1
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Wang X, Krieger-Redwood K, Cui Y, Smallwood J, Du Y, Jefferies E. Macroscale brain states support the control of semantic cognition. Commun Biol 2024; 7:926. [PMID: 39090387 PMCID: PMC11294576 DOI: 10.1038/s42003-024-06630-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 07/24/2024] [Indexed: 08/04/2024] Open
Abstract
A crucial aim in neuroscience is to understand how the human brain adapts to varying cognitive demands. This study investigates network reconfiguration during controlled semantic retrieval in differing contexts. We analyze brain responses to two semantic tasks of varying difficulty - global association and feature matching judgments - which are contrasted with non-semantic tasks on the cortical surface and within a whole-brain state space. Demanding semantic association tasks elicit activation in anterior prefrontal and temporal regions, while challenging semantic feature matching and non-semantic tasks predominantly activate posterior regions. Task difficulty also modulates activation along different dimensions of functional organization, suggesting different mechanisms of cognitive control. More demanding semantic association judgments engage cognitive control and default mode networks together, while feature matching and non-semantic tasks are skewed towards cognitive control networks. These findings highlight the brain's dynamic ability to tailor its networks to support diverse neurocognitive states, enriching our understanding of controlled cognition.
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Affiliation(s)
- Xiuyi Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China.
- Department of Psychology, University of York, Heslington, York, YO10 5DD, UK.
| | | | - Yanni Cui
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
| | | | - Yi Du
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, 200031, China.
| | - Elizabeth Jefferies
- Department of Psychology, University of York, Heslington, York, YO10 5DD, UK.
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2
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Balgova E, Diveica V, Jackson RL, Binney RJ. Overlapping neural correlates underpin theory of mind and semantic cognition: Evidence from a meta-analysis of 344 functional neuroimaging studies. Neuropsychologia 2024; 200:108904. [PMID: 38759780 DOI: 10.1016/j.neuropsychologia.2024.108904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/21/2024] [Accepted: 05/06/2024] [Indexed: 05/19/2024]
Abstract
Key unanswered questions for cognitive neuroscience include whether social cognition is underpinned by specialised brain regions and to what extent it simultaneously depends on more domain-general systems. Until we glean a better understanding of the full set of contributions made by various systems, theories of social cognition will remain fundamentally limited. In the present study, we evaluate a recent proposal that semantic cognition plays a crucial role in supporting social cognition. While previous brain-based investigations have focused on dissociating these two systems, our primary aim was to assess the degree to which the neural correlates are overlapping, particularly within two key regions, the anterior temporal lobe (ATL) and the temporoparietal junction (TPJ). We focus on activation associated with theory of mind (ToM) and adopt a meta-analytic activation likelihood approach to synthesise a large set of functional neuroimaging studies and compare their results with studies of semantic cognition. As a key consideration, we sought to account for methodological differences across the two sets of studies, including the fact that ToM studies tend to use nonverbal stimuli while the semantics literature is dominated by language-based tasks. Overall, we observed consistent overlap between the two sets of brain regions, especially in the ATL and TPJ. This supports the claim that tasks involving ToM draw upon more general semantic retrieval processes. We also identified activation specific to ToM in the right TPJ, bilateral anterior mPFC, and right precuneus. This is consistent with the view that, nested amongst more domain-general systems, there is specialised circuitry that is tuned to social processes.
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Affiliation(s)
- Eva Balgova
- Cognitive Neuroscience Institute, Department of Psychology, Bangor University, Gwynedd, Wales, UK; Department of Psychology, Aberystwyth University, Ceredigion, Wales, UK
| | - Veronica Diveica
- Cognitive Neuroscience Institute, Department of Psychology, Bangor University, Gwynedd, Wales, UK; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Rebecca L Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, Heslington, York, UK
| | - Richard J Binney
- Cognitive Neuroscience Institute, Department of Psychology, Bangor University, Gwynedd, Wales, UK.
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3
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Luppi AI, Mediano PAM, Rosas FE, Allanson J, Pickard J, Carhart-Harris RL, Williams GB, Craig MM, Finoia P, Owen AM, Naci L, Menon DK, Bor D, Stamatakis EA. A synergistic workspace for human consciousness revealed by Integrated Information Decomposition. eLife 2024; 12:RP88173. [PMID: 39022924 PMCID: PMC11257694 DOI: 10.7554/elife.88173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024] Open
Abstract
How is the information-processing architecture of the human brain organised, and how does its organisation support consciousness? Here, we combine network science and a rigorous information-theoretic notion of synergy to delineate a 'synergistic global workspace', comprising gateway regions that gather synergistic information from specialised modules across the human brain. This information is then integrated within the workspace and widely distributed via broadcaster regions. Through functional MRI analysis, we show that gateway regions of the synergistic workspace correspond to the human brain's default mode network, whereas broadcasters coincide with the executive control network. We find that loss of consciousness due to general anaesthesia or disorders of consciousness corresponds to diminished ability of the synergistic workspace to integrate information, which is restored upon recovery. Thus, loss of consciousness coincides with a breakdown of information integration within the synergistic workspace of the human brain. This work contributes to conceptual and empirical reconciliation between two prominent scientific theories of consciousness, the Global Neuronal Workspace and Integrated Information Theory, while also advancing our understanding of how the human brain supports consciousness through the synergistic integration of information.
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Affiliation(s)
- Andrea I Luppi
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- University Division of Anaesthesia, School of Clinical Medicine, University of CambridgeCambridgeUnited Kingdom
| | - Pedro AM Mediano
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Fernando E Rosas
- Center for Psychedelic Research, Department of Brain Science, Imperial College LondonLondonUnited Kingdom
- Center for Complexity Science, Imperial College LondonLondonUnited Kingdom
- Data Science Institute, Imperial College LondonLondonUnited Kingdom
| | - Judith Allanson
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- Department of Neurosciences, Cambridge University Hospitals NHS Foundation, Addenbrooke's HospitalCambridgeUnited Kingdom
| | - John Pickard
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- Wolfson Brain Imaging Centre, University of CambridgeCambridgeUnited Kingdom
- Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Addenbrooke's HospitalCambridgeUnited Kingdom
| | - Robin L Carhart-Harris
- Center for Psychedelic Research, Department of Brain Science, Imperial College LondonLondonUnited Kingdom
- Psychedelics Division - Neuroscape, Department of Neurology, University of CaliforniaSan FranciscoUnited States
| | - Guy B Williams
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- Wolfson Brain Imaging Centre, University of CambridgeCambridgeUnited Kingdom
| | - Michael M Craig
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
- University Division of Anaesthesia, School of Clinical Medicine, University of CambridgeCambridgeUnited Kingdom
| | - Paola Finoia
- Department of Clinical Neurosciences, University of CambridgeCambridgeUnited Kingdom
| | - Adrian M Owen
- Department of Psychology and Department of Physiology and Pharmacology, The Brain and Mind Institute, University of Western OntarioLondonCanada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Lloyd Building, Trinity CollegeDublinIreland
| | - David K Menon
- University Division of Anaesthesia, School of Clinical Medicine, University of CambridgeCambridgeUnited Kingdom
- Wolfson Brain Imaging Centre, University of CambridgeCambridgeUnited Kingdom
| | - Daniel Bor
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Emmanuel A Stamatakis
- University Division of Anaesthesia, School of Clinical Medicine, University of CambridgeCambridgeUnited Kingdom
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4
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Shashidhara S, Assem M, Glasser MF, Duncan J. Task and stimulus coding in the multiple-demand network. Cereb Cortex 2024; 34:bhae278. [PMID: 39004756 PMCID: PMC11246790 DOI: 10.1093/cercor/bhae278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/14/2024] [Accepted: 06/18/2024] [Indexed: 07/16/2024] Open
Abstract
In the human brain, a multiple-demand (MD) network plays a key role in cognitive control, with core components in lateral frontal, dorsomedial frontal and lateral parietal cortex, and multivariate activity patterns that discriminate the contents of many cognitive activities. In prefrontal cortex of the behaving monkey, different cognitive operations are associated with very different patterns of neural activity, while details of a particular stimulus are encoded as small variations on these basic patterns (Sigala et al, 2008). Here, using the advanced fMRI methods of the Human Connectome Project and their 360-region cortical parcellation, we searched for a similar result in MD activation patterns. In each parcel, we compared multivertex patterns for every combination of three tasks (working memory, task-switching, and stop-signal) and two stimulus classes (faces and buildings). Though both task and stimulus category were discriminated in every cortical parcel, the strength of discrimination varied strongly across parcels. The different cognitive operations of the three tasks were strongly discriminated in MD regions. Stimulus categories, in contrast, were most strongly discriminated in a large region of primary and higher visual cortex, and intriguingly, in both parietal and frontal lobe regions adjacent to core MD regions. In the monkey, frontal neurons show a strong pattern of nonlinear mixed selectivity, with activity reflecting specific conjunctions of task events. In our data, however, there was limited evidence for mixed selectivity; throughout the brain, discriminations of task and stimulus combined largely linearly, with a small nonlinear component. In MD regions, human fMRI data recapitulate some but not all aspects of electrophysiological data from nonhuman primates.
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Affiliation(s)
- Sneha Shashidhara
- Center for Social and Behaviour Change, Ashoka University, Sonipat, 131029, India
- MRC Cognition and Brain Sciences Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB27EF, United Kingdom
| | - Moataz Assem
- MRC Cognition and Brain Sciences Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB27EF, United Kingdom
| | - Matthew F Glasser
- Departments of Radiology and 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 CB27EF, United Kingdom
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5
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Kauf C, Kim HS, Lee EJ, Jhingan N, Selena She J, Taliaferro M, Gibson E, Fedorenko E. Linguistic inputs must be syntactically parsable to fully engage the language network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.21.599332. [PMID: 38948870 PMCID: PMC11212959 DOI: 10.1101/2024.06.21.599332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Human language comprehension is remarkably robust to ill-formed inputs (e.g., word transpositions). This robustness has led some to argue that syntactic parsing is largely an illusion, and that incremental comprehension is more heuristic, shallow, and semantics-based than is often assumed. However, the available data are also consistent with the possibility that humans always perform rule-like symbolic parsing and simply deploy error correction mechanisms to reconstruct ill-formed inputs when needed. We put these hypotheses to a new stringent test by examining brain responses to a) stimuli that should pose a challenge for syntactic reconstruction but allow for complex meanings to be built within local contexts through associative/shallow processing (sentences presented in a backward word order), and b) grammatically well-formed but semantically implausible sentences that should impede semantics-based heuristic processing. Using a novel behavioral syntactic reconstruction paradigm, we demonstrate that backward-presented sentences indeed impede the recovery of grammatical structure during incremental comprehension. Critically, these backward-presented stimuli elicit a relatively low response in the language areas, as measured with fMRI. In contrast, semantically implausible but grammatically well-formed sentences elicit a response in the language areas similar in magnitude to naturalistic (plausible) sentences. In other words, the ability to build syntactic structures during incremental language processing is both necessary and sufficient to fully engage the language network. Taken together, these results provide strongest to date support for a generalized reliance of human language comprehension on syntactic parsing.
