scale connectome with the traditional parcel-wise (coarse scale) functional connectomes. Though individual differences in the fine-scale connectome are more reliable than those in the coarse-scale, they are less heritable. Further, the alignment and scale of connectomes influence their ability to predict behavior, whereby some cognitive traits are equally well predicted by both connectome scales, but other, less heritable cognitive traits are better predicted by the fine-scale connectome. Together, our findings suggest there are dissociable individual differences in information processing represented at different scales of the functional connectome which, in turn, have distinct implications for heritability and cognition.
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Affiliation(s)
- Erica L Busch
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - Kristina M Rapuano
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - Kevin M Anderson
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - Monica D Rosenberg
- Department of Psychology, University of Chicago, Chicago, Illinois, 60637
| | - Richard Watts
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - B J Casey
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - James V Haxby
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, 03755
| | - Ma Feilong
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, 03755
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15
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Tan JB, Müller EJ, Orlando IF, Taylor NL, Margulies DS, Szeto J, Lewis SJG, Shine JM, O'Callaghan C. Abnormal higher-order network interactions in Parkinson's disease visual hallucinations. Brain 2024; 147:458-471. [PMID: 37677056 DOI: 10.1093/brain/awad305] [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: 04/11/2023] [Revised: 07/14/2023] [Accepted: 08/11/2023] [Indexed: 09/09/2023] Open
Abstract
Visual hallucinations in Parkinson's disease can be viewed from a systems-level perspective, whereby dysfunctional communication between brain networks responsible for perception predisposes a person to hallucinate. To this end, abnormal functional interactions between higher-order and primary sensory networks have been implicated in the pathophysiology of visual hallucinations in Parkinson's disease, however the precise signatures remain to be determined. Dimensionality reduction techniques offer a novel means for simplifying the interpretation of multidimensional brain imaging data, identifying hierarchical patterns in the data that are driven by both within- and between-functional network changes. Here, we applied two complementary non-linear dimensionality reduction techniques-diffusion-map embedding and t-distributed stochastic neighbour embedding (t-SNE)-to resting state functional MRI data, in order to characterize the altered functional hierarchy associated with susceptibility to visual hallucinations. Our study involved 77 people with Parkinson's disease (31 with hallucinations; 46 without hallucinations) and 19 age-matched healthy control subjects. In patients with visual hallucinations, we found compression of the unimodal-heteromodal gradient consistent with increased functional integration between sensory and higher order networks. This was mirrored in a traditional functional connectivity analysis, which showed increased connectivity between the visual and default mode networks in the hallucinating group. Together, these results suggest a route by which higher-order regions may have excessive influence over earlier sensory processes, as proposed by theoretical models of hallucinations across disorders. By contrast, the t-SNE analysis identified distinct alterations in prefrontal regions, suggesting an additional layer of complexity in the functional brain network abnormalities implicated in hallucinations, which was not apparent in traditional functional connectivity analyses. Together, the results confirm abnormal brain organization associated with the hallucinating phenotype in Parkinson's disease and highlight the utility of applying convergent dimensionality reduction techniques to investigate complex clinical symptoms. In addition, the patterns we describe in Parkinson's disease converge with those seen in other conditions, suggesting that reduced hierarchical differentiation across sensory-perceptual systems may be a common transdiagnostic vulnerability in neuropsychiatric disorders with perceptual disturbances.
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Affiliation(s)
- Joshua B Tan
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
| | - Eli J Müller
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
- Centre for Complex Systems, School of Physics, University of Sydney, Sydney 2050, Australia
| | - Isabella F Orlando
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
| | - Natasha L Taylor
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
| | - Daniel S Margulies
- Integrative Neuroscience and Cognition Center, Center National de la Recherche Scientifique (CNRS) and Université de Paris, 75006 Paris, France
| | - Jennifer Szeto
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
| | - Simon J G Lewis
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
| | - James M Shine
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
- Centre for Complex Systems, School of Physics, University of Sydney, Sydney 2050, Australia
| | - Claire O'Callaghan
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
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16
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Jang Y, Choi H, Yoo S, Park H, Park BY. Structural connectome alterations between individuals with autism and neurotypical controls using feature representation learning. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2024; 20:2. [PMID: 38267953 PMCID: PMC10807082 DOI: 10.1186/s12993-024-00228-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/10/2024] [Indexed: 01/26/2024]
Abstract
Autism spectrum disorder is one of the most common neurodevelopmental conditions associated with sensory and social communication impairments. Previous neuroimaging studies reported that atypical nodal- or network-level functional brain organization in individuals with autism was associated with autistic behaviors. Although dimensionality reduction techniques have the potential to uncover new biomarkers, the analysis of whole-brain structural connectome abnormalities in a low-dimensional latent space is underinvestigated. In this study, we utilized autoencoder-based feature representation learning for diffusion magnetic resonance imaging-based structural connectivity in 80 individuals with autism and 61 neurotypical controls that passed strict quality controls. We generated low-dimensional latent features using the autoencoder model for each group and adopted an integrated gradient approach to assess the contribution of the input data for predicting latent features during the encoding process. Subsequently, we compared the integrated gradient values between individuals with autism and neurotypical controls and observed differences within the transmodal regions and between the sensory and limbic systems. Finally, we identified significant associations between integrated gradient values and communication abilities in individuals with autism. Our findings provide insights into the whole-brain structural connectome in autism and may help identify potential biomarkers for autistic connectopathy.
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Affiliation(s)
- Yurim Jang
- Artificial Intelligence Convergence Research Center, Inha University, Incheon, Republic of Korea
| | - Hyoungshin Choi
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Seulki Yoo
- Convergence Research Institute, Sungkyunkwan University, Suwon, Republic of Korea
| | - Hyunjin Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
- School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Bo-Yong Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea.
- Department of Data Science, Inha University, Incheon, Republic of Korea.
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17
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Tong Z, Zhang J, Xing C, Xu X, Wu Y, Salvi R, Yin X, Zhao F, Chen YC, Cai Y. Reorganization of the cortical connectome functional gradient in age-related hearing loss. Neuroimage 2023; 284:120475. [PMID: 38013009 DOI: 10.1016/j.neuroimage.2023.120475] [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: 07/12/2023] [Revised: 11/10/2023] [Accepted: 11/24/2023] [Indexed: 11/29/2023] Open
Abstract
Age-related hearing loss (ARHL), one of the most common sensory deficits in elderly individuals, is a risk factor for dementia; however, it is unclear how ARHL affects the decline in cognitive function. To address this issue, a connectome gradient framework was used to identify critical features of information integration between sensory and cognitive processing centers using resting-state functional magnetic resonance imaging (rs-fMRI) data from 40 individuals with ARHL and 36 healthy controls (HCs). The first three functional gradient alterations associated with ARHL were investigated at the global, network and regional levels. Using a support vector machine (SVM) model, our analysis distinguished individuals with ARHL with normal cognitive function from those with cognitive decline. Compared to HCs, individuals with ARHL had a contracted principal primary-to-transmodal gradient axis, especially in the visual and default mode networks, with an altered gradient explained ratio and variance. Among individuals with ARHL, cognitive decline was detected in the visual network in the principal gradient as well as in the limbic, salience and default mode networks in the third gradient (salience to frontoparietal/default mode). These results suggest that ARHL is associated with disrupted information processing from the primary sensory networks to higher-order cognitive networks and highlight the key nodes closely associated with cognitive decline during cognitive processing in ARHL, providing new insights into the mechanism of cognitive impairment and suggesting potential treatments related to ARHL.
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Affiliation(s)
- Zhaopeng Tong
- Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; Institute of Hearing and Speech-Language Science, Sun Yat-sen University, Guangzhou, China
| | - Juan Zhang
- Department of Neurology, Nanjing Yuhua Hospital, Yuhua Branch of Nanjing First Hospital, Nanjing, China
| | - Chunhua Xing
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, Nanjing 210006, China
| | - Xiaomin Xu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, Nanjing 210006, China
| | - Yuanqing Wu
- Department of Otolaryngology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Richard Salvi
- Center for Hearing and Deafness, University at Buffalo, The State University of New York, Buffalo, United States
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, Nanjing 210006, China
| | - Fei Zhao
- Department of Speech and Language Therapy and Hearing Science, Cardiff Metropolitan University, Cardiff, United Kingdom
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, Nanjing 210006, China.
| | - Yuexin Cai
- Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; Institute of Hearing and Speech-Language Science, Sun Yat-sen University, Guangzhou, China.
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18
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Diveica V, Riedel MC, Salo T, Laird AR, Jackson RL, Binney RJ. Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity. Cereb Cortex 2023; 33:11384-11399. [PMID: 37833772 PMCID: PMC10690868 DOI: 10.1093/cercor/bhad373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 08/17/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.
