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Barrett LF, Atzil S, Bliss-Moreau E, Chanes L, Gendron M, Hoemann K, Katsumi Y, Kleckner IR, Lindquist KA, Quigley KS, Satpute AB, Sennesh E, Shaffer C, Theriault JE, Tugade M, Westlin C. The Theory of Constructed Emotion: More Than a Feeling. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2025; 20:392-420. [PMID: 40357691 DOI: 10.1177/17456916251319045] [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] [Indexed: 05/15/2025]
Abstract
A recently published article by van Heijst et al. attempted to reconcile two research approaches in the science of emotion-basic emotion theory and the theory of constructed emotion-by suggesting that the former explains emotions as bioregulatory states of the body whereas the latter explains feelings that arise from those state changes. This bifurcation of emotion into objective physical states and subjective feelings involves three misleading simplifications that fundamentally misrepresent the theory of constructed emotion and prevent progress in the science of emotion. In this article we identify these misleading simplifications and the resulting factual errors, empirical oversights, and evolutionary oversimplifications. We then discuss why such errors will continue to arise until scientists realize that the two theories are intrinsically irreconcilable. They rest on incommensurate assumptions and require different methods of evaluation. Only by directly considering these differences will these research silos in the science of emotion finally dissolve, speeding the accumulation of trustworthy scientific knowledge about emotion that is usable in the real world.
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Affiliation(s)
- Lisa Feldman Barrett
- Department of Psychology, Northeastern University
- Department of Psychiatry, Massachusetts General Hospital
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
| | - Shir Atzil
- Department of Psychology, Vanderbilt University
| | - Eliza Bliss-Moreau
- Department of Psychology, University of California, Davis
- California National Primate Research Center, University of California, Davis
| | - Lorena Chanes
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona
- Institut de Neurociències, Universitat Autònoma de Barcelona
| | | | | | - Yuta Katsumi
- Department of Psychiatry, Massachusetts General Hospital
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Department of Neurology, Massachusetts General Hospital
| | | | | | | | - Ajay B Satpute
- Department of Psychology, Northeastern University
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
| | - Eli Sennesh
- Department of Psychology, Vanderbilt University
| | | | - Jordan E Theriault
- Department of Psychology, Northeastern University
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Department of Biology, Northeastern University
| | | | - Christiana Westlin
- Department of Psychiatry, Massachusetts General Hospital
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital
- Department of Psychology, University of Kansas
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2
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Luppi AI, Golkowski D, Ranft A, Ilg R, Jordan D, Bzdok D, Owen AM, Naci L, Stamatakis EA, Amico E, Misic B. General anaesthesia decreases the uniqueness of brain functional connectivity across individuals and species. Nat Hum Behav 2025; 9:987-1004. [PMID: 40128306 PMCID: PMC12106074 DOI: 10.1038/s41562-025-02121-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 01/16/2025] [Indexed: 03/26/2025]
Abstract
The human brain is characterized by idiosyncratic patterns of spontaneous thought, rendering each brain uniquely identifiable from its neural activity. However, deep general anaesthesia suppresses subjective experience. Does it also suppress what makes each brain unique? Here we used functional MRI scans acquired under the effects of the general anaesthetics sevoflurane and propofol to determine whether anaesthetic-induced unconsciousness diminishes the uniqueness of the human brain, both with respect to the brains of other individuals and the brains of another species. Using functional connectivity, we report that under anaesthesia individual brains become less self-similar and less distinguishable from each other. Loss of distinctiveness is highly organized: it co-localizes with the archetypal sensory-association axis, correlating with genetic and morphometric markers of phylogenetic differences between humans and other primates. This effect is more evident at greater anaesthetic depths, reproducible across sevoflurane and propofol and reversed upon recovery. Providing convergent evidence, we show that anaesthesia shifts the functional connectivity of the human brain closer to the functional connectivity of the macaque brain in a low-dimensional space. Finally, anaesthesia diminishes the match between spontaneous brain activity and cognitive brain patterns aggregated from the Neurosynth meta-analytic engine. Collectively, the present results reveal that anaesthetized human brains are not only less distinguishable from each other, but also less distinguishable from the brains of other primates, with specifically human-expanded regions being the most affected by anaesthesia.
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Affiliation(s)
- Andrea I Luppi
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada.
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Daniel Golkowski
- Department of Neurology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Rudiger Ilg
- Department of Neurology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
- Asklepios Clinic, Department of Neurology, Bad Tölz, Germany
| | - Denis Jordan
- Department of Anaesthesiology and Intensive Care Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Danilo Bzdok
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada
- Mila, Quebec Artificial Intelligence Institute, Montréal, Québec, Canada
| | - Adrian M Owen
- Western Institute for Neuroscience, Western University, London, Ontario, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Emmanuel A Stamatakis
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Enrico Amico
- School of Mathematics, University of Birmingham, Birmingham, UK
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, UK
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Québec, Canada
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3
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da Silva Castanheira J, Poli J, Hansen JY, Misic B, Baillet S. Genetic Foundations of Inter-individual Neurophysiological Variability. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.07.19.604292. [PMID: 39071281 PMCID: PMC11275903 DOI: 10.1101/2024.07.19.604292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Neurophysiological brain activity shapes cognitive functions and individual traits. Here, we investigated the extent to which individual neurophysiological properties are genetically determined and how these adult traits align with cortical gene expression patterns across development. Using task-free magnetoencephalography in monozygotic and dizygotic twins, as well as unrelated individuals, we found that neurophysiological traits were significantly more similar between monozygotic twins, indicating a genetic influence, although individual-specific variability remained predominant. These heritable brain dynamics were predominantly associated with genes involved in neurotransmission, expressed along a topographical gradient that mirrors psychological functions, including attention, planning, and emotional processes. Furthermore, the cortical expression patterns of genes associated with individual differentiation aligned most strongly with gene expression profiles observed during adulthood in previously published longitudinal datasets. These findings underscore a persistent genetic influence on neurophysiological activity, supporting individual cognitive and behavioral variability.
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4
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Zhang J, Wu K, Dong J, Feng J, Yu L. Modeling the interplay between regional heterogeneity and critical dynamics underlying brain functional networks. Neural Netw 2025; 184:107100. [PMID: 39740389 DOI: 10.1016/j.neunet.2024.107100] [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: 04/14/2024] [Revised: 10/03/2024] [Accepted: 12/23/2024] [Indexed: 01/02/2025]
Abstract
The human brain exhibits heterogeneity across regions and network connectivity patterns; However, how these heterogeneities contribute to whole-brain network functions and cognitive capacities remains unclear. In this study, we focus on the regional heterogeneity reflected in local dynamics and study how it contributes to the emergence of functional connectivity patterns, network ignition dynamics of the empirical brains. We find that the level of synchrony among voxelwise neural activities measured from the fMRI data is significantly correlated with the transcriptional variations in excitatory and inhibitory receptor gene expression. Consequently, we construct heterogeneous whole-brain network models with nodal excitability calibrated by the synchronization measure of regional dynamics. We demonstrate that as the extent of heterogeneity increases, the models operating around the critical point between order and disorder generate simulated functional connectivity networks increasingly similar to empirical resting-state or working memory task-evoked function connectivity networks. Furthermore, the heterogeneous models can predict individual differences in resting-state and task-evoked reconfiguration of the functional connectivity, as well as the comparative causal effect of empirical brain networks-that is, how the dynamics of one brain region affect whole-brain synchronization. Overall, this work demonstrates the viability of using regional heterogeneous functional signals to improve the performance of the whole-brain models, and illustrates how regional heterogeneity in human brains interplays with structural connections and critical dynamics to contribute to the emergence of functional connectivity networks.
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Affiliation(s)
- Jijin Zhang
- School of Physical Science and Technology, Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, and Key Laboratory of Quantum Theory and Applications of MoE, Lanzhou University, Lanzhou, Gansu 730000, China
| | - Kejian Wu
- School of Physical Science and Technology, Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, and Key Laboratory of Quantum Theory and Applications of MoE, Lanzhou University, Lanzhou, Gansu 730000, China
| | - Jiaqi Dong
- School of Physical Science and Technology, Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, and Key Laboratory of Quantum Theory and Applications of MoE, Lanzhou University, Lanzhou, Gansu 730000, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, 200433, China; Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK; School of Mathematical Sciences, School of Life Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, 200433, China
| | - Lianchun Yu
- School of Physical Science and Technology, Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, and Key Laboratory of Quantum Theory and Applications of MoE, Lanzhou University, Lanzhou, Gansu 730000, China.
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5
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Luppi AI, Liu ZQ, Hansen JY, Cofre R, Niu M, Kuzmin E, Froudist-Walsh S, Palomero-Gallagher N, Misic B. Benchmarking macaque brain gene expression for horizontal and vertical translation. SCIENCE ADVANCES 2025; 11:eads6967. [PMID: 40020056 PMCID: PMC11870082 DOI: 10.1126/sciadv.ads6967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2024] [Accepted: 01/27/2025] [Indexed: 03/03/2025]
Abstract
The spatial patterning of gene expression shapes cortical organization and function. The macaque is a fundamental model organism in neuroscience, but the translational potential of macaque gene expression rests on the assumption that it is a good proxy for patterns of corresponding proteins (vertical translation) and for patterns of orthologous human genes (horizontal translation). Here, we systematically benchmark regional gene expression in macaque cortex against (i) macaque cortical receptor density and in vivo and ex vivo microstructure and (ii) human cortical gene expression. We find moderate cortex-wide correspondence between macaque gene expression and protein density, which improves by considering layer-specific gene expression. Half of the examined genes exhibit significant correlation between macaque and human across the cortex. Interspecies correspondence of gene expression is greater in unimodal than in transmodal cortex, recapitulating evolutionary cortical expansion and gene-protein correspondence in the macaque. These results showcase the potential and limitations of macaque cortical transcriptomics for translational discovery within and across species.
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Affiliation(s)
- Andrea I. Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- Department of Psychiatry, University of Oxford, Oxford, UK
- St John’s College, University of Cambridge, Cambridge, UK
| | - Zhen-Qi Liu
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Rodrigo Cofre
- Paris-Saclay University, CNRS, Paris-Saclay Institute for Neuroscience (NeuroPSI), Saclay, France
| | - Meiqi Niu
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Elena Kuzmin
- Department of Biology, Centre for Applied Synthetic Biology, Concordia University, Montréal, QC, Canada
- Department of Human Genetics, Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | | | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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6
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Wang Y, Cheng L, Li D, Lu Y, Wang C, Wang Y, Gao C, Wang H, Erichsen CT, Vanduffel W, Hopkins WD, Sherwood CC, Jiang T, Chu C, Fan L. The Chimpanzee Brainnetome Atlas reveals distinct connectivity and gene expression profiles relative to humans. Innovation (N Y) 2025; 6:100755. [PMID: 39991479 PMCID: PMC11846036 DOI: 10.1016/j.xinn.2024.100755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Accepted: 12/07/2024] [Indexed: 02/25/2025] Open
Abstract
Chimpanzees (Pan troglodytes) are one of humans' closest living relatives, making them the most directly relevant comparison point for understanding human brain evolution. Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occurred along the human lineage. However, such comparisons are hindered by the absence of cross-species brain atlases established within the same framework. To address this gap, we developed the Chimpanzee Brainnetome Atlas (ChimpBNA) using a connectivity-based parcellation framework. Leveraging this new resource, we found substantial divergence in connectivity patterns between the two species across most association cortices, notably in the lateral temporal and dorsolateral prefrontal cortex. These differences deviate sharply from the pattern of cortical expansion observed when comparing humans to chimpanzees, highlighting more complex and nuanced connectivity changes in brain evolution than previously recognized. Additionally, we identified regions displaying connectional asymmetries that differed between species, likely resulting from evolutionary divergence. Genes highly expressed in regions of divergent connectivities were enriched in cell types crucial for cortical projection circuits and synapse formation, whose pronounced differences in expression patterns hint at genetic influences on neural circuit development, function, and evolution. Our study provides a fine-scale chimpanzee brain atlas and highlights the chimpanzee-human connectivity divergence in a rigorous and comparative manner. In addition, these results suggest potential gene expression correlates for species-specific differences by linking neuroimaging and genetic data, offering insights into the evolution of human-unique cognitive capabilities.