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Affiliation(s)
- Carina Kauf
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Hee So Kim
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Elizabeth J. Lee
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Niharika Jhingan
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Jingyuan Selena She
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Maya Taliaferro
- Department of Psychology, New York University, New York, NY 10012 USA
| | - Edward Gibson
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- The Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA 02138 USA
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6
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Wolna A, Szewczyk J, Diaz M, Domagalik A, Szwed M, Wodniecka Z. Tracking Components of Bilingual Language Control in Speech Production: An fMRI Study Using Functional Localizers. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:315-340. [PMID: 38832359 PMCID: PMC11093400 DOI: 10.1162/nol_a_00128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 11/13/2023] [Indexed: 06/05/2024]
Abstract
When bilingual speakers switch back to speaking in their native language (L1) after having used their second language (L2), they often experience difficulty in retrieving words in their L1. This phenomenon is referred to as the L2 after-effect. We used the L2 after-effect as a lens to explore the neural bases of bilingual language control mechanisms. Our goal was twofold: first, to explore whether bilingual language control draws on domain-general or language-specific mechanisms; second, to investigate the precise mechanism(s) that drive the L2 after-effect. We used a precision fMRI approach based on functional localizers to measure the extent to which the brain activity that reflects the L2 after-effect overlaps with the language network (Fedorenko et al., 2010) and the domain-general multiple demand network (Duncan, 2010), as well as three task-specific networks that tap into interference resolution, lexical retrieval, and articulation. Forty-two Polish-English bilinguals participated in the study. Our results show that the L2 after-effect reflects increased engagement of domain-general but not language-specific resources. Furthermore, contrary to previously proposed interpretations, we did not find evidence that the effect reflects increased difficulty related to lexical access, articulation, and the resolution of lexical interference. We propose that difficulty of speech production in the picture naming paradigm-manifested as the L2 after-effect-reflects interference at a nonlinguistic level of task schemas or a general increase of cognitive control engagement during speech production in L1 after L2.
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Affiliation(s)
- Agata Wolna
- Institute of Psychology, Jagiellonian University, Kraków, Poland
| | - Jakub Szewczyk
- Institute of Psychology, Jagiellonian University, Kraków, Poland
- Donders Institute for Brain Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Michele Diaz
- Social, Life, and Engineering Sciences Imaging Center, Pennsylvania State University, Pennsylvania, USA
| | | | - Marcin Szwed
- Institute of Psychology, Jagiellonian University, Kraków, Poland
| | - Zofia Wodniecka
- Institute of Psychology, Jagiellonian University, Kraków, Poland
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7
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Dworetsky A, Seitzman BA, Adeyemo B, Nielsen AN, Hatoum AS, Smith DM, Nichols TE, Neta M, Petersen SE, Gratton C. Two common and distinct forms of variation in human functional brain networks. Nat Neurosci 2024; 27:1187-1198. [PMID: 38689142 PMCID: PMC11248096 DOI: 10.1038/s41593-024-01618-2] [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: 02/28/2023] [Accepted: 03/07/2024] [Indexed: 05/02/2024]
Abstract
The cortex has a characteristic layout with specialized functional areas forming distributed large-scale networks. However, substantial work shows striking variation in this organization across people, which relates to differences in behavior. While most previous work treats individual differences as linked to boundary shifts between the borders of regions, here we show that cortical 'variants' also occur at a distance from their typical position, forming ectopic intrusions. Both 'border' and 'ectopic' variants are common across individuals, but differ in their location, network associations, properties of subgroups of individuals, activations during tasks, and prediction of behavioral phenotypes. Border variants also track significantly more with shared genetics than ectopic variants, suggesting a closer link between ectopic variants and environmental influences. This work argues that these two dissociable forms of variation-border shifts and ectopic intrusions-must be separately accounted for in the analysis of individual differences in cortical systems across people.
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Affiliation(s)
- Ally Dworetsky
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychology, Florida State University, Tallahassee, FL, USA
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Benjamin A Seitzman
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ashley N Nielsen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Alexander S Hatoum
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Derek M Smith
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Neurology, Division of Cognitive Neurology/Neuropsychology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thomas E Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Maital Neta
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology, and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Steven E 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
| | - Caterina Gratton
- Department of Psychology, Florida State University, Tallahassee, FL, USA.
- Department of Psychology, Northwestern University, Evanston, IL, USA.
- Neuroscience Program, Florida State University, Tallahassee, FL, USA.
- Department of Neurology, Northwestern University, Evanston, IL, USA.
- Interdepartmental Neuroscience Program, Northwestern University, Evanston, IL, USA.
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8
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Wang X, Krieger-Redwood K, Lyu B, Lowndes R, Wu G, Souter NE, Wang X, Kong R, Shafiei G, Bernhardt BC, Cui Z, Smallwood J, Du Y, Jefferies E. The Brain's Topographical Organization Shapes Dynamic Interaction Patterns That Support Flexible Behavior Based on Rules and Long-Term Knowledge. J Neurosci 2024; 44:e2223232024. [PMID: 38527807 PMCID: PMC11140685 DOI: 10.1523/jneurosci.2223-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 03/14/2024] [Accepted: 03/17/2024] [Indexed: 03/27/2024] Open
Abstract
Adaptive behavior relies both on specific rules that vary across situations and stable long-term knowledge gained from experience. The frontoparietal control network (FPCN) is implicated in the brain's ability to balance these different influences on action. Here, we investigate how the topographical organization of the cortex supports behavioral flexibility within the FPCN. Functional properties of this network might reflect its juxtaposition between the dorsal attention network (DAN) and the default mode network (DMN), two large-scale systems implicated in top-down attention and memory-guided cognition, respectively. Our study tests whether subnetworks of FPCN are topographically proximal to the DAN and the DMN, respectively, and how these topographical differences relate to functional differences: the proximity of each subnetwork is anticipated to play a pivotal role in generating distinct cognitive modes relevant to working memory and long-term memory. We show that FPCN subsystems share multiple anatomical and functional similarities with their neighboring systems (DAN and DMN) and that this topographical architecture supports distinct interaction patterns that give rise to different patterns of functional behavior. The FPCN acts as a unified system when long-term knowledge supports behavior but becomes segregated into discrete subsystems with different patterns of interaction when long-term memory is less relevant. In this way, our study suggests that the topographical organization of the FPCN and the connections it forms with distant regions of cortex are important influences on how this system supports flexible behavior.
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Affiliation(s)
- Xiuyi Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Katya Krieger-Redwood
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Baihan Lyu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Rebecca Lowndes
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Guowei Wu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nicholas E Souter
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Xiaokang Wang
- Department of Biomedical Engineering, University of California, Davis, California 95616
| | - Ru Kong
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Jonathan Smallwood
- Department of Psychology, Queens University, Kingston, Ontario K7L 3N6, Canada
| | - Yi Du
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
- Chinese Institute for Brain Research, Beijing 102206, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai 200031, China
| | - Elizabeth Jefferies
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
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9
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Borne A, Lemaitre C, Bulteau C, Baciu M, Perrone-Bertolotti M. Unveiling the cognitive network organization through cognitive performance. Sci Rep 2024; 14:11645. [PMID: 38773246 PMCID: PMC11109237 DOI: 10.1038/s41598-024-62234-5] [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: 11/17/2023] [Accepted: 05/15/2024] [Indexed: 05/23/2024] Open
Abstract
The evaluation of cognitive functions interactions has become increasingly implemented in the cognition exploration. In the present study, we propose to examine the organization of the cognitive network in healthy participants through the analysis of behavioral performances in several cognitive domains. Specifically, we aim to explore cognitive interactions profiles, in terms of cognitive network, and as a function of participants' handedness. To this end, we proposed several behavioral tasks evaluating language, memory, executive functions, and social cognition performances in 175 young healthy right-handed and left-handed participants and we analyzed cognitive scores, from a network perspective, using graph theory. Our results highlight the existence of intricate interactions between cognitive functions both within and beyond the same cognitive domain. Language functions are interrelated with executive functions and memory in healthy cognitive functioning and assume a central role in the cognitive network. Interestingly, for similar high performance, our findings unveiled differential organizations within the cognitive network between right-handed and left-handed participants, with variations observed both at a global and nodal level. This original integrative network approach to the study of cognition provides new insights into cognitive interactions and modulations. It allows a more global understanding and consideration of cognitive functioning, from which complex behaviors emerge.
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Affiliation(s)
- A Borne
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France
| | - C Lemaitre
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France
| | - C Bulteau
- Service de Neurochirurgie Pédiatrique, Hôpital Fondation Adolphe de Rothschild, 75019, Paris, France
- MC2 Lab, Institut de Psychologie, Université de Paris-Cité, 92100, Boulogne-Billancourt, France
| | - M Baciu
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France
| | - M Perrone-Bertolotti
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France.
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10
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Chiou R, Branzi FM, Krieger-Redwood K, Jefferies E. Dissecting the neuroanatomy of creativity and curiosity: The subdivisions within networks matter. Behav Brain Sci 2024; 47:e96. [PMID: 38770872 DOI: 10.1017/s0140525x23003473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Ivancovsky et al. argue that the neurocognitive mechanisms of creativity and curiosity both rely on the interplay among brain networks. Research to date demonstrates that such inter-network dynamics are further complicated by functional fractionation within networks. Investigating how networks subdivide and reconfigure in service of a task offers insights about the precise anatomy that underpins creative and curious behaviour.
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Affiliation(s)
- Rocco Chiou
- School of Psychology, University of Surrey, Guildford, UK https://roccochiou.weebly.com/
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
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11
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Fedorenko E, Ivanova AA, Regev TI. The language network as a natural kind within the broader landscape of the human brain. Nat Rev Neurosci 2024; 25:289-312. [PMID: 38609551 DOI: 10.1038/s41583-024-00802-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2024] [Indexed: 04/14/2024]
Abstract
Language behaviour is complex, but neuroscientific evidence disentangles it into distinct components supported by dedicated brain areas or networks. In this Review, we describe the 'core' language network, which includes left-hemisphere frontal and temporal areas, and show that it is strongly interconnected, independent of input and output modalities, causally important for language and language-selective. We discuss evidence that this language network plausibly stores language knowledge and supports core linguistic computations related to accessing words and constructions from memory and combining them to interpret (decode) or generate (encode) linguistic messages. We emphasize that the language network works closely with, but is distinct from, both lower-level - perceptual and motor - mechanisms and higher-level systems of knowledge and reasoning. The perceptual and motor mechanisms process linguistic signals, but, in contrast to the language network, are sensitive only to these signals' surface properties, not their meanings; the systems of knowledge and reasoning (such as the system that supports social reasoning) are sometimes engaged during language use but are not language-selective. This Review lays a foundation both for in-depth investigations of these different components of the language processing pipeline and for probing inter-component interactions.
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Affiliation(s)
- Evelina Fedorenko
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA.
