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Kosakowski HL, Saadon-Grosman N, Du J, Eldaief MC, Buckner RL. Human striatal association megaclusters. J Neurophysiol 2024; 131:1083-1100. [PMID: 38505898 DOI: 10.1152/jn.00387.2023] [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: 10/19/2023] [Revised: 03/13/2024] [Accepted: 03/13/2024] [Indexed: 03/21/2024] Open
Abstract
The striatum receives projections from multiple regions of the cerebral cortex consistent with the role of the basal ganglia in diverse motor, affective, and cognitive functions. Within the striatum, the caudate receives projections from association cortex, including multiple distinct regions of prefrontal cortex. Building on recent insights about the details of how juxtaposed cortical networks are specialized for distinct aspects of higher-order cognition, we revisited caudate organization using within-individual precision neuroimaging initially in two intensively scanned individuals (each scanned 31 times). Results revealed that the caudate has side-by-side regions that are coupled to at least five distinct distributed association networks, paralleling the organization observed in the cerebral cortex. We refer to these spatial groupings of regions as striatal association megaclusters. Correlation maps from closely juxtaposed seed regions placed within the megaclusters recapitulated the five distinct cortical networks, including their multiple spatially distributed regions. Striatal association megaclusters were explored in 15 additional participants (each scanned at least 8 times), finding that their presence generalizes to new participants. Analysis of the laterality of the regions within the megaclusters further revealed that they possess asymmetries paralleling their cortical counterparts. For example, caudate regions linked to the language network were left lateralized. These results extend the general notion of parallel specialized basal ganglia circuits with the additional discovery that, even within the caudate, there is fine-grained separation of multiple distinct higher-order networks that reflects the organization and lateralization found in the cerebral cortex.NEW & NOTEWORTHY An individualized precision neuroimaging approach reveals juxtaposed zones of the caudate that are coupled with five distinct networks in association cortex. The organization of these caudate zones recapitulates organization observed in the cerebral cortex and extends the notion of specialized basal ganglia circuits.
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Affiliation(s)
- Heather L Kosakowski
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
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2
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Du J, DiNicola LM, Angeli PA, Saadon-Grosman N, Sun W, Kaiser S, Ladopoulou J, Xue A, Yeo BTT, Eldaief MC, Buckner RL. Organization of the human cerebral cortex estimated within individuals: networks, global topography, and function. J Neurophysiol 2024; 131:1014-1082. [PMID: 38489238 DOI: 10.1152/jn.00308.2023] [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: 08/16/2023] [Revised: 01/18/2024] [Accepted: 02/16/2024] [Indexed: 03/17/2024] Open
Abstract
The cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks from functional MRI (fMRI) data in intensively sampled participants. The procedure was developed in two participants (scanned 31 times) and then prospectively applied to 15 participants (scanned 8-11 times). Analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that linked to distant regions. Third-order networks possessed regions distributed widely throughout association cortex. Regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated across multiple cortical zones. We refer to these as supra-areal association megaclusters (SAAMs). Within each SAAM, two candidate control regions were adjacent to three separate domain-specialized regions. Response properties were explored with task data. The somatomotor and visual networks responded to body movements and visual stimulation, respectively. Second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions dissociated across language, social, and spatial/episodic processing domains. These results suggest that progressively higher-order networks nest outward from primary sensory and motor cortices. Within the apex zones of association cortex, there is specialization that repeatedly divides domain-flexible from domain-specialized regions. We discuss implications of these findings, including how repeating organizational motifs may emerge during development.NEW & NOTEWORTHY The organization of cerebral networks was estimated within individuals with intensive, repeat sampling of fMRI data. A hierarchical organization emerged in each individual that delineated first-, second-, and third-order cortical networks. Regions of distinct third-order association networks consistently exhibited side-by-side juxtapositions that repeated across multiple cortical zones, with clear and robust functional specialization among the embedded regions.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Peter A Angeli
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Wendy Sun
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Stephanie Kaiser
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Joanna Ladopoulou
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Aihuiping Xue
- Centre for Sleep & Cognition and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - B T Thomas Yeo
- Centre for Sleep & Cognition and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
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3
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Koslov SR, Kable JW, Foster BL. Dissociable Contributions of the Medial Parietal Cortex to Recognition Memory. J Neurosci 2024; 44:e2220232024. [PMID: 38527809 PMCID: PMC11063824 DOI: 10.1523/jneurosci.2220-23.2024] [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: 11/28/2023] [Revised: 03/04/2024] [Accepted: 03/15/2024] [Indexed: 03/27/2024] Open
Abstract
Human neuroimaging studies of episodic memory retrieval routinely observe the engagement of specific cortical regions beyond the medial temporal lobe. Of these, medial parietal cortex (MPC) is of particular interest given its distinct functional characteristics during different retrieval tasks. Specifically, while recognition and autobiographical recall tasks are both used to probe episodic retrieval, these paradigms consistently drive distinct spatial patterns of response within MPC. However, other studies have emphasized alternate MPC functional dissociations in terms of brain network connectivity profiles or stimulus category selectivity. As the unique contributions of MPC to episodic memory remain unclear, adjudicating between these different accounts can provide better consensus regarding MPC function. Therefore, we used a precision-neuroimaging dataset (7T functional magnetic resonance imaging) to examine how MPC regions are differentially engaged during recognition memory and how these task-related dissociations may also reflect distinct connectivity and stimulus category functional profiles. We observed interleaved, though spatially distinct, subregions of MPC where responses were sensitive to either recognition decisions or the semantic representation of stimuli. In addition, this dissociation was further accentuated by functional subregions displaying distinct profiles of connectivity with the hippocampus during task and rest. Finally, we show that recent observations of dissociable person and place selectivity within the MPC reflect category-specific responses from within identified semantic regions that are sensitive to mnemonic demands. Together, by examining precision functional mapping within individuals, these data suggest that previously distinct observations of functional dissociation within MPC conform to a common principle of organization throughout hippocampal-neocortical memory systems.
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Affiliation(s)
- Seth R Koslov
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Joseph W Kable
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Brett L Foster
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
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4
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Hermosillo RJM, Moore LA, Feczko E, Miranda-Domínguez Ó, Pines A, Dworetsky A, Conan G, Mooney MA, Randolph A, Graham A, Adeyemo B, Earl E, Perrone A, Carrasco CM, Uriarte-Lopez J, Snider K, Doyle O, Cordova M, Koirala S, Grimsrud GJ, Byington N, Nelson SM, Gratton C, Petersen S, Feldstein Ewing SW, Nagel BJ, Dosenbach NUF, Satterthwaite TD, Fair DA. A precision functional atlas of personalized network topography and probabilities. Nat Neurosci 2024; 27:1000-1013. [PMID: 38532024 PMCID: PMC11089006 DOI: 10.1038/s41593-024-01596-5] [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: 02/14/2022] [Accepted: 02/08/2024] [Indexed: 03/28/2024]
Abstract
Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.
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Affiliation(s)
- Robert J M Hermosillo
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA.
| | - Lucille A Moore
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Óscar Miranda-Domínguez
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Adam Pines
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Ally Dworetsky
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Gregory Conan
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Michael A Mooney
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
- Center for Mental Health Innovation, Oregon Health and Science University, Portland, OR, USA
| | - Anita Randolph
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Alice Graham
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric Earl
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Cristian Morales Carrasco
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | | | - Kathy Snider
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Olivia Doyle
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Michaela Cordova
- Joint Doctoral Program in Clinical Psychology, San Diego State University, San Diego, CA, USA
- Joint Doctoral Program in Clinical Psychology, University of California San Diego, San Diego, CA, USA
| | - Sanju Koirala
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Gracie J Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Steven M Nelson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Steven Petersen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Bonnie J Nagel
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
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5
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Roalf DR, Figee M, Oathes DJ. Elevating the field for applying neuroimaging to individual patients in psychiatry. Transl Psychiatry 2024; 14:87. [PMID: 38341414 PMCID: PMC10858949 DOI: 10.1038/s41398-024-02781-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 12/06/2023] [Accepted: 01/15/2024] [Indexed: 02/12/2024] Open
Abstract
Although neuroimaging has been widely applied in psychiatry, much of the exuberance in decades past has been tempered by failed replications and a lack of definitive evidence to support the utility of imaging to inform clinical decisions. There are multiple promising ways forward to demonstrate the relevance of neuroimaging for psychiatry at the individual patient level. Ultra-high field magnetic resonance imaging is developing as a sensitive measure of neurometabolic processes of particular relevance that holds promise as a new way to characterize patient abnormalities as well as variability in response to treatment. Neuroimaging may also be particularly suited to the science of brain stimulation interventions in psychiatry given that imaging can both inform brain targeting as well as measure changes in brain circuit communication as a function of how effectively interventions improve symptoms. We argue that a greater focus on individual patient imaging data will pave the way to stronger relevance to clinical care in psychiatry. We also stress the importance of using imaging in symptom-relevant experimental manipulations and how relevance will be best demonstrated by pairing imaging with differential treatment prediction and outcome measurement. The priorities for using brain imaging to inform psychiatry may be shifting, which compels the field to solidify clinical relevance for individual patients over exploratory associations and biomarkers that ultimately fail to replicate.
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Affiliation(s)
- David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Neurodevelopment & Psychosis Section, University of Pennsylvania, Philadelphia, PA, USA
| | - Martijn Figee
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Desmond J Oathes
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Center for Brain Imaging and Stimulation, University of Pennsylvania, Philadelphia, PA, USA.
- Center for Neuromodulation in Depression and Stress, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Brain Science Translation, Innovation, and Modulation Center, University of Pennsylvania, Philadelphia, PA, USA.