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Affiliation(s)
- Veronica Diveica
- Department of Psychology & Cognitive Neuroscience Institute, Bangor University, Bangor, Wales LL57 2AS, United Kingdom
- Department of Neurology and Neurosurgery & Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Michael C Riedel
- Department of Physics, Florida International University, Miami, FL 33199, United States
| | - Taylor Salo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, United States
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL 33199, United States
| | - Rebecca L Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, York, YO10 5DD, United Kingdom
| | - Richard J Binney
- Department of Psychology & Cognitive Neuroscience Institute, Bangor University, Bangor, Wales LL57 2AS, United Kingdom
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19
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Heitmann C, Zhan M, Linke M, Hölig C, Kekunnaya R, van Hoof R, Goebel R, Röder B. Early visual experience refines the retinotopic organization within and across visual cortical regions. Curr Biol 2023; 33:4950-4959.e4. [PMID: 37918397 DOI: 10.1016/j.cub.2023.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 09/29/2023] [Accepted: 10/06/2023] [Indexed: 11/04/2023]
Abstract
Early visual areas are retinotopically organized in human and non-human primates. Population receptive field (pRF) size increases with eccentricity and from lower- to higher-level visual areas. Furthermore, the cortical magnification factor (CMF), a measure of how much cortical space is devoted to each degree of visual angle, is typically larger for foveal as opposed to peripheral regions of the visual field. Whether this fine-scale organization within and across visual areas depends on early visual experience has yet been unknown. Here, we employed 7T functional magnetic resonance imaging pRF mapping to assess the retinotopic organization of early visual regions (i.e., V1, V2, and V3) in eight sight recovery individuals with a history of congenital blindness until a maximum of 4 years of age. Compared with sighted controls, foveal pRF sizes in these individuals were larger, and pRF sizes did not show the typical increase with eccentricity and down the visual cortical processing stream (V1-V2-V3). Cortical magnification was overall diminished and decreased less from foveal to parafoveal visual field locations. Furthermore, cortical magnification correlated with visual acuity in sight recovery individuals. The results of this study suggest that early visual experience is essential for refining a presumably innate prototypical retinotopic organization in humans within and across visual areas, which seems to be crucial for acquiring full visual capabilities.
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Affiliation(s)
- Carolin Heitmann
- Biological Psychology and Neuropsychology Lab, Faculty of Psychology and Movement Sciences, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany.
| | - Minye Zhan
- U992 (Cognitive neuroimaging unit), NeuroSpin, INSERM-CEA, 91191 Gif sur Yvette, France
| | - Madita Linke
- Biological Psychology and Neuropsychology Lab, Faculty of Psychology and Movement Sciences, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany
| | - Cordula Hölig
- Biological Psychology and Neuropsychology Lab, Faculty of Psychology and Movement Sciences, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany
| | - Ramesh Kekunnaya
- U992 (Cognitive neuroimaging unit), NeuroSpin, INSERM-CEA, 91191 Gif sur Yvette, France
| | - Rick van Hoof
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, the Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, the Netherlands; Department of Development and Research, Brain Innovation B.V., Oxfordlaan 55, 6229 EV Maastricht, the Netherlands
| | - Brigitte Röder
- Biological Psychology and Neuropsychology Lab, Faculty of Psychology and Movement Sciences, Universität Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany; Child Sight Institute, Jasti V. Ramanamma Children's Eye Care Center, LV Prasad Eye Institute, Hyderabad, Telangana 500034, India.
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20
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Morgenroth E, Vilaclara L, Muszynski M, Gaviria J, Vuilleumier P, Van De Ville D. Probing neurodynamics of experienced emotions-a Hitchhiker's guide to film fMRI. Soc Cogn Affect Neurosci 2023; 18:nsad063. [PMID: 37930850 PMCID: PMC10656947 DOI: 10.1093/scan/nsad063] [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: 03/16/2023] [Revised: 08/04/2023] [Accepted: 11/01/2023] [Indexed: 11/08/2023] Open
Abstract
Film functional magnetic resonance imaging (fMRI) has gained tremendous popularity in many areas of neuroscience. However, affective neuroscience remains somewhat behind in embracing this approach, even though films lend themselves to study how brain function gives rise to complex, dynamic and multivariate emotions. Here, we discuss the unique capabilities of film fMRI for emotion research, while providing a general guide of conducting such research. We first give a brief overview of emotion theories as these inform important design choices. Next, we discuss films as experimental paradigms for emotion elicitation and address the process of annotating them. We then situate film fMRI in the context of other fMRI approaches, and present an overview of results from extant studies so far with regard to advantages of film fMRI. We also give an overview of state-of-the-art analysis techniques including methods that probe neurodynamics. Finally, we convey limitations of using film fMRI to study emotion. In sum, this review offers a practitioners' guide to the emerging field of film fMRI and underscores how it can advance affective neuroscience.
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Affiliation(s)
- Elenor Morgenroth
- Neuro-X Institute, École Polytechnique Fédérale de Lausanne, Geneva 1202, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva 1202, Switzerland
- Swiss Center for Affective Sciences, University of Geneva, Geneva 1202, Switzerland
| | - Laura Vilaclara
- Neuro-X Institute, École Polytechnique Fédérale de Lausanne, Geneva 1202, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva 1202, Switzerland
| | - Michal Muszynski
- Department of Basic Neurosciences, University of Geneva, Geneva 1202, Switzerland
| | - Julian Gaviria
- Swiss Center for Affective Sciences, University of Geneva, Geneva 1202, Switzerland
- Department of Basic Neurosciences, University of Geneva, Geneva 1202, Switzerland
- Department of Psychiatry, University of Geneva, Geneva 1202, Switzerland
| | - Patrik Vuilleumier
- Swiss Center for Affective Sciences, University of Geneva, Geneva 1202, Switzerland
- Department of Basic Neurosciences, University of Geneva, Geneva 1202, Switzerland
- CIBM Center for Biomedical Imaging, Geneva 1202, Switzerland
| | - Dimitri Van De Ville
- Neuro-X Institute, École Polytechnique Fédérale de Lausanne, Geneva 1202, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva 1202, Switzerland
- CIBM Center for Biomedical Imaging, Geneva 1202, Switzerland
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21
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He Y, Li Q, Fu Z, Zeng D, Han Y, Li S. Functional gradients reveal altered functional segregation in patients with amnestic mild cognitive impairment and Alzheimer's disease. Cereb Cortex 2023; 33:10836-10847. [PMID: 37718155 DOI: 10.1093/cercor/bhad328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/26/2023] [Accepted: 08/23/2023] [Indexed: 09/19/2023] Open
Abstract
Alzheimer's disease and amnestic mild cognitive impairment are associated with disrupted functional organization in brain networks, involved with alteration of functional segregation. Connectome gradients are a new tool representing brain functional topological organization to smoothly capture the human macroscale hierarchy. Here, we examined altered topological organization in amnestic mild cognitive impairment and Alzheimer's disease by connectome gradient mapping. We further quantified functional segregation by gradient dispersion. Then, we systematically compared the alterations observed in amnestic mild cognitive impairment and Alzheimer's disease patients with those in normal controls in a two-dimensional functional gradient space from both the whole-brain level and module level. Compared with normal controls, the first gradient, which described the neocortical hierarchy from unimodal to transmodal regions, showed a more distributed and significant suppression in Alzheimer's disease than amnestic mild cognitive impairment patients. Furthermore, gradient dispersion showed significant decreases in Alzheimer's disease at both the global level and module level, whereas this alteration was limited only to limbic areas in amnestic mild cognitive impairment. Notably, we demonstrated that suppressed gradient dispersion in amnestic mild cognitive impairment and Alzheimer's disease was associated with cognitive scores. These findings provide new evidence for altered brain hierarchy in amnestic mild cognitive impairment and Alzheimer's disease, which strengthens our understanding of the progressive mechanism of cognitive decline.
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Affiliation(s)
- Yirong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Zhenrong Fu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing 100083, China
| | - Debin Zeng
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing 100083, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- Biomedical Engineering Institute, Hainan University, Haikou 570228, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing 100050, China
- National Clinical Research Center for Geriatric Disorders, Beijing 100053, China
| | - Shuyu Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
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22
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Bijsterbosch JD, Farahibozorg SR, Glasser MF, Essen DV, Snyder LH, Woolrich MW, Smith SM. Evaluating functional brain organization in individuals and identifying contributions to network overlap. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.21.558809. [PMID: 37790508 PMCID: PMC10542549 DOI: 10.1101/2023.09.21.558809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Individual differences in the spatial organization of resting state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting state networks can be derived using high quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that network overlap is indicative of linear additive coupling. These results suggest that regions of network overlap concurrently process information from all contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.
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Affiliation(s)
- Janine D Bijsterbosch
- Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | | | - Matthew F Glasser
- Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | - David Van Essen
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | - Lawrence H Snyder
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | - Mark W Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
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23
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Veréb D, Mijalkov M, Canal-Garcia A, Chang YW, Gomez-Ruiz E, Gerboles BZ, Kivipelto M, Svenningsson P, Zetterberg H, Volpe G, Betts M, Jacobs HIL, Pereira JB. Age-related differences in the functional topography of the locus coeruleus and their implications for cognitive and affective functions. eLife 2023; 12:RP87188. [PMID: 37650882 PMCID: PMC10471162 DOI: 10.7554/elife.87188] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/01/2023] Open
Abstract
The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging, and whether it is associated with cognition and mood. Here, we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years of age (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project [HCP] 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory, and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography, and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale (HADS) ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.