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
- The Program in Speech and Hearing in Bioscience and Technology, Harvard University, Cambridge, MA, USA.
| | - Anna A Ivanova
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA
| | - Tamar I Regev
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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12
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Zhang X, Wang Y, Yang X, Yang Y. The spontaneous activities of the multiple demand network are related to individual differences in indirect replies comprehension. Behav Brain Res 2024; 469:115021. [PMID: 38692358 DOI: 10.1016/j.bbr.2024.115021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/16/2024] [Accepted: 04/26/2024] [Indexed: 05/03/2024]
Abstract
This study aims to investigate the brain networks engaged in the comprehension of indirect language, as well as the individual difference in this capacity. Specially, we aim to determine whether the difference is solely influenced by the difference in individuals' default network (DN)/language network or whether it also relies on the networks associated with processing of complex cognitive tasks, particularly the multiple demand network (MDN). Conversational indirectness scale (CIS) scores in the interpretation dimension were used as a behavioral indicator of the indirect comprehension tendency. Reading time difference between indirect replies and direct replies collected through a self-paced reading experiment was deemed as a behavioral indicator of comprehension speed of indirect replies comprehension. The two behavioral indicators were combined with resting-state functional magnetic resonance imaging (rs-fMRI). The behaviour-rfMRI analysis showed that ALFF value of right SPL and the functional connectivity (FC) between the right SPL and right IPL/SMA/ITG/Precuneus/bilateral IFG were positively correlated with the interpretation dimension of CIS scores. In addition, the ALFF value of right fusiform gyrus, the FC between the right fusiform gyrus and right precuneus, and the FCs between right SPL and right IPL/Precuneus/IFG were negatively correlated with indirect replies comprehension speed. Overlapping of these regions with large-scale brain network revealed that the right SPL was mainly located in the MDN, and the right fusiform gyrus was mainly located in the language network. Additionally, the areas showing functional connectivity with these regions were primarily located in the MDN, with a smaller subset located in the DN. Our findings suggest that the ability of individuals to actively and rapidly acquire indirect meaning relies not only on the support of the DN and the language network, but also requires collective support from the MDN.
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Affiliation(s)
- Xiuping Zhang
- School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Yizhu Wang
- School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Xiaohong Yang
- Department of Psychology, Renmin University of China, Beijing 100872, China; Jiangsu Collaborative Innovation Center for Language Ability, Jiangsu Normal University, Xuzhou, China.
| | - Yufang Yang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
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13
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Freund MC, Chen R, Chen G, Braver TS. Complementary benefits of multivariate and hierarchical models for identifying individual differences in cognitive control. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.591032. [PMID: 38712215 PMCID: PMC11071497 DOI: 10.1101/2024.04.24.591032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Understanding individual differences in cognitive control is a central goal in psychology and neuroscience. Reliably measuring these differences, however, has proven extremely challenging, at least when using standard measures in cognitive neuroscience such as response times or task-based fMRI activity. While prior work has pinpointed the source of the issue - the vast amount of cross-trial variability within these measures - no study has rigorously evaluated potential solutions. Here, we do so with one potential way forward: an analytic framework that combines hierarchical Bayesian modeling with multivariate decoding of trial-level fMRI data. Using this framework and longitudinal data from the Dual Mechanisms of Cognitive Control project, we estimated individuals' neural responses associated with cognitive control within a color-word Stroop task, then assessed the reliability of these individuals' responses across a time interval of several months. We show that in many prefrontal and parietal brain regions, test-retest reliability was near maximal, and that only hierarchical models were able to reveal this state of affairs. Further, when compared to traditional univariate contrasts, multivariate decoding enabled individual-level correlations to be estimated with significantly greater precision. We specifically link these improvements in precision to the optimized suppression of cross-trial variability in decoding. Together, these findings not only indicate that cognitive control-related neural responses individuate people in a highly stable manner across time, but also suggest that integrating hierarchical and multivariate models provides a powerful approach for investigating individual differences in cognitive control, one that can effectively address the issue of high-variability measures.
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Affiliation(s)
- Michael C. Freund
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University
- Department of Psychological & Brain Sciences, Washington University in St. Louis
| | - Ruiqi Chen
- Division of Biology and Biomedical Sciences, Washington University in St. Louis
| | - Gang Chen
- Scientific and Statistical Computing Core, NIMH, NIH, Bethesda, MD, USA
| | - Todd S. Braver
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University
- Department of Psychological & Brain Sciences, Washington University in St. Louis
- Department of Radiology, Washington University in St. Louis
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14
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Jackson JB, Rich AN, Moerel D, Teichmann L, Duncan J, Woolgar A. Domain general frontoparietal regions show modality-dependent coding of auditory and visual rules. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.04.583318. [PMID: 38903119 PMCID: PMC11188079 DOI: 10.1101/2024.03.04.583318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
A defining feature of human cognition is our ability to respond flexibly to what we see and hear, changing how we respond depending on our current goals. In fact, we can rapidly associate almost any input stimulus with any arbitrary behavioural response. This remarkable ability is thought to depend on a frontoparietal "multiple demand" circuit which is engaged by many types of cognitive demand and widely referred to as domain general. However, it is not clear how responses to multiple input modalities are structured within this system. Domain generality could be achieved by holding information in an abstract form that generalises over input modality, or in a modality-tagged form, which uses similar resources but produces unique codes to represent the information in each modality. We used a stimulus-response task, with conceptually identical rules in two sensory modalities (visual and auditory), to distinguish between these possibilities. Multivariate decoding of functional magnetic resonance imaging data showed that representations of visual and auditory rules recruited overlapping neural resources but were expressed in modality-tagged non-generalisable neural codes. Our data suggest that this frontoparietal system may draw on the same or similar resources to solve multiple tasks, but does not create modality-general representations of task rules, even when those rules are conceptually identical between domains.
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Affiliation(s)
- J. B. Jackson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - A. N. Rich
- Perception in Action Research Centre & School of Psychological Sciences, Macquarie University, Australia
| | - D. Moerel
- School of Psychology, University of Sydney, Sydney, NSW, Australia
| | - L. Teichmann
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - J. Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - A. Woolgar
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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15
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Duncan J. Building cognitive functions from distributed brain activity. Neuron 2024; 112:692-693. [PMID: 38452737 DOI: 10.1016/j.neuron.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 03/09/2024]
Abstract
With recordings from temporal, parietal, and frontal regions of the behaving monkey brain, accompanied by a powerful method for optogenetic silencing of the frontal region, Mendoza-Halliday et al. compare network functions for working memory and visual selective attention.
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Affiliation(s)
- John Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
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16
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Yang G, Wu H, Li Q, Liu X, Fu Z, Jiang J. Dorsolateral prefrontal activity supports a cognitive space organization of cognitive control. eLife 2024; 12:RP87126. [PMID: 38446535 PMCID: PMC10942645 DOI: 10.7554/elife.87126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024] Open
Abstract
Cognitive control resolves conflicts between task-relevant and -irrelevant information to enable goal-directed behavior. As conflicts can arise from different sources (e.g., sensory input, internal representations), how a limited set of cognitive control processes can effectively address diverse conflicts remains a major challenge. Based on the cognitive space theory, different conflicts can be parameterized and represented as distinct points in a (low-dimensional) cognitive space, which can then be resolved by a limited set of cognitive control processes working along the dimensions. It leads to a hypothesis that conflicts similar in their sources are also represented similarly in the cognitive space. We designed a task with five types of conflicts that could be conceptually parameterized. Both human performance and fMRI activity patterns in the right dorsolateral prefrontal cortex support that different types of conflicts are organized based on their similarity, thus suggesting cognitive space as a principle for representing conflicts.
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Affiliation(s)
- Guochun Yang
- CAS Key Laboratory of Behavioral Science, Institute of PsychologyBeijingChina
- Department of Psychology, University of Chinese Academy of SciencesBeijingChina
- Department of Psychological and Brain Sciences, University of IowaIowa CityUnited States
- Cognitive Control Collaborative, University of IowaIowa CityUnited States
| | - Haiyan Wu
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of MacauMacauChina
| | - Qi Li
- Beijing Key Laboratory of Learning and Cognition, School of Psychology, Capital Normal UniversityBeijingChina
| | - Xun Liu
- CAS Key Laboratory of Behavioral Science, Institute of PsychologyBeijingChina
- Department of Psychology, University of Chinese Academy of SciencesBeijingChina
| | - Zhongzheng Fu
- Department of Neurological Surgery, Unversity of Texas Southwestern Medical CenterDallasUnited States
| | - Jiefeng Jiang
- Department of Psychological and Brain Sciences, University of IowaIowa CityUnited States
- Cognitive Control Collaborative, University of IowaIowa CityUnited States
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17
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Willbrand EH, Jackson S, Chen S, Hathaway CB, Voorhies WI, Bunge SA, Weiner KS. Sulcal variability in anterior lateral prefrontal cortex contributes to variability in reasoning performance among young adults. Brain Struct Funct 2024; 229:387-402. [PMID: 38184493 DOI: 10.1007/s00429-023-02734-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 11/12/2023] [Indexed: 01/08/2024]
Abstract
Identifying structure-function correspondences is a major goal among biologists, cognitive neuroscientists, and brain mappers. Recent studies have identified relationships between performance on cognitive tasks and the presence or absence of small, shallow indentations, or sulci, of the human brain. Building on the previous finding that the presence of the ventral para-intermediate frontal sulcus (pimfs-v) in the left anterior lateral prefrontal cortex (aLPFC) was related to reasoning task performance in children and adolescents, we tested whether this relationship extended to a different sample, age group, and reasoning task. As predicted, the presence of this aLPFC sulcus was also associated with higher reasoning scores in young adults (ages 22-36). These findings have not only direct developmental, but also evolutionary relevance-as recent work shows that the pimfs-v is exceedingly rare in chimpanzees. Thus, the pimfs-v is a key developmental, cognitive, and evolutionarily relevant feature that should be considered in future studies examining how the complex relationships among multiscale anatomical and functional features of the brain give rise to abstract thought.
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Affiliation(s)
- Ethan H Willbrand
- Medical Scientist Training Program, School of Medicine and Public Health, University of WI-Madison, Madison, WI, USA
| | - Samantha Jackson
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Szeshuen Chen
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
| | | | - Willa I Voorhies
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
| | - Silvia A Bunge
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA.
| | - Kevin S Weiner
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA.
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18
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Malik-Moraleda S, Jouravlev O, Taliaferro M, Mineroff Z, Cucu T, Mahowald K, Blank IA, Fedorenko E. Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI. Cereb Cortex 2024; 34:bhae049. [PMID: 38466812 PMCID: PMC10928488 DOI: 10.1093/cercor/bhae049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 03/13/2024] Open
Abstract
How do polyglots-individuals who speak five or more languages-process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants' high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language network's response magnitude scales with the degree of engagement of linguistic computations (e.g. related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages coexist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.