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6
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Assem M, Shashidhara S, Glasser MF, Duncan J. Basis of executive functions in fine-grained architecture of cortical and subcortical human brain networks. Cereb Cortex 2024; 34:bhad537. [PMID: 38244562 PMCID: PMC10839840 DOI: 10.1093/cercor/bhad537] [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: 09/25/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/22/2024] Open
Abstract
Theoretical models suggest that executive functions rely on both domain-general and domain-specific processes. Supporting this view, prior brain imaging studies have revealed that executive activations converge and diverge within broadly characterized brain networks. However, the lack of precise anatomical mappings has impeded our understanding of the interplay between domain-general and domain-specific processes. To address this challenge, we used the high-resolution multimodal magnetic resonance imaging approach of the Human Connectome Project to scan participants performing 3 canonical executive tasks: n-back, rule switching, and stop signal. The results reveal that, at the individual level, different executive activations converge within 9 domain-general territories distributed in frontal, parietal, and temporal cortices. Each task exhibits a unique topography characterized by finely detailed activation gradients within domain-general territory shifted toward adjacent resting-state networks; n-back activations shift toward the default mode, rule switching toward dorsal attention, and stop signal toward cingulo-opercular networks. Importantly, the strongest activations arise at multimodal neurobiological definitions of network borders. Matching results are seen in circumscribed regions of the caudate nucleus, thalamus, and cerebellum. The shifting peaks of local gradients at the intersection of task-specific networks provide a novel mechanistic insight into how partially-specialized networks interact with neighboring domain-general territories to generate distinct executive functions.
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Affiliation(s)
- Moataz Assem
- MRC Cognition and Brain Sciences Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 7EF, United Kingdom
| | - Sneha Shashidhara
- MRC Cognition and Brain Sciences Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 7EF, United Kingdom
- Psychology Department, Ashoka University, Sonipat, 131029, India
| | - Matthew F Glasser
- Department of Radiology, Washington University in St. Louis, Saint Louis, MO, 63110, United States
- Department of Neuroscience, Washington University in St. Louis, Saint Louis, MO, 63110, United States
| | - John Duncan
- MRC Cognition and Brain Sciences Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 7EF, United Kingdom
- Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, United Kingdom
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7
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Kucyi A, Anderson N, Bounyarith T, Braun D, Shareef-Trudeau L, Treves I, Braga RM, Hsieh PJ, Hung SM. Individual variability in neural representations of mind-wandering. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576471. [PMID: 38328109 PMCID: PMC10849545 DOI: 10.1101/2024.01.20.576471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population-rather than individual-based inferences due to limited within-individual sampling. Here, three densely-sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely-sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously-unrecognized inter-individual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.
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8
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Barnett AJ, Nguyen M, Spargo J, Yadav R, Cohn-Sheehy BI, Ranganath C. Hippocampal-cortical interactions during event boundaries support retention of complex narrative events. Neuron 2024; 112:319-330.e7. [PMID: 37944517 DOI: 10.1016/j.neuron.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: 11/02/2022] [Revised: 05/31/2023] [Accepted: 10/08/2023] [Indexed: 11/12/2023]
Abstract
According to most memory theories, encoding involves continuous communication between the hippocampus and neocortex, but recent work has shown that key moments at the end of an event, called event boundaries, may be especially critical for memory formation. We sought to determine how communication between the hippocampus and neocortical regions during the encoding of naturalistic events related to subsequent retrieval of those events and whether this was particularly important at event boundaries. Participants encoded and recalled two cartoon movies during fMRI scanning. Higher functional connectivity between the hippocampus and the posterior medial network (PMN) at an event's offset is related to the subsequent successful recall of that event. Furthermore, hippocampal-PMN offset connectivity also predicted the amount of detail retrieved after a 2-day delay. These data demonstrate that the relationship between memory encoding and hippocampal-neocortical interaction is dynamic and biased toward boundaries.
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Affiliation(s)
| | - Mitchell Nguyen
- University of California, Davis, Center for Neuroscience, Davis, CA, USA
| | - James Spargo
- University of California, Davis, Department of Psychology, Davis, CA, USA
| | - Reesha Yadav
- University of California, Davis, Department of Psychology, Davis, CA, USA
| | | | - Charan Ranganath
- University of California, Davis, Center for Neuroscience, Davis, CA, USA; University of California, Davis, Department of Psychology, Davis, CA, USA
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9
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Roseman M, Elias U, Kletenik I, Ferguson MA, Fox MD, Horowitz Z, Marshall GA, Spiers HJ, Arzy S. A neural circuit for spatial orientation derived from brain lesions. Cereb Cortex 2024; 34:bhad486. [PMID: 38100330 PMCID: PMC10793567 DOI: 10.1093/cercor/bhad486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 11/27/2023] [Accepted: 11/27/2023] [Indexed: 12/17/2023] Open
Abstract
There is disagreement regarding the major components of the brain network supporting spatial cognition. To address this issue, we applied a lesion mapping approach to the clinical phenomenon of topographical disorientation. Topographical disorientation is the inability to maintain accurate knowledge about the physical environment and use it for navigation. A review of published topographical disorientation cases identified 65 different lesion sites. Our lesion mapping analysis yielded a topographical disorientation brain map encompassing the classic regions of the navigation network: medial parietal, medial temporal, and temporo-parietal cortices. We also identified a ventromedial region of the prefrontal cortex, which has been absent from prior descriptions of this network. Moreover, we revealed that the regions mapped are correlated with the Default Mode Network sub-network C. Taken together, this study provides causal evidence for the distribution of the spatial cognitive system, demarking the major components and identifying novel regions.
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Affiliation(s)
- Moshe Roseman
- Neuropsychiatry Lab, Department of Medical Neurosciences, Faculty of Medicine, Hadassah Ein Kerem Campus, Hebrew University of Jerusalem, Jerusalem 9112001, Israel
| | - Uri Elias
- Neuropsychiatry Lab, Department of Medical Neurosciences, Faculty of Medicine, Hadassah Ein Kerem Campus, Hebrew University of Jerusalem, Jerusalem 9112001, Israel
| | - Isaiah Kletenik
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham & Women’s Hospital, Boston, MA 02115, United States
- Harvard Medical School, Boston, MA 02115, United States
- Division of Cognitive and Behavioral Neurology, Department of Neurology, Brigham and Women’s Hospital, Boston, MA 02115, United States
| | - Michael A Ferguson
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham & Women’s Hospital, Boston, MA 02115, United States
- Harvard Medical School, Boston, MA 02115, United States
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham & Women’s Hospital, Boston, MA 02115, United States
- Harvard Medical School, Boston, MA 02115, United States
| | - Zalman Horowitz
- Neuropsychiatry Lab, Department of Medical Neurosciences, Faculty of Medicine, Hadassah Ein Kerem Campus, Hebrew University of Jerusalem, Jerusalem 9112001, Israel
| | - Gad A Marshall
- Harvard Medical School, Boston, MA 02115, United States
- Division of Cognitive and Behavioral Neurology, Department of Neurology, Brigham and Women’s Hospital, Boston, MA 02115, United States
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, MA 02115, United States
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Hugo J Spiers
- Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, United Kingdom
| | - Shahar Arzy
- Neuropsychiatry Lab, Department of Medical Neurosciences, Faculty of Medicine, Hadassah Ein Kerem Campus, Hebrew University of Jerusalem, Jerusalem 9112001, Israel
- Department of Neurology, Hadassah Hebrew University Medical School, Jerusalem 9112001, Israel
- Department of Brain and Cognitive Sciences, Hebrew University of Jerusalem, Jerusalem 9190501, Israel
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10
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Edmonds D, Salvo JJ, Anderson N, Lakshman M, Yang Q, Kay K, Zelano C, Braga RM. Social cognitive regions of human association cortex are selectively connected to the amygdala. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.06.570477. [PMID: 38106046 PMCID: PMC10723387 DOI: 10.1101/2023.12.06.570477] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Reasoning about someone's thoughts and intentions - i.e., forming a theory of mind - is an important aspect of social cognition that relies on association areas of the brain that have expanded disproportionately in the human lineage. We recently showed that these association zones comprise parallel distributed networks that, despite occupying adjacent and interdigitated regions, serve dissociable functions. One network is selectively recruited by theory of mind processes. What circuit properties differentiate these parallel networks? Here, we show that social cognitive association areas are intrinsically and selectively connected to regions of the anterior medial temporal lobe that are implicated in emotional learning and social behaviors, including the amygdala at or near the basolateral complex and medial nucleus. The results suggest that social cognitive functions emerge through coordinated activity between amygdala circuits and a distributed association network, and indicate the medial nucleus may play an important role in social cognition in humans.
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Affiliation(s)
- Donnisa Edmonds
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Joseph J. Salvo
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Nathan Anderson
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Maya Lakshman
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Qiaohan Yang
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Kendrick Kay
- Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Christina Zelano
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Rodrigo M. Braga
- Department of Neurology, Northwestern University, Chicago, IL, USA
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11
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Angeli PA, DiNicola LM, Saadon-Grosman N, Eldaief MC, Buckner RL. Specialization of the Human Hippocampal Long Axis Revisited. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.19.572264. [PMID: 38187548 PMCID: PMC10769203 DOI: 10.1101/2023.12.19.572264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
The hippocampus possesses anatomical differences along its long axis. Here the functional specialization of the human hippocampal long axis was explored using network-anchored precision functional MRI (N = 11) paired with behavioral analyses (N=266). Functional connectivity analyses demonstrated that the anterior hippocampus was preferentially correlated with a cerebral network associated with remembering, while the posterior hippocampus was correlated with a distinct network associated with behavioral salience. Seed regions placed within the hippocampus recapitulated the distinct cerebral networks. Functional characterization using task data within the same intensively sampled individuals discovered a functional double dissociation between the anterior and posterior hippocampal regions. The anterior hippocampal region was sensitive to remembering and imagining the future, specifically tracking the process of scene construction, while the posterior hippocampal region displayed transient responses to targets in an oddball detection task and to transitions between task blocks. These findings suggest specialization along the long axis of the hippocampus with differential responses reflecting the functional properties of the partner cerebral networks.