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Affiliation(s)
- Dániel Veréb
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Mite Mijalkov
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Anna Canal-Garcia
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Yu-Wei Chang
- Department of Physics, Goteborg UniversityGoteborgSweden
| | | | - Blanca Zufiria Gerboles
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
- University of Eastern FinlandKuopioFinland
| | - Per Svenningsson
- University of Eastern FinlandKuopioFinland
- Department of Clinical Neuroscience, Karolinska InstitutetStockholmSweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative Disease, UCL Institute of NeurologyLondonUnited Kingdom
- UK Dementia Research Institute at UCLLondonUnited Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water BayHong KongChina
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-MadisonMadisonUnited States
| | - Giovanni Volpe
- Department of Physics, Goteborg UniversityGoteborgSweden
| | - Matthew Betts
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative Diseases (DZNE), Otto-von-Guericke University MagdeburgMagdeburgGermany
- Center for Behavioral Brain Sciences, University of MagdeburgMagdeburgGermany
| | - Heidi IL Jacobs
- Maastricht UniversityMaastrichtNetherlands
- Massachusetts General HospitalBostonUnited States
| | - Joana B Pereira
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
- Memory Research Unit, Department of Clinical Sciences Malmö, Lund UniversityLundSweden
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24
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Isakoglou C, Haak KV, Wolfers T, Floris DL, Llera A, Oldehinkel M, Forde NJ, Oakley BFM, Tillmann J, Holt RJ, Moessnang C, Loth E, Bourgeron T, Baron-Cohen S, Charman T, Banaschewski T, Murphy DGM, Buitelaar JK, Marquand AF, Beckmann CF. Fine-grained topographic organization within somatosensory cortex during resting-state and emotional face-matching task and its association with ASD traits. Transl Psychiatry 2023; 13:270. [PMID: 37500630 PMCID: PMC10374902 DOI: 10.1038/s41398-023-02559-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 03/26/2023] [Accepted: 07/04/2023] [Indexed: 07/29/2023] Open
Abstract
Sensory atypicalities are particularly common in autism spectrum disorders (ASD). Nevertheless, our knowledge about the divergent functioning of the underlying somatosensory region and its association with ASD phenotype features is limited. We applied a data-driven approach to map the fine-grained variations in functional connectivity of the primary somatosensory cortex (S1) to the rest of the brain in 240 autistic and 164 neurotypical individuals from the EU-AIMS LEAP dataset, aged between 7 and 30. We estimated the S1 connection topography ('connectopy') at rest and during the emotional face-matching (Hariri) task, an established measure of emotion reactivity, and accessed its association with a set of clinical and behavioral variables. We first demonstrated that the S1 connectopy is organized along a dorsoventral axis, mapping onto the S1 somatotopic organization. We then found that its spatial characteristics were linked to the individuals' adaptive functioning skills, as measured by the Vineland Adaptive Behavior Scales, across the whole sample. Higher functional differentiation characterized the S1 connectopies of individuals with higher daily life adaptive skills. Notably, we detected significant differences between rest and the Hariri task in the S1 connectopies, as well as their projection maps onto the rest of the brain suggesting a task-modulating effect on S1 due to emotion processing. All in all, variation of adaptive skills appears to be reflected in the brain's mesoscale neural circuitry, as shown by the S1 connectivity profile, which is also differentially modulated during rest and emotional processing.
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Affiliation(s)
- Christina Isakoglou
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands.
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands.
| | - Koen V Haak
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
| | - Thomas Wolfers
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Dorothea L Floris
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
- Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Alberto Llera
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Marianne Oldehinkel
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Natalie J Forde
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Bethany F M Oakley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Julian Tillmann
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Rosemary J Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Carolin Moessnang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Department of Applied Psychology, SRH University, Heidelberg, Germany
| | - Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, Université de Paris, Paris, France
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Jan K Buitelaar
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, Netherlands
| | - Andre F Marquand
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Christian F Beckmann
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
- Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom
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25
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Zhang XH, Anderson KM, Dong HM, Chopra S, Dhamala E, Emani PS, Margulies D, Holmes AJ. The Cellular Underpinnings of the Human Cortical Connectome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.05.547828. [PMID: 37461642 PMCID: PMC10349999 DOI: 10.1101/2023.07.05.547828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
The functional properties of the human brain arise, in part, from the vast assortment of cell types that pattern the cortex. The cortical sheet can be broadly divided into distinct networks, which are further embedded into processing streams, or gradients, that extend from unimodal systems through higher-order association territories. Here, using transcriptional data from the Allen Human Brain Atlas, we demonstrate that imputed cell type distributions are spatially coupled to the functional organization of cortex, as estimated through fMRI. Cortical cellular profiles follow the macro-scale organization of the functional gradients as well as the associated large-scale networks. Distinct cellular fingerprints were evident across networks, and a classifier trained on post-mortem cell-type distributions was able to predict the functional network allegiance of cortical tissue samples. These data indicate that the in vivo organization of the cortical sheet is reflected in the spatial variability of its cellular composition.
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Affiliation(s)
- Xi-Han Zhang
- Department of Psychology, Yale University, New Haven, CT, USA
| | | | - Hao-Ming Dong
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Sidhant Chopra
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Elvisha Dhamala
- Department of Psychology, Yale University, New Haven, CT, USA
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA
| | - Prashant S. Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Daniel Margulies
- CNRS, Integrative Neuroscience and Cognition Center (UMR 8002), Université de Paris, Paris, France
| | - Avram J. Holmes
- Department of Psychology, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA
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26
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Watson DM, Andrews TJ. Connectopic mapping techniques do not reflect functional gradients in the brain. Neuroimage 2023:120228. [PMID: 37339700 DOI: 10.1016/j.neuroimage.2023.120228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/08/2023] [Accepted: 06/12/2023] [Indexed: 06/22/2023] Open
Abstract
Functional gradients, in which response properties change gradually across a brain region, have been proposed as a key organising principle of the brain. Recent studies using both resting-state and natural viewing paradigms have indicated that these gradients may be reconstructed from functional connectivity patterns via "connectopic mapping" analyses. However, local connectivity patterns may be confounded by spatial autocorrelations artificially introduced during data analysis, for instance by spatial smoothing or interpolation between coordinate spaces. Here, we investigate whether such confounds can produce illusory connectopic gradients. We generated datasets comprising random white noise in subjects' functional volume spaces, then optionally applied spatial smoothing and/or interpolated the data to a different volume or surface space. Both smoothing and interpolation induced spatial autocorrelations sufficient for connectopic mapping to produce both volume- and surface-based local gradients in numerous brain regions. Furthermore, these gradients appeared highly similar to those obtained from real natural viewing data, although gradients generated from real and random data were statistically different in certain scenarios. We also reconstructed global gradients across the whole-brain - while these appeared less susceptible to artificial spatial autocorrelations, the ability to reproduce previously reported gradients was closely linked to specific features of the analysis pipeline. These results indicate that previously reported gradients identified by connectopic mapping techniques may be confounded by artificial spatial autocorrelations introduced during the analysis, and in some cases may reproduce poorly across different analysis pipelines. These findings imply that connectopic gradients need to be interpreted with caution.
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Affiliation(s)
- David M Watson
- Department of Psychology and York Neuroimaging Centre, University of York, York, UK, YO10 5DD.
| | - Timothy J Andrews
- Department of Psychology and York Neuroimaging Centre, University of York, York, UK, YO10 5DD
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27
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Veréb D, Mijalkov M, Canal-Garcia A, Chang YW, Gomez-Ruis E, Gerboles BZ, Kivipelto M, Svenningsson P, Zetterberg H, Volpe G, Betts MJ, Jacobs H, Pereira JB. Age-related differences in the functional topography of the locus coeruleus: implications for cognitive and affective functions. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.25.23286442. [PMID: 37333117 PMCID: PMC10274957 DOI: 10.1101/2023.02.25.23286442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging and whether it is associated with cognition and mood. Here we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years old (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.
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Affiliation(s)
- Dániel Veréb
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Mite Mijalkov
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Anna Canal-Garcia
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Yu-Wei Chang
- Department of Physics, Goteborg University, Goteborg, Sweden
| | | | - Blanca Zufiria Gerboles
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- University of Eastern Finland, Kuopio, Finland
| | - Per Svenningsson
- University of Eastern Finland, Kuopio, Finland
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Giovanni Volpe
- Department of Physics, Goteborg University, Goteborg, Sweden
| | - Mathew J. Betts
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- Center for Behavioral Brain Sciences, University of Magdeburg, Magdeburg, Germany
| | - Heidi Jacobs
- Maastricht University, Maastricht, The Netherlands
- Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Joana B. Pereira
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
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28
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Pang JC, Aquino KM, Oldehinkel M, Robinson PA, Fulcher BD, Breakspear M, Fornito A. Geometric constraints on human brain function. Nature 2023; 618:566-574. [PMID: 37258669 PMCID: PMC10266981 DOI: 10.1038/s41586-023-06098-1] [Citation(s) in RCA: 68] [Impact Index Per Article: 68.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 04/18/2023] [Indexed: 06/02/2023]
Abstract
The anatomy of the brain necessarily constrains its function, but precisely how remains unclear. The classical and dominant paradigm in neuroscience is that neuronal dynamics are driven by interactions between discrete, functionally specialized cell populations connected by a complex array of axonal fibres1-3. However, predictions from neural field theory, an established mathematical framework for modelling large-scale brain activity4-6, suggest that the geometry of the brain may represent a more fundamental constraint on dynamics than complex interregional connectivity7,8. Here, we confirm these theoretical predictions by analysing human magnetic resonance imaging data acquired under spontaneous and diverse task-evoked conditions. Specifically, we show that cortical and subcortical activity can be parsimoniously understood as resulting from excitations of fundamental, resonant modes of the brain's geometry (that is, its shape) rather than from modes of complex interregional connectivity, as classically assumed. We then use these geometric modes to show that task-evoked activations across over 10,000 brain maps are not confined to focal areas, as widely believed, but instead excite brain-wide modes with wavelengths spanning over 60 mm. Finally, we confirm predictions that the close link between geometry and function is explained by a dominant role for wave-like activity, showing that wave dynamics can reproduce numerous canonical spatiotemporal properties of spontaneous and evoked recordings. Our findings challenge prevailing views and identify a previously underappreciated role of geometry in shaping function, as predicted by a unifying and physically principled model of brain-wide dynamics.