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Affiliation(s)
- Yufan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Luqi Cheng
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China
| | - Deying Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuheng Lu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Changshuo Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yaping Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Chaohong Gao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Department of Neurosciences, Laboratory of Neuro- and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium
| | - Camilla T. Erichsen
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
- Core Center for Molecular Morphology, Section for Stereology and Microscopy, Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
| | - Wim Vanduffel
- Department of Neurosciences, Laboratory of Neuro- and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium
- Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
| | - William D. Hopkins
- Department of Comparative Medicine, University of Texas MD Anderson Cancer Center, Bastrop, TX 78602, USA
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
- Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
- School of Life Sciences and Health, University of Health and Rehabilitation Sciences, Qingdao 266000, China
- Shandong Key Lab of Complex Medical Intelligence and Aging, Binzhou Medical University, Yantai 264003, China
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7
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Sandroni V, Chaumette B. Understanding the Emergence of Schizophrenia in the Light of Human Evolution: New Perspectives in Genetics. GENES, BRAIN, AND BEHAVIOR 2025; 24:e70013. [PMID: 39801370 PMCID: PMC11725983 DOI: 10.1111/gbb.70013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Revised: 12/17/2024] [Accepted: 12/21/2024] [Indexed: 01/16/2025]
Abstract
Schizophrenia is a frequent and disabling disease. The persistence of the disorder despite its harmful consequences represents an evolutionary paradox. Based on recent discoveries in genetics, scientists have formulated the "price-to-pay" hypothesis: schizophrenia would be intimately related to human evolution, particularly to brain development and human-specific higher cognitive functions. The objective of the present work is to question scientific literature about the relationship between schizophrenia and human evolution from a genetic point of view. In the last two decades, research investigated the association between schizophrenia and a few genetic evolutionary markers: Human accelerated regions, segmental duplications, and highly repetitive DNA such as the Olduvai domain. Other studies focused on the action of natural selection on schizophrenia-associated genetic variants, also thanks to the complete sequencing of archaic hominins' genomes (Neanderthal, Denisova). Results suggested that a connection between human evolution and schizophrenia may exist; nonetheless, much research is still needed, and it is possible that a definitive answer to the evolutionary paradox of schizophrenia will never be found.
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Affiliation(s)
- Veronica Sandroni
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP)ParisFrance
- GHU‐Paris Psychiatrie et NeurosciencesHôpital Sainte AnneParisFrance
| | - Boris Chaumette
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP)ParisFrance
- GHU‐Paris Psychiatrie et NeurosciencesHôpital Sainte AnneParisFrance
- Human Genetics and Cognitive FunctionsInstitut Pasteur, Université Paris CitéParisFrance
- Department of PsychiatryMcGill UniversityMontrealCanada
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8
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Datta D, Arnsten AFT. The etiology and prevention of early-stage tau pathology in higher cortical circuits: Insights from aging rhesus macaques. Alzheimers Dement 2025; 21:e14477. [PMID: 39776253 PMCID: PMC11848412 DOI: 10.1002/alz.14477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2024] [Revised: 11/20/2024] [Accepted: 11/22/2024] [Indexed: 01/11/2025]
Abstract
Aging rhesus macaques provide a unique model for learning how age and inflammation drive early-stage pathology in sporadic Alzheimer's disease, and for testing potential therapeutics. Unlike mice, aging macaques have extensive association cortices and inflammatory signaling similar to humans, are apolipoprotein E ε4 homozygotes, and naturally develop tau and amyloid pathology with marked cognitive deficits. Importantly, monkeys provide the unique opportunity to study early-stage, soluble hyperphosphorylated tau (p-tau), including p-tau217. As soluble p-tau is rapidly dephosphorylated post mortem, it is not captured in human brains except with biopsy material. However, new macaque data show that soluble p-tau is toxic to neurons and capable of seeding across cortical circuits. Extensive evidence indicates that age-related inflammatory signaling contributes to calcium dysregulation, which drives tau hyperphosphorylation and amyloid beta generation. Pharmacological studies in aged macaques suggest that inhibiting inflammation and restoring calcium regulation can reduce tau hyperphosphorylation with minimal side effects, appropriate for potential preventive therapeutics. HIGHLIGHTS: Aging monkeys provide a unique window into early stage, soluble phosphorylated tau (p-tau). Inflammation with advancing age leads to calcium dysregulation, p-tau, and amyloid beta (Aβ). Macaque research shows p-tau undergoes transsynaptic seeding early in the cortex. p-tau traps amyloid precursor protein-containing endosomes, which may increase Aβ and drive vicious cycles. Restoring calcium regulation in cortex reduced p-tau217 levels in aged macaques.
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Affiliation(s)
- Dibyadeep Datta
- Department of PsychiatryYale Medical SchoolNew HavenConnecticutUSA
| | - Amy F. T. Arnsten
- Department of NeuroscienceYale Medical SchoolNew HavenConnecticutUSA
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9
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Amano H, Tanabe HC, Ogihara N. Enlargement of the human prefrontal cortex and brain mentalizing network: anatomically homogenous cross-species brain transformation. Brain Struct Funct 2025; 230:34. [PMID: 39853417 PMCID: PMC11762074 DOI: 10.1007/s00429-025-02896-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2024] [Accepted: 01/13/2025] [Indexed: 01/26/2025]
Abstract
To achieve a better understanding of the evolution of the large brain in humans, a comparative analysis of species differences in the brains of extant primate species is crucial, as it allows direct comparisons of the brains. We developed a method to achieve anatomically precise region-to-region homologous brain transformations across species using computational neuroanatomy. Utilizing three-dimensional neuroimaging data from humans (Homo sapiens), chimpanzees (Pan troglodytes), and Japanese macaques (Macaca fuscata), along with the anatomical labels of their respective brains, we aimed to create a cross-species average template brain that preserves neuroanatomical correspondence across species. Homologous transformation of the brain from one species to another can be computed using the cross-species average brain. Applying this transformation to human and chimpanzee brains revealed that, compared to chimpanzees, humans had significantly larger and more expanded prefrontal cortex, middle and posterior temporal gyrus, angular gyrus, precuneus, and cortical areas associated with mentalization. This neuroanatomically homologous brain transformation enables the systematic investigation of the similarities and differences in brain anatomy and structure across different species.
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Affiliation(s)
- Hideki Amano
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, 113-0033, Japan.
| | - Hiroki C Tanabe
- Department of Cognitive and Psychological Sciences, Graduate School of Informatics, Nagoya University, Nagoya, 464-8601, Japan
| | - Naomichi Ogihara
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, 113-0033, Japan.
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10
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Vasan L, Chinchalongporn V, Saleh F, Zinyk D, Ke C, Suresh H, Ghazale H, Belfiore L, Touahri Y, Oproescu AM, Patel S, Rozak M, Amemiya Y, Han S, Moffat A, Black SE, McLaurin J, Near J, Seth A, Goubran M, Reiner O, Gillis J, Wang C, Okawa S, Schuurmans C. Examining the NEUROG2 lineage and associated gene expression in human cortical organoids. Development 2025; 152:dev202703. [PMID: 39680368 PMCID: PMC11829764 DOI: 10.1242/dev.202703] [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: 01/11/2024] [Accepted: 12/07/2024] [Indexed: 12/17/2024]
Abstract
Proneural genes are conserved drivers of neurogenesis across the animal kingdom. How their functions have adapted to guide human-specific neurodevelopmental features is poorly understood. Here, we mined transcriptomic data from human fetal cortices and generated from human embryonic stem cell-derived cortical organoids (COs) to show that NEUROG1 and NEUROG2 are most highly expressed in basal neural progenitor cells, with pseudotime trajectory analyses indicating that NEUROG1-derived lineages predominate early and NEUROG2 lineages later. Using ChIP-qPCR, gene silencing and overexpression studies in COs, we show that NEUROG2 is necessary and sufficient to directly transactivate known target genes (NEUROD1, EOMES, RND2). To identify new targets, we engineered NEUROG2-mCherry knock-in human embryonic stem cells for CO generation. The mCherry-high CO cell transcriptome is enriched in extracellular matrix-associated genes, and two genes associated with human-accelerated regions: PPP1R17 and FZD8. We show that NEUROG2 binds COL1A1, COL3A1 and PPP1R17 regulatory elements, and induces their ectopic expression in COs, although NEUROG2 is not required for this expression. Neurog2 similarly induces Col3a1 and Ppp1r17 in murine P19 cells. These data are consistent with a conservation of NEUROG2 function across mammalian species.
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Affiliation(s)
- Lakshmy Vasan
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Vorapin Chinchalongporn
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Biochemistry, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Fermisk Saleh
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Biochemistry, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Dawn Zinyk
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Biochemistry, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Cao Ke
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Immunology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Hamsini Suresh
- Department of Physiology, University of Toronto, Medical Sciences Building, 1 King's College Cir, Toronto, ON M5S 1A8, Canada
- Terrence Donnelly Centre for Cellular and Biomolecular Research, 160 College St, Toronto, ON M5S 3E1, Canada
| | - Hussein Ghazale
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Biochemistry, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Lauren Belfiore
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Yacine Touahri
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Biochemistry, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Ana-Maria Oproescu
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Shruti Patel
- Department of Medical Biophysics, 101 College St Suite 15-701, Toronto General Hospital, University of Toronto, Toronto, ON M5G 1L7, Canada
- Sunnybrook Research Institute, Physical Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
| | - Matthew Rozak
- Department of Medical Biophysics, 101 College St Suite 15-701, Toronto General Hospital, University of Toronto, Toronto, ON M5G 1L7, Canada
- Sunnybrook Research Institute, Physical Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
| | - Yutaka Amemiya
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Sisu Han
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Biochemistry, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Alexandra Moffat
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Sandra E. Black
- Dr. Sandra Black Centre for Brain Resilience & Recovery, LC Campbell Cognitive Neurology Unit, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Hurvitz Brain Sciences Program
- Department of Medicine (Neurology) (SEB), University of Toronto, Toronto, ON M5S 3H2, Canada
| | - JoAnne McLaurin
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Jamie Near
- Department of Medical Biophysics, 101 College St Suite 15-701, Toronto General Hospital, University of Toronto, Toronto, ON M5G 1L7, Canada
- Sunnybrook Research Institute, Physical Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
| | - Arun Seth
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Maged Goubran
- Department of Medical Biophysics, 101 College St Suite 15-701, Toronto General Hospital, University of Toronto, Toronto, ON M5G 1L7, Canada
- Sunnybrook Research Institute, Physical Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
| | - Orly Reiner
- Departments of Molecular Genetics and Molecular Neuroscience, Weizmann Institute of Science, 76100 Rehovot, Israel
| | - Jesse Gillis
- Department of Physiology, University of Toronto, Medical Sciences Building, 1 King's College Cir, Toronto, ON M5S 1A8, Canada
- Terrence Donnelly Centre for Cellular and Biomolecular Research, 160 College St, Toronto, ON M5S 3E1, Canada
| | - Chao Wang
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Immunology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Satoshi Okawa
- Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA 15219, USA
| | - Carol Schuurmans
- Sunnybrook Research Institute, Biological Sciences Platform, Hurvitz Brain Sciences Program, 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Biochemistry, Medical Sciences Building, 1 King's College Cir, University of Toronto, Toronto, ON M5S 1A8, Canada
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11
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Zhao HT, Schmidt ER. Human-specific genetic modifiers of cortical architecture and function. Curr Opin Genet Dev 2024; 88:102241. [PMID: 39111228 PMCID: PMC11547859 DOI: 10.1016/j.gde.2024.102241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/30/2024] [Accepted: 07/23/2024] [Indexed: 09/11/2024]
Abstract
Evolution of the cerebral cortex is thought to have been critical for the emergence of our cognitive abilities. Major features of cortical evolution include increased neuron number and connectivity and altered morpho-electric properties of cortical neurons. Significant progress has been made in identifying human-specific genetic modifiers (HSGMs), some of which are involved in shaping these features of cortical architecture. But how did these evolutionary changes support the emergence of our cognitive abilities? Here, we highlight recent studies aimed at examining the impact of HSGMs on cortical circuit function and behavior. We also discuss the need for greater insight into the link between evolution of cortical architecture and the functional and computational properties of neuronal circuits, as we seek to provide a neurobiological foundation for human cognition.
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Affiliation(s)
- Hanzhi T Zhao
- Department of Neuroscience, Medical University of South Carolina, Suite 403 BSB, MSC510, 173 Ashley Ave, Charleston, SC 29425, USA
| | - Ewoud Re Schmidt
- Department of Neuroscience, Medical University of South Carolina, Suite 403 BSB, MSC510, 173 Ashley Ave, Charleston, SC 29425, USA.