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Affiliation(s)
- Peter A Angeli
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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12
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Saadon-Grosman N, Du J, Kosakowski HL, Angeli PA, DiNicola LM, Eldaief MC, Buckner RL. Within-Individual Organization of the Human Cognitive Cerebellum: Evidence for Closely Juxtaposed, Functionally Specialized Regions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.18.572062. [PMID: 38187706 PMCID: PMC10769291 DOI: 10.1101/2023.12.18.572062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
The human cerebellum possesses multiple regions linked to cerebral association cortex. Here we mapped the cerebellum using precision functional MRI within individual participants (N=15), first estimating regions using connectivity and then prospectively testing functional properties using independent task data. Network estimates in all participants revealed a Crus I / II cerebellar megacluster of five higher-order association networks often with multiple, discontinuous regions for the same network. Seed regions placed within the megaclusters, including the disjointed regions, yielded spatially selective networks in the cerebral cortex. Compelling evidence for functional specialization within the cerebellar megaclusters emerged from the task responses. Reflecting functional distinctions found in the cerebrum, domain-flexible cerebellar regions involved in cognitive control dissociated from distinct domain-specialized regions with differential responses to language, social, and spatial / episodic task demands. These findings provide a clear demonstration that the cerebellum encompasses multiple zones dedicated to cognition, featuring juxtaposed regions specialized for distinct processing domains.
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Affiliation(s)
- Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Heather L Kosakowski
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Peter A Angeli
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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13
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DiNicola LM, Sun W, Buckner RL. Side-by-side regions in dorsolateral prefrontal cortex estimated within the individual respond differentially to domain-specific and domain-flexible processes. J Neurophysiol 2023; 130:1602-1615. [PMID: 37937340 PMCID: PMC11068361 DOI: 10.1152/jn.00277.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/06/2023] [Accepted: 10/28/2023] [Indexed: 11/09/2023] Open
Abstract
A recurring debate concerns whether regions of primate prefrontal cortex (PFC) support domain-flexible or domain-specific processes. Here we tested the hypothesis with functional MRI (fMRI) that side-by-side PFC regions, within distinct parallel association networks, differentially support domain-flexible and domain-specialized processing. Individuals (N = 9) were intensively sampled, and all effects were estimated within their own idiosyncratic anatomy. Within each individual, we identified PFC regions linked to distinct networks, including a dorsolateral PFC (DLPFC) region coupled to the medial temporal lobe (MTL) and an extended region associated with the canonical multiple-demand network. We further identified an inferior PFC region coupled to the language network. Exploration in separate task data, collected within the same individuals, revealed a robust functional triple dissociation. The DLPFC region linked to the MTL was recruited during remembering and imagining the future, distinct from juxtaposed regions that were modulated in a domain-flexible manner during working memory. The inferior PFC region linked to the language network was recruited during sentence processing. Detailed analysis of the trial-level responses further revealed that the DLPFC region linked to the MTL specifically tracked processes associated with scene construction. These results suggest that the DLPFC possesses a domain-specialized region that is small and easily confused with nearby (larger) regions associated with cognitive control. The newly described region is domain specialized for functions traditionally associated with the MTL. We discuss the implications of these findings in relation to convergent anatomical analysis in the monkey.NEW & NOTEWORTHY Competing hypotheses link regions of prefrontal cortex (PFC) to domain-flexible or domain-specific processes. Here, using a precision neuroimaging approach, we identify a domain-specialized region in dorsolateral PFC, coupled to the medial temporal lobe and recruited for scene construction. This region is juxtaposed to, but distinct from, broader PFC regions recruited flexibly for cognitive control. Region distinctions align with broader network differences, suggesting that PFC regions gain dissociable processing properties via segregated anatomical projections.
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Affiliation(s)
- Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Wendy Sun
- Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts, United States
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
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14
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Kosakowski HL, Saadon-Grosman N, Du J, Eldaief ME, Buckner RL. Human Striatal Association Megaclusters. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.03.560666. [PMID: 37873093 PMCID: PMC10592903 DOI: 10.1101/2023.10.03.560666] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The striatum receives projections from multiple regions of the cerebral cortex consistent with its role in diverse motor, affective, and cognitive functions. Supporting cognitive functions, the caudate receives projections from cortical association regions. Building on recent insights about the details of how multiple cortical networks are specialized for distinct aspects of higher-order cognition, we revisited caudate organization using within-individual precision neuroimaging (n=2, each participant scanned 31 times). Detailed analysis revealed that the caudate has side-by-side zones that are coupled to at least Give distinct distributed association networks, paralleling the specialization observed in the cerebral cortex. Examining correlation maps from closely juxtaposed seed regions in the caudate recapitulated the Give distinct cerebral networks including their multiple spatially distributed regions. These results extend the general notion of parallel specialized basal ganglia circuits, with the additional discovery that even within the caudate, there is Gine-grained separation of multiple distinct higher-order networks.
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Affiliation(s)
- Heather L Kosakowski
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Mark E Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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15
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Uddin LQ, Betzel RF, Cohen JR, Damoiseaux JS, De Brigard F, Eickhoff SB, Fornito A, Gratton C, Gordon EM, Laird AR, Larson-Prior L, McIntosh AR, Nickerson LD, Pessoa L, Pinho AL, Poldrack RA, Razi A, Sadaghiani S, Shine JM, Yendiki A, Yeo BTT, Spreng RN. Controversies and progress on standardization of large-scale brain network nomenclature. Netw Neurosci 2023; 7:864-905. [PMID: 37781138 PMCID: PMC10473266 DOI: 10.1162/netn_a_00323] [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: 09/01/2022] [Accepted: 05/10/2023] [Indexed: 10/03/2023] Open
Abstract
Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.
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Affiliation(s)
- Lucina Q. Uddin
- Department of Psychiatry and Biobehavioral Sciences and Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Richard F. Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Jessica R. Cohen
- Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, USA
| | - Jessica S. Damoiseaux
- Institute of Gerontology and Department of Psychology, Wayne State University, Detroit, MI, USA
| | | | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Evan M. Gordon
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA
| | - Angela R. Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Linda Larson-Prior
- Deptartment of Psychiatry and Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - A. Randal McIntosh
- Institute for Neuroscience and Neurotechnology, Simon Fraser University, Vancouver, BC, Canada
| | | | - Luiz Pessoa
- Department of Psychology, University of Maryland, College Park, MD, USA
| | - Ana Luísa Pinho
- Brain and Mind Institute, Western University, London, Ontario, Canada
| | | | - Adeel Razi
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | - Sepideh Sadaghiani
- Department of Psychology, University of Illinois, Urbana Champaign, IL, USA
| | - James M. Shine
- Brain and Mind Center, University of Sydney, Sydney, Australia
| | - Anastasia Yendiki
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - B. T. Thomas Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
| | - R. Nathan Spreng
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
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16
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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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17
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Koslov SR, Kable JW, Foster BL. Dissociable contributions of the medial parietal cortex to recognition memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.12.557048. [PMID: 37745317 PMCID: PMC10515876 DOI: 10.1101/2023.09.12.557048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Human neuroimaging studies of episodic memory retrieval routinely observe the engagement of specific cortical regions beyond the medial temporal lobe. Of these, medial parietal cortex (MPC) is of particular interest given its ubiquitous, and yet distinct, functional characteristics during different types of retrieval tasks. Specifically, while recognition memory and autobiographical recall tasks are both used to probe episodic retrieval, these paradigms consistently drive distinct patterns of response within MPC. This dissociation adds to growing evidence suggesting a common principle of functional organization across memory related brain structures, specifically regarding the control or content demands of memory-based decisions. To carefully examine this putative organization, we used a high-resolution fMRI dataset collected at ultra-high field (7T) while subjects performed thousands of recognition-memory trials to identify MPC regions responsive to recognition-decisions or semantic content of stimuli within and across individuals. We observed interleaving, though distinct, functional subregions of MPC where responses were sensitive to either recognition decisions or the semantic representation of stimuli, but rarely both. In addition, this functional dissociation within MPC was further accentuated by distinct profiles of connectivity bias with the hippocampus during task and rest. Finally, we show that recent observations of person and place selectivity within MPC reflect category specific responses from within identified semantic regions that are sensitive to mnemonic demands. Together, these data better account for how distinct patterns of MPC responses can occur as a result of task demands during episodic retrieval and may reflect a common principle of organization throughout hippocampal-neocortical memory systems.
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Affiliation(s)
- Seth R. Koslov
- Department of Neurosurgery, Perelman School of Medicine; University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Joseph W. Kable
- Department of Psychology; University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Brett L. Foster
- Department of Neurosurgery, Perelman School of Medicine; University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
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18
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Reznik D, Trampel R, Weiskopf N, Witter MP, Doeller CF. Dissociating distinct cortical networks associated with subregions of the human medial temporal lobe using precision neuroimaging. Neuron 2023; 111:2756-2772.e7. [PMID: 37390820 DOI: 10.1016/j.neuron.2023.05.029] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 05/26/2023] [Accepted: 05/27/2023] [Indexed: 07/02/2023]
Abstract
Tract-tracing studies in primates indicate that different subregions of the medial temporal lobe (MTL) are connected with multiple brain regions. However, no clear framework defining the distributed anatomy associated with the human MTL exists. This gap in knowledge originates in notoriously low MRI data quality in the anterior human MTL and in group-level blurring of idiosyncratic anatomy between adjacent brain regions, such as entorhinal and perirhinal cortices, and parahippocampal areas TH/TF. Using MRI, we intensively scanned four human individuals and collected whole-brain data with unprecedented MTL signal quality. Following detailed exploration of cortical networks associated with MTL subregions within each individual, we discovered three biologically meaningful networks associated with the entorhinal cortex, perirhinal cortex, and parahippocampal area TH, respectively. Our findings define the anatomical constraints within which human mnemonic functions must operate and are insightful for examining the evolutionary trajectory of the MTL connectivity across species.