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Affiliation(s)
- James C Pang
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
| | - Kevin M Aquino
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
- BrainKey Inc., San Francisco, CA, USA
| | - Marianne Oldehinkel
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Peter A Robinson
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
| | - Ben D Fulcher
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
| | - Michael Breakspear
- School of Psychological Sciences, College of Engineering, Science and the Environment, University of Newcastle, Callaghan, New South Wales, Australia
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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29
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Franceschiello B, Rumac S, Hilbert T, Nau M, Dziadosz M, Degano G, Roy CW, Gaglianese A, Petri G, Yerly J, Stuber M, Kober T, van Heeswijk RB, Murray MM, Fornari E. Hi-Fi fMRI: High-resolution, fast-sampled and sub-second whole-brain functional MRI at 3T in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.13.540663. [PMID: 37425913 PMCID: PMC10327135 DOI: 10.1101/2023.05.13.540663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Functional magnetic resonance imaging (fMRI) is a methodological cornerstone of neuroscience. Most studies measure blood-oxygen-level-dependent (BOLD) signal using echo-planar imaging (EPI), Cartesian sampling, and image reconstruction with a one-to-one correspondence between the number of acquired volumes and reconstructed images. However, EPI schemes are subject to trade-offs between spatial and temporal resolutions. We overcome these limitations by measuring BOLD with a gradient recalled echo (GRE) with 3D radial-spiral phyllotaxis trajectory at a high sampling rate (28.24ms) on standard 3T field-strength. The framework enables the reconstruction of 3D signal time courses with whole-brain coverage at simultaneously higher spatial (1mm 3 ) and temporal (up to 250ms) resolutions, as compared to optimized EPI schemes. Additionally, artifacts are corrected before image reconstruction; the desired temporal resolution is chosen after scanning and without assumptions on the shape of the hemodynamic response. By showing activation in the calcarine sulcus of 20 participants performing an ON-OFF visual paradigm, we demonstrate the reliability of our method for cognitive neuroscience research.
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30
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Lucas A, Mouchtaris S, Cornblath EJ, Sinha N, Caciagli L, Hadar P, Gugger JJ, Das S, Stein JM, Davis KA. Subcortical functional connectivity gradients in temporal lobe epilepsy. Neuroimage Clin 2023; 38:103418. [PMID: 37187042 PMCID: PMC10196948 DOI: 10.1016/j.nicl.2023.103418] [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: 01/21/2023] [Revised: 04/20/2023] [Accepted: 04/22/2023] [Indexed: 05/17/2023]
Abstract
BACKGROUND AND MOTIVATION Functional gradients have been used to study differences in connectivity between healthy and diseased brain states, however this work has largely focused on the cortex. Because the subcortex plays a key role in seizure initiation in temporal lobe epilepsy (TLE), subcortical functional-connectivity gradients may help further elucidate differences between healthy brains and TLE, as well as differences between left (L)-TLE and right (R)-TLE. METHODS In this work, we calculated subcortical functional-connectivity gradients (SFGs) from resting-state functional MRI (rs-fMRI) by measuring the similarity in connectivity profiles of subcortical voxels to cortical gray matter voxels. We performed this analysis in 24 R-TLE patients and 31 L-TLE patients (who were otherwise matched for age, gender, disease specific characteristics, and other clinical variables), and 16 controls. To measure differences in SFGs between L-TLE and R-TLE, we quantified deviations in the average functional gradient distributions, as well as their variance, across subcortical structures. RESULTS We found an expansion, measured by increased variance, in the principal SFG of TLE relative to controls. When comparing the gradient across subcortical structures between L-TLE and R-TLE, we found that abnormalities in the ipsilateral hippocampal gradient distributions were significantly different between L-TLE and R-TLE. CONCLUSION Our results suggest that expansion of the SFG is characteristic of TLE. Subcortical functional gradient differences exist between left and right TLE and are driven by connectivity changes in the hippocampus ipsilateral to the seizure onset zone.
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Affiliation(s)
- Alfredo Lucas
- Perelman School of Medicine, University of Pennsylvania, United States; Department of Bioengineering, University of Pennsylvania, United States.
| | - Sofia Mouchtaris
- Department of Bioengineering, University of Pennsylvania, United States
| | - Eli J Cornblath
- Department of Neurology, University of Pennsylvania, United States
| | - Nishant Sinha
- Department of Neurology, University of Pennsylvania, United States
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, United States
| | - Peter Hadar
- Department of Neurology, Massachusetts General Hospital, United States
| | - James J Gugger
- Department of Neurology, University of Pennsylvania, United States
| | - Sandhitsu Das
- Department of Neurology, University of Pennsylvania, United States
| | - Joel M Stein
- Department of Radiology, University of Pennsylvania, United States
| | - Kathryn A Davis
- Department of Neurology, University of Pennsylvania, United States
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31
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Veréb D, Mijalkov M, Chang YW, Canal-Garcia A, Gomez-Ruis E, Maass A, Villeneuve S, Volpe G, Pereira JB. Functional gradients of the medial parietal cortex in a healthy cohort with family history of sporadic Alzheimer's disease. Alzheimers Res Ther 2023; 15:82. [PMID: 37076873 PMCID: PMC10114342 DOI: 10.1186/s13195-023-01228-3] [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: 09/05/2022] [Accepted: 04/05/2023] [Indexed: 04/21/2023]
Abstract
BACKGROUND The medial parietal cortex is an early site of pathological protein deposition in Alzheimer's disease (AD). Previous studies have identified different subregions within this area; however, these subregions are often heterogeneous and disregard individual differences or subtle pathological alterations in the underlying functional architecture. To address this limitation, here we measured the continuous connectivity gradients of the medial parietal cortex and assessed their relationship with cerebrospinal fluid (CSF) biomarkers, ApoE ε4 carriership and memory in asymptomatic individuals at risk to develop AD. METHODS Two hundred sixty-three cognitively normal participants with a family history of sporadic AD who underwent resting-state and task-based functional MRI using encoding and retrieval tasks were included from the PREVENT-AD cohort. A novel method for characterizing spatially continuous patterns of functional connectivity was applied to estimate functional gradients in the medial parietal cortex during the resting-state and task-based conditions. This resulted in a set of nine parameters that described the appearance of the gradient across different spatial directions. We performed correlation analyses to assess whether these parameters were associated with CSF biomarkers of phosphorylated tau181 (p-tau), total tau (t-tau), and amyloid-ß1-42 (Aß). Then, we compared the spatial parameters between ApoE ε4 carriers and noncarriers, and evaluated the relationship between these parameters and memory. RESULTS Alterations involving the superior part of the medial parietal cortex, which was connected to regions of the default mode network, were associated with higher p-tau, t-tau levels as well as lower Aß/p-tau levels during the resting-state condition (p < 0.01). Similar alterations were found in ApoE ε4 carriers compared to non-carriers (p < 0.003). In contrast, lower immediate memory scores were associated with changes in the middle part of the medial parietal cortex, which was connected to inferior temporal and posterior parietal regions, during the encoding task (p = 0.001). No results were found when using conventional connectivity measures. CONCLUSIONS Functional alterations in the medial parietal gradients are associated with CSF AD biomarkers, ApoE ε4 carriership, and lower memory in an asymptomatic cohort with a family history of sporadic AD, suggesting that functional gradients are sensitive to subtle changes associated with early AD stages.
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Affiliation(s)
- Dániel Veréb
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden.
| | - Mite Mijalkov
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Yu-Wei Chang
- Department of Physics, Goteborg University, Goteborg, Sweden
| | - Anna Canal-Garcia
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | | | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), 39120, Magdeburg, Germany
| | - Sylvia Villeneuve
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Giovanni Volpe
- Department of Physics, Goteborg University, Goteborg, Sweden
| | - Joana B Pereira
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden.
- Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
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32
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Oldehinkel M, Tiego J, Sabaroedin K, Chopra S, Francey SM, O'Donoghue B, Cropley V, Nelson B, Graham J, Baldwin L, Yuen HP, Allott K, Alvarez-Jimenez M, Harrigan S, Pantelis C, Wood SJ, McGorry P, Bellgrove MA, Fornito A. Gradients of striatal function in antipsychotic-free first-episode psychosis and schizotypy. Transl Psychiatry 2023; 13:128. [PMID: 37072388 PMCID: PMC10113219 DOI: 10.1038/s41398-023-02417-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 03/20/2023] [Accepted: 03/27/2023] [Indexed: 04/20/2023] Open
Abstract
Both psychotic illness and subclinical psychosis-like experiences (PLEs) have been associated with cortico-striatal dysfunction. This work has largely relied on a discrete parcellation of the striatum into distinct functional areas, but recent evidence suggests that the striatum comprises multiple overlapping and smoothly varying gradients (i.e., modes) of functional organization. Here, we investigated two of these functional connectivity modes, previously associated with variations in the topographic patterning of cortico-striatal connectivity (first-order gradient), and dopaminergic innervation of the striatum (second-order gradient), and assessed continuities in striatal function from subclinical to clinical domains. We applied connectopic mapping to resting-state fMRI data to obtain the first-order and second-order striatal connectivity modes in two distinct samples: (1) 56 antipsychotic-free patients (26 females) with first-episode psychosis (FEP) and 27 healthy controls (17 females); and (2) a community-based cohort of 377 healthy individuals (213 females) comprehensively assessed for subclinical PLEs and schizotypy. The first-order "cortico-striatal" and second-order "dopaminergic" connectivity gradients were significantly different in FEP patients compared to controls bilaterally. In the independent sample of healthy individuals, variations in the left first-order "cortico-striatal" connectivity gradient were associated with inter-individual differences in a factor capturing general schizotypy and PLE severity. The presumed cortico-striatal connectivity gradient was implicated in both subclinical and clinical cohorts, suggesting that variations in its organization may represent a neurobiological trait marker across the psychosis continuum. Disruption of the presumed dopaminergic gradient was only noticeable in patients, suggesting that neurotransmitter dysfunction may be more apparent to clinical illness.
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Affiliation(s)
- Marianne Oldehinkel
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Australia.
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands.
| | - Jeggan Tiego
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Kristina Sabaroedin
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Shona M Francey
- Orygen Youth Health, Parkville, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | | | - Vanessa Cropley
- Orygen Youth Health, Parkville, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Barnaby Nelson
- Orygen Youth Health, Parkville, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | | | - Lara Baldwin
- Orygen Youth Health, Parkville, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | | | - Kelly Allott
- Orygen Youth Health, Parkville, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Mario Alvarez-Jimenez
- Orygen Youth Health, Parkville, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Susy Harrigan
- Department of Social Work, Monash University, Melbourne, Australia
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, Australia
| | - Stephen J Wood
- Orygen Youth Health, Parkville, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, Australia
- School of Psychology, University of Birmingham, Birmingham, UK
| | - Patrick McGorry
- Orygen Youth Health, Parkville, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, Australia
| | - Mark A Bellgrove
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Australia
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33
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Zhang X, Zang Z. Evaluate the efficacy and reliability of functional gradients in within-subject designs. Hum Brain Mapp 2023; 44:2336-2344. [PMID: 36661209 PMCID: PMC10028665 DOI: 10.1002/hbm.26213] [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: 09/20/2022] [Revised: 01/05/2023] [Accepted: 01/09/2023] [Indexed: 01/21/2023] Open
Abstract
The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain-general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions between different functional principles, and has been successively applied to investigate pathological conditions in between-group designs. What still lacking and urgently needed is the efficacy of this method to differentiate within-subject circumstances. In this study, we applied the diffusion embedding to eyes closed (EC) and eyes on (EO) resting-state conditions from 145 participants. We found significantly lower within-network dispersion of visual network (VN) (p = 7.3 × 10-4 ) as well as sensorimotor network (SMN) (p = 1 × 10-5 ) and between-network dispersion of VN (p = 2.3 × 10-4 ) under EC than EO, while frontoparietal network (p = 9.2 × 10-4 ) showed significantly higher between-network dispersion during EC than EO. Test-retest reliability analysis further displayed fair reliability (intraclass correlation coefficient [ICC] < 0.4) of the network dispersions (mean ICC = 0.116 ± 0.143 [standard deviation]) except for the within-network dispersion of SMN under EO (ICC = 0.407). And the reliability under EO was higher but not significantly higher than reliability under EC. Our study demonstrated that the diffusion embedding approach that shows fair reliability is capable of distinguishing EC and EO resting-state conditions, such that this method could be generalized to other within-subject designs.
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Affiliation(s)
- Xiaolong Zhang
- Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing, China
| | - Zhenxiang Zang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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34
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Lee CH, Park H, Lee MJ, Park BY. Whole-brain functional gradients reveal cortical and subcortical alterations in patients with episodic migraine. Hum Brain Mapp 2023; 44:2224-2233. [PMID: 36649309 PMCID: PMC10028679 DOI: 10.1002/hbm.26204] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 12/25/2022] [Accepted: 01/02/2023] [Indexed: 01/18/2023] Open
Abstract
Migraine is a type of headache with multiple neurological symptoms. Prior neuroimaging studies in patients with migraine based on functional magnetic resonance imaging have found regional as well as network-level alterations in brain function. Here, we expand on prior studies by establishing whole-brain functional connectivity patterns in patients with migraine using dimensionality reduction techniques. We studied functional brain connectivity in 50 patients with episodic migraine and sex- and age-matched healthy controls. Using dimensionality reduction techniques that project high-dimensional functional connectivity onto low-dimensional representations (i.e., eigenvectors), we found significant between-group differences in the eigenvectors between patients with migraine and healthy controls, particularly in the sensory/motor and limbic cortices. Furthermore, we assessed between-group differences in subcortical connectivity with subcortical weighted manifolds defined by subcortico-cortical connectivity multiplied by cortical eigenvectors and revealed significant alterations in the amygdala. Finally, leveraging supervised machine learning, we moderately predicted headache frequency using cortical and subcortical functional connectivity features, again indicating that sensory and limbic regions play a particularly important role in predicting migraine frequency. Our study confirmed that migraine is a hierarchical disease of the brain that shows alterations along the sensory-limbic axis, and therefore, the functional connectivity in these areas could be a useful marker to investigate migraine symptomatology.
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Affiliation(s)
- Chae Hyeon Lee
- Department of Statistics, Inha University, Incheon, Republic of Korea
| | - Hyunjin Park
- School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Mi Ji Lee
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Bo-Yong Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
- Department of Data Science, Inha University, Incheon, Republic of Korea
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35
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Katsumi Y, Zhang J, Chen D, Kamona N, Bunce JG, Hutchinson JB, Yarossi M, Tunik E, Dickerson BC, Quigley KS, Barrett LF. Correspondence of functional connectivity gradients across human isocortex, cerebellum, and hippocampus. Commun Biol 2023; 6:401. [PMID: 37046050 PMCID: PMC10097701 DOI: 10.1038/s42003-023-04796-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/03/2023] [Indexed: 04/14/2023] Open
Abstract
Gradient mapping is an important technique to summarize high dimensional biological features as low dimensional manifold representations in exploring brain structure-function relationships at various levels of the cerebral cortex. While recent studies have characterized the major gradients of functional connectivity in several brain structures using this technique, very few have systematically examined the correspondence of such gradients across structures under a common systems-level framework. Using resting-state functional magnetic resonance imaging, here we show that the organizing principles of the isocortex, and those of the cerebellum and hippocampus in relation to the isocortex, can be described using two common functional gradients. We suggest that the similarity in functional connectivity gradients across these structures can be meaningfully interpreted within a common computational framework based on the principles of predictive processing. The present results, and the specific hypotheses that they suggest, represent an important step toward an integrative account of brain function.
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Affiliation(s)
- Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
| | - Jiahe Zhang
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Danlei Chen
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Nada Kamona
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Jamie G Bunce
- Department of Biology, Northeastern University, Boston, MA, 02115, USA
| | | | - Mathew Yarossi
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, 02115, USA
- Department of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, Boston, MA, 02115, USA
| | - Eugene Tunik
- Department of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, Boston, MA, 02115, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Karen S Quigley
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
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36
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Ngo GN, Hori Y, Everling S, Menon RS. Joint-embeddings reveal functional differences in default-mode network architecture between marmosets and humans. Neuroimage 2023; 272:120035. [PMID: 36948281 DOI: 10.1016/j.neuroimage.2023.120035] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 12/30/2022] [Accepted: 03/14/2023] [Indexed: 03/24/2023] Open
Abstract
The default-mode network (DMN) is a distributed functional brain system integral for social and higher-order cognition in humans with implications in a myriad of neuropsychological disorders. In this study, we compared the functional architecture of the DMN between humans and marmosets to assess their similarities and differences using joint gradients. This approach permits simultaneous large-scale mapping of functional systems across the cortex of humans and marmosets, revealing evidence of putative homologies between them. In doing so, we find that the DMN architecture of the marmoset exhibits differences along its anterolateral-posterior axis. Specifically, the anterolateral node of the DMN (dorsolateral prefrontal cortex) displayed weak connections and inconsistent connection topographies as compared to its posterior DMN-nodes (posterior cingulate and posterior parietal cortices). We also present evidence that the marmoset medial prefrontal cortex and temporal lobe areas correspond to other macroscopical distributed functional systems that are not part of the DMN. Given the importance of the marmoset as a pre-clinical primate model for higher-order cognitive functioning and the DMN's relevance to cognition, our results suggest that the marmoset may lack the capacity to integrate neural information to subserve cortical dynamics that is necessary for supporting diverse cognitive demands.