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12
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Pasquini L, Pereira FL, Seddighi S, Zeng Y, Wei Y, Illán-Gala I, Vatsavayai SC, Friedberg A, Lee AJ, Brown JA, Spina S, Grinberg LT, Sirkis DW, Bonham LW, Yokoyama JS, Boxer AL, Kramer JH, Rosen HJ, Humphrey J, Gitler AD, Miller BL, Pollard KS, Ward ME, Seeley WW. Frontotemporal lobar degeneration targets brain regions linked to expression of recently evolved genes. Brain 2024; 147:3032-3047. [PMID: 38940350 PMCID: PMC11370792 DOI: 10.1093/brain/awae205] [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: 10/27/2023] [Revised: 05/08/2024] [Accepted: 05/20/2024] [Indexed: 06/29/2024] Open
Abstract
In frontotemporal lobar degeneration (FTLD), pathological protein aggregation in specific brain regions is associated with declines in human-specialized social-emotional and language functions. In most patients, disease protein aggregates contain either TDP-43 (FTLD-TDP) or tau (FTLD-tau). Here, we explored whether FTLD-associated regional degeneration patterns relate to regional gene expression of human accelerated regions (HARs), conserved sequences that have undergone positive selection during recent human evolution. To this end, we used structural neuroimaging from patients with FTLD and human brain regional transcriptomic data from controls to identify genes expressed in FTLD-targeted brain regions. We then integrated primate comparative genomic data to test our hypothesis that FTLD targets brain regions linked to expression levels of recently evolved genes. In addition, we asked whether genes whose expression correlates with FTLD atrophy are enriched for genes that undergo cryptic splicing when TDP-43 function is impaired. We found that FTLD-TDP and FTLD-tau subtypes target brain regions with overlapping and distinct gene expression correlates, highlighting many genes linked to neuromodulatory functions. FTLD atrophy-correlated genes were strongly enriched for HARs. Atrophy-correlated genes in FTLD-TDP showed greater overlap with TDP-43 cryptic splicing genes and genes with more numerous TDP-43 binding sites compared with atrophy-correlated genes in FTLD-tau. Cryptic splicing genes were enriched for HAR genes, and vice versa, but this effect was due to the confounding influence of gene length. Analyses performed at the individual-patient level revealed that the expression of HAR genes and cryptically spliced genes within putative regions of disease onset differed across FTLD-TDP subtypes. Overall, our findings suggest that FTLD targets brain regions that have undergone recent evolutionary specialization and provide intriguing potential leads regarding the transcriptomic basis for selective vulnerability in distinct FTLD molecular-anatomical subtypes.
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Affiliation(s)
- Lorenzo Pasquini
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
- Department of Neurology, Neuroscape, University of California, San Francisco, CA 94158, USA
| | - Felipe L Pereira
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Sahba Seddighi
- National Institute of Neurological Disorders and Stroke, Neurogenetics Branch, Bethesda, MD 20892, USA
| | - Yi Zeng
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Ignacio Illán-Gala
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
- Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, 94158USA
- Trinity College Dublin, Dublin D02 X9W9, Ireland
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute, Universitat Autònoma de Barcelona, Barcelona, Catalunya, 08041, Spain
| | - Sarat C Vatsavayai
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Adit Friedberg
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
- Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, 94158USA
- Trinity College Dublin, Dublin D02 X9W9, Ireland
| | - Alex J Lee
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Jesse A Brown
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Salvatore Spina
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Lea T Grinberg
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
- Department of Pathology, University of California, San Francisco, CA 94158, USA
| | - Daniel W Sirkis
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Luke W Bonham
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
- Department of Radiology, University of California, San Francisco, CA 94158, USA
| | - Jennifer S Yokoyama
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
- Department of Radiology, University of California, San Francisco, CA 94158, USA
| | - Adam L Boxer
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Joel H Kramer
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Jack Humphrey
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Aaron D Gitler
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Katherine S Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Epidemiology and Biostatistics and Bakar Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Michael E Ward
- National Institute of Neurological Disorders and Stroke, Neurogenetics Branch, Bethesda, MD 20892, USA
| | - William W Seeley
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
- Department of Pathology, University of California, San Francisco, CA 94158, USA
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13
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Vickery S, Patil KR, Dahnke R, Hopkins WD, Sherwood CC, Caspers S, Eickhoff SB, Hoffstaedter F. The uniqueness of human vulnerability to brain aging in great ape evolution. SCIENCE ADVANCES 2024; 10:eado2733. [PMID: 39196942 PMCID: PMC11352902 DOI: 10.1126/sciadv.ado2733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 07/24/2024] [Indexed: 08/30/2024]
Abstract
Aging is associated with progressive gray matter loss in the brain. This spatially specific, morphological change over the life span in humans is also found in chimpanzees, and the comparison between these great ape species provides a unique evolutionary perspective on human brain aging. Here, we present a data-driven, comparative framework to explore the relationship between gray matter atrophy with age and recent cerebral expansion in the phylogeny of chimpanzees and humans. In humans, we show a positive relationship between cerebral aging and cortical expansion, whereas no such relationship was found in chimpanzees. This human-specific association between strong aging effects and large relative cortical expansion is particularly present in higher-order cognitive regions of the ventral prefrontal cortex and supports the "last-in-first-out" hypothesis for brain maturation in recent evolutionary development of human faculties.
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Affiliation(s)
- Sam Vickery
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany
- Division of Physiotherapy, Department of Applied Health Sciences, Hochschule für Gesundheit (University of Applied Sciences), Bochum, Germany
| | - Kaustubh R. Patil
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany
| | - Robert Dahnke
- Structural Brain Mapping Group, Department of Neurology, Jena University Hospital, Jena, Germany
- Structural Brain Mapping Group, Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - William D. Hopkins
- Department of Comparative Medicine, Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany
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14
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Johansen A, Beliveau V, Colliander E, Raval NR, Dam VH, Gillings N, Aznar S, Svarer C, Plavén-Sigray P, Knudsen GM. An In Vivo High-Resolution Human Brain Atlas of Synaptic Density. J Neurosci 2024; 44:e1750232024. [PMID: 38997157 PMCID: PMC11326867 DOI: 10.1523/jneurosci.1750-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 04/28/2024] [Accepted: 07/03/2024] [Indexed: 07/14/2024] Open
Abstract
Synapses are fundamental to the function of the central nervous system and are implicated in a number of brain disorders. Despite their pivotal role, a comprehensive imaging resource detailing the distribution of synapses in the human brain has been lacking until now. Here, we employ high-resolution PET neuroimaging in healthy humans (17F/16M) to create a 3D atlas of the synaptic marker Synaptic Vesicle glycoprotein 2A (SV2A). Calibration to absolute density values (pmol/ml) was achieved by leveraging postmortem human brain autoradiography data. The atlas unveils distinctive cortical and subcortical gradients of synapse density that reflect functional topography and hierarchical order from core sensory to higher-order integrative areas-a distribution that diverges from SV2A mRNA patterns. Furthermore, we found a positive association between IQ and SV2A density in several higher-order cortical areas. This new resource will help advance our understanding of brain physiology and the pathogenesis of brain disorders, serving as a pivotal tool for future neuroscience research.
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Affiliation(s)
- Annette Johansen
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Vincent Beliveau
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
- Department of Neurology, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Emil Colliander
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Nakul Ravi Raval
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut 06520
- Yale PET Center, Yale University, New Haven, Connecticut 06520
| | - Vibeke Høyrup Dam
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
| | - Nic Gillings
- Department of Clinical Physiology and Nuclear Medicine, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
| | - Susana Aznar
- Center for Neuroscience and Stereology, Copenhagen University Hospital, Bispebjerg-Frederiksberg Hospital, Copenhagen 2400, Denmark
| | - Claus Svarer
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
| | - Pontus Plavén-Sigray
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Karolinska University Hospital, Stockholm 171 77, Sweden
| | - Gitte Moos Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen 2100, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
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15
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Hanson KL, Greiner DM, Schumann CM, Semendeferi K. Inhibitory Systems in Brain Evolution: Pathways of Vulnerability in Neurodevelopmental Disorders. BRAIN, BEHAVIOR AND EVOLUTION 2024; 100:29-48. [PMID: 39137740 PMCID: PMC11822052 DOI: 10.1159/000540865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 08/08/2024] [Indexed: 08/15/2024]
Abstract
BACKGROUND The evolution of the primate brain has been characterized by the reorganization of key structures and circuits underlying derived specializations in sensory systems, as well as social behavior and cognition. Among these, expansion and elaboration of the prefrontal cortex has been accompanied by alterations to the connectivity and organization of subcortical structures, including the striatum and amygdala, underlying advanced aspects of executive function, inhibitory behavioral control, and socioemotional cognition seen in our lineages. At the cellular level, the primate brain has further seen an increase in the diversity and number of inhibitory GABAergic interneurons. A prevailing hypothesis holds that disruptions in the balance of excitatory to inhibitory activity in the brain underlies the pathophysiology of many neurodevelopmental and psychiatric disorders. SUMMARY This review highlights the evolution of inhibitory brain systems and circuits and suggests that recent evolutionary modifications to GABAergic circuitry may provide the substrate for vulnerability to aberrant neurodevelopment. We further discuss how modifications to primate and human social organization and life history may shape brain development in ways that contribute to neurodivergence and the origins of neurodevelopmental disorders. KEY MESSAGES Many brain systems have seen functional reorganization in the mammalian, primate, and human brain. Alterations to inhibitory circuitry in frontostriatal and frontoamygdalar systems support changes in social behavior and cognition. Increased complexity of inhibitory systems may underlie vulnerabilities to neurodevelopmental and psychiatric disorders, including autism and schizophrenia. Changes observed in Williams syndrome may further elucidate the mechanisms by which alterations in inhibitory systems lead to changes in behavior and cognition. Developmental processes, including altered neuroimmune function and age-related vulnerability of inhibitory cells and synapses, may lead to worsening symptomatology in neurodevelopmental and psychiatric disorders. BACKGROUND The evolution of the primate brain has been characterized by the reorganization of key structures and circuits underlying derived specializations in sensory systems, as well as social behavior and cognition. Among these, expansion and elaboration of the prefrontal cortex has been accompanied by alterations to the connectivity and organization of subcortical structures, including the striatum and amygdala, underlying advanced aspects of executive function, inhibitory behavioral control, and socioemotional cognition seen in our lineages. At the cellular level, the primate brain has further seen an increase in the diversity and number of inhibitory GABAergic interneurons. A prevailing hypothesis holds that disruptions in the balance of excitatory to inhibitory activity in the brain underlies the pathophysiology of many neurodevelopmental and psychiatric disorders. SUMMARY This review highlights the evolution of inhibitory brain systems and circuits and suggests that recent evolutionary modifications to GABAergic circuitry may provide the substrate for vulnerability to aberrant neurodevelopment. We further discuss how modifications to primate and human social organization and life history may shape brain development in ways that contribute to neurodivergence and the origins of neurodevelopmental disorders. KEY MESSAGES Many brain systems have seen functional reorganization in the mammalian, primate, and human brain. Alterations to inhibitory circuitry in frontostriatal and frontoamygdalar systems support changes in social behavior and cognition. Increased complexity of inhibitory systems may underlie vulnerabilities to neurodevelopmental and psychiatric disorders, including autism and schizophrenia. Changes observed in Williams syndrome may further elucidate the mechanisms by which alterations in inhibitory systems lead to changes in behavior and cognition. Developmental processes, including altered neuroimmune function and age-related vulnerability of inhibitory cells and synapses, may lead to worsening symptomatology in neurodevelopmental and psychiatric disorders.
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Affiliation(s)
- Kari L. Hanson
- Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, Sacramento, CA, USA
- MIND Institute, UC Davis School of Medicine, Sacramento, CA, USA
| | - Demi M.Z. Greiner
- Department of Anthropology, University of California San Diego, La Jolla, CA, USA
| | - Cynthia M. Schumann
- Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, Sacramento, CA, USA
- MIND Institute, UC Davis School of Medicine, Sacramento, CA, USA
| | - Katerina Semendeferi
- Department of Anthropology, University of California San Diego, La Jolla, CA, USA
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16
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Zhen Y, Yang Y, Zheng Y, Wang X, Liu L, Zheng Z, Zheng H, Tang S. The heritability and structural correlates of resting-state fMRI complexity. Neuroimage 2024; 296:120657. [PMID: 38810892 DOI: 10.1016/j.neuroimage.2024.120657] [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: 03/09/2024] [Revised: 05/24/2024] [Accepted: 05/26/2024] [Indexed: 05/31/2024] Open
Abstract
The complexity of fMRI signals quantifies temporal dynamics of spontaneous neural activity, which has been increasingly recognized as providing important insights into cognitive functions and psychiatric disorders. However, its heritability and structural underpinnings are not well understood. Here, we utilize multi-scale sample entropy to extract resting-state fMRI complexity in a large healthy adult sample from the Human Connectome Project. We show that fMRI complexity at multiple time scales is heritable in broad brain regions. Heritability estimates are modest and regionally variable. We relate fMRI complexity to brain structure including surface area, cortical myelination, cortical thickness, subcortical volumes, and total brain volume. We find that surface area is negatively correlated with fine-scale complexity and positively correlated with coarse-scale complexity in most cortical regions, especially the association cortex. Most of these correlations are related to common genetic and environmental effects. We also find positive correlations between cortical myelination and fMRI complexity at fine scales and negative correlations at coarse scales in the prefrontal cortex, lateral temporal lobe, precuneus, lateral parietal cortex, and cingulate cortex, with these correlations mainly attributed to common environmental effects. We detect few significant associations between fMRI complexity and cortical thickness. Despite the non-significant association with total brain volume, fMRI complexity exhibits significant correlations with subcortical volumes in the hippocampus, cerebellum, putamen, and pallidum at certain scales. Collectively, our work establishes the genetic basis and structural correlates of resting-state fMRI complexity across multiple scales, supporting its potential application as an endophenotype for psychiatric disorders.