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Affiliation(s)
- Daniel Reznik
- Department of Psychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Menno P Witter
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer's Disease, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Christian F Doeller
- Department of Psychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Kavli Institute for Systems Neuroscience, Centre for Neural Computation, Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits, Jebsen Centre for Alzheimer's Disease, NTNU Norwegian University of Science and Technology, Trondheim, Norway; Wilhelm Wundt Institute of Psychology, Leipzig University, Leipzig, Germany; Department of Psychology, Technische Universität Dresden, Dresden, Germany.
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19
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Kraus B, Zinbarg R, Braga RM, Nusslock R, Mittal VA, Gratton C. Insights from personalized models of brain and behavior for identifying biomarkers in psychiatry. Neurosci Biobehav Rev 2023; 152:105259. [PMID: 37268180 PMCID: PMC10527506 DOI: 10.1016/j.neubiorev.2023.105259] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/22/2023] [Accepted: 05/30/2023] [Indexed: 06/04/2023]
Abstract
A main goal in translational neuroscience is to identify neural correlates of psychopathology ("biomarkers") that can be used to facilitate diagnosis, prognosis, and treatment. This goal has led to substantial research into how psychopathology symptoms relate to large-scale brain systems. However, these efforts have not yet resulted in practical biomarkers used in clinical practice. One reason for this underwhelming progress may be that many study designs focus on increasing sample size instead of collecting additional data within each individual. This focus limits the reliability and predictive validity of brain and behavioral measures in any one person. As biomarkers exist at the level of individuals, an increased focus on validating them within individuals is warranted. We argue that personalized models, estimated from extensive data collection within individuals, can address these concerns. We review evidence from two, thus far separate, lines of research on personalized models of (1) psychopathology symptoms and (2) fMRI measures of brain networks. We close by proposing approaches uniting personalized models across both domains to improve biomarker research.
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Affiliation(s)
- Brian Kraus
- Department of Psychology, Northwestern University, Evanston, IL, USA.
| | - Richard Zinbarg
- Department of Psychology, Northwestern University, Evanston, IL, USA; The Family Institute at Northwestern University, Evanston, IL, USA
| | - Rodrigo M Braga
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Robin Nusslock
- Department of Psychology, Northwestern University, Evanston, IL, USA; Institute for Policy Research, Northwestern University, Evanston, IL, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA; Institute for Policy Research, Northwestern University, Evanston, IL, USA; Institute for Innovations in Developmental Sciences (DevSci), Northwestern University, Chicago, IL, USA; Northwestern University, Department of Psychiatry, Chicago, IL, USA; Northwestern University, Medical Social Sciences, Chicago, IL, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA; Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Interdepartmental Neuroscience Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Psychology, Florida State University, Tallahassee, FL, USA; Program in Neuroscience, Florida State University, Tallahassee, FL, USA
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20
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Kwon Y, Salvo JJ, Anderson N, Holubecki AM, Lakshman M, Yoo K, Kay K, Gratton C, Braga RM. Situating the parietal memory network in the context of multiple parallel distributed networks using high-resolution functional connectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.16.553585. [PMID: 37645962 PMCID: PMC10462098 DOI: 10.1101/2023.08.16.553585] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
A principle of brain organization is that networks serving higher cognitive functions are widely distributed across the brain. One exception has been the parietal memory network (PMN), which plays a role in recognition memory but is often defined as being restricted to posteromedial association cortex. We hypothesized that high-resolution estimates of the PMN would reveal small regions that had been missed by prior approaches. High-field 7T functional magnetic resonance imaging (fMRI) data from extensively sampled participants was used to define the PMN within individuals. The PMN consistently extended beyond the core posteromedial set to include regions in the inferior parietal lobule; rostral, dorsal, medial, and ventromedial prefrontal cortex; the anterior insula; and ramus marginalis of the cingulate sulcus. The results suggest that, when fine-scale anatomy is considered, the PMN matches the expected distributed architecture of other association networks, reinforcing that parallel distributed networks are an organizing principle of association cortex.
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Affiliation(s)
- Y Kwon
- Northwestern University Department of Neurology
| | - J J Salvo
- Northwestern University Department of Neurology
| | - N Anderson
- Northwestern University Department of Neurology
| | | | - M Lakshman
- Northwestern University Department of Neurology
| | - K Yoo
- Yale University Department of Psychology
| | - K Kay
- University of Minnesota Department of Radiology
| | - C Gratton
- Florida State University Department of Psychology
| | - R M Braga
- Northwestern University Department of Neurology
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21
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Menon V. 20 years of the default mode network: A review and synthesis. Neuron 2023; 111:2469-2487. [PMID: 37167968 PMCID: PMC10524518 DOI: 10.1016/j.neuron.2023.04.023] [Citation(s) in RCA: 41] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/04/2023] [Accepted: 04/20/2023] [Indexed: 05/13/2023]
Abstract
The discovery of the default mode network (DMN) has revolutionized our understanding of the workings of the human brain. Here, I review developments that led to the discovery of the DMN, offer a personal reflection, and consider how our ideas of DMN function have evolved over the past two decades. I summarize literature examining the role of the DMN in self-reference, social cognition, episodic and autobiographical memory, language and semantic memory, and mind wandering. I identify unifying themes and propose new perspectives on the DMN's role in human cognition. I argue that the DMN integrates and broadcasts memory, language, and semantic representations to create a coherent "internal narrative" reflecting our individual experiences. This narrative is central to the construction of a sense of self, shapes how we perceive ourselves and interact with others, may have ontogenetic origins in self-directed speech during childhood, and forms a vital component of human consciousness.
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Affiliation(s)
- Vinod Menon
- Department of Psychiatry & Behavioral Sciences and Department of Neurology & Neurological Sciences, Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
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22
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Smith DM, Kraus BT, Dworetsky A, Gordon EM, Gratton C. Brain hubs defined in the group do not overlap with regions of high inter-individual variability. Neuroimage 2023; 277:120195. [PMID: 37286152 PMCID: PMC10427117 DOI: 10.1016/j.neuroimage.2023.120195] [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] [Received: 05/26/2022] [Revised: 04/18/2023] [Accepted: 05/24/2023] [Indexed: 06/09/2023] Open
Abstract
Connector 'hubs' are brain regions with links to multiple networks. These regions are hypothesized to play a critical role in brain function. While hubs are often identified based on group-average functional magnetic resonance imaging (fMRI) data, there is considerable inter-subject variation in the functional connectivity profiles of the brain, especially in association regions where hubs tend to be located. Here we investigated how group hubs are related to locations of inter-individual variability. To answer this question, we examined inter-individual variation at group-level hubs in both the Midnight Scan Club and Human Connectome Project datasets. The top group hubs defined based on the participation coefficient did not overlap strongly with the most prominent regions of inter-individual variation (termed 'variants' in prior work). These hubs have relatively strong similarity across participants and consistent cross-network profiles, similar to what was seen for many other areas of cortex. Consistency across participants was further improved when these hubs were allowed to shift slightly in local position. Thus, our results demonstrate that the top group hubs defined with the participation coefficient are generally consistent across people, suggesting they may represent conserved cross-network bridges. More caution is warranted with alternative hub measures, such as community density (which are based on spatial proximity to network borders) and intermediate hub regions which show higher correspondence to locations of individual variability.
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Affiliation(s)
- Derek M Smith
- Department of Psychology, Northwestern University, Evanston, IL, United States; Department of Neurology, Division of Cognitive Neurology/Neuropsychology, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.
| | - Brian T Kraus
- Department of Psychology, Northwestern University, Evanston, IL, United States
| | - Ally Dworetsky
- Department of Psychology, Northwestern University, Evanston, IL, United States; Department of Psychology, Florida State University, Tallahassee, FL, United States
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, United States; Department of Psychology, Florida State University, Tallahassee, FL, United States; Department of Neurology, Northwestern University, Evanston, IL, United States.
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23
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Lynch CJ, Elbau I, Ng T, Ayaz A, Zhu S, Manfredi N, Johnson M, Wolk D, Power JD, Gordon EM, Kay K, Aloysi A, Moia S, Caballero-Gaudes C, Victoria LW, Solomonov N, Goldwaser E, Zebley B, Grosenick L, Downar J, Vila-Rodriguez F, Daskalakis ZJ, Blumberger DM, Williams N, Gunning FM, Liston C. Expansion of a frontostriatal salience network in individuals with depression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.09.551651. [PMID: 37645792 PMCID: PMC10461904 DOI: 10.1101/2023.08.09.551651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Hundreds of neuroimaging studies spanning two decades have revealed differences in brain structure and functional connectivity in depression, but with modest effect sizes, complicating efforts to derive mechanistic pathophysiologic insights or develop biomarkers. 1 Furthermore, although depression is a fundamentally episodic condition, few neuroimaging studies have taken a longitudinal approach, which is critical for understanding cause and effect and delineating mechanisms that drive mood state transitions over time. The emerging field of precision functional mapping using densely-sampled longitudinal neuroimaging data has revealed unexpected, functionally meaningful individual differences in brain network topology in healthy individuals, 2-5 but these approaches have never been applied to individuals with depression. Here, using precision functional mapping techniques and 11 datasets comprising n=187 repeatedly sampled individuals and >21,000 minutes of fMRI data, we show that the frontostriatal salience network is expanded two-fold in most individuals with depression. This effect was replicable in multiple samples, including large-scale, group-average data (N=1,231 subjects), and caused primarily by network border shifts affecting specific functional systems, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was unexpectedly stable over time, unaffected by changes in mood state, and detectable in children before the subsequent onset of depressive symptoms in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in specific frontostriatal circuits that tracked fluctuations in specific symptom domains and predicted future anhedonia symptoms before they emerged. Together, these findings identify a stable trait-like brain network topology that may confer risk for depression and mood-state dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time.