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Affiliation(s)
- Saima Malik-Moraleda
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114, United States
| | - Olessia Jouravlev
- Department of Cognitive Science, Carleton University, Ottawa K1S 5B6, Canada
| | - Maya Taliaferro
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
| | - Zachary Mineroff
- Eberly Center, Carnegie Mellon University, Pittsburgh, PA 15289, United States
| | - Theodore Cucu
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15289, United States
| | - Kyle Mahowald
- Department of Linguistics, The University of Texas at Austin, Austin, TX 78712, United States
| | - Idan A Blank
- Department of Psychology, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114, United States
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19
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Naqvi NH, Srivastava AB, Sanchez-Peña J, Lee JK, Drysdale AT, Mariani JJ, Ochsner KN, Morgenstern J, Patel GH, Levin FR. Neural correlates of drinking reduction during a clinical trial of cognitive behavioral therapy for alcohol use disorder. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024; 48:260-272. [PMID: 38225187 PMCID: PMC11015435 DOI: 10.1111/acer.15259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 12/05/2023] [Accepted: 12/17/2023] [Indexed: 01/17/2024]
Abstract
BACKGROUND Cognitive behavioral therapy (CBT) is an effective treatment for alcohol use disorder (AUD). We hypothesized that the dorsolateral prefrontal cortex (DLPFC), a region implicated in cognitive control and goal-directed behavior, plays a role in behavior change during CBT by facilitating the regulation of craving (ROC). METHODS Treatment-seeking participants with AUD (N = 22) underwent functional magnetic resonance imaging (fMRI) scanning both before and after a 12-week, single-arm trial of CBT, using an ROC task that was previously shown to engage the DLPFC. RESULTS We found that both the percentage of heavy drinking days (PHDD) and the overall self-reported alcohol craving measured during the ROC task were significantly reduced from pre- to post-CBT. However, we did not find significant changes over time in either the ability to regulate craving or regulation-related activity in any brain region. We found a significant 3-way interaction between the effects of cue-induced craving, cue-induced brain activity and timepoint of assessment (pre- or post-CBT) on PHDD in the left DLPFC. Follow-up analysis showed that cue-induced craving was associated with cue-induced activity in the left DLPFC among participants who ceased heavy drinking during CBT, both at pre-CBT and post-CBT timepoints. No such associations were present at either timepoint among participants who continued to drink heavily. CONCLUSIONS These results suggest that patients in whom DLPFC functioning is more strongly related to cue-induced craving may preferentially respond to CBT.
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Affiliation(s)
- Nasir H Naqvi
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, New York, USA
| | - A Benjamin Srivastava
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, New York, USA
| | - Juan Sanchez-Peña
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, New York, USA
| | - Jessica K Lee
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, New York, USA
| | - Andrew T Drysdale
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, New York, USA
| | - John J Mariani
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, New York, USA
| | - Kevin N Ochsner
- Department of Psychology, Columbia University, New York, New York, USA
| | - Jon Morgenstern
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra University/Northwell Health, Hempstead, New York, USA
| | - Gaurav H Patel
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, New York, USA
| | - Frances R Levin
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, New York, USA
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20
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Liu S, Ye H, Yang B, Li M, Cao F. A joint parcellation and boundary network with multi-rate-shared dilated graph attention for cortical surface parcellation. Med Biol Eng Comput 2024; 62:537-549. [PMID: 37945794 DOI: 10.1007/s11517-023-02942-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 09/27/2023] [Indexed: 11/12/2023]
Abstract
Cortical surface parcellation aims to segment the surface into anatomically and functionally significant regions, which are crucial for diagnosing and treating numerous neurological diseases. However, existing methods generally ignore the difficulty in learning labeling patterns of boundaries, hindering the performance of parcellation. To this end, this paper proposes a joint parcellation and boundary network (JPBNet) to promote the effectiveness of cortical surface parcellation. Its core is developing a multi-rate-shared dilated graph attention (MDGA) module and incorporating boundary learning into the parcellation process. The former, in particular, constructs a dilated graph attention strategy, extending the dilated convolution from regular data to irregular graph data. We fuse it with different dilated rates to extract context information in various scales by devising a shared graph attention layer. After that, a boundary enhancement module and a parcellation enhancement module based on graph attention mechanisms are built in each layer, forcing MDGA to capture informative and valuable features for boundary detection and parcellation tasks. Integrating MDGA, the boundary enhancement module, and the parcellation enhancement module at each layer to supervise boundary and parcellation information, an effective JPBNet is formed by stacking multiple layers. Experiments on the public dataset reveal that the proposed method outperforms comparison methods and performs well on boundaries for cortical surface parcellation.
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Affiliation(s)
- Siqi Liu
- College of Sciences, China Jiliang University, Hangzhou, 310018, China
| | - Hailiang Ye
- College of Sciences, China Jiliang University, Hangzhou, 310018, China.
| | - Bing Yang
- College of Sciences, China Jiliang University, Hangzhou, 310018, China
| | - Ming Li
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua, 321004, China
| | - Feilong Cao
- College of Sciences, China Jiliang University, Hangzhou, 310018, China.
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21
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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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22
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Malik-Moraleda S, Jouravlev O, Taliaferro M, Mineroff Z, Cucu T, Mahowald K, Blank IA, Fedorenko E. Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.19.524657. [PMID: 36711949 PMCID: PMC9882290 DOI: 10.1101/2023.01.19.524657] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
How do polyglots-individuals who speak five or more languages-process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher-proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants' high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language network's response magnitude scales with the degree of engagement of linguistic computations (e.g., related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages co-exist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.
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Affiliation(s)
- Saima Malik-Moraleda
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114
| | - Olessia Jouravlev
- Department of Cognitive Science, Carleton University, Ottawa, Canada, K1S 5B6
| | - Maya Taliaferro
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
| | | | - Theodore Cucu
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15289
| | - Kyle Mahowald
- Department of Linguistics, The University of Texas at Austin, Austin, TX 78712
| | - Idan A. Blank
- Department of Psychology, University of California Los Angeles, CA 90095
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114
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23
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Fornia L, Leonetti A, Puglisi G, Rossi M, Viganò L, Della Santa B, Simone L, Bello L, Cerri G. The parietal architecture binding cognition to sensorimotor integration: a multimodal causal study. Brain 2024; 147:297-310. [PMID: 37715997 PMCID: PMC10766244 DOI: 10.1093/brain/awad316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/18/2023] [Accepted: 08/10/2023] [Indexed: 09/18/2023] Open
Abstract
Despite human's praxis abilities are unique among primates, comparative observations suggest that these cognitive motor skills could have emerged from exploitation and adaptation of phylogenetically older building blocks, namely the parieto-frontal networks subserving prehension and manipulation. Within this framework, investigating to which extent praxis and prehension-manipulation overlap and diverge within parieto-frontal circuits could help in understanding how human cognition shapes hand actions. This issue has never been investigated by combining lesion mapping and direct electrophysiological approaches in neurosurgical patients. To this purpose, 79 right-handed left-brain tumour patient candidates for awake neurosurgery were selected based on inclusion criteria. First, a lesion mapping was performed in the early postoperative phase to localize the regions associated with an impairment in praxis (imitation of meaningless and meaningful intransitive gestures) and visuo-guided prehension (reaching-to-grasping) abilities. Then, lesion results were anatomically matched with intraoperatively identified cortical and white matter regions, whose direct electrical stimulation impaired the Hand Manipulation Task. The lesion mapping analysis showed that prehension and praxis impairments occurring in the early postoperative phase were associated with specific parietal sectors. Dorso-mesial parietal resections, including the superior parietal lobe and precuneus, affected prehension performance, while resections involving rostral intraparietal and inferior parietal areas affected praxis abilities (covariate clusters, 5000 permutations, cluster-level family-wise error correction P < 0.05). The dorsal bank of the rostral intraparietal sulcus was associated with both prehension and praxis (overlap of non-covariate clusters). Within praxis results, while resection involving inferior parietal areas affected mainly the imitation of meaningful gestures, resection involving intraparietal areas affected both meaningless and meaningful gesture imitation. In parallel, the intraoperative electrical stimulation of the rostral intraparietal and the adjacent inferior parietal lobe with their surrounding white matter during the hand manipulation task evoked different motor impairments, i.e. the arrest and clumsy patterns, respectively. When integrating lesion mapping and intraoperative stimulation results, it emerges that imitation of praxis gestures first depends on the integrity of parietal areas within the dorso-ventral stream. Among these areas, the rostral intraparietal and the inferior parietal area play distinct roles in praxis and sensorimotor process controlling manipulation. Due to its visuo-motor 'attitude', the rostral intraparietal sulcus, putative human homologue of monkey anterior intraparietal, might enable the visuo-motor conversion of the observed gesture (direct pathway). Moreover, its functional interaction with the adjacent, phylogenetic more recent, inferior parietal areas might contribute to integrate the semantic-conceptual knowledge (indirect pathway) within the sensorimotor workflow, contributing to the cognitive upgrade of hand actions.
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Affiliation(s)
- Luca Fornia
- Department of Medical Biotechnology and Translational Medicine, MoCA Laboratory, Università degli Studi di Milano, Milano, 20122, Italy
| | - Antonella Leonetti
- Department of Oncology and Hemato-Oncology, Neurosurgical Oncology Unit, Università degli Studi di Milano, Milano, 20122, Italy
| | - Guglielmo Puglisi
- Department of Medical Biotechnology and Translational Medicine, MoCA Laboratory, Università degli Studi di Milano, Milano, 20122, Italy
| | - Marco Rossi
- Department of Medical Biotechnology and Translational Medicine, MoCA Laboratory, Università degli Studi di Milano, Milano, 20122, Italy
| | - Luca Viganò
- Department of Oncology and Hemato-Oncology, Neurosurgical Oncology Unit, Università degli Studi di Milano, Milano, 20122, Italy
| | - Bianca Della Santa
- Department of Medical Biotechnology and Translational Medicine, MoCA Laboratory, Università degli Studi di Milano, Milano, 20122, Italy
| | - Luciano Simone
- Department of Medicine and Surgery, Università Degli Studi di Parma, Parma, 43125, Italy
| | - Lorenzo Bello
- Department of Oncology and Hemato-Oncology, Neurosurgical Oncology Unit, Università degli Studi di Milano, Milano, 20122, Italy
| | - Gabriella Cerri
- Department of Medical Biotechnology and Translational Medicine, MoCA Laboratory, Università degli Studi di Milano, Milano, 20122, Italy
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24
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Wolna A, Szewczyk J, Diaz M, Domagalik A, Szwed M, Wodniecka Z. Domain-general and language-specific contributions to speech production in a second language: an fMRI study using functional localizers. Sci Rep 2024; 14:57. [PMID: 38168139 PMCID: PMC10761726 DOI: 10.1038/s41598-023-49375-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 12/07/2023] [Indexed: 01/05/2024] Open
Abstract
For bilinguals, speaking in a second language (L2) compared to the native language (L1) is usually more difficult. In this study we asked whether the difficulty in L2 production reflects increased demands imposed on domain-general or core language mechanisms. We compared the brain response to speech production in L1 and L2 within two functionally-defined networks in the brain: the Multiple Demand (MD) network and the language network. We found that speech production in L2 was linked to a widespread increase of brain activity in the domain-general MD network. The language network did not show a similarly robust differences in processing speech in the two languages, however, we found increased response to L2 production in the language-specific portion of the left inferior frontal gyrus (IFG). To further explore our results, we have looked at domain-general and language-specific response within the brain structures postulated to form a Bilingual Language Control (BLC) network. Within this network, we found a robust increase in response to L2 in the domain-general, but also in some language-specific voxels including in the left IFG. Our findings show that L2 production strongly engages domain-general mechanisms, but only affects language sensitive portions of the left IFG. These results put constraints on the current model of bilingual language control by precisely disentangling the domain-general and language-specific contributions to the difficulty in speech production in L2.
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Affiliation(s)
- Agata Wolna
- Institute of Psychology, Jagiellonian University, Ul. Ingardena 6, 30-060, Kraków, Poland.
| | - Jakub Szewczyk
- Institute of Psychology, Jagiellonian University, Ul. Ingardena 6, 30-060, Kraków, Poland
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Michele Diaz
- Social, Life, and Engineering Sciences Imaging Center, The Pennsylvania State University, Pennsylvania, USA
| | | | - Marcin Szwed
- Institute of Psychology, Jagiellonian University, Ul. Ingardena 6, 30-060, Kraków, Poland
| | - Zofia Wodniecka
- Institute of Psychology, Jagiellonian University, Ul. Ingardena 6, 30-060, Kraków, Poland.