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Affiliation(s)
- Yi Zhen
- School of Mathematical Sciences, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
| | - Yaqian Yang
- School of Mathematical Sciences, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
| | - Yi Zheng
- School of Mathematical Sciences, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China
| | - Xin Wang
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China; Zhongguancun Laboratory, Beijing 100094, China; Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China; PengCheng Laboratory, Shenzhen 518055, China
| | - Longzhao Liu
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China; Zhongguancun Laboratory, Beijing 100094, China; Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China; PengCheng Laboratory, Shenzhen 518055, China
| | - Zhiming Zheng
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China; Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China; Zhongguancun Laboratory, Beijing 100094, China; Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China; PengCheng Laboratory, Shenzhen 518055, China; State Key Lab of Software Development Environment, Beihang University, Beijing 100191, China
| | - Hongwei Zheng
- Beijing Academy of Blockchain and Edge Computing, Beijing 100085, China.
| | - Shaoting Tang
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China; Key laboratory of Mathematics, Informatics and Behavioral Semantics, Beihang University, Beijing 100191, China; Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China; Zhongguancun Laboratory, Beijing 100094, China; Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China; PengCheng Laboratory, Shenzhen 518055, China; State Key Lab of Software Development Environment, Beihang University, Beijing 100191, China.
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17
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Lu Y, Cui Y, Cao L, Dong Z, Cheng L, Wu W, Wang C, Liu X, Liu Y, Zhang B, Li D, Zhao B, Wang H, Li K, Ma L, Shi W, Li W, Ma Y, Du Z, Zhang J, Xiong H, Luo N, Liu Y, Hou X, Han J, Sun H, Cai T, Peng Q, Feng L, Wang J, Paxinos G, Yang Z, Fan L, Jiang T. Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology. Sci Bull (Beijing) 2024; 69:2241-2259. [PMID: 38580551 DOI: 10.1016/j.scib.2024.03.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/18/2024] [Accepted: 03/11/2024] [Indexed: 04/07/2024]
Abstract
The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.
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Affiliation(s)
- Yuheng Lu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Long Cao
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China; Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Zhenwei Dong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Luqi Cheng
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Wen Wu
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Changshuo Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Xinyi Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Youtong Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Baogui Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Deying Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Bokai Zhao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Kaixin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China
| | - Liang Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weiyang Shi
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wen Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yawei Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Zongchang Du
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiaqi Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Xiong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Na Luo
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yanyan Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Xiaoxiao Hou
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jinglu Han
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Science, Beijing 100049, China
| | - Hongji Sun
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Tao Cai
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Qiang Peng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Linqing Feng
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - George Paxinos
- Neuroscience Research Australia and The University of New South Wales, Sydney NSW 2031, Australia
| | - Zhengyi Yang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China.
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, China.
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18
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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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19
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Allen TA, Hallquist MN, Dombrovski AY. Callousness, exploitativeness, and tracking of cooperation incentives in the human default network. Proc Natl Acad Sci U S A 2024; 121:e2307221121. [PMID: 38980906 PMCID: PMC11260090 DOI: 10.1073/pnas.2307221121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 04/12/2024] [Indexed: 07/11/2024] Open
Abstract
Human cognitive capacities that enable flexible cooperation may have evolved in parallel with the expansion of frontoparietal cortical networks, particularly the default network. Conversely, human antisocial behavior and trait antagonism are broadly associated with reduced activity, impaired connectivity, and altered structure of the default network. Yet, behaviors like interpersonal manipulation and exploitation may require intact or even superior social cognition. Using a reinforcement learning model of decision-making on a modified trust game, we examined how individuals adjusted their cooperation rate based on a counterpart's cooperation and social reputation. We observed that learning signals in the default network updated the predicted utility of cooperation or defection and scaled with reciprocal cooperation. These signals were weaker in callous (vs. compassionate) individuals but stronger in those who were more exploitative (vs. honest and humble). Further, they accounted for associations between exploitativeness, callousness, and reciprocal cooperation. Separately, behavioral sensitivity to prior reputation was reduced in callous but not exploitative individuals and selectively scaled with responses of the medial temporal subsystem of the default network. Overall, callousness was characterized by blunted behavioral and default network sensitivity to cooperation incentives. Exploitativeness predicted heightened sensitivity to others' cooperation but not social reputation. We speculate that both compassion and exploitativeness may reflect cognitive adaptations to social living, enabled by expansion of the default network in anthropogenesis.
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Affiliation(s)
- Timothy A. Allen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA15213
| | - Michael N. Hallquist
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC27599
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20
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Eichert N, DeKraker J, Howard AFD, Huszar IN, Zhu S, Sallet J, Miller KL, Mars RB, Jbabdi S, Bernhardt BC. Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain. Nat Commun 2024; 15:5963. [PMID: 39013855 PMCID: PMC11252401 DOI: 10.1038/s41467-024-49823-8] [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: 09/25/2023] [Accepted: 06/17/2024] [Indexed: 07/18/2024] Open
Abstract
While the hippocampus is key for human cognitive abilities, it is also a phylogenetically old cortex and paradoxically considered evolutionarily preserved. Here, we introduce a comparative framework to quantify preservation and reconfiguration of hippocampal organisation in primate evolution, by analysing the hippocampus as an unfolded cortical surface that is geometrically matched across species. Our findings revealed an overall conservation of hippocampal macro- and micro-structure, which shows anterior-posterior and, perpendicularly, subfield-related organisational axes in both humans and macaques. However, while functional organisation in both species followed an anterior-posterior axis, we observed a marked reconfiguration in the latter across species, which mirrors a rudimentary integration of the default-mode-network in non-human primates. Here we show that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration in primate evolution, due to their embedding within heteromodal association networks.
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Affiliation(s)
- Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.
| | - Jordan DeKraker
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Amy F D Howard
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Silei Zhu
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Jérôme Sallet
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- INSERM U1208 Stem Cell and Brain Research Institute, Univ Lyon, Bron, France
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Boris C Bernhardt
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
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21
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Wang Y, Cheng L, Li D, Lu Y, Wang C, Wang Y, Gao C, Wang H, Vanduffel W, Hopkins WD, Sherwood CC, Jiang T, Chu C, Fan L. Comparative Analysis of Human-Chimpanzee Divergence in Brain Connectivity and its Genetic Correlates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.03.597252. [PMID: 38895242 PMCID: PMC11185649 DOI: 10.1101/2024.06.03.597252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Chimpanzees (Pan troglodytes) are humans' closest living relatives, making them the most directly relevant comparison point for understanding human brain evolution. Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occured along the human lineage. However, conducting comparisons of brain connectivity between humans and chimpanzees remains challenging, as cross-species brain atlases established within the same framework are currently lacking. Without the availability of cross-species brain atlases, the region-wise connectivity patterns between humans and chimpanzees cannot be directly compared. To address this gap, we built the first Chimpanzee Brainnetome Atlas (ChimpBNA) by following a well-established connectivity-based parcellation framework. Leveraging this new resource, we found substantial divergence in connectivity patterns across most association cortices, notably in the lateral temporal and dorsolateral prefrontal cortex between the two species. Intriguingly, these patterns significantly deviate from the patterns of cortical expansion observed in humans compared to chimpanzees. Additionally, we identified regions displaying connectional asymmetries that differed between species, likely resulting from evolutionary divergence. Genes associated with these divergent connectivities were found to be enriched in cell types crucial for cortical projection circuits and synapse formation. These genes exhibited more pronounced differences in expression patterns in regions with higher connectivity divergence, suggesting a potential foundation for brain connectivity evolution. Therefore, our study not only provides a fine-scale brain atlas of chimpanzees but also highlights the connectivity divergence between humans and chimpanzees in a more rigorous and comparative manner and suggests potential genetic correlates for the observed divergence in brain connectivity patterns between the two species. This can help us better understand the origins and development of uniquely human cognitive capabilities.
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Affiliation(s)
- Yufan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Luqi Cheng
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Deying Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yuheng Lu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Changshuo Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yaping Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Chaohong Gao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- Department of Neurosciences, Laboratory of Neuro- and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium
| | - Wim Vanduffel
- Department of Neurosciences, Laboratory of Neuro- and Psychophysiology, KU Leuven Medical School, 3000 Leuven, Belgium
- Leuven Brain Institute, KU Leuven, 3000 Leuven, Belgium
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02144, USA
| | - William D. Hopkins
- Department of Comparative Medicine, University of Texas MD Anderson Cancer Center, Bastrop, TX 78602, USA
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC 20052, USA
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311100, China
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China
- School of Health and Life Sciences, University of Health and Rehabilitation Sciences, Qingdao 266000, China
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22
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Bo K, Kraynak TE, Kwon M, Sun M, Gianaros PJ, Wager TD. A systems identification approach using Bayes factors to deconstruct the brain bases of emotion regulation. Nat Neurosci 2024; 27:975-987. [PMID: 38519748 DOI: 10.1038/s41593-024-01605-7] [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: 05/15/2023] [Accepted: 02/15/2024] [Indexed: 03/25/2024]
Abstract
Cognitive reappraisal is fundamental to cognitive therapies and everyday emotion regulation. Analyses using Bayes factors and an axiomatic systems identification approach identified four reappraisal-related components encompassing distributed neural activity patterns across two independent functional magnetic resonance imaging (fMRI) studies (n = 182 and n = 176): (1) an anterior prefrontal system selectively involved in cognitive reappraisal; (2) a fronto-parietal-insular system engaged by both reappraisal and emotion generation, demonstrating a general role in appraisal; (3) a largely subcortical system activated during negative emotion generation but unaffected by reappraisal, including amygdala, hypothalamus and periaqueductal gray; and (4) a posterior cortical system of negative emotion-related regions downregulated by reappraisal. These systems covaried with individual differences in reappraisal success and were differentially related to neurotransmitter binding maps, implicating cannabinoid and serotonin systems in reappraisal. These findings challenge 'limbic'-centric models of reappraisal and provide new systems-level targets for assessing and enhancing emotion regulation.
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Affiliation(s)
- Ke Bo
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Thomas E Kraynak
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mijin Kwon
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Michael Sun
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Peter J Gianaros
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Tor D Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
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23
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Wu G, Cui Z, Wang X, Du Y. Unveiling the Core Functional Networks of Cognition: An Ontology-Guided Machine Learning Approach. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.02.587855. [PMID: 38617291 PMCID: PMC11014632 DOI: 10.1101/2024.04.02.587855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Deciphering the functional architecture that underpins diverse cognitive functions is fundamental quest in neuroscience. In this study, we employed an innovative machine learning framework that integrated cognitive ontology with functional connectivity analysis to identify brain networks essential for cognition. We identified a core assembly of functional connectomes, primarily located within the association cortex, which showed superior predictive performance compared to two conventional methods widely employed in previous research across various cognitive domains. Our approach achieved a mean prediction accuracy of 0.13 across 16 cognitive tasks, including working memory, reading comprehension, and sustained attention, outperforming the traditional methods' accuracy of 0.08. In contrast, our method showed limited predictive power for sensory, motor, and emotional functions, with a mean prediction accuracy of 0.03 across 9 relevant tasks, slightly lower than the traditional methods' accuracy of 0.04. These cognitive connectomes were further characterized by distinctive patterns of resting-state functional connectivity, structural connectivity via white matter tracts, and gene expression, highlighting their neurogenetic underpinnings. Our findings reveal a domain-general functional network fingerprint that pivotal to cognition, offering a novel computational approach to explore the neural foundations of cognitive abilities.
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Affiliation(s)
- Guowei Wu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Chaoyang, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Xiuyi Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Chaoyang, Beijing 100101, China
| | - Yi Du
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Chaoyang, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
- Chinese Institute for Brain Research, Beijing 102206, China
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24
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Luppi AI, Rosas FE, Noonan MP, Mediano PAM, Kringelbach ML, Carhart-Harris RL, Stamatakis EA, Vernon AC, Turkheimer FE. Oxygen and the Spark of Human Brain Evolution: Complex Interactions of Metabolism and Cortical Expansion across Development and Evolution. Neuroscientist 2024; 30:173-198. [PMID: 36476177 DOI: 10.1177/10738584221138032] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
Scientific theories on the functioning and dysfunction of the human brain require an understanding of its development-before and after birth and through maturation to adulthood-and its evolution. Here we bring together several accounts of human brain evolution by focusing on the central role of oxygen and brain metabolism. We argue that evolutionary expansion of human transmodal association cortices exceeded the capacity of oxygen delivery by the vascular system, which led these brain tissues to rely on nonoxidative glycolysis for additional energy supply. We draw a link between the resulting lower oxygen tension and its effect on cytoarchitecture, which we posit as a key driver of genetic developmental programs for the human brain-favoring lower intracortical myelination and the presence of biosynthetic materials for synapse turnover. Across biological and temporal scales, this protracted capacity for neural plasticity sets the conditions for cognitive flexibility and ongoing learning, supporting complex group dynamics and intergenerational learning that in turn enabled improved nutrition to fuel the metabolic costs of further cortical expansion. Our proposed model delineates explicit mechanistic links among metabolism, molecular and cellular brain heterogeneity, and behavior, which may lead toward a clearer understanding of brain development and its disorders.