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Affiliation(s)
- Geoffrey N Ngo
- Department of Medical Biophysics, University of Western Ontario, London, Ontario N6A 5C1, Canada
| | - Yuki Hori
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada; Department of Functional Brain Imaging, National Institutes of Quantum and Radiological Science and Technology, Chiba 263-8555, Japan
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada; Department of Physiology and Pharmacology, University of Western Ontario, London, Ontario N6A 5C1, Canada
| | - Ravi S Menon
- Department of Medical Biophysics, University of Western Ontario, London, Ontario N6A 5C1, Canada.; Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5B7, Canada.
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37
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Kong R, Tan YR, Wulan N, Ooi LQR, Farahibozorg SR, Harrison S, Bijsterbosch JD, Bernhardt BC, Eickhoff S, Yeo BTT. Comparison Between Gradients and Parcellations for Functional Connectivity Prediction of Behavior. Neuroimage 2023; 273:120044. [PMID: 36940760 DOI: 10.1016/j.neuroimage.2023.120044] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 03/15/2023] [Accepted: 03/17/2023] [Indexed: 03/23/2023] Open
Abstract
Resting-state functional connectivity (RSFC) is widely used to predict behavioral measures. To predict behavioral measures, representing RSFC with parcellations and gradients are the two most popular approaches. Here, we compare parcellation and gradient approaches for RSFC-based prediction of a broad range of behavioral measures in the Human Connectome Project (HCP) and Adolescent Brain Cognitive Development (ABCD) datasets. Among the parcellation approaches, we consider group-average "hard" parcellations (Schaefer et al., 2018), individual-specific "hard" parcellations (Kong et al., 2021a), and an individual-specific "soft" parcellation (spatial independent component analysis with dual regression; Beckmann et al., 2009). For gradient approaches, we consider the well-known principal gradients (Margulies et al., 2016) and the local gradient approach that detects local RSFC changes (Laumann et al., 2015). Across two regression algorithms, individual-specific hard-parcellation performs the best in the HCP dataset, while the principal gradients, spatial independent component analysis and group-average "hard" parcellations exhibit similar performance. On the other hand, principal gradients and all parcellation approaches perform similarly in the ABCD dataset. Across both datasets, local gradients perform the worst. Finally, we find that the principal gradient approach requires at least 40 to 60 gradients to perform as well as parcellation approaches. While most principal gradient studies utilize a single gradient, our results suggest that incorporating higher order gradients can provide significant behaviorally relevant information. Future work will consider the inclusion of additional parcellation and gradient approaches for comparison.
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Affiliation(s)
- Ru Kong
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
| | - Yan Rui Tan
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
| | - Naren Wulan
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
| | - Leon Qi Rong Ooi
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
| | - Seyedeh-Rezvan Farahibozorg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Samuel Harrison
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Janine D Bijsterbosch
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Simon Eickhoff
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Center Jülich, Jülich, Germany
| | - B T Thomas Yeo
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
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Nenning KH, Xu T, Franco AR, Swallow K, Tambini A, Margulies DS, Smallwood J, Colcombe SJ, Milham MP. Omnipresence of the sensorimotor-association axis topography in the human connectome. Neuroimage 2023; 272:120059. [PMID: 37001835 DOI: 10.1016/j.neuroimage.2023.120059] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/04/2023] [Accepted: 03/27/2023] [Indexed: 04/03/2023] Open
Abstract
Low-dimensional representations are increasingly used to study meaningful organizational principles within the human brain. Most notably, the sensorimotor-association axis consistently explains the most variance in the human connectome as its so-called principal gradient, suggesting that it represents a fundamental organizational principle. While recent work indicates these low dimensional representations are relatively robust, they are limited by modeling only certain aspects of the functional connectivity structure. To date, the majority of studies have restricted these approaches to the strongest connections in the brain, treating weaker or negative connections as noise despite evidence of meaningful structure among them. The present work examines connectivity gradients of the human connectome across a full range of connectivity strengths and explores the implications for outcomes of individual differences, identifying potential dependencies on thresholds and opportunities to improve prediction tasks. Interestingly, the sensorimotor-association axis emerged as the principal gradient of the human connectome across the entire range of connectivity levels. Moreover, the principal gradient of connections at intermediate strengths encoded individual differences, better followed individual-specific anatomical features, and was also more predictive of intelligence. Taken together, our results add to evidence of the sensorimotor-association axis as a fundamental principle of the brain's functional organization, since it is evident even in the connectivity structure of more lenient connectivity thresholds. These more loosely coupled connections further appear to contain valuable and potentially important information that could be used to improve our understanding of individual differences, diagnosis, and the prediction of treatment outcomes.
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Diveica V, Riedel MC, Salo T, Laird AR, Jackson RL, Binney RJ. Graded functional organisation in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.02.526818. [PMID: 36778322 PMCID: PMC9915604 DOI: 10.1101/2023.02.02.526818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The left inferior frontal gyrus (LIFG) has been ascribed key roles in numerous cognitive domains, including language, executive function and social cognition. However, its functional organisation, and how the specific areas implicated in these cognitive domains relate to each other, is unclear. Possibilities include that the LIFG underpins a domain-general function or, alternatively, that it is characterized by functional differentiation, which might occur in either a discrete or a graded pattern. The aim of the present study was to explore the topographical organisation of the LIFG using a bimodal data-driven approach. To this end, we extracted functional connectivity (FC) gradients from 1) the resting-state fMRI time-series of 150 participants (77 female), and 2) patterns of co-activation derived meta-analytically from task data across a diverse set of cognitive domains. We then sought to characterize the FC differences driving these gradients with seed-based resting-state FC and meta-analytic co-activation modelling analyses. Both analytic approaches converged on an FC profile that shifted in a graded fashion along two main organisational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior LIFG) to being more tightly coupled with perceptually-driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal LIFG), and with the semantic network, on the other (ventral). These results provide novel insights into a graded functional organisation of the LIFG underpinning both task-free and task-constrained mental states, and suggest that the LIFG is an interface between distinct large-scale functional networks.
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Affiliation(s)
- Veronica Diveica
- Cognitive Neuroscience Institute, Department of Psychology, School of Human and Behavioural Sciences, Bangor University, Wales, UK
| | - Michael C. Riedel
- Department of Physics, Florida International University, Miami, FL, USA
| | - Taylor Salo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Angela R. Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Rebecca L. Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, UK
| | - Richard J. Binney
- Cognitive Neuroscience Institute, Department of Psychology, School of Human and Behavioural Sciences, Bangor University, Wales, UK
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Lucas A, Mouchtaris S, Cornblath EJ, Sinha N, Caciagli L, Hadar P, Gugger JJ, Das S, Stein JM, Davis KA. Subcortical Functional Connectivity Gradients in Temporal Lobe Epilepsy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.08.23284313. [PMID: 36711498 PMCID: PMC9882434 DOI: 10.1101/2023.01.08.23284313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background and Motivation Functional gradients have been used to study differences in connectivity between healthy and diseased brain states, however this work has largely focused on the cortex. Because the subcortex plays a key role in seizure initiation in temporal lobe epilepsy (TLE), subcortical functional-connectivity gradients may help further elucidate differences between healthy brains and TLE, as well as differences between left (L)-TLE and right (R)-TLE. Methods In this work, we calculated subcortical functional-connectivity gradients (SFGs) from resting-state functional MRI (rs-fMRI) by measuring the similarity in connectivity profiles of subcortical voxels to cortical gray matter voxels. We performed this analysis in 23 R-TLE patients and 32 L-TLE patients (who were otherwise matched for age, gender, disease specific characteristics, and other clinical variables), and 16 controls. To measure differences in SFGs between L-TLE and R-TLE, we quantified deviations in the average functional gradient distributions, as well as their variance, across subcortical structures. Results We found an expansion, measured by increased variance, in the principal SFG of TLE relative to controls. When comparing the gradient across subcortical structures between L-TLE and R-TLE, we found that abnormalities in the ipsilateral hippocampal gradient distributions were significantly different between L-TLE and R-TLE. Conclusion Our results suggest that expansion of the SFG is characteristic of TLE. Subcortical functional gradient differences exist between left and right TLE and are driven by connectivity changes in the hippocampus ipsilateral to the seizure onset zone.