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24
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Du J, DiNicola LM, Angeli PA, Saadon-Grosman N, Sun W, Kaiser S, Ladopoulou J, Xue A, Yeo BTT, Eldaief MC, Buckner RL. Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.08.552437. [PMID: 37609246 PMCID: PMC10441314 DOI: 10.1101/2023.08.08.552437] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian Model (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was initially developed and tested in two participants (each scanned 31 times) and then prospectively applied to 15 new participants (each scanned 8 to 11 times). Detailed analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that also linked to distant regions. Third-order networks each possessed regions distributed widely throughout association cortex. Moreover, regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated similarly across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were typically adjacent to three separate domain-specialized regions. Independent task data were analyzed to explore functional response properties. The somatomotor and visual first-order networks responded to body movements and visual stimulation, respectively. A subset of the second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient or novel events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions within each SAAM did not track working memory load but rather dissociated across language, social, and spatial / episodic processing domains. These results support a model of the cerebral cortex in which progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex there is specialization of large-scale networks that divides domain-flexible from domain-specialized regions repeatedly across parietal, temporal, and prefrontal cortices. We discuss implications of these findings including how repeating organizational motifs may emerge during development.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Peter A Angeli
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Wendy Sun
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Stephanie Kaiser
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Joanna Ladopoulou
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Aihuiping Xue
- Centre for Sleep & Cognition & Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - B T Thomas Yeo
- Centre for Sleep & Cognition & Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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25
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Porter A, Nielsen A, Dorn M, Dworetsky A, Edmonds D, Gratton C. Masked features of task states found in individual brain networks. Cereb Cortex 2023; 33:2879-2900. [PMID: 35802477 PMCID: PMC10016040 DOI: 10.1093/cercor/bhac247] [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: 10/05/2021] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 11/14/2022] Open
Abstract
Completing complex tasks requires that we flexibly integrate information across brain areas. While studies have shown how functional networks are altered during different tasks, this work has generally focused on a cross-subject approach, emphasizing features that are common across people. Here we used extended sampling "precision" fMRI data to test the extent to which task states generalize across people or are individually specific. We trained classifiers to decode state using functional network data in single-person datasets across 5 diverse task states. Classifiers were then tested on either independent data from the same person or new individuals. Individualized classifiers were able to generalize to new participants. However, classification performance was significantly higher within a person, a pattern consistent across model types, people, tasks, feature subsets, and even for decoding very similar task conditions. Notably, these findings also replicated in a new independent dataset. These results suggest that individual-focused approaches can uncover robust features of brain states, including features obscured in cross-subject analyses. Individual-focused approaches have the potential to deepen our understanding of brain interactions during complex cognition.
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Affiliation(s)
- Alexis Porter
- Department of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States
| | - Ashley Nielsen
- Department of Neurology, Washington University in St. Louis, 1 Brookings Dr, St. Louis, MO 63130, United States
| | - Megan Dorn
- Department of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States
| | - Ally Dworetsky
- Department of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States
| | - Donnisa Edmonds
- Department of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States
| | - Caterina Gratton
- Department of Psychology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States
- Department of Neurology, Northwestern University, 633 Clark St, Evanston, IL 60208, United States
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26
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Foster BL, Koslov SR, Aponik-Gremillion L, Monko ME, Hayden BY, Heilbronner SR. A tripartite view of the posterior cingulate cortex. Nat Rev Neurosci 2023; 24:173-189. [PMID: 36456807 PMCID: PMC10041987 DOI: 10.1038/s41583-022-00661-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2022] [Indexed: 12/03/2022]
Abstract
The posterior cingulate cortex (PCC) is one of the least understood regions of the cerebral cortex. By contrast, the anterior cingulate cortex has been the subject of intensive investigation in humans and model animal systems, leading to detailed behavioural and computational theoretical accounts of its function. The time is right for similar progress to be made in the PCC given its unique anatomical and physiological properties and demonstrably important contributions to higher cognitive functions and brain diseases. Here, we describe recent progress in understanding the PCC, with a focus on convergent findings across species and techniques that lay a foundation for establishing a formal theoretical account of its functions. Based on this converging evidence, we propose that the broader PCC region contains three major subregions - the dorsal PCC, ventral PCC and retrosplenial cortex - that respectively support the integration of executive, mnemonic and spatial processing systems. This tripartite subregional view reconciles inconsistencies in prior unitary theories of PCC function and offers promising new avenues for progress.
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Affiliation(s)
- Brett L Foster
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Seth R Koslov
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lyndsey Aponik-Gremillion
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.,Department of Health Sciences, Dumke College for Health Professionals, Weber State University, Ogden, UT, USA
| | - Megan E Monko
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Benjamin Y Hayden
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA.,Center for Magnetic Resonance Research and Center for Neural Engineering, University of Minnesota, Minneapolis, MN, USA
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27
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Chiou R, Cox CR, Lambon Ralph MA. Bipartite functional fractionation within the neural system for social cognition supports the psychological continuity of self versus other. Cereb Cortex 2023; 33:1277-1299. [PMID: 35394005 PMCID: PMC9930627 DOI: 10.1093/cercor/bhac135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 02/10/2022] [Accepted: 03/14/2022] [Indexed: 11/12/2022] Open
Abstract
Research of social neuroscience establishes that regions in the brain's default-mode network (DN) and semantic network (SN) are engaged by socio-cognitive tasks. Research of the human connectome shows that DN and SN regions are both situated at the transmodal end of a cortical gradient but differ in their loci along this gradient. Here we integrated these 2 bodies of research, used the psychological continuity of self versus other as a "test-case," and used functional magnetic resonance imaging to investigate whether these 2 networks would encode social concepts differently. We found a robust dissociation between the DN and SN-while both networks contained sufficient information for decoding broad-stroke distinction of social categories, the DN carried more generalizable information for cross-classifying across social distance and emotive valence than did the SN. We also found that the overarching distinction of self versus other was a principal divider of the representational space while social distance was an auxiliary factor (subdivision, nested within the principal dimension), and this representational landscape was more manifested in the DN than in the SN. Taken together, our findings demonstrate how insights from connectome research can benefit social neuroscience and have implications for clarifying the 2 networks' differential contributions to social cognition.
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Affiliation(s)
| | - Christopher R Cox
- Department of Psychology, Louisiana State University, LA 70803, Baton Rouge, United States
| | - Matthew A Lambon Ralph
- MRC Cognition & Brain Science Unit, University of Cambridge, Cambridge, CB2 7EF, United Kingdom
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28
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DiNicola LM, Ariyo OI, Buckner RL. Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands. J Neurophysiol 2023; 129:17-40. [PMID: 36197013 PMCID: PMC9799157 DOI: 10.1152/jn.00211.2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Multiple large-scale networks populate human association cortex. Here, we explored the functional properties of these networks by exploiting trial-to-trial variation in component-processing demands. In two behavioral studies (n = 136 and n = 238), participants quantified strategies used to solve individual task trials that spanned remembering, imagining future scenarios, and various control trials. These trials were also all scanned in an independent sample of functional MRI participants (n = 10), each with sufficient data to precisely define within-individual networks. Stable latent factors varied across trials and correlated with trial-level functional responses selectively across networks. One network linked to parahippocampal cortex, labeled Default Network A (DN-A), tracked scene construction, including for control trials that possessed minimal episodic memory demands. To the degree, a trial encouraged participants to construct a mental scene with imagery and awareness about spatial locations of objects or places, the response in DN-A increased. The juxtaposed Default Network B (DN-B) showed no such response but varied in relation to social processing demands. Another adjacent network, labeled Frontoparietal Network B (FPN-B), robustly correlated with trial difficulty. These results support that DN-A and DN-B are specialized networks differentially supporting information processing within spatial and social domains. Both networks are dissociable from a closely juxtaposed domain-general control network that tracks cognitive effort.NEW & NOTEWORTHY Tasks shown to differentially recruit parallel association networks are multifaceted, leaving open questions about network processes. Here, examining trial-to-trial network response properties in relation to trial traits reveals new insights into network functions. In particular, processes linked to scene construction selectively recruit a distributed network with links to parahippocampal and retrosplenial cortices, including during trials designed not to rely on the personal past. Adjacent networks show distinct patterns, providing novel evidence of functional specialization.
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Affiliation(s)
- Lauren M. DiNicola
- 1Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts
| | - Oluwatobi I. Ariyo
- 1Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts
| | - Randy L. Buckner
- 1Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts,2Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts,3Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts
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29
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Lynch CJ, Elbau IG, Ng TH, Wolk D, Zhu S, Ayaz A, Power JD, Zebley B, Gunning FM, Liston C. Automated optimization of TMS coil placement for personalized functional network engagement. Neuron 2022; 110:3263-3277.e4. [PMID: 36113473 DOI: 10.1016/j.neuron.2022.08.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/20/2022] [Accepted: 08/05/2022] [Indexed: 12/11/2022]
Abstract
Transcranial magnetic stimulation (TMS) is used to treat multiple psychiatric and neurological conditions by manipulating activity in particular brain networks and circuits, but individual responses are highly variable. In clinical settings, TMS coil placement is typically based on either group average functional maps or scalp heuristics. Here, we found that this approach can inadvertently target different functional networks in depressed patients due to variability in their functional brain organization. More precise TMS targeting should be feasible by accounting for each patient's unique functional neuroanatomy. To this end, we developed a targeting approach, termed targeted functional network stimulation (TANS). The TANS approach improved stimulation specificity in silico in 8 highly sampled patients with depression and 6 healthy individuals and in vivo when targeting somatomotor functional networks representing the upper and lower limbs. Code for implementing TANS and an example dataset are provided as a resource.