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Affiliation(s)
- Andrea I Luppi
- Department of Clinical Neurosciences and Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - Fernando E Rosas
- Department of Informatics, University of Sussex, Brighton, UK
- Centre for Psychedelic Research, Department of Brain Science, Imperial College London, London, UK
- Centre for Complexity Science, Imperial College London, London, UK
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
| | - MaryAnn P Noonan
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Pedro A M Mediano
- Department of Psychology, University of Cambridge, Cambridge, UK
- Department of Psychology, Queen Mary University of London, London, UK
- Department of Computing, Imperial College London, London, UK
| | - Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Robin L Carhart-Harris
- Psychedelics Division-Neuroscape, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Emmanuel A Stamatakis
- Department of Clinical Neurosciences and Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Anthony C Vernon
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Federico E Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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25
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Luppi AI, Rosas FE, Mediano PAM, Menon DK, Stamatakis EA. Information decomposition and the informational architecture of the brain. Trends Cogn Sci 2024; 28:352-368. [PMID: 38199949 DOI: 10.1016/j.tics.2023.11.005] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 11/09/2023] [Accepted: 11/17/2023] [Indexed: 01/12/2024]
Abstract
To explain how the brain orchestrates information-processing for cognition, we must understand information itself. Importantly, information is not a monolithic entity. Information decomposition techniques provide a way to split information into its constituent elements: unique, redundant, and synergistic information. We review how disentangling synergistic and redundant interactions is redefining our understanding of integrative brain function and its neural organisation. To explain how the brain navigates the trade-offs between redundancy and synergy, we review converging evidence integrating the structural, molecular, and functional underpinnings of synergy and redundancy; their roles in cognition and computation; and how they might arise over evolution and development. Overall, disentangling synergistic and redundant information provides a guiding principle for understanding the informational architecture of the brain and cognition.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, University of Cambridge, Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Fernando E Rosas
- Department of Informatics, University of Sussex, Brighton, UK; Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK; Centre for Complexity Science, Imperial College London, London, UK; Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
| | - Pedro A M Mediano
- Department of Computing, Imperial College London, London, UK; Department of Psychology, University of Cambridge, Cambridge, UK
| | - David K Menon
- Department of Medicine, University of Cambridge, Cambridge, UK; Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, University of Cambridge, Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
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26
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Wang Y, Wang Y, Wang H, Ma L, Eickhoff SB, Madsen KH, Chu C, Fan L. Spatio-molecular profiles shape the human cerebellar hierarchy along the sensorimotor-association axis. Cell Rep 2024; 43:113770. [PMID: 38363683 DOI: 10.1016/j.celrep.2024.113770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/27/2023] [Accepted: 01/25/2024] [Indexed: 02/18/2024] Open
Abstract
Cerebellar involvement in both motor and non-motor functions manifests in specific regions of the human cerebellum, revealing the functional heterogeneity within it. One compelling theory places the heterogeneity within the cerebellar functional hierarchy along the sensorimotor-association (SA) axis. Despite extensive neuroimaging studies, evidence for the cerebellar SA axis from different modalities and scales was lacking. Thus, we establish a significant link between the cerebellar SA axis and spatio-molecular profiles. Utilizing the gene set variation analysis, we find the intermediate biological principles the significant genes leveraged to scaffold the cerebellar SA axis. Interestingly, we find these spatio-molecular profiles notably associated with neuropsychiatric dysfunction and recent evolution. Furthermore, cerebello-cerebral interactions at genetic and functional connectivity levels mirror the cerebral cortex and cerebellum's SA axis. These findings can provide a deeper understanding of how the human cerebellar SA axis is shaped and its role in transitioning from sensorimotor to association functions.
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Affiliation(s)
- Yaping Wang
- Sino-Danish Center, University of Chinese Academy of Sciences, Beijing 100190, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yufan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Haiyan Wang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Liang Ma
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, 52425 Jülich, Germany; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Kristoffer Hougaard Madsen
- Sino-Danish Center, University of Chinese Academy of Sciences, Beijing 100190, China; Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, 2650 Hvidovre, Denmark
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
| | - Lingzhong Fan
- Sino-Danish Center, University of Chinese Academy of Sciences, Beijing 100190, China; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Health and Life Sciences, University of Health and Rehabilitation Sciences, Qingdao 266000, China.
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27
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Piszczek L, Kaczanowska J, Haubensak W. Towards correlative archaeology of the human mind. Biol Chem 2024; 405:5-12. [PMID: 37819768 PMCID: PMC10687516 DOI: 10.1515/hsz-2023-0199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 09/20/2023] [Indexed: 10/13/2023]
Abstract
Retracing human cognitive origins started out at the systems level with the top-down interpretation of archaeological records spanning from man-made artifacts to endocasts of ancient skulls. With emerging evolutionary genetics and organoid technologies, it is now possible to deconstruct evolutionary processes on a molecular/cellular level from the bottom-up by functionally testing archaic alleles in experimental models. The current challenge is to complement these approaches with novel strategies that allow a holistic reconstruction of evolutionary patterns across human cognitive domains. We argue that computational neuroarcheology can provide such a critical mesoscale framework at the brain network-level, linking molecular/cellular (bottom-up) to systems (top-down) level data for the correlative archeology of the human mind.
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Affiliation(s)
- Lukasz Piszczek
- Department of Neuronal Cell Biology, Center for Brain Research, Medical University of Vienna, A-Vienna, Austria
| | | | - Wulf Haubensak
- Department of Neuronal Cell Biology, Center for Brain Research, Medical University of Vienna, A-Vienna, Austria
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-Biocenter 1, A-1030Vienna, Austria
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28
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Luppi AI, Girn M, Rosas FE, Timmermann C, Roseman L, Erritzoe D, Nutt DJ, Stamatakis EA, Spreng RN, Xing L, Huttner WB, Carhart-Harris RL. A role for the serotonin 2A receptor in the expansion and functioning of human transmodal cortex. Brain 2024; 147:56-80. [PMID: 37703310 DOI: 10.1093/brain/awad311] [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: 04/13/2023] [Revised: 08/14/2023] [Accepted: 08/18/2023] [Indexed: 09/15/2023] Open
Abstract
Integrating independent but converging lines of research on brain function and neurodevelopment across scales, this article proposes that serotonin 2A receptor (5-HT2AR) signalling is an evolutionary and developmental driver and potent modulator of the macroscale functional organization of the human cerebral cortex. A wealth of evidence indicates that the anatomical and functional organization of the cortex follows a unimodal-to-transmodal gradient. Situated at the apex of this processing hierarchy-where it plays a central role in the integrative processes underpinning complex, human-defining cognition-the transmodal cortex has disproportionately expanded across human development and evolution. Notably, the adult human transmodal cortex is especially rich in 5-HT2AR expression and recent evidence suggests that, during early brain development, 5-HT2AR signalling on neural progenitor cells stimulates their proliferation-a critical process for evolutionarily-relevant cortical expansion. Drawing on multimodal neuroimaging and cross-species investigations, we argue that, by contributing to the expansion of the human cortex and being prevalent at the apex of its hierarchy in the adult brain, 5-HT2AR signalling plays a major role in both human cortical expansion and functioning. Owing to its unique excitatory and downstream cellular effects, neuronal 5-HT2AR agonism promotes neuroplasticity, learning and cognitive and psychological flexibility in a context-(hyper)sensitive manner with therapeutic potential. Overall, we delineate a dual role of 5-HT2ARs in enabling both the expansion and modulation of the human transmodal cortex.
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Affiliation(s)
- Andrea I Luppi
- Department of Clinical Neurosciences and Division of Anaesthesia, University of Cambridge, Cambridge, CB2 0QQ, UK
- Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, CB2 1SB, UK
- The Alan Turing Institute, London, NW1 2DB, UK
| | - Manesh Girn
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, H3A 2B4, Canada
- Psychedelics Division-Neuroscape, Department of Neurology, University of California SanFrancisco, San Francisco, CA 94158, USA
| | - Fernando E Rosas
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
- Data Science Institute, Imperial College London, London, SW7 2AZ, UK
- Centre for Complexity Science, Imperial College London, London, SW7 2AZ, UK
| | - Christopher Timmermann
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Leor Roseman
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - David Erritzoe
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - David J Nutt
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Emmanuel A Stamatakis
- Department of Clinical Neurosciences and Division of Anaesthesia, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - R Nathan Spreng
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, H3A 2B4, Canada
| | - Lei Xing
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, 01307, Germany
| | - Wieland B Huttner
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, 01307, Germany
| | - Robin L Carhart-Harris
- Psychedelics Division-Neuroscape, Department of Neurology, University of California SanFrancisco, San Francisco, CA 94158, USA
- Centre for Psychedelic Research, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
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29
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Gu YW, Fan JW, Zhào H, Zhao SW, Liu XF, Yu R, Ren L, Wang X, Yin H, Cui LB. Imaging Transcriptomics of the Brain for Schizophrenia. ALPHA PSYCHIATRY 2024; 25:9-14. [PMID: 38799487 PMCID: PMC11114239 DOI: 10.5152/alphapsychiatry.2024.231369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 12/04/2023] [Indexed: 05/29/2024]
Abstract
Schizophrenia is a severe mental disorder with a neurodevelopmental origin. Although schizophrenia results from changes in the brain, the underlying biological mechanisms are unknown. Transcriptomics studies quantitative expression changes or qualitative changes of all genes and isoforms, providing a more meaningful biological insight. Magnetic resonance imaging (MRI) techniques play roles in revealing brain structure and function. We give a narrative focused review on the current transcriptome combined with MRI studies related to schizophrenia and summarize the research methodology and content of these studies to identify the research commonalities as well as the implications for future research, in an attempt to provide new insights into the mechanism, clinical diagnosis, and treatments of schizophrenia.
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Affiliation(s)
- Yue-Wen Gu
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
- Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Jing-Wen Fan
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
- Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Hóngyi Zhào
- Department of Neurology, NO. 984 Hospital of PLA, Beijing, China
| | - Shu-Wan Zhao
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
- Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Xiao-Fan Liu
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
| | - Renqiang Yu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lei Ren
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
| | - Xinjiang Wang
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China
- Department of Radiology, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, Air Force Medical University, Xi’an, China
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
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30
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Castrillon G, Epp S, Bose A, Fraticelli L, Hechler A, Belenya R, Ranft A, Yakushev I, Utz L, Sundar L, Rauschecker JP, Preibisch C, Kurcyus K, Riedl V. An energy costly architecture of neuromodulators for human brain evolution and cognition. SCIENCE ADVANCES 2023; 9:eadi7632. [PMID: 38091393 PMCID: PMC10848727 DOI: 10.1126/sciadv.adi7632] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 11/10/2023] [Indexed: 12/18/2023]
Abstract
In comparison to other species, the human brain exhibits one of the highest energy demands relative to body metabolism. It remains unclear whether this heightened energy demand uniformly supports an enlarged brain or if specific signaling mechanisms necessitate greater energy. We hypothesized that the regional distribution of energy demands will reveal signaling strategies that have contributed to human cognitive development. We measured the energy distribution within the brain functional connectome using multimodal brain imaging and found that signaling pathways in evolutionarily expanded regions have up to 67% higher energetic costs than those in sensory-motor regions. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an up-regulation of signaling at G-protein-coupled receptors in energy-demanding regions. Our findings indicate that neuromodulator activity is predominantly involved in cognitive functions, such as reading or memory processing. This study suggests that an up-regulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.