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25
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Branzi FM, Lambon Ralph MA. Semantic-specific and domain-general mechanisms for integration and update of contextual information. Hum Brain Mapp 2023; 44:5547-5566. [PMID: 37787648 PMCID: PMC10619409 DOI: 10.1002/hbm.26454] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 07/26/2023] [Accepted: 08/02/2023] [Indexed: 10/04/2023] Open
Abstract
Recent research has highlighted the importance of domain-general processes and brain regions for language and semantic cognition. Yet, this has been mainly observed in executively demanding tasks, leaving open the question of the contribution of domain-general processes to natural language and semantic cognition. Using fMRI, we investigated whether neural processes reflecting context integration and context update-two key aspects of naturalistic language and semantic processing-are domain-specific versus domain-general. Thus, we compared neural responses during the integration of contextual information across semantic and non-semantic tasks. Whole-brain results revealed both shared (left posterior-dorsal inferior frontal gyrus, left posterior inferior temporal gyrus, and left dorsal angular gyrus/intraparietal sulcus) and distinct (left anterior-ventral inferior frontal gyrus, left anterior ventral angular gyrus, left posterior middle temporal gyrus for semantic control only) regions involved in context integration and update. Furthermore, data-driven functional connectivity analysis clustered domain-specific versus domain-general brain regions into distinct but interacting functional neural networks. These results provide a first characterisation of the neural processes required for context-dependent integration during language processing along the domain-specificity dimension, and at the same time, they bring new insights into the role of left posterior lateral temporal cortex and left angular gyrus for semantic cognition.
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Affiliation(s)
- Francesca M. Branzi
- Department of Psychological SciencesInstitute of Population Health, University of LiverpoolLiverpoolUK
- MRC Cognition & Brain Sciences UnitThe University of CambridgeCambridgeUK
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26
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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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27
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Seidlitz J, Mallard TT, Vogel JW, Lee YH, Warrier V, Ball G, Hansson O, Hernandez LM, Mandal AS, Wagstyl K, Lombardo MV, Courchesne E, Glessner JT, Satterthwaite TD, Bethlehem RAI, Bernstock JD, Tasaki S, Ng B, Gaiteri C, Smoller JW, Ge T, Gur RE, Gandal MJ, Alexander-Bloch AF. The molecular genetic landscape of human brain size variation. Cell Rep 2023; 42:113439. [PMID: 37963017 DOI: 10.1016/j.celrep.2023.113439] [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: 11/09/2022] [Revised: 06/13/2023] [Accepted: 10/27/2023] [Indexed: 11/16/2023] Open
Abstract
Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.
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Affiliation(s)
- Jakob Seidlitz
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA
| | - Jacob W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Younga H Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge CB2 1TN, UK; Department of Psychology, University of Cambridge, Cambridge CB2 1TN, UK
| | - Gareth Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, VIC 3052, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Melbourne, VIC 3052, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö P663+Q9, Sweden; Memory Clinic, Skåne University Hospital, Malmö P663+Q9, Sweden
| | - Leanna M Hernandez
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Ayan S Mandal
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, 38068 Rovereto, Italy
| | - Eric Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA 92093, USA; Autism Center of Excellence, University of California, San Diego, San Diego, CA 92093, USA
| | - Joseph T Glessner
- The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | | | - Joshua D Bernstock
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard University, Boston, MA 02115, USA; Department of Neurosurgery, Boston Children's Hospital, Harvard University, Boston, MA 02115, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Bernard Ng
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA; Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA; Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Raquel E Gur
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael J Gandal
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron F Alexander-Bloch
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
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28
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Hansen JY, Cauzzo S, Singh K, García-Gomar MG, Shine JM, Bianciardi M, Misic B. Integrating brainstem and cortical functional architectures. RESEARCH SQUARE 2023:rs.3.rs-3569352. [PMID: 38076888 PMCID: PMC10705693 DOI: 10.21203/rs.3.rs-3569352/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
The brainstem is a fundamental component of the central nervous system yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. Here we use high-resolution 7 Tesla fMRI to derive a functional connectome encompassing cortex as well as 58 brainstem nuclei spanning the midbrain, pons and medulla. We identify a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as multiple emergent phenomena including neurophysiological oscillatory rhythms, patterns of cognitive functional specialization, and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicate all findings using 3 Tesla data from the same participants. Collectively, we find that multiple organizational features of cortical activity can be traced back to the brainstem.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Parkinson’s Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - James M. Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard University, Boston, MA, USA
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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29
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Diveica V, Riedel MC, Salo T, Laird AR, Jackson RL, Binney RJ. Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity. Cereb Cortex 2023; 33:11384-11399. [PMID: 37833772 PMCID: PMC10690868 DOI: 10.1093/cercor/bhad373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 08/17/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.
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Affiliation(s)
- Veronica Diveica
- Department of Psychology & Cognitive Neuroscience Institute, Bangor University, Bangor, Wales LL57 2AS, United Kingdom
- Department of Neurology and Neurosurgery & Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Michael C Riedel
- Department of Physics, Florida International University, Miami, FL 33199, United States
| | - Taylor Salo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, United States
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL 33199, United States
| | - Rebecca L Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, York, YO10 5DD, United Kingdom
| | - Richard J Binney
- Department of Psychology & Cognitive Neuroscience Institute, Bangor University, Bangor, Wales LL57 2AS, United Kingdom
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30
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Karadachka K, Assem M, Mitchell DJ, Duncan J, Medendorp WP, Mars RB. Structural connectivity of the multiple demand network in humans and comparison to the macaque brain. Cereb Cortex 2023; 33:10959-10971. [PMID: 37798142 PMCID: PMC10646692 DOI: 10.1093/cercor/bhad314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 10/07/2023] Open
Abstract
Fluid intelligence encompasses a wide range of abilities such as working memory, problem-solving, and relational reasoning. In the human brain, these abilities are associated with the Multiple Demand Network, traditionally thought to involve combined activity of specific regions predominantly in the prefrontal and parietal cortices. However, the structural basis of the interactions between areas in the Multiple Demand Network, as well as their evolutionary basis among primates, remains largely unexplored. Here, we exploit diffusion MRI to elucidate the major white matter pathways connecting areas of the human core and extended Multiple Demand Network. We then investigate whether similar pathways can be identified in the putative homologous areas of the Multiple Demand Network in the macaque monkey. Finally, we contrast human and monkey networks using a recently proposed approach to compare different species' brains within a common organizational space. Our results indicate that the core Multiple Demand Network relies mostly on dorsal longitudinal connections and, although present in the macaque, these connections are more pronounced in the human brain. The extended Multiple Demand Network relies on distinct pathways and communicates with the core Multiple Demand Network through connections that also appear enhanced in the human compared with the macaque.
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Affiliation(s)
- Katrin Karadachka
- Donders Institute for Brain, Cognition and Behaviour, Faculty of Social Sciences, Radboud University Nijmegen, 6525HR Nijmegen, The Netherlands
| | - Moataz Assem
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom
| | - Daniel J Mitchell
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom
| | - John Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom
| | - W Pieter Medendorp
- Donders Institute for Brain, Cognition and Behaviour, Faculty of Social Sciences, Radboud University Nijmegen, 6525HR Nijmegen, The Netherlands
| | - Rogier B Mars
- Donders Institute for Brain, Cognition and Behaviour, Faculty of Social Sciences, Radboud University Nijmegen, 6525HR Nijmegen, The Netherlands
- Wellcome Centre for Integrative Neuroimaging Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford OX3 9DU, United Kingdom
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31
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Willbrand EH, Bunge SA, Weiner KS. Neuroanatomical and Functional Dissociations between Variably Present Anterior Lateral Prefrontal Sulci. J Cogn Neurosci 2023; 35:1846-1867. [PMID: 37677051 PMCID: PMC10586811 DOI: 10.1162/jocn_a_02049] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
The lateral prefrontal cortex (LPFC) is an evolutionarily expanded region in humans that is critical for numerous complex functions, many of which are largely hominoid specific. Although recent work shows that the presence or absence of specific sulci in anterior LPFC is associated with cognitive performance across age groups, it is unknown whether the presence of these structures relates to individual differences in the functional organization of LPFC. To fill this gap in knowledge, we leveraged multimodal neuroimaging data from two samples encompassing 82 young adult humans (aged 22-36 years) and show that the dorsal and ventral components of the paraintermediate frontal sulcus, or pimfs, present distinct morphological (surface area), architectural (thickness and myelination), and functional (resting-state connectivity networks) properties. We further contextualize the pimfs components within classic and modern cortical parcellations. Taken together, the dorsal and ventral pimfs components mark transitions in LPFC anatomy and function, across metrics and parcellations. These results emphasize that the pimfs is a critical structure to consider when examining individual differences in the anatomical and functional organization of LPFC and suggest that future individual-level parcellations could benefit from incorporating sulcal anatomy when delineating LPFC cortical regions.
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32
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Tuckute G, Sathe A, Srikant S, Taliaferro M, Wang M, Schrimpf M, Kay K, Fedorenko E. Driving and suppressing the human language network using large language models. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.16.537080. [PMID: 37090673 PMCID: PMC10120732 DOI: 10.1101/2023.04.16.537080] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Transformer models such as GPT generate human-like language and are highly predictive of human brain responses to language. Here, using fMRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict the magnitude of brain response associated with each sentence. Then, we use the model to identify new sentences that are predicted to drive or suppress responses in the human language network. We show that these model-selected novel sentences indeed strongly drive and suppress activity of human language areas in new individuals. A systematic analysis of the model-selected sentences reveals that surprisal and well-formedness of linguistic input are key determinants of response strength in the language network. These results establish the ability of neural network models to not only mimic human language but also noninvasively control neural activity in higher-level cortical areas, like the language network.