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Affiliation(s)
- Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA.
| | - Immanuel G Elbau
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Tommy H Ng
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Danielle Wolk
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Shasha Zhu
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Aliza Ayaz
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Jonathan D Power
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Benjamin Zebley
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Faith M Gunning
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA
| | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, 413 East 69th Street, Box 204, New York, NY 10021, USA.
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30
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Mancuso L, Cavuoti-Cabanillas S, Liloia D, Manuello J, Buzi G, Cauda F, Costa T. Tasks activating the default mode network map multiple functional systems. Brain Struct Funct 2022; 227:1711-1734. [PMID: 35179638 PMCID: PMC9098625 DOI: 10.1007/s00429-022-02467-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/31/2022] [Indexed: 12/30/2022]
Abstract
Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic-extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.
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Affiliation(s)
- Lorenzo Mancuso
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
| | | | - Donato Liloia
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Jordi Manuello
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Giulia Buzi
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
| | - Franco Cauda
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Tommaso Costa
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy.
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
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31
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Edlow BL, Bodien YG, Baxter T, Belanger H, Cali R, Deary K, Fischl B, Foulkes AS, Gilmore N, Greve DN, Hooker JM, Huang SY, Kelemen JN, Kimberly WT, Maffei C, Masood M, Perl D, Polimeni JR, Rosen BR, Tromly S, Tseng CEJ, Yao EF, Zurcher NR, Mac Donald CL, Dams-O'Connor K. Long-Term Effects of Repeated Blast Exposure in United States Special Operations Forces Personnel: A Pilot Study Protocol. J Neurotrauma 2022; 39:1391-1407. [PMID: 35620901 PMCID: PMC9529318 DOI: 10.1089/neu.2022.0030] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Emerging evidence suggests that repeated blast exposure (RBE) is associated with brain injury in military personnel. United States (U.S.) Special Operations Forces (SOF) personnel experience high rates of blast exposure during training and combat, but the effects of low-level RBE on brain structure and function in SOF have not been comprehensively characterized. Further, the pathophysiological link between RBE-related brain injuries and cognitive, behavioral, and physical symptoms has not been fully elucidated. We present a protocol for an observational pilot study, Long-Term Effects of Repeated Blast Exposure in U.S. SOF Personnel (ReBlast). In this exploratory study, 30 active-duty SOF personnel with RBE will participate in a comprehensive evaluation of: 1) brain network structure and function using Connectome magnetic resonance imaging (MRI) and 7 Tesla MRI; 2) neuroinflammation and tau deposition using positron emission tomography; 3) blood proteomics and metabolomics; 4) behavioral and physical symptoms using self-report measures; and 5) cognition using a battery of conventional and digitized assessments designed to detect subtle deficits in otherwise high-performing individuals. We will identify clinical, neuroimaging, and blood-based phenotypes that are associated with level of RBE, as measured by the Generalized Blast Exposure Value. Candidate biomarkers of RBE-related brain injury will inform the design of a subsequent study that will test a diagnostic assessment battery for detecting RBE-related brain injury. Ultimately, we anticipate that the ReBlast study will facilitate the development of interventions to optimize the brain health, quality of life, and battle readiness of U.S. SOF personnel.
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Affiliation(s)
- Brian L Edlow
- Harvard Medical School, 1811, 175 Cambridge Street - Suite 300, Boston, Massachusetts, United States, 02115.,Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Yelena G Bodien
- Massachusetts General Hospital, 2348, Department of Neurology, 101 Merrimac, Boston, Massachusetts, United States, 02114;
| | - Timothy Baxter
- University of South Florida, 7831, Institute for Applied Engineering, Tampa, Florida, United States;
| | - Heather Belanger
- University of South Florida, 7831, Department of Psychiatry and Behavioral Neurosciences, Tampa, Florida, United States;
| | - Ryan Cali
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Katryna Deary
- Navy SEAL Foundation, Virginia Beach, Virginia, United States;
| | - Bruce Fischl
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Room 2301, 149 13th Street, Charlestown, Massachusetts, United States, 02129-2020.,Massachusetts General Hospital;
| | - Andrea S Foulkes
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Natalie Gilmore
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Douglas N Greve
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Jacob M Hooker
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Susie Y Huang
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Jessica N Kelemen
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - W Taylor Kimberly
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Chiara Maffei
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Maryam Masood
- Massachusetts General Hospital, 2348, Boston, Massachusetts, United States;
| | - Daniel Perl
- Uniformed Services University of the Health Sciences, 1685, Pathology, 4301 Jones Bridge Road, Room B3138, Bethesda, Maryland, United States, 20814;
| | - Jonathan R Polimeni
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Bruce R Rosen
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States;
| | - Samantha Tromly
- University of South Florida, 7831, Institute for Applied Engineering, Tampa, Florida, United States;
| | - Chieh-En J Tseng
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Eveline F Yao
- United States Special Operations Command, Office of the Surgeon General, MacDill Air Force Base, United States;
| | - Nicole R Zurcher
- Massachusetts General Hospital, 2348, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States;
| | - Christine L Mac Donald
- University of Washington, 7284, Department of Neurological Surgery, Seattle, Washington, United States;
| | - Kristen Dams-O'Connor
- Icahn School of Medicine at Mount Sinai, 5925, Rehabilitation Medicine, One Gustave Levy Place, Box 1163, New York, New York, United States, 10029; kristen.dams-o'
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Ren J, Hu Q, Wang W, Zhang W, Hubbard CS, Zhang P, An N, Zhou Y, Dahmani L, Wang D, Fu X, Sun Z, Wang Y, Wang R, Li L, Liu H. Fast cortical surface reconstruction from MRI using deep learning. Brain Inform 2022; 9:6. [PMID: 35262808 PMCID: PMC8907118 DOI: 10.1186/s40708-022-00155-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 02/25/2022] [Indexed: 11/23/2022] Open
Abstract
Reconstructing cortical surfaces from structural magnetic resonance imaging (MRI) is a prerequisite for surface-based functional and anatomical image analyses. Conventional algorithms for cortical surface reconstruction are computationally inefficient and typically take several hours for each subject, causing a bottleneck in applications when a fast turnaround time is needed. To address this challenge, we propose a fast cortical surface reconstruction (FastCSR) pipeline by leveraging deep machine learning. We trained our model to learn an implicit representation of the cortical surface in volumetric space, termed the “level set representation”. A fast volumetric topology correction method and a topology-preserving surface mesh extraction procedure were employed to reconstruct the cortical surface based on the level set representation. Using 1-mm isotropic T1-weighted images, the FastCSR pipeline was able to reconstruct a subject’s cortical surfaces within 5 min with comparable surface quality, which is approximately 47 times faster than the traditional FreeSurfer pipeline. The advantage of FastCSR becomes even more apparent when processing high-resolution images. Importantly, the model demonstrated good generalizability in previously unseen data and showed high test–retest reliability in cortical morphometrics and anatomical parcellations. Finally, FastCSR was robust to images with compromised quality or with distortions caused by lesions. This fast and robust pipeline for cortical surface reconstruction may facilitate large-scale neuroimaging studies and has potential in clinical applications wherein brain images may be compromised.
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Affiliation(s)
- Jianxun Ren
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Qingyu Hu
- School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230027, China
| | | | - Wei Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100080, China
| | - Catherine S Hubbard
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA
| | | | - Ning An
- Neural Galaxy, Beijing, 102206, China
| | - Ying Zhou
- Neural Galaxy, Beijing, 102206, China
| | - Louisa Dahmani
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Xiaoxuan Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA.,Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA.,State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, 300401, China
| | | | | | - Ruiqi Wang
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China. .,Precision Medicine and Healthcare Research Center, Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, 518055, China. .,IDG/McGovern Institute for Brain Research at Tsinghua University, Beijing, 100084, China. .,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA. .,Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA.
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Zajner C, Spreng RN, Bzdok D. Lacking Social Support is Associated With Structural Divergences in Hippocampus-Default Network Co-Variation Patterns. Soc Cogn Affect Neurosci 2022; 17:802-818. [PMID: 35086149 PMCID: PMC9433851 DOI: 10.1093/scan/nsac006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 11/17/2021] [Accepted: 01/25/2022] [Indexed: 11/22/2022] Open
Abstract
Elaborate social interaction is a pivotal asset of the human species. The complexity of people’s social lives may constitute the dominating factor in the vibrancy of many individuals’ environment. The neural substrates linked to social cognition thus appear especially susceptible when people endure periods of social isolation: here, we zoom in on the systematic inter-relationships between two such neural substrates, the allocortical hippocampus (HC) and the neocortical default network (DN). Previous human social neuroscience studies have focused on the DN, while HC subfields have been studied in most detail in rodents and monkeys. To bring into contact these two separate research streams, we directly quantified how DN subregions are coherently co-expressed with specific HC subfields in the context of social isolation. A two-pronged decomposition of structural brain scans from ∼40 000 UK Biobank participants linked lack of social support to mostly lateral subregions in the DN patterns. This lateral DN association co-occurred with HC patterns that implicated especially subiculum, presubiculum, CA2, CA3 and dentate gyrus. Overall, the subregion divergences within spatially overlapping signatures of HC–DN co-variation followed a clear segregation into the left and right brain hemispheres. Separable regimes of structural HC–DN co-variation also showed distinct associations with the genetic predisposition for lacking social support at the population level.