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Affiliation(s)
- Gabriel Castrillon
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Research Group in Medical Imaging, SURA Ayudas Diagnósticas, Medellin, Colombia
- Department of Neuroradiology at Uniklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Samira Epp
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Antonia Bose
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Laura Fraticelli
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Munich, Germany
| | - André Hechler
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Roman Belenya
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care Medicine at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Igor Yakushev
- Department of Nuclear Medicine at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Lukas Utz
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Lalith Sundar
- Quantitative Imaging and Medical Physics Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Josef P Rauschecker
- Center for Neuroengineering, Georgetown University, Washington, DC, USA
- Institute for Advanced Study, Technical University of Munich, Munich, Germany
| | - Christine Preibisch
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Department of Neurology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Katarzyna Kurcyus
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Valentin Riedl
- Department of Neuroradiology at Klinikum rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
- Department of Neuroradiology at Uniklinikum Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
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31
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Bazinet V, Hansen JY, Misic B. Towards a biologically annotated brain connectome. Nat Rev Neurosci 2023; 24:747-760. [PMID: 37848663 DOI: 10.1038/s41583-023-00752-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/20/2023] [Indexed: 10/19/2023]
Abstract
The brain is a network of interleaved neural circuits. In modern connectomics, brain connectivity is typically encoded as a network of nodes and edges, abstracting away the rich biological detail of local neuronal populations. Yet biological annotations for network nodes - such as gene expression, cytoarchitecture, neurotransmitter receptors or intrinsic dynamics - can be readily measured and overlaid on network models. Here we review how connectomes can be represented and analysed as annotated networks. Annotated connectomes allow us to reconceptualize architectural features of networks and to relate the connection patterns of brain regions to their underlying biology. Emerging work demonstrates that annotated connectomes help to make more veridical models of brain network formation, neural dynamics and disease propagation. Finally, annotations can be used to infer entirely new inter-regional relationships and to construct new types of network that complement existing connectome representations. In summary, biologically annotated connectomes offer a compelling way to study neural wiring in concert with local biological features.
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Affiliation(s)
- Vincent Bazinet
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Justine Y Hansen
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada.
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32
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Li Z, Li J, Wang N, Lv Y, Zou Q, Wang J. Single-subject cortical morphological brain networks: Phenotypic associations and neurobiological substrates. Neuroimage 2023; 283:120434. [PMID: 37907157 DOI: 10.1016/j.neuroimage.2023.120434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 10/28/2023] [Accepted: 10/28/2023] [Indexed: 11/02/2023] Open
Abstract
Although single-subject morphological brain networks provide an important way for human connectome studies, their roles and origins are poorly understood. Combining cross-sectional and repeated structural magnetic resonance imaging scans from adults, children and twins with behavioral and cognitive measures and brain-wide transcriptomic, cytoarchitectonic and chemoarchitectonic data, this study examined phenotypic associations and neurobiological substrates of single-subject morphological brain networks. We found that single-subject morphological brain networks explained inter-individual variance and predicted individual outcomes in Motor and Cognition domains, and distinguished individuals from each other. The performance can be further improved by integrating different morphological indices for network construction. Low-moderate heritability was observed for single-subject morphological brain networks with the highest heritability for sulcal depth-derived networks and higher heritability for inter-module connections. Furthermore, differential roles of genetic, cytoarchitectonic and chemoarchitectonic factors were observed for single-subject morphological brain networks. Cortical thickness-derived networks were related to the three factors with contributions from genes enriched in membrane and transport related functions, genes preferentially located in supragranular and granular layers, overall thickness in the molecular layer and thickness of wall in the infragranular layers, and metabotropic glutamate receptor 5 and dopamine transporter; fractal dimension-, gyrification index- and sulcal depth-derived networks were only associated with the chemoarchitectonic factor with contributions from different sets of neurotransmitter receptors. Most results were reproducible across different parcellation schemes and datasets. Altogether, this study demonstrates phenotypic associations and neurobiological substrates of single-subject morphological brain networks, which provide intermediate endophenotypes to link molecular and cellular architecture and behavior and cognition.
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Affiliation(s)
- Zhen Li
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Junle Li
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Ningkai Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Yating Lv
- Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Qihong Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; Center for Studies of Psychological Application, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China.
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33
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Luppi AI, Golkowski D, Ranft A, Ilg R, Jordan D, Bzdok D, Owen AM, Naci L, Stamatakis EA, Amico E, Misic B. General anaesthesia reduces the uniqueness of brain connectivity across individuals and across species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.08.566332. [PMID: 38014199 PMCID: PMC10680788 DOI: 10.1101/2023.11.08.566332] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The human brain is characterised by idiosyncratic patterns of spontaneous thought, rendering each brain uniquely identifiable from its neural activity. However, deep general anaesthesia suppresses subjective experience. Does it also suppress what makes each brain unique? Here we used functional MRI under the effects of the general anaesthetics sevoflurane and propofol to determine whether anaesthetic-induced unconsciousness diminishes the uniqueness of the human brain: both with respect to the brains of other individuals, and the brains of another species. We report that under anaesthesia individual brains become less self-similar and less distinguishable from each other. Loss of distinctiveness is highly organised: it co-localises with the archetypal sensory-association axis, correlating with genetic and morphometric markers of phylogenetic differences between humans and other primates. This effect is more evident at greater anaesthetic depths, reproducible across sevoflurane and propofol, and reversed upon recovery. Providing convergent evidence, we show that under anaesthesia the functional connectivity of the human brain becomes more similar to the macaque brain. Finally, anaesthesia diminishes the match between spontaneous brain activity and meta-analytic brain patterns aggregated from the NeuroSynth engine. Collectively, the present results reveal that anaesthetised human brains are not only less distinguishable from each other, but also less distinguishable from the brains of other primates, with specifically human-expanded regions being the most affected by anaesthesia.
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Affiliation(s)
- Andrea I Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Daniel Golkowski
- Department of Neurology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Andreas Ranft
- Department of Anesthesiology and Intensive Care, School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Rudiger Ilg
- Department of Neurology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- Asklepios Clinic, Department of Neurology, Bad Tolz, Germany
| | - Denis Jordan
- Department of Anaesthesiology and Intensive Care Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Danilo Bzdok
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- MILA, Quebec Artificial Intelligence Institute, Montréal, QC, Canada
| | - Adrian M Owen
- Western Institute for Neuroscience (WIN), Western University, London, ON, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Emmanuel A Stamatakis
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Enrico Amico
- Neuro-X Institute, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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34
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Pasquini L, Pereira FL, Seddighi S, Zeng Y, Wei Y, Illán-Gala I, Vatsavayai SC, Friedberg A, Lee AJ, Brown JA, Spina S, Grinberg LT, Sirkis DW, Bonham LW, Yokoyama JS, Boxer AL, Kramer JH, Rosen HJ, Humphrey J, Gitler AD, Miller BL, Pollard KS, Ward ME, Seeley WW. FTLD targets brain regions expressing recently evolved genes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.27.23297687. [PMID: 37961381 PMCID: PMC10635220 DOI: 10.1101/2023.10.27.23297687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
In frontotemporal lobar degeneration (FTLD), pathological protein aggregation is associated with a decline in human-specialized social-emotional and language functions. Most disease protein aggregates contain either TDP-43 (FTLD-TDP) or tau (FTLD-tau). Here, we explored whether FTLD targets brain regions that express genes containing human accelerated regions (HARs), conserved sequences that have undergone positive selection during recent human evolution. To this end, we used structural neuroimaging from patients with FTLD and normative human regional transcriptomic data to identify genes expressed in FTLD-targeted brain regions. We then integrated primate comparative genomic data to test our hypothesis that FTLD targets brain regions expressing recently evolved genes. In addition, we asked whether genes expressed in FTLD-targeted brain regions are enriched for genes that undergo cryptic splicing when TDP-43 function is impaired. We found that FTLD-TDP and FTLD-tau subtypes target brain regions that express overlapping and distinct genes, including many linked to neuromodulatory functions. Genes whose normative brain regional expression pattern correlated with FTLD cortical atrophy were strongly associated with HARs. Atrophy-correlated genes in FTLD-TDP showed greater overlap with TDP-43 cryptic splicing genes compared with atrophy-correlated genes in FTLD-tau. Cryptic splicing genes were enriched for HAR genes, and vice versa, but this effect was due to the confounding influence of gene length. Analyses performed at the individual-patient level revealed that the expression of HAR genes and cryptically spliced genes within putative regions of disease onset differed across FTLD-TDP subtypes. Overall, our findings suggest that FTLD targets brain regions that have undergone recent evolutionary specialization and provide intriguing potential leads regarding the transcriptomic basis for selective vulnerability in distinct FTLD molecular-anatomical subtypes.
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Affiliation(s)
- Lorenzo Pasquini
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
- Department of Neurology, Neuroscape, University of California, San Francisco, CA, USA
| | - Felipe L Pereira
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Sahba Seddighi
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Yi Zeng
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Ignacio Illán-Gala
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
- Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, USA and Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute, Universitat Autònoma de Barcelona, Barcelona, Catalunya, Spain
| | - Sarat C Vatsavayai
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Adit Friedberg
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
- Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, USA and Trinity College Dublin, Dublin, Ireland
| | - Alex J Lee
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Jesse A Brown
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Salvatore Spina
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Lea T Grinberg
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, CA, USA
| | - Daniel W Sirkis
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Luke W Bonham
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
- Department of Radiology, University of California, San Francisco, CA, USA
| | - Jennifer S Yokoyama
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
- Department of Radiology, University of California, San Francisco, CA, USA
| | - Adam L Boxer
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Joel H Kramer
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Jack Humphrey
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aaron D Gitler
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Katherine S Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics and Bakar Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Michael E Ward
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - William W Seeley
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, CA, USA
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Guardiola-Ripoll M, Almodóvar-Payá C, Arias-Magnasco A, Latorre-Guardia M, Papiol S, Canales-Rodríguez EJ, García-León MÁ, Fuentes-Claramonte P, Salavert J, Tristany J, Torres L, Rodríguez-Cano E, Salvador R, Pomarol-Clotet E, Fatjó-Vilas M. Human-specific evolutionary markers linked to foetal neurodevelopment modulate brain surface area in schizophrenia. Commun Biol 2023; 6:1040. [PMID: 37833414 PMCID: PMC10576001 DOI: 10.1038/s42003-023-05356-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 09/13/2023] [Indexed: 10/15/2023] Open
Abstract
Schizophrenia may represent a trade-off in the evolution of human-specific ontogenetic mechanisms that guide neurodevelopment. Human Accelerated Regions (HARs) are evolutionary markers functioning as neurodevelopmental transcription enhancers that have been associated with brain configuration, neural information processing, and schizophrenia risk. Here, we have investigated the influence of HARs' polygenic load on neuroanatomical measures through a case-control approach (128 patients with schizophrenia and 115 controls). To this end, we have calculated the global schizophrenia Polygenic Risk Score (Global PRSSZ) and that specific to HARs (HARs PRSSZ). We have also estimated the polygenic burden restricted to the HARs linked to transcriptional regulatory elements active in the foetal brain (FB-HARs PRSSZ) and the adult brain (AB-HARs PRSSZ). We have explored the main effects of the PRSs and the PRSs x diagnosis interactions on brain regional cortical thickness (CT) and surface area (SA). The results indicate that a higher FB-HARs PRSSZ is associated with patients' lower SA in the lateral orbitofrontal cortex, the superior temporal cortex, the pars triangularis and the paracentral lobule. While noHARs-derived PRSs show an effect on the risk, our neuroanatomical findings suggest that the human-specific transcriptional regulation during the prenatal period underlies SA variability, highlighting the role of these evolutionary markers in the schizophrenia genomic architecture.
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Affiliation(s)
- Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain.
| | - Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain
| | | | | | - Sergi Papiol
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Erick J Canales-Rodríguez
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - María Ángeles García-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain
| | - Josep Salavert
- Hospital Sant Rafael, Germanes Hospitalàries, Barcelona, Spain
| | - Josep Tristany
- Hospital Sagrat Cor, Germanes Hospitalàries, Martorell, Spain
| | - Llanos Torres
- Hospital Mare de Déu de la Mercè, Germanes Hospitalàries, Barcelona, Spain
| | - Elena Rodríguez-Cano
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain
- Hospital Benito Menni, Germanes Hospitalàries, Sant Boi de Llobregat, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.
- CIBERSAM (Biomedical Research Network in Mental Health; Instituto de Salud Carlos III), Madrid, Spain.
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona, Barcelona, Spain.
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Shaffer C, Barrett LF, Quigley KS. Signal processing in the vagus nerve: Hypotheses based on new genetic and anatomical evidence. Biol Psychol 2023; 182:108626. [PMID: 37419401 PMCID: PMC10563766 DOI: 10.1016/j.biopsycho.2023.108626] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 06/25/2023] [Accepted: 07/03/2023] [Indexed: 07/09/2023]
Abstract
Each organism must regulate its internal state in a metabolically efficient way as it interacts in space and time with an ever-changing and only partly predictable world. Success in this endeavor is largely determined by the ongoing communication between brain and body, and the vagus nerve is a crucial structure in that dialogue. In this review, we introduce the novel hypothesis that the afferent vagus nerve is engaged in signal processing rather than just signal relay. New genetic and structural evidence of vagal afferent fiber anatomy motivates two hypotheses: (1) that sensory signals informing on the physiological state of the body compute both spatial and temporal viscerosensory features as they ascend the vagus nerve, following patterns found in other sensory architectures, such as the visual and olfactory systems; and (2) that ascending and descending signals modulate one another, calling into question the strict segregation of sensory and motor signals, respectively. Finally, we discuss several implications of our two hypotheses for understanding the role of viscerosensory signal processing in predictive energy regulation (i.e., allostasis) as well as the role of metabolic signals in memory and in disorders of prediction (e.g., mood disorders).