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Affiliation(s)
- Greta Tuckute
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Aalok Sathe
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Shashank Srikant
- Computer Science & Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- MIT-IBM Watson AI Lab, Cambridge, MA 02142, USA
| | - Maya Taliaferro
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Mingye Wang
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Martin Schrimpf
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Quest for Intelligence, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- Neuro-X Institute, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Kendrick Kay
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455 USA
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
- The Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA 02138 USA
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33
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Hansen JY, Cauzzo S, Singh K, García-Gomar MG, Shine JM, Bianciardi M, Misic B. Integrating brainstem and cortical functional architectures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564245. [PMID: 37961347 PMCID: PMC10634864 DOI: 10.1101/2023.10.26.564245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The brainstem is a fundamental component of the central nervous system yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. Here we use high-resolution 7 Tesla fMRI to derive a functional connectome encompassing cortex as well as 58 brainstem nuclei spanning the midbrain, pons and medulla. We identify a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as multiple emergent phenomena including neurophysiological oscillatory rhythms, patterns of cognitive functional specialization, and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicate all findings using 3 Tesla data from the same participants. Collectively, we find that multiple organizational features of cortical activity can be traced back to the brainstem.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Simone Cauzzo
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Parkinson’s Disease and Movement Disorders Unit, Center for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Kavita Singh
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - María Guadalupe García-Gomar
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Escuela Nacional de Estudios Superiores, Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - James M. Shine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Marta Bianciardi
- Brainstem Imaging Laboratory, Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard University, Boston, MA, USA
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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34
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Benn Y, Ivanova AA, Clark O, Mineroff Z, Seikus C, Silva JS, Varley R, Fedorenko E. The language network is not engaged in object categorization. Cereb Cortex 2023; 33:10380-10400. [PMID: 37557910 PMCID: PMC10545444 DOI: 10.1093/cercor/bhad289] [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: 09/27/2021] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 08/11/2023] Open
Abstract
The relationship between language and thought is the subject of long-standing debate. One claim states that language facilitates categorization of objects based on a certain feature (e.g. color) through the use of category labels that reduce interference from other, irrelevant features. Therefore, language impairment is expected to affect categorization of items grouped by a single feature (low-dimensional categories, e.g. "Yellow Things") more than categorization of items that share many features (high-dimensional categories, e.g. "Animals"). To test this account, we conducted two behavioral studies with individuals with aphasia and an fMRI experiment with healthy adults. The aphasia studies showed that selective low-dimensional categorization impairment was present in some, but not all, individuals with severe anomia and was not characteristic of aphasia in general. fMRI results revealed little activity in language-responsive brain regions during both low- and high-dimensional categorization; instead, categorization recruited the domain-general multiple-demand network (involved in wide-ranging cognitive tasks). Combined, results demonstrate that the language system is not implicated in object categorization. Instead, selective low-dimensional categorization impairment might be caused by damage to brain regions responsible for cognitive control. Our work adds to the growing evidence of the dissociation between the language system and many cognitive tasks in adults.
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Affiliation(s)
- Yael Benn
- Department of Psychology, Manchester Metropolitan University, Manchester M15 6BH, United Kingdom
| | - Anna A Ivanova
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
| | - Oliver Clark
- Department of Psychology, Manchester Metropolitan University, Manchester M15 6BH, United Kingdom
| | - Zachary Mineroff
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
| | - Chloe Seikus
- Division of Psychology & Language Sciences, University College London, London WC1E 6BT, UK
| | - Jack Santos Silva
- Division of Psychology & Language Sciences, University College London, London WC1E 6BT, UK
| | - Rosemary Varley
- Division of Psychology & Language Sciences, University College London, London WC1E 6BT, UK
| | - Evelina Fedorenko
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
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35
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Willbrand EH, Jackson S, Chen S, Hathaway CB, Voorhies WI, Bunge SA, Weiner KS. Sulcal variability in anterior lateral prefrontal cortex contributes to variability in reasoning performance among young adults. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.10.528061. [PMID: 36798378 PMCID: PMC9934691 DOI: 10.1101/2023.02.10.528061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
Identifying structure-function correspondences is a major goal among biologists, cognitive neuroscientists, and brain mappers. Recent studies have identified relationships between performance on cognitive tasks and the presence or absence of small, shallow indentations, or sulci, of the human brain. Building on the previous finding that the presence of one such sulcus in the left anterior lateral prefrontal cortex (aLPFC) was related to reasoning task performance in children and adolescents, we tested whether this relationship extended to a different sample, age group, and reasoning task. As predicted, the presence of this aLPFC sulcus-the ventral para-intermediate frontal sulcus-was also associated with higher reasoning scores in young adults (ages 22-36). These findings have not only direct developmental, but also evolutionary relevance-as recent work shows that the pimfs-v is exceedingly rare in chimpanzees. Thus, the pimfs-v is a novel developmental, cognitive, and evolutionarily relevant feature that should be considered in future studies examining how the complex relationships among multiscale anatomical and functional features of the brain give rise to abstract thought.
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Affiliation(s)
- Ethan H. Willbrand
- Medical Scientist Training Program, University of Wisconsin–Madison, Madison, WI USA
- School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI USA
| | - Samantha Jackson
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Szeshuen Chen
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
| | | | - Willa I. Voorhies
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
| | - Silvia A. Bunge
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
| | - Kevin S. Weiner
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
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36
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Kuhnke P, Kiefer M, Hartwigsen G. Conceptual representations in the default, control and attention networks are task-dependent and cross-modal. BRAIN AND LANGUAGE 2023; 244:105313. [PMID: 37595340 DOI: 10.1016/j.bandl.2023.105313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/03/2023] [Accepted: 08/10/2023] [Indexed: 08/20/2023]
Abstract
Conceptual knowledge is central to human cognition. Neuroimaging studies suggest that conceptual processing involves modality-specific and multimodal brain regions in a task-dependent fashion. However, it remains unclear (1) to what extent conceptual feature representations are also modulated by the task, (2) whether conceptual representations in multimodal regions are indeed cross-modal, and (3) how the conceptual system relates to the large-scale functional brain networks. To address these issues, we conducted multivariate pattern analyses on fMRI data. 40 participants performed three tasks-lexical decision, sound judgment, and action judgment-on written words. We found that (1) conceptual feature representations are strongly modulated by the task, (2) conceptual representations in several multimodal regions are cross-modal, and (3) conceptual feature retrieval involves the default, frontoparietal control, and dorsal attention networks. Conceptual representations in these large-scale networks are task-dependent and cross-modal. Our findings support theories that assume conceptual processing to rely on a flexible, multi-level architecture.
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Affiliation(s)
- Philipp Kuhnke
- Wilhelm Wundt Institute for Psychology, Leipzig University, Germany; Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | | | - Gesa Hartwigsen
- Wilhelm Wundt Institute for Psychology, Leipzig University, Germany; Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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37
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Jackson RL, Humphreys GF, Rice GE, Binney RJ, Lambon Ralph MA. A network-level test of the role of the co-activated default mode network in episodic recall and social cognition. Cortex 2023; 165:141-159. [PMID: 37285763 PMCID: PMC10284259 DOI: 10.1016/j.cortex.2022.12.016] [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: 02/21/2022] [Revised: 10/10/2022] [Accepted: 12/19/2022] [Indexed: 06/09/2023]
Abstract
Resting-state network research is extremely influential, yet the functions of many networks remain unknown. In part, this is due to typical (e.g., univariate) analyses independently testing the function of individual regions and not examining the full set of regions that form a network whilst co-activated. Connectivity is dynamic and the function of a region may change based on its current connections. Therefore, determining the function of a network requires assessment at this network-level. Yet popular theories implicating the default mode network (DMN) in episodic memory and social cognition, rest principally upon analyses performed at the level of individual brain regions. Here we use independent component analysis to formally test the role of the DMN in episodic and social processing at the network level. As well as an episodic retrieval task, two independent datasets were employed to assess DMN function across the breadth of social cognition; a person knowledge judgement and a theory of mind task. Each task dataset was separated into networks of co-activated regions. In each, the co-activated DMN, was identified through comparison to an a priori template and its relation to the task model assessed. This co-activated DMN did not show greater activity in episodic or social tasks than high-level baseline conditions. Thus, no evidence was found to support hypotheses that the co-activated DMN is involved in explicit episodic or social tasks at a network-level. The networks associated with these processes are described. Implications for prior univariate findings and the functional significance of the co-activated DMN are considered.
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Affiliation(s)
- Rebecca L Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, York, UK; MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Gina F Humphreys
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Grace E Rice
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
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38
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Malik-Moraleda S, Taliaferro M, Shannon S, Jhingan N, Swords S, Peterson DJ, Frommer P, Okrand M, Sams J, Cardwell R, Freeman C, Fedorenko E. Constructed languages are processed by the same brain mechanisms as natural languages. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.28.550667. [PMID: 37546901 PMCID: PMC10402139 DOI: 10.1101/2023.07.28.550667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
What constitutes a language? Natural languages share some features with other domains: from math, to music, to gesture. However, the brain mechanisms that process linguistic input are highly specialized, showing little or no response to diverse non-linguistic tasks. Here, we examine constructed languages (conlangs) to ask whether they draw on the same neural mechanisms as natural languages, or whether they instead pattern with domains like math and logic. Using individual-subject fMRI analyses, we show that understanding conlangs recruits the same brain areas as natural language comprehension. This result holds for Esperanto (n=19 speakers)- created to resemble natural languages-and fictional conlangs (Klingon (n=10), Na'vi (n=9), High Valyrian (n=3), and Dothraki (n=3)), created to differ from natural languages, and suggests that conlangs and natural languages share critical features and that the notable differences between conlangs and natural language are not consequential for the cognitive and neural mechanisms that they engage.
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Affiliation(s)
- Saima Malik-Moraleda
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114
| | - Maya Taliaferro
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Steve Shannon
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Niharika Jhingan
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Sara Swords
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
| | | | - Paul Frommer
- Marshall School of Business, University of Southern California, Los Angeles, CA 90089
| | | | | | | | | | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114
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39
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Wisniewski D, González-García C, Formica S, Woolgar A, Brass M. Adaptive coding of stimulus information in human frontoparietal cortex during visual classification. Neuroimage 2023; 274:120150. [PMID: 37191656 DOI: 10.1016/j.neuroimage.2023.120150] [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: 10/20/2022] [Revised: 04/19/2023] [Accepted: 04/29/2023] [Indexed: 05/17/2023] Open
Abstract
The neural mechanisms of how frontal and parietal brain regions support flexible adaptation of behavior remain poorly understood. Here, we used functional magnetic resonance imaging (fMRI) and representational similarity analysis (RSA) to investigate frontoparietal representations of stimulus information during visual classification under varying task demands. Based on prior research, we predicted that increasing perceptual task difficulty should lead to adaptive changes in stimulus coding: task-relevant category information should be stronger, while task-irrelevant exemplar-level stimulus information should become weaker, reflecting a focus on the behaviorally relevant category information. Counter to our expectations, however, we found no evidence for adaptive changes in category coding. We did find weakened coding at the exemplar-level within categories however, demonstrating that task-irrelevant information is de-emphasized in frontoparietal cortex. These findings reveal adaptive coding of stimulus information at the exemplar-level, highlighting how frontoparietal regions might support behavior even under challenging conditions.