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Affiliation(s)
- Chris Zajner
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal H3A2B4, Canada
| | - R Nathan Spreng
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal H3A2B4, Canada
| | - Danilo Bzdok
- Correspondence should be addressed to Danilo Bzdok, McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal H3A2B4, Canada. E-mail:
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Transcranial stimulation of alpha oscillations up-regulates the default mode network. Proc Natl Acad Sci U S A 2022; 119:2110868119. [PMID: 34969856 PMCID: PMC8740757 DOI: 10.1073/pnas.2110868119] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/12/2021] [Indexed: 12/26/2022] Open
Abstract
The default mode network (DMN) is the most-prominent intrinsic connectivity network, serving as a key architecture of the brain's functional organization. Conversely, dysregulated DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly alpha (8 to 12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition alpha-frequency transcranial alternating current stimulation (α-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous electroencephalography and functional MRI (EEG-fMRI), we demonstrated that α-tACS (versus Sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can up-regulate the DMN further highlights an effective noninvasive intervention to normalize DMN functioning in various disorders.
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35
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Dave S, VanHaerents S, Bonakdarpour B, Mesulam MM, Voss JL. Stimulation of distinct parietal locations differentiates frontal versus hippocampal network involvement in memory formation. CURRENT RESEARCH IN NEUROBIOLOGY 2022; 3:100030. [DOI: 10.1016/j.crneur.2022.100030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 01/30/2022] [Accepted: 02/07/2022] [Indexed: 11/16/2022] Open
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Du J, Buckner RL. Precision Estimates of Macroscale Network Organization in the Human and Their Relation to Anatomical Connectivity in the Marmoset Monkey. Curr Opin Behav Sci 2021; 40:144-152. [PMID: 34722833 DOI: 10.1016/j.cobeha.2021.04.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Precision estimates of network organization from functional connectivity MRI in the human and tract-tracing data in the marmoset monkey converge to reveal an orderly macroscale gradient of sequential networks across the cerebral cortex. Parallel networks begin with a sequence of multiple nested sensory-motor networks in both species progressing to more distributed association networks in rostral prefrontal and temporal association zones, which are expanded and differentiated in the human. From this perspective, the spatially-distributed motif encountered in association networks appears to be on a continuum with primary sensory-motor networks. Network motifs supporting sophisticated forms of human cognition may arise from specializations of distributed anatomical networks formed in an ancestor at least 45 million years ago.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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37
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Zheng A, Montez DF, Marek S, Gilmore AW, Newbold DJ, Laumann TO, Kay BP, Seider NA, Van AN, Hampton JM, Alexopoulos D, Schlaggar BL, Sylvester CM, Greene DJ, Shimony JS, Nelson SM, Wig GS, Gratton C, McDermott KB, Raichle ME, Gordon EM, Dosenbach NUF. Parallel hippocampal-parietal circuits for self- and goal-oriented processing. Proc Natl Acad Sci U S A 2021; 118:e2101743118. [PMID: 34404728 PMCID: PMC8403906 DOI: 10.1073/pnas.2101743118] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing.
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Affiliation(s)
- Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110;
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Adrian W Gilmore
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Jacqueline M Hampton
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD 21205
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | - Chad M Sylvester
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Deanna J Greene
- Department of Cognitive Science, University of California, San Diego, CA 92093
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414
| | - Gagan S Wig
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL 60208
- Department of Neurology, Northwestern University, Evanston, IL 60208
| | - Kathleen B McDermott
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110;
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110
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Bryce NV, Flournoy JC, Guassi Moreira JF, Rosen ML, Sambook KA, Mair P, McLaughlin KA. Brain parcellation selection: An overlooked decision point with meaningful effects on individual differences in resting-state functional connectivity. Neuroimage 2021; 243:118487. [PMID: 34419594 PMCID: PMC8629133 DOI: 10.1016/j.neuroimage.2021.118487] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 08/16/2021] [Accepted: 08/18/2021] [Indexed: 12/16/2022] Open
Abstract
Over the past decade extensive research has examined the segregation of the human brain into large-scale functional networks. The resulting network maps, i.e. parcellations, are now commonly used for the a priori identification of functional networks. However, the use of these parcellations, particularly in developmental and clinical samples, hinges on four fundamental assumptions: (1) the various parcellations are equally able to recover the networks of interest; (2) adult-derived parcellations well represent the networks in children’s brains; (3) network properties, such as within-network connectivity, are reliably measured across parcellations; and (4) parcellation selection does not impact the results with regard to individual differences in given network properties. In the present study we examined these assumptions using eight common parcellation schemes in two independent developmental samples. We found that the parcellations are equally able to capture networks of interest in both children and adults. However, networks bearing the same name across parcellations (e.g., default network) do not produce reliable within-network measures of functional connectivity. Critically, parcellation selection significantly impacted the magnitude of associations of functional connectivity with age, poverty, and cognitive ability, producing meaningful differences in interpretation of individual differences in functional connectivity based on parcellation choice. Our findings suggest that work employing parcellations may benefit from the use of multiple schemes to confirm the robustness and generalizability of results. Furthermore, researchers looking to gain insight into functional networks may benefit from employing more nuanced network identification approaches such as using densely-sampled data to produce individual-derived network parcellations. A transition towards precision neuroscience will provide new avenues in the characterization of functional brain organization across development and within clinical populations.
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Affiliation(s)
- Nessa V Bryce
- Department of Psychology, Harvard University, Cambridge, MA 02139, United States.
| | - John C Flournoy
- Department of Psychology, Harvard University, Cambridge, MA 02139, United States
| | - João F Guassi Moreira
- Department of Psychology, University of California, Los Angeles, CA 90095, United States
| | - Maya L Rosen
- Department of Psychology, Harvard University, Cambridge, MA 02139, United States
| | - Kelly A Sambook
- Department of Psychology, Harvard University, Cambridge, MA 02139, United States
| | - Patrick Mair
- Department of Psychology, Harvard University, Cambridge, MA 02139, United States
| | - Katie A McLaughlin
- Department of Psychology, Harvard University, Cambridge, MA 02139, United States
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Three types of individual variation in brain networks revealed by single-subject functional connectivity analyses. Curr Opin Behav Sci 2021. [DOI: 10.1016/j.cobeha.2021.02.014] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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41
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Fedorenko E. The early origins and the growing popularity of the individual-subject analytic approach in human neuroscience. Curr Opin Behav Sci 2021. [DOI: 10.1016/j.cobeha.2021.02.023] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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42
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Gilmore AW, Nelson SM, McDermott KB. Precision functional mapping of human memory systems. Curr Opin Behav Sci 2021. [DOI: 10.1016/j.cobeha.2020.12.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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43
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Salvo JJ, Holubecki AM, Braga RM. Correspondence between functional connectivity and task-related activity patterns within the individual. Curr Opin Behav Sci 2021. [DOI: 10.1016/j.cobeha.2021.05.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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44
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Abstract
In this manuscript, we report a rare case of a patient with localized seizures originating from the right anterior and dorsal posteromedial cortex (PMC). We mapped the electrophysiological and neuroimaging connectivity of the ictal onset site and replicated seizure auras by stimulating the homotopical PMC site in the left hemisphere. Our findings provide a causal link between PMC and the sense of self and provide unique clues about the pathophysiology of self-dissociation in neuropsychiatric conditions. The posteromedial cortex (PMC) is known to be a core node of the default mode network. Given its anatomical location and blood supply pattern, the effects of targeted disruption of this part of the brain are largely unknown. Here, we report a rare case of a patient (S19_137) with confirmed seizures originating within the PMC. Intracranial recordings confirmed the onset of seizures in the right dorsal posterior cingulate cortex, adjacent to the marginal sulcus, likely corresponding to Brodmann area 31. Upon the onset of seizures, the patient reported a reproducible sense of self-dissociation—a condition he described as a distorted awareness of the position of his body in space and feeling as if he had temporarily become an outside observer to his own thoughts, his “me” having become a separate entity that was listening to different parts of his brain speak to each other. Importantly, 50-Hz electrical stimulation of the seizure zone and a homotopical region within the contralateral PMC induced a subjectively similar state, reproducibly. We supplement our clinical findings with the definition of the patient’s network anatomy at sites of interest using cortico-cortical–evoked potentials, experimental and resting-state electrophysiological connectivity, and individual-level functional imaging. This rare case of patient S19_137 highlights the potential causal importance of the PMC for integrating self-referential information and provides clues for future mechanistic studies of self-dissociation in neuropsychiatric populations.