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Affiliation(s)
- Alfredo Lucas
- Perelman School of Medicine, University of Pennsylvania,Department of Bioengineering, University of Pennsylvania
| | | | | | | | | | - Peter Hadar
- Department of Neurology, Massachusetts General Hospital
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Loth E. Does the current state of biomarker discovery in autism reflect the limits of reductionism in precision medicine? Suggestions for an integrative approach that considers dynamic mechanisms between brain, body, and the social environment. Front Psychiatry 2023; 14:1085445. [PMID: 36911126 PMCID: PMC9992810 DOI: 10.3389/fpsyt.2023.1085445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 01/23/2023] [Indexed: 02/24/2023] Open
Abstract
Over the past decade, precision medicine has become one of the most influential approaches in biomedical research to improve early detection, diagnosis, and prognosis of clinical conditions and develop mechanism-based therapies tailored to individual characteristics using biomarkers. This perspective article first reviews the origins and concept of precision medicine approaches to autism and summarises recent findings from the first "generation" of biomarker studies. Multi-disciplinary research initiatives created substantially larger, comprehensively characterised cohorts, shifted the focus from group-comparisons to individual variability and subgroups, increased methodological rigour and advanced analytic innovations. However, although several candidate markers with probabilistic value have been identified, separate efforts to divide autism by molecular, brain structural/functional or cognitive markers have not identified a validated diagnostic subgroup. Conversely, studies of specific monogenic subgroups revealed substantial variability in biology and behaviour. The second part discusses both conceptual and methodological factors in these findings. It is argued that the predominant reductionist approach, which seeks to parse complex issues into simpler, more tractable units, let us to neglect the interactions between brain and body, and divorce individuals from their social environment. The third part draws on insights from systems biology, developmental psychology and neurodiversity approaches to outline an integrative approach that considers the dynamic interaction between biological (brain, body) and social mechanisms (stress, stigma) to understanding the origins of autistic features in particular conditions and contexts. This requires 1) closer collaboration with autistic people to increase face validity of concepts and methodologies; (2) development of measures/technologies that enable repeat assessment of social and biological factors in different (naturalistic) conditions and contexts, (3) new analytic methods to study (simulate) these interactions (including emergent properties), and (4) cross-condition designs to understand which mechanisms are transdiagnostic or specific for particular autistic sub-populations. Tailored support may entail both creating more favourable conditions in the social environment and interventions for some autistic people to increase well-being.
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Affiliation(s)
- Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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42
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Anticevic A, Halassa MM. The thalamus in psychosis spectrum disorder. Front Neurosci 2023; 17:1163600. [PMID: 37123374 PMCID: PMC10133512 DOI: 10.3389/fnins.2023.1163600] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 03/21/2023] [Indexed: 05/02/2023] Open
Abstract
Psychosis spectrum disorder (PSD) affects 1% of the world population and results in a lifetime of chronic disability, causing devastating personal and economic consequences. Developing new treatments for PSD remains a challenge, particularly those that target its core cognitive deficits. A key barrier to progress is the tenuous link between the basic neurobiological understanding of PSD and its clinical phenomenology. In this perspective, we focus on a key opportunity that combines innovations in non-invasive human neuroimaging with basic insights into thalamic regulation of functional cortical connectivity. The thalamus is an evolutionary conserved region that forms forebrain-wide functional loops critical for the transmission of external inputs as well as the construction and update of internal models. We discuss our perspective across four lines of evidence: First, we articulate how PSD symptomatology may arise from a faulty network organization at the macroscopic circuit level with the thalamus playing a central coordinating role. Second, we discuss how recent animal work has mechanistically clarified the properties of thalamic circuits relevant to regulating cortical dynamics and cognitive function more generally. Third, we present human neuroimaging evidence in support of thalamic alterations in PSD, and propose that a similar "thalamocortical dysconnectivity" seen in pharmacological imaging (under ketamine, LSD and THC) in healthy individuals may link this circuit phenotype to the common set of symptoms in idiopathic and drug-induced psychosis. Lastly, we synthesize animal and human work, and lay out a translational path for biomarker and therapeutic development.
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Affiliation(s)
- Alan Anticevic
- School of Medicine, Yale University, New Haven, CT, United States
- *Correspondence: Alan Anticevic,
| | - Michael M. Halassa
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA, United States
- Michael M. Halassa,
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Mulders PCR, van Eijndhoven PFP, van Oort J, Oldehinkel M, Duyser FA, Kist JD, Collard RM, Vrijsen JN, Haak KV, Beckmann CF, Tendolkar I, Marquand AF. Striatal connectopic maps link to functional domains across psychiatric disorders. Transl Psychiatry 2022; 12:513. [PMID: 36513630 PMCID: PMC9747785 DOI: 10.1038/s41398-022-02273-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 11/21/2022] [Accepted: 11/29/2022] [Indexed: 12/15/2022] Open
Abstract
Transdiagnostic approaches to psychiatry have significant potential in overcoming the limitations of conventional diagnostic paradigms. However, while frameworks such as the Research Domain Criteria have garnered significant enthusiasm among researchers and clinicians from a theoretical angle, examples of how such an approach might translate in practice to understand the biological mechanisms underlying complex patterns of behaviors in realistic and heterogeneous populations have been sparse. In a richly phenotyped clinical sample (n = 186) specifically designed to capture the complex nature of heterogeneity and comorbidity within- and between stress- and neurodevelopmental disorders, we use exploratory factor analysis on a wide range of clinical questionnaires to identify four stable functional domains that transcend diagnosis and relate to negative valence, cognition, social functioning and inhibition/arousal before replicating them in an independent dataset (n = 188). We then use connectopic mapping to map inter-individual variation in fine-grained topographical organization of functional connectivity in the striatum-a central hub in motor, cognitive, affective and reward-related brain circuits-and use multivariate machine learning (canonical correlation analysis) to show that these individualized topographic representations predict transdiagnostic functional domains out of sample (r = 0.20, p = 0.026). We propose that investigating psychiatric symptoms across disorders is a promising path to linking them to underlying biology, and can help bridge the gap between neuroscience and clinical psychiatry.
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Affiliation(s)
- Peter C. R. Mulders
- grid.10417.330000 0004 0444 9382Radboud university medical center, Department of Psychiatry, Nijmegen, The Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Philip F. P. van Eijndhoven
- grid.10417.330000 0004 0444 9382Radboud university medical center, Department of Psychiatry, Nijmegen, The Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Jasper van Oort
- grid.10417.330000 0004 0444 9382Radboud university medical center, Department of Psychiatry, Nijmegen, The Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Marianne Oldehinkel
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands ,grid.10417.330000 0004 0444 9382Department of Cognitive Neuroscience, Radboud university medical center Nijmegen, Nijmegen, The Netherlands
| | - Fleur A. Duyser
- grid.10417.330000 0004 0444 9382Radboud university medical center, Department of Psychiatry, Nijmegen, The Netherlands
| | - Josina D. Kist
- grid.10417.330000 0004 0444 9382Radboud university medical center, Department of Psychiatry, Nijmegen, The Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Rose M. Collard
- grid.10417.330000 0004 0444 9382Radboud university medical center, Department of Psychiatry, Nijmegen, The Netherlands
| | - Janna N. Vrijsen
- grid.10417.330000 0004 0444 9382Radboud university medical center, Department of Psychiatry, Nijmegen, The Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands ,grid.491369.00000 0004 0466 1666Depression Expertise Centre, Pro Persona Mental Health Care, Nijmegen, The Netherlands
| | - Koen V. Haak
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Christian F. Beckmann
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands ,grid.4991.50000 0004 1936 8948Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Indira Tendolkar
- grid.10417.330000 0004 0444 9382Radboud university medical center, Department of Psychiatry, Nijmegen, The Netherlands ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Andre F. Marquand
- grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
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Guell X. Functional Gradients of the Cerebellum: a Review of Practical Applications. CEREBELLUM (LONDON, ENGLAND) 2022; 21:1061-1072. [PMID: 34741753 PMCID: PMC9072599 DOI: 10.1007/s12311-021-01342-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/25/2021] [Indexed: 11/29/2022]
Abstract
Gradient-based analyses have contributed to the description of cerebellar functional neuroanatomy. More recently, functional gradients of the cerebellum have been used as a multi-purpose tool for neuroimaging research. Here, we provide an overview of the many practical applications of cerebellar functional gradient analyses. These practical applications include examination of intra-cerebellar and cerebellar-extracerebellar organization; transformation of functional gradients into parcellations with discrete borders; projection of functional gradients calculated within cerebellar structures to other extracerebellar structures; interpretation of cerebellar neuroimaging findings using qualitative and quantitative methods; detection of differences in patient populations; and other more complex practical applications of cerebellar gradient-based analyses. This review may serve as an introduction and catalog of options for neuroscientists who wish to design and analyze imaging studies using functional gradients of the cerebellum.
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Affiliation(s)
- Xavier Guell
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, MA, 20114, USA.
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research at MIT, Massachusetts Institute of Technology, Cambridge, MA, USA.
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Ruehl RM, Flanagin VL, Ophey L, Raiser TM, Seiderer K, Ertl M, Conrad J, Zu Eulenburg P. The human egomotion network. Neuroimage 2022; 264:119715. [PMID: 36334557 DOI: 10.1016/j.neuroimage.2022.119715] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 10/18/2022] [Accepted: 10/25/2022] [Indexed: 11/07/2022] Open
Abstract
All volitional movement in a three-dimensional space requires multisensory integration, in particular of visual and vestibular signals. Where and how the human brain processes and integrates self-motion signals remains enigmatic. Here, we applied visual and vestibular self-motion stimulation using fast and precise whole-brain neuroimaging to delineate and characterize the entire cortical and subcortical egomotion network in a substantial cohort (n=131). Our results identify a core egomotion network consisting of areas in the cingulate sulcus (CSv, PcM/pCi), the cerebellum (uvula), and the temporo-parietal cortex including area VPS and an unnamed region in the supramarginal gyrus. Based on its cerebral connectivity pattern and anatomical localization, we propose that this region represents the human homologue of macaque area 7a. Whole-brain connectivity and gradient analyses imply an essential role of the connections between the cingulate sulcus and the cerebellar uvula in egomotion perception. This could be via feedback loops involved updating visuo-spatial and vestibular information. The unique functional connectivity patterns of PcM/pCi hint at central role in multisensory integration essential for the perception of self-referential spatial awareness. All cortical egomotion hubs showed modular functional connectivity with other visual, vestibular, somatosensory and higher order motor areas, underlining their mutual function in general sensorimotor integration.