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Affiliation(s)
- David Wisniewski
- Department of Experimental Psychology, Ghent University, Ghent, Belgium; Berlin School of Mind and Brain/ Department of Psychology, Humboldt University of Berlin, Federal Republic of Germany.
| | - Carlos González-García
- Department of Experimental Psychology, Ghent University, Ghent, Belgium; Mind, Brain and Behavior Research Center, University of Granada, Spain; Department of Experimental Psychology, University of Granada, Spain
| | - Silvia Formica
- Department of Experimental Psychology, Ghent University, Ghent, Belgium; Berlin School of Mind and Brain/ Department of Psychology, Humboldt University of Berlin, Federal Republic of Germany
| | - Alexandra Woolgar
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, UK
| | - Marcel Brass
- Department of Experimental Psychology, Ghent University, Ghent, Belgium; Berlin School of Mind and Brain/ Department of Psychology, Humboldt University of Berlin, Federal Republic of Germany
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40
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Chen X, Affourtit J, Ryskin R, Regev TI, Norman-Haignere S, Jouravlev O, Malik-Moraleda S, Kean H, Varley R, Fedorenko E. The human language system, including its inferior frontal component in "Broca's area," does not support music perception. Cereb Cortex 2023; 33:7904-7929. [PMID: 37005063 PMCID: PMC10505454 DOI: 10.1093/cercor/bhad087] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 01/02/2023] [Accepted: 01/03/2023] [Indexed: 04/04/2023] Open
Abstract
Language and music are two human-unique capacities whose relationship remains debated. Some have argued for overlap in processing mechanisms, especially for structure processing. Such claims often concern the inferior frontal component of the language system located within "Broca's area." However, others have failed to find overlap. Using a robust individual-subject fMRI approach, we examined the responses of language brain regions to music stimuli, and probed the musical abilities of individuals with severe aphasia. Across 4 experiments, we obtained a clear answer: music perception does not engage the language system, and judgments about music structure are possible even in the presence of severe damage to the language network. In particular, the language regions' responses to music are generally low, often below the fixation baseline, and never exceed responses elicited by nonmusic auditory conditions, like animal sounds. Furthermore, the language regions are not sensitive to music structure: they show low responses to both intact and structure-scrambled music, and to melodies with vs. without structural violations. Finally, in line with past patient investigations, individuals with aphasia, who cannot judge sentence grammaticality, perform well on melody well-formedness judgments. Thus, the mechanisms that process structure in language do not appear to process music, including music syntax.
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Affiliation(s)
- Xuanyi Chen
- Department of Cognitive Sciences, Rice University, TX 77005, United States
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Josef Affourtit
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Rachel Ryskin
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
- Department of Cognitive & Information Sciences, University of California, Merced, Merced, CA 95343, United States
| | - Tamar I Regev
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Samuel Norman-Haignere
- Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, NY, United States
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, United States
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY, United States
| | - Olessia Jouravlev
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
- Department of Cognitive Science, Carleton University, Ottawa, ON, Canada
| | - Saima Malik-Moraleda
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
- The Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA 02138, United States
| | - Hope Kean
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Rosemary Varley
- Psychology & Language Sciences, UCL, London, WCN1 1PF, United Kingdom
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
- The Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA 02138, United States
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41
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Willbrand EH, Bunge SA, Weiner KS. Neuroanatomical and functional dissociations between variably present anterior lateral prefrontal sulci. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.25.542301. [PMID: 37292839 PMCID: PMC10245924 DOI: 10.1101/2023.05.25.542301] [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: 06/10/2023]
Abstract
The lateral prefrontal cortex (LPFC) is an evolutionarily expanded region in humans that is critical for numerous complex functions, many of which are largely hominoid-specific. While recent work shows that the presence or absence of specific sulci in anterior LPFC is associated with cognitive performance across age groups, it is unknown whether the presence of these structures relates to individual differences in the functional organization of LPFC. To fill this gap in knowledge, we leveraged multimodal neuroimaging data from 72 young adult humans aged 22-36 and show that dorsal and ventral components of the paraintermediate frontal sulcus (pimfs) present distinct morphological (surface area), architectural (thickness and myelination), and functional (resting-state connectivity networks) properties. We further contextualize the pimfs components within classic and modern cortical parcellations. Taken together, the dorsal and ventral pimfs components mark transitions in anatomy and function in LPFC, across metrics and parcellations. These results emphasize that the pimfs is a critical structure to consider when examining individual differences in the anatomical and functional organization of LPFC and highlight the importance of considering individual anatomy when investigating structural and functional features of the cortex.
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Affiliation(s)
- Ethan H. Willbrand
- Department of Psychology, University of California Berkeley, Berkeley, CA, 94720 USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720 USA
| | - Silvia A. Bunge
- Department of Psychology, University of California Berkeley, Berkeley, CA, 94720 USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720 USA
| | - Kevin S. Weiner
- Department of Psychology, University of California Berkeley, Berkeley, CA, 94720 USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720 USA
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42
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Bedini M, Olivetti E, Avesani P, Baldauf D. Accurate localization and coactivation profiles of the frontal eye field and inferior frontal junction: an ALE and MACM fMRI meta-analysis. Brain Struct Funct 2023; 228:997-1017. [PMID: 37093304 PMCID: PMC10147761 DOI: 10.1007/s00429-023-02641-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 04/08/2023] [Indexed: 04/25/2023]
Abstract
The frontal eye field (FEF) and the inferior frontal junction (IFJ) are prefrontal structures involved in mediating multiple aspects of goal-driven behavior. Despite being recognized as prominent nodes of the networks underlying spatial attention and oculomotor control, and working memory and cognitive control, respectively, the limited quantitative evidence on their precise localization has considerably impeded the detailed understanding of their structure and connectivity. In this study, we performed an activation likelihood estimation (ALE) fMRI meta-analysis by selecting studies that employed standard paradigms to accurately infer the localization of these regions in stereotaxic space. For the FEF, we found the highest spatial convergence of activations for prosaccade and antisaccade paradigms at the junction of the precentral sulcus and superior frontal sulcus. For the IFJ, we found consistent activations across oddball/attention, working memory, task-switching and Stroop paradigms at the junction of the inferior precentral sulcus and inferior frontal sulcus. We related these clusters to previous meta-analyses, sulcal/gyral neuroanatomy, and a comprehensive brain parcellation, highlighting important differences compared to their results and taxonomy. Finally, we leveraged the ALE peak coordinates as seeds to perform a meta-analytic connectivity modeling (MACM) analysis, which revealed systematic coactivation patterns spanning the frontal, parietal, and temporal cortices. We decoded the behavioral domains associated with these coactivations, suggesting that these may allow FEF and IFJ to support their specialized roles in flexible behavior. Our study provides the meta-analytic groundwork for investigating the relationship between functional specialization and connectivity of two crucial control structures of the prefrontal cortex.
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Affiliation(s)
- Marco Bedini
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Via delle Regole 101, 38123, Trento, Italy.
- Department of Psychology, University of California, San Diego, McGill Hall 9500 Gilman Dr, La Jolla, CA, 92093-0109, USA.
| | - Emanuele Olivetti
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Via delle Regole 101, 38123, Trento, Italy
- NILab, Bruno Kessler Foundation (FBK), Via delle Regole 101, 38123, Trento, Italy
| | - Paolo Avesani
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Via delle Regole 101, 38123, Trento, Italy
- NILab, Bruno Kessler Foundation (FBK), Via delle Regole 101, 38123, Trento, Italy
| | - Daniel Baldauf
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Via delle Regole 101, 38123, Trento, Italy
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Vadinova V, Sihvonen AJ, Garden KL, Ziraldo L, Roxbury T, O'Brien K, Copland DA, McMahon KL, Brownsett SLE. Early Subacute White Matter Hyperintensities and Recovery of Language After Stroke. Neurorehabil Neural Repair 2023; 37:218-227. [PMID: 37083133 PMCID: PMC10152219 DOI: 10.1177/15459683231168384] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023]
Abstract
BACKGROUND White matter hyperintensities (WMH) are considered to contribute to diminished brain reserve, negatively impacting on stroke recovery. While WMH identified in the chronic phase after stroke have been associated with post-stroke aphasia, the contribution of premorbid WMH to the early recovery of language across production and comprehension has not been investigated. OBJECTIVE To investigate the relationship between premorbid WMH severity and longitudinal comprehension and production outcomes in aphasia, after controlling for stroke lesion variables. METHODS Longitudinal behavioral data from individuals with a left-hemisphere stroke were included at the early subacute (n = 37) and chronic (n = 28) stage. Spoken language comprehension and production abilities were assessed at both timepoints using word and sentence-level tasks. Magnetic resonance imaging (MRI) was performed at the early subacute stage to derive stroke lesion variables (volume and proportion damage to critical regions) and WMH severity rating. RESULTS The presence of severe WMH explained an additional 18% and 25% variance in early subacute (t = -3.00, p = .004) and chronic (t = -3.60, P = .001) language comprehension abilities respectively, after controlling for stroke lesion variables. WMH did not predict additional variance of language production scores. CONCLUSIONS Subacute clinical MRI can be used to improve prognoses of recovery of aphasia after stroke. We demonstrate that severe early subacute WMH add to the prediction of impaired longitudinal language recovery in comprehension, but not production. This emphasizes the need to consider different domains of language when investigating novel neurobiological predictors of aphasia recovery.
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Affiliation(s)
- Veronika Vadinova
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane Australia
- Surgical Treatment and Rehabilitation Service (STARS) Education and Research Alliance, The University of Queensland and Metro North Health, Queensland, Australia
| | - Aleksi J Sihvonen
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane Australia
- Surgical Treatment and Rehabilitation Service (STARS) Education and Research Alliance, The University of Queensland and Metro North Health, Queensland, Australia
- Centre of Research Excellence in Aphasia Recovery and Rehabilitation, La Trobe University, Australia
- Cognitive Brain Research Unit (CBRU), University of Helsinki, Helsinki, Finland
- Centre of Excellence in Music, Mind, Body and Brain, University of Helsinki, Helsinki, Finland
| | - Kimberley L Garden
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane Australia
- Surgical Treatment and Rehabilitation Service (STARS) Education and Research Alliance, The University of Queensland and Metro North Health, Queensland, Australia
| | - Laura Ziraldo
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane Australia
| | - Tracy Roxbury
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane Australia
| | - Kate O'Brien
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane Australia
| | - David A Copland
- Surgical Treatment and Rehabilitation Service (STARS) Education and Research Alliance, The University of Queensland and Metro North Health, Queensland, Australia
- Centre of Research Excellence in Aphasia Recovery and Rehabilitation, La Trobe University, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology, Queensland, Australia
| | - Sonia L E Brownsett
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane Australia
- Surgical Treatment and Rehabilitation Service (STARS) Education and Research Alliance, The University of Queensland and Metro North Health, Queensland, Australia
- Centre of Research Excellence in Aphasia Recovery and Rehabilitation, La Trobe University, Australia
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44
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Yang X, Lin N, Wang L. Situation updating during discourse comprehension recruits right posterior portion of the multiple-demand network. Hum Brain Mapp 2023; 44:2129-2141. [PMID: 36602295 PMCID: PMC10028651 DOI: 10.1002/hbm.26198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 12/01/2022] [Accepted: 12/17/2022] [Indexed: 01/06/2023] Open
Abstract
Discourse comprehension involves the construction of a mental representation of the situation model as well as a continuous update of this representation. This mental update is cognitively demanding and likely engages the multiple-demand network. However, there is little evidence for the involvement of the multiple-demand network during situation updating. In this study, we used fMRI to test whether situation updating based on the change of spatial location activated the multiple-demand network. In a discourse comprehension task, readers read two-sentence discourses in which the second sentence either continues or introduces a shift of the spatial location information presented in the first sentence. Compared to situation continuation, situation updating reliably activated the right superior parietal lobule. This area is a part of the multiple-demand network as defined by a digit N-back localizer task and locates within the dorsal attention network as defined in the previous study by Yeo et al. in 2011. Our results provide evidence for the reliable involvement of a specific area of the multiple-demand network in situation updating during high-level discourse processing.