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Affiliation(s)
- Clare Shaffer
- Department of Psychology, College of Science, Northeastern University, Boston, MA, USA.
| | - Lisa Feldman Barrett
- Department of Psychology, College of Science, Northeastern University, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Karen S Quigley
- Department of Psychology, College of Science, Northeastern University, Boston, MA, USA.
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37
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Iraji A, Chen J, Lewis N, Faghiri A, Fu Z, Agcaoglu O, Kochunov P, Adhikari BM, Mathalon D, Pearlson G, Macciardi F, Preda A, van Erp T, Bustillo JR, Díaz-Caneja CM, Andrés-Camazón P, Dhamala M, Adali T, Calhoun V. Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and its Links to Genetic Risk. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.18.548880. [PMID: 37503085 PMCID: PMC10370141 DOI: 10.1101/2023.07.18.548880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Background Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects. Methods We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data. Results Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks. Conclusions Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape.
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Affiliation(s)
- A. Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - J. Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - N. Lewis
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of CSE, Georgia Institute of Technology, Atlanta, Georgia
| | - A. Faghiri
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Z. Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - O. Agcaoglu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - P. Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD, USA
| | - B. M. Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD, USA
| | - D.H. Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - G.D. Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - F. Macciardi
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - A. Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - T.G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - J. R. Bustillo
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - C. M. Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - P. Andrés-Camazón
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - M. Dhamala
- Department of Physics and Astronomy, Georgia State University, Atlanta, GA, USA
| | - T. Adali
- Department of CSEE, University of Maryland, Baltimore County, Baltimore, Maryland
| | - V.D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
- Department of CSE, Georgia Institute of Technology, Atlanta, Georgia
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38
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Driessens SLW, Galakhova AA, Heyer DB, Pieterse IJ, Wilbers R, Mertens EJ, Waleboer F, Heistek TS, Coenen L, Meijer JR, Idema S, de Witt Hamer PC, Noske DP, de Kock CPJ, Lee BR, Smith K, Ting JT, Lein ES, Mansvelder HD, Goriounova NA. Genes associated with cognitive ability and HAR show overlapping expression patterns in human cortical neuron types. Nat Commun 2023; 14:4188. [PMID: 37443107 PMCID: PMC10345092 DOI: 10.1038/s41467-023-39946-9] [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: 11/07/2022] [Accepted: 07/04/2023] [Indexed: 07/15/2023] Open
Abstract
GWAS have identified numerous genes associated with human cognition but their cell type expression profiles in the human brain are unknown. These genes overlap with human accelerated regions (HARs) implicated in human brain evolution and might act on the same biological processes. Here, we investigated whether these gene sets are expressed in adult human cortical neurons, and how their expression relates to neuronal function and structure. We find that these gene sets are preferentially expressed in L3 pyramidal neurons in middle temporal gyrus (MTG). Furthermore, neurons with higher expression had larger total dendritic length (TDL) and faster action potential (AP) kinetics, properties previously linked to intelligence. We identify a subset of genes associated with TDL or AP kinetics with predominantly synaptic functions and high abundance of HARs.
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Affiliation(s)
- Stan L W Driessens
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Anna A Galakhova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Djai B Heyer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Isabel J Pieterse
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - René Wilbers
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Eline J Mertens
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Femke Waleboer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Tim S Heistek
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Loet Coenen
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Julia R Meijer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Sander Idema
- Department of Neurosurgery, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands
| | - Philip C de Witt Hamer
- Department of Neurosurgery, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands
| | - David P Noske
- Department of Neurosurgery, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, the Netherlands
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Brian R Lee
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA, 98109, USA
| | - Kimberly Smith
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA, 98109, USA
| | - Jonathan T Ting
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA, 98109, USA
| | - Ed S Lein
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA, 98109, USA
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands
| | - Natalia A Goriounova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands.
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Cui LB, Wang XY, Fu YF, Liu XF, Wei Y, Zhao SW, Gu YW, Fan JW, Wu WJ, Gong H, Lin BD, Yin H, Guan F, Chang X. Transcriptional level of inflammation markers associates with short-term brain structural changes in first-episode schizophrenia. BMC Med 2023; 21:250. [PMID: 37424013 PMCID: PMC10332052 DOI: 10.1186/s12916-023-02963-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 06/26/2023] [Indexed: 07/11/2023] Open
Abstract
BACKGROUND Inflammation has been implicated in the pathology of schizophrenia and may cause neuronal cell death and dendrite loss. Neuroimaging studies have highlighted longitudinal brain structural changes in patients with schizophrenia, yet it is unclear whether this is related to inflammation. We aim to address this question, by relating brain structural changes with the transcriptional profile of inflammation markers in the early stage of schizophrenia. METHODS Thirty-eight patients with first-episode schizophrenia and 51 healthy controls were included. High-resolution T1-weighted magnetic resonance imaging (MRI) and clinical assessments were performed at baseline and 2 ~ 6 months follow-up for all subjects. Changes in the brain structure were analyzed using surface-based morphological analysis and correlated with the expression of immune cells-related gene sets of interest reported by previous reviews. Transcriptional data were retrieved from the Allen Human Brain Atlas. Furthermore, we examined the brain structural changes and peripheral inflammation markers in association with behavioral symptoms and cognitive functioning in patients. RESULTS Patients exhibited accelerated cortical thickness decrease in the left frontal cortices, less decrease or an increase in the superior parietal lobule and right lateral occipital lobe, and increased volume in the bilateral pallidum, compared with controls. Changes in cortical thickness correlated with the transcriptional level of monocyte across cortical regions in patients (r = 0.54, p < 0.01), but not in controls (r = - 0.05, p = 0.76). In addition, cortical thickness change in the left superior parietal lobule positively correlated with changes in digital span-backward test scores in patients. CONCLUSIONS Patients with schizophrenia exhibit regional-specific cortical thickness changes in the prefrontal and parietooccipital cortices, which is related to their cognitive impairment. Inflammation may be an important factor contributing to cortical thinning in first-episode schizophrenia. Our findings suggest that the immunity-brain-behavior association may play a crucial role in the pathogenesis of schizophrenia.
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Affiliation(s)
- Long-Biao Cui
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China.
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China.
| | - Xian-Yang Wang
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Xiao-Fan Liu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Shu-Wan Zhao
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yue-Wen Gu
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Jing-Wen Fan
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hengfen Gong
- School of Medicine, Shanghai Pudong New Area Mental Health Center, Tongji University, Shanghai, China
| | - Bochao Danae Lin
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Fanglin Guan
- Department of Forensic Psychiatry, School of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, China.
| | - Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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40
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Fan JW, Gu YW, Wang DB, Liu XF, Zhao SW, Li X, Li B, Yin H, Wu WJ, Cui LB. Transcriptomics and magnetic resonance imaging in major psychiatric disorders. Front Psychiatry 2023; 14:1185471. [PMID: 37383618 PMCID: PMC10296768 DOI: 10.3389/fpsyt.2023.1185471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 05/16/2023] [Indexed: 06/30/2023] Open
Abstract
Major psychiatric disorders create a significant public health burden, and mental disorders such as major depressive disorder, bipolar disorder, and schizophrenia are major contributors to the national disease burden. The search for biomarkers has been a leading endeavor in the field of biological psychiatry in recent decades. And the application of cross-scale and multi-omics approaches combining genes and imaging in major psychiatric studies has facilitated the elucidation of gene-related pathogenesis and the exploration of potential biomarkers. In this article, we summarize the results of using combined transcriptomics and magnetic resonance imaging to understand structural and functional brain changes associated with major psychiatric disorders in the last decade, demonstrating the neurobiological mechanisms of genetically related structural and functional brain alterations in multiple directions, and providing new avenues for the development of quantifiable objective biomarkers, as well as clinical diagnostic and prognostic indicators.
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Affiliation(s)
- Jing-Wen Fan
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yue-Wen Gu
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Dong-Bao Wang
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi’an, China
| | - Xiao-Fan Liu
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
| | - Shu-Wan Zhao
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xiao Li
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Baojuan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi’an, China
- Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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41
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van den Heuvel MP, Ardesch DJ, Scholtens LH, de Lange SC, van Haren NEM, Sommer IEC, Dannlowski U, Repple J, Preuss TM, Hopkins WD, Rilling JK. Human and chimpanzee shared and divergent neurobiological systems for general and specific cognitive brain functions. Proc Natl Acad Sci U S A 2023; 120:e2218565120. [PMID: 37216540 PMCID: PMC10235977 DOI: 10.1073/pnas.2218565120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 04/03/2023] [Indexed: 05/24/2023] Open
Abstract
A long-standing topic of interest in human neurosciences is the understanding of the neurobiology underlying human cognition. Less commonly considered is to what extent such systems may be shared with other species. We examined individual variation in brain connectivity in the context of cognitive abilities in chimpanzees (n = 45) and humans in search of a conserved link between cognition and brain connectivity across the two species. Cognitive scores were assessed on a variety of behavioral tasks using chimpanzee- and human-specific cognitive test batteries, measuring aspects of cognition related to relational reasoning, processing speed, and problem solving in both species. We show that chimpanzees scoring higher on such cognitive skills display relatively strong connectivity among brain networks also associated with comparable cognitive abilities in the human group. We also identified divergence in brain networks that serve specialized functions across humans and chimpanzees, such as stronger language connectivity in humans and relatively more prominent connectivity between regions related to spatial working memory in chimpanzees. Our findings suggest that core neural systems of cognition may have evolved before the divergence of chimpanzees and humans, along with potential differential investments in other brain networks relating to specific functional specializations between the two species.
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Affiliation(s)
- Martijn P. van den Heuvel
- Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam1081 HV, the Netherlands
- Department of Child Psychiatry, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam1081 HV, the Netherlands
| | - Dirk Jan Ardesch
- Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam1081 HV, the Netherlands
| | - Lianne H. Scholtens
- Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam1081 HV, the Netherlands
| | - Siemon C. de Lange
- Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam1081 HV, the Netherlands
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, An institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam1105 BA, the Netherlands
| | - Neeltje E. M. van Haren
- Department of Psychiatry, Brain Center University Medical Center Utrecht, Utrecht University, Utrecht3584 CX, the Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam3015 CE, the Netherlands
| | - Iris E. C. Sommer
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen9700 RB, the Netherlands
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster48149, Germany
| | - Jonathan Repple
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt60438, Germany
| | - Todd M. Preuss
- Emory National Primate Research Center, Emory University, Atlanta, GA30329
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA30307
| | - William D. Hopkins
- Department of Comparative Medicine, Michael E. Keeling Center for Comparative Medicine and Research, University of Texas MD Anderson Cancer Center, Bastrop, TX77030
| | - James K. Rilling
- Emory National Primate Research Center, Emory University, Atlanta, GA30329
- Center for Translational Social Neuroscience, Emory University, Atlanta, GA30329
- Department of Anthropology, Emory University, Atlanta, GA30322
- Silvio O. Conte Center for Oxytocin and Social Cognition, Emory University, Atlanta, GA30322
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA30322
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42
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Modenini G, Abondio P, Guffanti G, Boattini A, Macciardi F. Evolutionarily recent retrotransposons contribute to schizophrenia. Transl Psychiatry 2023; 13:181. [PMID: 37244930 DOI: 10.1038/s41398-023-02472-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/02/2023] [Accepted: 05/12/2023] [Indexed: 05/29/2023] Open
Abstract
Transposable elements (TEs) are mobile genetic elements that constitute half of the human genome. Recent studies suggest that polymorphic non-reference TEs (nrTEs) may contribute to cognitive diseases, such as schizophrenia, through a cis-regulatory effect. The aim of this work is to identify sets of nrTEs putatively linked to an increased risk of developing schizophrenia. To do so, we inspected the nrTE content of genomes from the dorsolateral prefrontal cortex of schizophrenic and control individuals and identified 38 nrTEs that possibly contribute to the emergence of this psychiatric disorder, two of them further confirmed with haplotype-based methods. We then performed in silico functional inferences and found that 9 of the 38 nrTEs act as expression/alternative splicing quantitative trait loci (eQTLs/sQTLs) in the brain, suggesting a possible role in shaping the human cognitive genome structure. To our knowledge, this is the first attempt at identifying polymorphic nrTEs that can contribute to the functionality of the brain. Finally, we suggest that a neurodevelopmental genetic mechanism, which involves evolutionarily young nrTEs, can be key to understanding the ethio-pathogenesis of this complex disorder.