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Affiliation(s)
- Ria Maxine Ruehl
- Department of Neurology, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany; German Center for Vertigo and Balance Disorders, IFB-LMU, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany.
| | - Virginia L Flanagin
- Department of Neurology, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany; German Center for Vertigo and Balance Disorders, IFB-LMU, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany; Graduate School of Systemic Neurosciences, Department of Biology II and Neurobiology, Großhaderner Str. 2, 82151 Planegg-Martinsried, Ludwig-Maximilians-University Munich, Germany
| | - Leoni Ophey
- German Center for Vertigo and Balance Disorders, IFB-LMU, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany
| | - Theresa Marie Raiser
- Department of Neurology, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany; German Center for Vertigo and Balance Disorders, IFB-LMU, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany
| | - Katharina Seiderer
- German Center for Vertigo and Balance Disorders, IFB-LMU, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany
| | - Matthias Ertl
- Institute of Psychology and Inselspital, Fabrikstrasse 8, 3012 Bern, University of Bern, Switzerland
| | - Julian Conrad
- Department of Neurology, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany; German Center for Vertigo and Balance Disorders, IFB-LMU, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany; Department of Neurology, Theodor-Kutze Ufer 1-3, 68167 Mannheim, Medical Faculty Mannheim, University of Heidelberg, Germany
| | - Peter Zu Eulenburg
- German Center for Vertigo and Balance Disorders, IFB-LMU, University Hospital Munich, Ludwig-Maximilians-University Munich, Marchionini Str. 15, 81377 Munich, Germany; Graduate School of Systemic Neurosciences, Department of Biology II and Neurobiology, Großhaderner Str. 2, 82151 Planegg-Martinsried, Ludwig-Maximilians-University Munich, Germany; Institute for Neuroradiology, University Hospital Munich, Marchionini Str. 15, 81377 Munich, Ludwig-Maximilians-University Munich, Germany
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Brown JA, Lee AJ, Pasquini L, Seeley WW. A dynamic gradient architecture generates brain activity states. Neuroimage 2022; 261:119526. [PMID: 35914669 PMCID: PMC9585924 DOI: 10.1016/j.neuroimage.2022.119526] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 07/26/2022] [Accepted: 07/28/2022] [Indexed: 11/24/2022] Open
Abstract
The human brain exhibits a diverse yet constrained range of activity states. While these states can be faithfully represented in a low-dimensional latent space, our understanding of the constitutive functional anatomy is still evolving. Here we applied dimensionality reduction to task-free and task fMRI data to address whether latent dimensions reflect intrinsic systems and if so, how these systems may interact to generate different activity states. We find that each dimension represents a dynamic activity gradient, including a primary unipolar sensory-association gradient underlying the global signal. The gradients appear stable across individuals and cognitive states, while recapitulating key functional connectivity properties including anticorrelation, modularity, and regional hubness. We then use dynamical systems modeling to show that gradients causally interact via state-specific coupling parameters to create distinct brain activity patterns. Together, these findings indicate that a set of dynamic, intrinsic spatial gradients interact to determine the repertoire of possible brain activity states.
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Affiliation(s)
- Jesse A Brown
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA.
| | - Alex J Lee
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Lorenzo Pasquini
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - William W Seeley
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
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Zhao Y, Gao Y, Li M, Anderson AW, Ding Z, Gore JC. Functional Parcellation of Human Brain Using Localized Topo-Connectivity Mapping. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:2670-2680. [PMID: 35442885 PMCID: PMC9844109 DOI: 10.1109/tmi.2022.3168888] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The analysis of connectivity between parcellated regions of cortex provides insights into the functional architecture of the brain at a systems level. However, the derivation of functional structures from voxel-wise analyses at finer scales remains a challenge. We propose a novel method, called localized topo-connectivity mapping with singular-value-decomposition-informed filtering (or filtered LTM), to identify and characterize voxel-wise functional structures in the human brain from resting-state fMRI data. Here we describe its mathematical formulation and provide a proof-of-concept using simulated data that allow an intuitive interpretation of the results of filtered LTM. The algorithm has also been applied to 7T fMRI data acquired as part of the Human Connectome Project to generate group-average LTM images. Generally, most of the functional structures revealed by LTM images agree in the boundaries with anatomical structures identified by T1-weighted images and fractional anisotropy maps derived from diffusion MRI. In addition, the LTM images also reveal subtle functional variations that are not apparent in the anatomical structures. To assess the performance of LTM images, the subcortical region and occipital white matter were separately parcellated. Statistical tests were performed to demonstrate that the synchronies of fMRI signals in LTM-derived functional parcels are significantly larger than those with geometric perturbations. Overall, the filtered LTM approach can serve as a tool to investigate the functional organization of the brain at the scale of individual voxels as measured in fMRI.
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An evaluation of how connectopic mapping reveals visual field maps in V1. Sci Rep 2022; 12:16249. [PMID: 36171242 PMCID: PMC9519585 DOI: 10.1038/s41598-022-20322-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 09/09/2022] [Indexed: 11/25/2022] Open
Abstract
Abstract Functional gradients, in which response properties change gradually across the cortical surface, have been proposed as a key organising principle of the brain. However, the presence of these gradients remains undetermined in many brain regions. Resting-state neuroimaging studies have suggested these gradients can be reconstructed from patterns of functional connectivity. Here we investigate the accuracy of these reconstructions and establish whether it is connectivity or the functional properties within a region that determine these “connectopic maps”. Different manifold learning techniques were used to recover visual field maps while participants were at rest or engaged in natural viewing. We benchmarked these reconstructions against maps measured by traditional visual field mapping. We report an initial exploratory experiment of a publicly available naturalistic imaging dataset, followed by a preregistered replication using larger resting-state and naturalistic imaging datasets from the Human Connectome Project. Connectopic mapping accurately predicted visual field maps in primary visual cortex, with better predictions for eccentricity than polar angle maps. Non-linear manifold learning methods outperformed simpler linear embeddings. We also found more accurate predictions during natural viewing compared to resting-state. Varying the source of the connectivity estimates had minimal impact on the connectopic maps, suggesting the key factor is the functional topography within a brain region. The application of these standardised methods for connectopic mapping will allow the discovery of functional gradients across the brain. Protocol registration The stage 1 protocol for this Registered Report was accepted in
principle on 19 April 2022. The protocol, as accepted by the journal, can be found at 10.6084/m9.figshare.19771717.
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Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology. Commun Biol 2022; 5:1024. [PMID: 36168040 PMCID: PMC9515219 DOI: 10.1038/s42003-022-03963-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 09/07/2022] [Indexed: 02/06/2023] Open
Abstract
It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability.
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O'Rawe JF, Leung HC. Topographic organization of the human caudate functional connectivity and age-related changes with resting-state fMRI. Front Syst Neurosci 2022; 16:966433. [PMID: 36211593 PMCID: PMC9543452 DOI: 10.3389/fnsys.2022.966433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 08/30/2022] [Indexed: 11/30/2022] Open
Abstract
The striatum is postulated to play a central role in gating cortical processing during goal-oriented behavior. While many human neuroimaging studies have treated the striatum as an undivided whole or several homogeneous compartments, some recent studies showed that its circuitry is topographically organized and has more complex relations with the cortical networks than previously assumed. Here, we took a gradient functional connectivity mapping approach that utilizes the entire anatomical space of the caudate nucleus to examine the organization of its functional relationship with the rest of the brain and how its topographic mapping changes with age. We defined the topography of the caudate functional connectivity using three publicly available resting-state fMRI datasets. We replicated and extended previous findings. First, we found two stable gradients of caudate connectivity patterns along its medial-lateral (M-L) and anterior-posterior (A-P) axes, supporting findings from previous tract-tracing studies of non-human primates that there are at least two main organizational principles within the caudate nucleus. Second, unlike previous emphasis of the A-P topology, we showed that the differential connectivity patterns along the M-L gradient of caudate are more clearly organized with the large-scale neural networks; such that brain networks associated with internal vs. external orienting behavior are respectively more closely linked to the medial vs. lateral extent of the caudate. Third, the caudate's M-L organization showed greater age-related reduction in integrity, which was further associated with age-related changes in behavioral measures of executive functions. In sum, our analysis confirmed a sometimes overlooked M-L functional connectivity gradient within the caudate nucleus, with its lateral longitudinal zone more closely linked to the frontoparietal cortical circuits and age-related changes in cognitive control. These findings provide a more precise mapping of the human caudate functional connectivity, both in terms of the gradient organization with cortical networks and age-related changes in such organization.
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Affiliation(s)
- Jonathan F. O'Rawe
- Integrative Neuroscience Program, Department of Psychology, Stony Brook University, Stony Brook, NY, United States
- National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD, United States
- *Correspondence: Hoi-Chung Leung
| | - Hoi-Chung Leung
- National Institute of Mental Health Intramural Program, National Institutes of Health, Bethesda, MD, United States
- Jonathan F. O'Rawe jonathan.o'
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