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Affiliation(s)
- XiaoHong Yang
- Department of Psychology, Renmin University of China, Beijing, China
| | - Nan Lin
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Lin Wang
- Department of Psychology, Tufts University, Medford, Massachusetts, USA
- Department of Psychiatry and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
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45
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Willbrand EH, Ferrer E, Bunge SA, Weiner KS. Development of Human Lateral Prefrontal Sulcal Morphology and Its Relation to Reasoning Performance. J Neurosci 2023; 43:2552-2567. [PMID: 36828638 PMCID: PMC10082454 DOI: 10.1523/jneurosci.1745-22.2023] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 01/25/2023] [Accepted: 02/01/2023] [Indexed: 02/26/2023] Open
Abstract
Previous findings show that the morphology of folds (sulci) of the human cerebral cortex flatten during postnatal development. However, previous studies did not consider the relationship between sulcal morphology and cognitive development in individual participants. Here, we fill this gap in knowledge by leveraging cross-sectional morphologic neuroimaging data in the lateral PFC (LPFC) from individual human participants (6-36 years old, males and females; N = 108; 3672 sulci), as well as longitudinal morphologic and behavioral data from a subset of child and adolescent participants scanned at two time points (6-18 years old; N = 44; 2992 sulci). Manually defining thousands of sulci revealed that LPFC sulcal morphology (depth, surface area, and gray matter thickness) differed between children (6-11 years old)/adolescents (11-18 years old) and young adults (22-36 years old) cross-sectionally, but only cortical thickness showed differences across childhood and adolescence and presented longitudinal changes during childhood and adolescence. Furthermore, a data-driven approach relating morphology and cognition identified that longitudinal changes in cortical thickness of four left-hemisphere LPFC sulci predicted longitudinal changes in reasoning performance, a higher-level cognitive ability that relies on LPFC. Contrary to previous findings, these results suggest that sulci may flatten either after this time frame or over a longer longitudinal period of time than previously presented. Crucially, these results also suggest that longitudinal changes in the cortex within specific LPFC sulci are behaviorally meaningful, providing targeted structures, and areas of the cortex, for future neuroimaging studies examining the development of cognitive abilities.SIGNIFICANCE STATEMENT Recent work has shown that individual differences in neuroanatomical structures (indentations, or sulci) within the lateral PFC are behaviorally meaningful during childhood and adolescence. Here, we describe how specific lateral PFC sulci develop at the level of individual participants for the first time: from both cross-sectional and longitudinal perspectives. Further, we show, also for the first time, that the longitudinal morphologic changes in these structures are behaviorally relevant. These findings lay the foundation for a future avenue to precisely study the development of the cortex and highlight the importance of studying the development of sulci in other cortical expanses and charting how these changes relate to the cognitive abilities those areas support at the level of individual participants.
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Affiliation(s)
- Ethan H Willbrand
- Department of Psychology
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Emilio Ferrer
- Department of Psychology
- Center for Mind and Brain, University of California-Davis, Davis, California 95616
| | - Silvia A Bunge
- Department of Psychology
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Kevin S Weiner
- Department of Psychology
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
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46
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Hu J, Small H, Kean H, Takahashi A, Zekelman L, Kleinman D, Ryan E, Nieto-Castañón A, Ferreira V, Fedorenko E. Precision fMRI reveals that the language-selective network supports both phrase-structure building and lexical access during language production. Cereb Cortex 2023; 33:4384-4404. [PMID: 36130104 PMCID: PMC10110436 DOI: 10.1093/cercor/bhac350] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 11/13/2022] Open
Abstract
A fronto-temporal brain network has long been implicated in language comprehension. However, this network's role in language production remains debated. In particular, it remains unclear whether all or only some language regions contribute to production, and which aspects of production these regions support. Across 3 functional magnetic resonance imaging experiments that rely on robust individual-subject analyses, we characterize the language network's response to high-level production demands. We report 3 novel results. First, sentence production, spoken or typed, elicits a strong response throughout the language network. Second, the language network responds to both phrase-structure building and lexical access demands, although the response to phrase-structure building is stronger and more spatially extensive, present in every language region. Finally, contra some proposals, we find no evidence of brain regions-within or outside the language network-that selectively support phrase-structure building in production relative to comprehension. Instead, all language regions respond more strongly during production than comprehension, suggesting that production incurs a greater cost for the language network. Together, these results align with the idea that language comprehension and production draw on the same knowledge representations, which are stored in a distributed manner within the language-selective network and are used to both interpret and generate linguistic utterances.
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Affiliation(s)
- Jennifer Hu
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
| | - Hannah Small
- Department of Cognitive Science, Johns Hopkins University, Baltimore, MD 21218, United States
| | - Hope Kean
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Atsushi Takahashi
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
| | - Leo Zekelman
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA 02138, United States
| | | | - Elizabeth Ryan
- St. George’s Medical School, St. George’s University, Grenada, West Indies
| | - Alfonso Nieto-Castañón
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, MA 02215, United States
| | - Victor Ferreira
- Department of Psychology, UCSD, La Jolla, CA 92093, United States
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, United States
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA 02138, United States
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47
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MacLean MW, Hadid V, Spreng RN, Lepore F. Revealing robust neural correlates of conscious and unconscious visual processing: activation likelihood estimation meta-analyses. Neuroimage 2023; 273:120088. [PMID: 37030413 DOI: 10.1016/j.neuroimage.2023.120088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 03/30/2023] [Accepted: 04/03/2023] [Indexed: 04/09/2023] Open
Abstract
Our ability to consciously perceive information from the visual scene relies on a myriad of intrinsic neural mechanisms. Functional neuroimaging studies have sought to identify the neural correlates of conscious visual processing and to further dissociate from those pertaining to preconscious and unconscious visual processing. However, delineating what core brain regions are involved in eliciting a conscious percept remains a challenge, particularly regarding the role of prefrontal-parietal regions. We performed a systematic search of the literature that yielded a total of 54 functional neuroimaging studies. We conducted two quantitative meta-analyses using activation likelihood estimation to identify reliable patterns of activation engaged by i. conscious (n = 45 studies, comprising 704 participants) and ii. unconscious (n = 16 studies, comprising 262 participants) visual processing during various task performances. Results of the meta-analysis specific to conscious percepts quantitatively revealed reliable activations across a constellation of regions comprising the bilateral inferior frontal junction, intraparietal sulcus, dorsal anterior cingulate, angular gyrus, temporo-occipital cortex and anterior insula. Neurosynth reverse inference revealed conscious visual processing to be intertwined with cognitive terms related to attention, cognitive control and working memory. Results of the meta-analysis on unconscious percepts revealed consistent activations in the lateral occipital complex, intraparietal sulcus and precuneus. These findings highlight the notion that conscious visual processing readily engages higher-level regions including the inferior frontal junction and unconscious processing reliably recruits posterior regions, mainly the lateral occipital complex.
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48
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Jiang J, Bruss J, Lee WT, Tranel D, Boes AD. White matter disconnection of left multiple demand network is associated with post-lesion deficits in cognitive control. Nat Commun 2023; 14:1740. [PMID: 36990985 PMCID: PMC10060223 DOI: 10.1038/s41467-023-37330-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 03/13/2023] [Indexed: 03/31/2023] Open
Abstract
Cognitive control modulates other cognitive functions to achieve internal goals and is important for adaptive behavior. Cognitive control is enabled by the neural computations distributed over cortical and subcortical areas. However, due to technical challenges in recording neural activity from the white matter, little is known about the anatomy of white matter tracts that coordinate the distributed neural computations that support cognitive control. Here, we leverage a large sample of human patients with focal brain lesions (n = 643) and investigate how lesion location and connectivity profiles account for variance in cognitive control performance. We find that lesions in white matter connecting left frontoparietal regions of the multiple demand network reliably predict deficits in cognitive control performance. These findings advance our understanding of the white matter correlates of cognitive control and provide an approach for incorporating network disconnection to predict deficits following lesions.
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Affiliation(s)
- Jiefeng Jiang
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, 52242, USA.
- Cognitive Control Collaborative, University of Iowa, Iowa City, IA, 52242, USA.
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, 52242, USA.
| | - Joel Bruss
- Department of Neurology (Division of Neuropsychology and Cognitive Neuroscience), Carver College of Medicine, Iowa City, IA, 52242, USA
- Department of Psychiatry, Carver College of Medicine, Iowa City, IA, 52242, USA
| | - Woo-Tek Lee
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, 52242, USA
- Cognitive Control Collaborative, University of Iowa, Iowa City, IA, 52242, USA
- Behavioral-biomedical Interface Training Program, University of Iowa, Iowa City, IA, 52242, USA
| | - Daniel Tranel
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, 52242, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, 52242, USA
- Department of Neurology (Division of Neuropsychology and Cognitive Neuroscience), Carver College of Medicine, Iowa City, IA, 52242, USA
| | - Aaron D Boes
- Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, 52242, USA.
- Department of Neurology (Division of Neuropsychology and Cognitive Neuroscience), Carver College of Medicine, Iowa City, IA, 52242, USA.
- Department of Psychiatry, Carver College of Medicine, Iowa City, IA, 52242, USA.
- Department of Pediatrics, Carver College of Medicine, Iowa City, IA, 52242, USA.
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49
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Seeing inferences: brain dynamics and oculomotor signatures of non-verbal deduction. Sci Rep 2023; 13:2341. [PMID: 36759690 PMCID: PMC9911777 DOI: 10.1038/s41598-023-29307-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 02/02/2023] [Indexed: 02/11/2023] Open
Abstract
We often express our thoughts through words, but thinking goes well beyond language. Here we focus on an elementary but basic thinking process, disjunction elimination, elicited by elementary visual scenes deprived of linguistic content, describing its neural and oculomotor correlates. We track two main components of a nonverbal deductive process: the construction of a logical representation (A or B), and its simplification by deduction (not A, therefore B). We identify the network active in the two phases and show that in the latter, but not in the former, it overlaps with areas known to respond to verbal logical reasoning. Oculomotor markers consistently differentiate logical processing induced by the construction of a representation, its simplification by deductive inference, and its maintenance when inferences cannot be drawn. Our results reveal how integrative logical processes incorporate novel experience in the flow of thoughts induced by visual scenes.
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50
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Characteristic cortico-cortical connection profile of human precuneus revealed by probabilistic tractography. Sci Rep 2023; 13:1936. [PMID: 36732604 PMCID: PMC9895448 DOI: 10.1038/s41598-023-29251-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 02/01/2023] [Indexed: 02/04/2023] Open
Abstract
It is generally hypothesized that functional connectivity (FC) reflects the underlying structural connectivity (SC). The precuneus is associated with highly integrated cognitive functions. However, our understanding of the structural connections that could underlie them is limited. This study aimed to characterize the cortico-cortical connections by probabilistic tractography. The precuneus corresponds to the five cortical areas (7Am, PCV, 7Pm, 7m, POS2) on the HCP MMP atlas. We first conducted the atlas-based probabilistic tractography. The anterior part (7Am) was strongly connected to the sensorimotor region. The dorsal part (7Am, 7Pm) was highly connected with the adjacent parietal and temporal cortex, while the ventral part (PCV, 7m) showed strong connections with the adjacent posterior cingulate and medial prefrontal cortex. The most posterior part (POS2) was explicitly connected to the visual cortex. In addition, there was a correlation between SC and resting-state fMRI connectivity (Spearman's rank correlation coefficient = 0.322 ± 0.019, p < 0.05 corrected at subject level). Collectively, the current study revealed the characteristic connectional profile of precuneus, which could shed light on the structural heterogeneity for the future functional analyses.
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