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Affiliation(s)
| | - Paolo Abondio
- BiGeA Department, University of Bologna, Bologna, Italy
- Department of Cultural Heritage, University of Bologna, Ravenna, Italy
| | - Guia Guffanti
- Department of Psychiatry, McLean Hospital-Harvard Medical School, Belmont, MA, USA
| | | | - Fabio Macciardi
- Department of Medical Education (Neuroscience), CUSM, Colton, CA, USA.
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43
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Allen TA, Hallquist MN, Dombrovski AY. The Dark Side of Mentalizing: Learning Signals in the Default Network During Social Exchanges Support Cooperation and Exploitation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.03.538867. [PMID: 37205574 PMCID: PMC10187177 DOI: 10.1101/2023.05.03.538867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The evolution of human social cognitive capacities such as mentalizing was associated with the expansion of frontoparietal cortical networks, particularly the default network. Mentalizing supports prosocial behaviors, but recent evidence indicates it may also serve a darker side of human social behavior. Using a computational reinforcement learning model of decision-making on a social exchange task, we examined how individuals optimized their approach to social interactions based on a counterpart's behavior and prior reputation. We found that learning signals encoded in the default network scaled with reciprocal cooperation and were stronger in individuals who were more exploitative and manipulative, but weaker in those who were more callous and less empathic. These learning signals, which help to update predictions about others' behavior, accounted for associations between exploitativeness, callousness, and social reciprocity. Separately, we found that callousness, but not exploitativeness, was associated with a behavioral insensitivity to prior reputation effects. While the entire default network was involved in reciprocal cooperation, sensitivity to reputation was selectively related to the activity of the medial temporal subsystem. Overall, our findings suggest that the emergence of social cognitive capacities associated with the expansion of the default network likely enabled humans to not only cooperate effectively with others, but to exploit and manipulate others as well.
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Affiliation(s)
- Timothy A Allen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213
| | - Michael N Hallquist
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599
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44
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Tissink E, Werme J, de Lange SC, Savage JE, Wei Y, de Leeuw CA, Nagel M, Posthuma D, van den Heuvel MP. The Genetic Architectures of Functional and Structural Connectivity Properties within Cerebral Resting-State Networks. eNeuro 2023; 10:ENEURO.0242-22.2023. [PMID: 36882310 PMCID: PMC10089056 DOI: 10.1523/eneuro.0242-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 12/12/2022] [Accepted: 01/08/2023] [Indexed: 03/09/2023] Open
Abstract
Functional connectivity within resting-state networks (RSN-FC) is vital for cognitive functioning. RSN-FC is heritable and partially translates to the anatomic architecture of white matter, but the genetic component of structural connections of RSNs (RSN-SC) and their potential genetic overlap with RSN-FC remain unknown. Here, we perform genome-wide association studies (N discovery = 24,336; N replication = 3412) and annotation on RSN-SC and RSN-FC. We identify genes for visual network-SC that are involved in axon guidance and synaptic functioning. Genetic variation in RSN-FC impacts biological processes relevant to brain disorders that previously were only phenotypically associated with RSN-FC alterations. Correlations of the genetic components of RSNs are mostly observed within the functional domain, whereas less overlap is observed within the structural domain and between the functional and structural domains. This study advances the understanding of the complex functional organization of the brain and its structural underpinnings from a genetics viewpoint.
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Affiliation(s)
- Elleke Tissink
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Josefin Werme
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Siemon C de Lange
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam 1105 BA, The Netherlands
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Yongbin Wei
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Christiaan A de Leeuw
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Mats Nagel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
- Department of Clinical Genetics, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam University Medical Centre, Amsterdam 1081 HZ, The Netherlands
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam 1081 HV, The Netherlands
- Department of Clinical Genetics, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam University Medical Centre, Amsterdam 1081 HZ, The Netherlands
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45
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Vanderhaeghen P, Polleux F. Developmental mechanisms underlying the evolution of human cortical circuits. Nat Rev Neurosci 2023; 24:213-232. [PMID: 36792753 PMCID: PMC10064077 DOI: 10.1038/s41583-023-00675-z] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2023] [Indexed: 02/17/2023]
Abstract
The brain of modern humans has evolved remarkable computational abilities that enable higher cognitive functions. These capacities are tightly linked to an increase in the size and connectivity of the cerebral cortex, which is thought to have resulted from evolutionary changes in the mechanisms of cortical development. Convergent progress in evolutionary genomics, developmental biology and neuroscience has recently enabled the identification of genomic changes that act as human-specific modifiers of cortical development. These modifiers influence most aspects of corticogenesis, from the timing and complexity of cortical neurogenesis to synaptogenesis and the assembly of cortical circuits. Mutations of human-specific genetic modifiers of corticogenesis have started to be linked to neurodevelopmental disorders, providing evidence for their physiological relevance and suggesting potential relationships between the evolution of the human brain and its sensitivity to specific diseases.
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Affiliation(s)
- Pierre Vanderhaeghen
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium.
- Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.
| | - Franck Polleux
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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46
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Zhang X, Fang B, Huang YF. Transcription factor binding sites are frequently under accelerated evolution in primates. Nat Commun 2023; 14:783. [PMID: 36774380 PMCID: PMC9922303 DOI: 10.1038/s41467-023-36421-3] [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: 04/30/2022] [Accepted: 01/31/2023] [Indexed: 02/13/2023] Open
Abstract
Recent comparative genomic studies have identified many human accelerated elements (HARs) with elevated substitution rates in the human lineage. However, it remains unknown to what extent transcription factor binding sites (TFBSs) are under accelerated evolution in humans and other primates. Here, we introduce two pooling-based phylogenetic methods with dramatically enhanced sensitivity to examine accelerated evolution in TFBSs. Using these new methods, we show that more than 6000 TFBSs annotated in the human genome have experienced accelerated evolution in Hominini, apes, and Old World monkeys. Although these TFBSs individually show relatively weak signals of accelerated evolution, they collectively are more abundant than HARs. Also, we show that accelerated evolution in Pol III binding sites may be driven by lineage-specific positive selection, whereas accelerated evolution in other TFBSs might be driven by nonadaptive evolutionary forces. Finally, the accelerated TFBSs are enriched around developmental genes, suggesting that accelerated evolution in TFBSs may drive the divergence of developmental processes between primates.
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Affiliation(s)
- Xinru Zhang
- Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA. .,Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA. .,Bioinformatics and Genomics Graduate Program, Pennsylvania State University, University Park, PA, 16802, USA.
| | - Bohao Fang
- Department of Organismic and Evolutionary Biology and the Museum of Comparative Zoology, Harvard University, Boston, MA, 02135, USA
| | - Yi-Fei Huang
- Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA. .,Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA.
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47
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A Systematic Review of the Human Accelerated Regions in Schizophrenia and Related Disorders: Where the Evolutionary and Neurodevelopmental Hypotheses Converge. Int J Mol Sci 2023; 24:ijms24043597. [PMID: 36835010 PMCID: PMC9962562 DOI: 10.3390/ijms24043597] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/03/2023] [Accepted: 02/07/2023] [Indexed: 02/15/2023] Open
Abstract
Schizophrenia is a psychiatric disorder that results from genetic and environmental factors interacting and disrupting neurodevelopmental trajectories. Human Accelerated Regions (HARs) are evolutionarily conserved genomic regions that have accumulated human-specific sequence changes. Thus, studies on the impact of HARs in the context of neurodevelopment, as well as with respect to adult brain phenotypes, have increased considerably in the last few years. Through a systematic approach, we aim to offer a comprehensive review of HARs' role in terms of human brain development, configuration, and cognitive abilities, as well as whether HARs modulate the susceptibility to neurodevelopmental psychiatric disorders such as schizophrenia. First, the evidence in this review highlights HARs' molecular functions in the context of the neurodevelopmental regulatory genetic machinery. Second, brain phenotypic analyses indicate that HAR genes' expression spatially correlates with the regions that suffered human-specific cortical expansion, as well as with the regional interactions for synergistic information processing. Lastly, studies based on candidate HAR genes and the global "HARome" variability describe the involvement of these regions in the genetic background of schizophrenia, but also in other neurodevelopmental psychiatric disorders. Overall, the data considered in this review emphasise the crucial role of HARs in human-specific neurodevelopment processes and encourage future research on this evolutionary marker for a better understanding of the genetic basis of schizophrenia and other neurodevelopmental-related psychiatric disorders. Accordingly, HARs emerge as interesting genomic regions that require further study in order to bridge the neurodevelopmental and evolutionary hypotheses in schizophrenia and other related disorders and phenotypes.
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48
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Wei Y, Zhang H, Liu Y. Charting Normative Brain Variability Across the Human Lifespan. Neurosci Bull 2023; 39:362-364. [PMID: 36129601 PMCID: PMC9905390 DOI: 10.1007/s12264-022-00952-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 07/27/2022] [Indexed: 10/14/2022] Open
Affiliation(s)
- Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
| | - Han Zhang
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
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49
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Levchenko A, Gusev F, Rogaev E. The evolutionary origin of psychosis. Front Psychiatry 2023; 14:1115929. [PMID: 36741116 PMCID: PMC9894884 DOI: 10.3389/fpsyt.2023.1115929] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 01/05/2023] [Indexed: 01/21/2023] Open
Abstract
Imagination, the driving force of creativity, and primary psychosis are human-specific, since we do not observe behaviors in other species that would convincingly suggest they possess the same traits. Both these traits have been linked to the function of the prefrontal cortex, which is the most evolutionarily novel region of the human brain. A number of evolutionarily novel genetic and epigenetic changes that determine the human brain-specific structure and function have been discovered in recent years. Among them are genomic loci subjected to increased rates of single nucleotide substitutions in humans, called human accelerated regions. These mostly regulatory regions are involved in brain development and sometimes contain genetic variants that confer a risk for schizophrenia. On the other hand, neuroimaging data suggest that mind wandering and related phenomena (as a proxy of imagination) are in many ways similar to rapid eye movement dreaming, a function also present in non-human species. Furthermore, both functions are similar to psychosis in several ways: for example, the same brain areas are activated both in dreams and visual hallucinations. In the present Perspective we hypothesize that imagination is an evolutionary adaptation of dreaming, while primary psychosis results from deficient control by higher-order brain areas over imagination. In the light of this, human accelerated regions might be one of the key drivers in evolution of human imagination and the pathogenesis of psychotic disorders.
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Affiliation(s)
- Anastasia Levchenko
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Fedor Gusev
- Center for Genetics and Life Sciences, Department of Genetics, Sirius University of Science and Technology, Sochi, Russia.,Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Evgeny Rogaev
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.,Department of Psychiatry, UMass Chan Medical School, Shrewsbury, MA, United States
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50
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Lemaitre H, Le Guen Y, Tilot AK, Stein JL, Philippe C, Mangin JF, Fisher SE, Frouin V. Genetic variations within human gained enhancer elements affect human brain sulcal morphology. Neuroimage 2023; 265:119773. [PMID: 36442731 DOI: 10.1016/j.neuroimage.2022.119773] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 10/07/2022] [Accepted: 11/24/2022] [Indexed: 11/26/2022] Open
Abstract
The expansion of the cerebral cortex is one of the most distinctive changes in the evolution of the human brain. Cortical expansion and related increases in cortical folding may have contributed to emergence of our capacities for high-order cognitive abilities. Molecular analysis of humans, archaic hominins, and non-human primates has allowed identification of chromosomal regions showing evolutionary changes at different points of our phylogenetic history. In this study, we assessed the contributions of genomic annotations spanning 30 million years to human sulcal morphology measured via MRI in more than 18,000 participants from the UK Biobank. We found that variation within brain-expressed human gained enhancers, regulatory genetic elements that emerged since our last common ancestor with Old World monkeys, explained more trait heritability than expected for the left and right calloso-marginal posterior fissures and the right central sulcus. Intriguingly, these are sulci that have been previously linked to the evolution of locomotion in primates and later on bipedalism in our hominin ancestors.
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Affiliation(s)
- Herve Lemaitre
- Institut des Maladies Neurodégénératives, CNRS UMR 5293, Université de bordeaux, Centre Broca Nouvelle-Aquitaine, Bordeaux, France.
| | - Yann Le Guen
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab UMR 9027, Gif-sur-Yvette, France
| | - Amanda K Tilot
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
| | - Jason L Stein
- Department of Genetics and the UNC Neuroscience Center, UNC-Chapel Hill, Chapel Hill, NC, United States of America
| | - Cathy Philippe
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab UMR 9027, Gif-sur-Yvette, France
| | - Jean-François Mangin
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab UMR 9027, Gif-sur-Yvette, France
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Vincent Frouin
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab UMR 9027, Gif-sur-Yvette, France
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