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Dissociations between glucose metabolism and blood oxygenation in the human default mode network revealed by simultaneous PET-fMRI. Proc Natl Acad Sci U S A 2021; 118:2021913118. [PMID: 34193521 PMCID: PMC8271663 DOI: 10.1073/pnas.2021913118] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
A consistent finding from functional MRI (fMRI) of externally focused cognitive control is negative signal change in the brain’s default mode network (DMN), but it is unknown whether this reflects an increase of synaptic activity during rest periods or active suppression during task. Using hybrid PET-MRI, we show that task-positive fMRI responses align with increasing glucose metabolism during cognitive control, but task-negative fMRI responses in DMN are not accompanied by corresponding decreases in metabolism. The results are incompatible with an interpretation of task-negative fMRI signal in DMN as a relative metabolic increase during a resting baseline condition. The present results open up avenues for understanding abnormal fMRI activity patterns in DMN in aging and psychiatric disease. The finding of reduced functional MRI (fMRI) activity in the default mode network (DMN) during externally focused cognitive control has been highly influential to our understanding of human brain function. However, these negative fMRI responses, measured as relative decreases in the blood-oxygenation-level–dependent (BOLD) response between rest and task, have also prompted major questions of interpretation. Using hybrid functional positron emission tomography (PET)-MRI, this study shows that task-positive and -negative BOLD responses do not reflect antagonistic patterns of synaptic metabolism. Task-positive BOLD responses in attention and control networks were accompanied by concomitant increases in glucose metabolism during cognitive control, but metabolism in widespread DMN remained high during rest and task despite negative BOLD responses. Dissociations between glucose metabolism and the BOLD response specific to the DMN reveal functional heterogeneity in this network and demonstrate that negative BOLD responses during cognitive control should not be interpreted to reflect relative increases in metabolic activity during rest. Rather, neurovascular coupling underlying BOLD response patterns during rest and task in DMN appears fundamentally different from BOLD responses in other association networks during cognitive control.
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Peer M, Hayman M, Tamir B, Arzy S. Brain Coding of Social Network Structure. J Neurosci 2021; 41:4897-4909. [PMID: 33903220 PMCID: PMC8260169 DOI: 10.1523/jneurosci.2641-20.2021] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 02/18/2021] [Accepted: 04/05/2021] [Indexed: 11/21/2022] Open
Abstract
Humans have large social networks, with hundreds of interacting individuals. How does the brain represent the complex connectivity structure of these networks? Here we used social media (Facebook) data to objectively map participants' real-life social networks. We then used representational similarity analysis (RSA) of functional magnetic resonance imaging (fMRI) activity patterns to investigate the neural coding of these social networks as participants reflected on each individual. We found coding of social network distances in the default-mode network (medial prefrontal, medial parietal, and lateral parietal cortices). When using partial correlation RSA to control for other factors that can be correlated to social distance (personal affiliation, personality traits. and visual appearance, as subjectively rated by the participants), we found that social network distance information was uniquely coded in the retrosplenial complex, a region involved in spatial processing. In contrast, information on individuals' personal affiliation to the participants and personality traits was found in the medial parietal and prefrontal cortices, respectively. These findings demonstrate a cortical division between representations of non-self-referenced (allocentric) social network structure, self-referenced (egocentric) social distance, and trait-based social knowledge.SIGNIFICANCE STATEMENT Each of us has a social network composed of hundreds of individuals, with different characteristics and different relations among them. How does our brain represent this complexity? To find out, we mapped participants' social connections using Facebook data and then asked them to think about individuals from their network while undergoing functional MRI scanning. We found that the position of individuals within the social network, as well as their affiliation to the participant, are mapped in the retrosplenial complex, a region involved in spatial processing. Individuals' personality traits were coded in another region, the medial prefrontal cortex. Our findings demonstrate a neural dissociation among different aspects of social knowledge and suggest a link between spatial and social cognitive mapping.
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Affiliation(s)
- Michael Peer
- Department of Medical Neurosciences, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel
- Department of Neurology, Hadassah Hebrew University Medical School, Jerusalem 91120, Israel
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Mordechai Hayman
- Department of Medical Neurosciences, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel
- Department of Neurology, Hadassah Hebrew University Medical School, Jerusalem 91120, Israel
| | - Bar Tamir
- Department of Medical Neurosciences, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel
| | - Shahar Arzy
- Department of Medical Neurosciences, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel
- Department of Neurology, Hadassah Hebrew University Medical School, Jerusalem 91120, Israel
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Barnett AJ, Reilly W, Dimsdale-Zucker HR, Mizrak E, Reagh Z, Ranganath C. Intrinsic connectivity reveals functionally distinct cortico-hippocampal networks in the human brain. PLoS Biol 2021; 19:e3001275. [PMID: 34077415 PMCID: PMC8202937 DOI: 10.1371/journal.pbio.3001275] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 06/14/2021] [Accepted: 05/07/2021] [Indexed: 12/13/2022] Open
Abstract
Episodic memory depends on interactions between the hippocampus and interconnected neocortical regions. Here, using data-driven analyses of resting-state functional magnetic resonance imaging (fMRI) data, we identified the networks that interact with the hippocampus-the default mode network (DMN) and a "medial temporal network" (MTN) that included regions in the medial temporal lobe (MTL) and precuneus. We observed that the MTN plays a critical role in connecting the visual network to the DMN and hippocampus. The DMN could be further divided into 3 subnetworks: a "posterior medial" (PM) subnetwork comprised of posterior cingulate and lateral parietal cortices; an "anterior temporal" (AT) subnetwork comprised of regions in the temporopolar and dorsomedial prefrontal cortex; and a "medial prefrontal" (MP) subnetwork comprised of regions primarily in the medial prefrontal cortex (mPFC). These networks vary in their functional connectivity (FC) along the hippocampal long axis and represent different kinds of information during memory-guided decision-making. Finally, a Neurosynth meta-analysis of fMRI studies suggests new hypotheses regarding the functions of the MTN and DMN subnetworks, providing a framework to guide future research on the neural architecture of episodic memory.
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Affiliation(s)
- Alexander J. Barnett
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
| | - Walter Reilly
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
| | | | - Eda Mizrak
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
- Department of Psychology, University of Zurich, Zürich, Switzerland
| | - Zachariah Reagh
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
- Department of Neurology, University of California at Davis, Sacramento, California, United States of America
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Charan Ranganath
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
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Kraus B, Salvador CE, Kamikubo A, Hsiao NC, Hu JF, Karasawa M, Kitayama S. Oscillatory alpha power at rest reveals an independent self: A cross-cultural investigation. Biol Psychol 2021; 163:108118. [PMID: 34019966 DOI: 10.1016/j.biopsycho.2021.108118] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 05/03/2021] [Accepted: 05/14/2021] [Indexed: 11/19/2022]
Abstract
In the current cultural psychology literature, it is commonly assumed that the personal self is cognitively more salient for those with an independent (vs. interdependent) self-construal (SC). So far, however, this assumption remains largely untested. Here, we drew on evidence that resting state alpha power (RSAP) reflects mental processes constituting the personal self, and tested whether RSAP is positively correlated with independent (vs. interdependent) SC. Study 1 tested European Americans and Taiwanese, whereas Study 2 tested European Americans and Japanese (total N = 164). A meta-analysis performed on the combined data confirmed a reliable association between independent (vs. interdependent) SC and RSAP. However, this association was only reliable when participants had their eyes closed. Even though European Americans were consistently more independent than East Asians, RSAP was no greater for European Americans than for East Asians. Our data helps explore a missing link in the theorizing of contemporary cultural psychology.
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Affiliation(s)
- Brian Kraus
- Northwestern University, Department of Psychology, United States.
| | | | - Aya Kamikubo
- Tokyo Woman's Christian University, Graduate School of Humanities and Sciences, Japan
| | - Nai-Ching Hsiao
- National Cheng Kung University, Department of Psychology, Taiwan
| | - Jon-Fan Hu
- National Cheng Kung University, Department of Psychology, Taiwan
| | - Mayumi Karasawa
- Tokyo Woman's Christian University, Department of Communication, Japan
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Steel A, Billings MM, Silson EH, Robertson CE. A network linking scene perception and spatial memory systems in posterior cerebral cortex. Nat Commun 2021; 12:2632. [PMID: 33976141 PMCID: PMC8113503 DOI: 10.1038/s41467-021-22848-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 04/05/2021] [Indexed: 02/03/2023] Open
Abstract
The neural systems supporting scene-perception and spatial-memory systems of the human brain are well-described. But how do these neural systems interact? Here, using fine-grained individual-subject fMRI, we report three cortical areas of the human brain, each lying immediately anterior to a region of the scene perception network in posterior cerebral cortex, that selectively activate when recalling familiar real-world locations. Despite their close proximity to the scene-perception areas, network analyses show that these regions constitute a distinct functional network that interfaces with spatial memory systems during naturalistic scene understanding. These "place-memory areas" offer a new framework for understanding how the brain implements memory-guided visual behaviors, including navigation.
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Affiliation(s)
- Adam Steel
- grid.254880.30000 0001 2179 2404Department of Psychology and Brain Sciences, Dartmouth College, Hanover, NH USA
| | - Madeleine M. Billings
- grid.254880.30000 0001 2179 2404Department of Psychology and Brain Sciences, Dartmouth College, Hanover, NH USA
| | - Edward H. Silson
- grid.4305.20000 0004 1936 7988Psychology, School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Caroline E. Robertson
- grid.254880.30000 0001 2179 2404Department of Psychology and Brain Sciences, Dartmouth College, Hanover, NH USA
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50
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DiNicola LM, Buckner RL. Precision Estimates of Parallel Distributed Association Networks: Evidence for Domain Specialization and Implications for Evolution and Development. Curr Opin Behav Sci 2021; 40:120-129. [PMID: 34263017 DOI: 10.1016/j.cobeha.2021.03.029] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Humans can reason about other minds, comprehend language and imagine. These abilities depend on association regions that exhibit evolutionary expansion and prolonged postnatal development. Precision maps within individuals reveal these expanded zones are populated by multiple specialized networks that each possess a spatially distributed motif but remain anatomically separated throughout the cortex for language, social and mnemonic / spatial functions. Rather than converge on multi-domain regions or hubs, these networks include distinct regions within rostral prefrontal and temporal association zones. To account for these observations, we propose the expansion-fractionation-specialization (EFS) hypothesis: evolutionary expansion of human association cortex may have allowed for an archetype distributed network to fractionate into multiple specialized networks. Human development may recapitulate fractionation and specialization when these abilities emerge.
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Affiliation(s)
- Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138 USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138 USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129 USA.,Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129 USA
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