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Joo SW, Jo YT, Choi W, Kim SM, Yoo SY, Joe S, Lee J. Topological abnormalities of the morphometric similarity network of the cerebral cortex in schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:57. [PMID: 38886369 PMCID: PMC11183129 DOI: 10.1038/s41537-024-00477-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 05/30/2024] [Indexed: 06/20/2024]
Abstract
A morphometric similarity (MS) network can be constructed using multiple magnetic resonance imaging parameters of each cortical region. An MS network can be used to assess the similarity between cortical regions. Although MS networks can detect microstructural alterations and capture connections between histologically similar cortical areas, the influence of schizophrenia on the topological characteristics of MS networks remains unclear. We obtained T1- and diffusion-weighted images of 239 healthy controls and 190 individuals with schizophrenia to construct the MS network. Group comparisons of the mean MS of the cortical regions and subnetworks were performed. The strengths of the connections between the cortical regions and the global and nodal network indices were compared between the groups. Clinical associations with the network indices were tested using Spearman's rho. Compared with healthy controls, individuals with schizophrenia had significant group differences in the mean MS of several cortical regions and subnetworks. Individuals with schizophrenia had both superior and inferior strengths of connections between cortical regions compared with those of healthy controls. We observed regional abnormalities of the MS network in individuals with schizophrenia regarding lower centrality values of the pars opercularis, superior frontal, and superior temporal areas. Specific nodal network measures of the right pars opercularis and left superior temporal areas were associated with illness duration in individuals with schizophrenia. We identified regional abnormalities of the MS network in schizophrenia with the left superior temporal area possibly being a key region in topological organization and cortical connections.
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Affiliation(s)
- Sung Woo Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Tak Jo
- Department of Psychiatry, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea
| | - Woohyeok Choi
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sun Min Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - So Young Yoo
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Soohyun Joe
- Brain Laboratory, Department of Psychiatry, University of California San Diego, School of Medicine, San Diego, California, USA
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
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2
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Diesburg DA, Wessel JR, Jones SR. Biophysical Modeling of Frontocentral ERP Generation Links Circuit-Level Mechanisms of Action-Stopping to a Behavioral Race Model. J Neurosci 2024; 44:e2016232024. [PMID: 38561227 PMCID: PMC11097283 DOI: 10.1523/jneurosci.2016-23.2024] [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: 10/25/2023] [Revised: 02/09/2024] [Accepted: 03/08/2024] [Indexed: 04/04/2024] Open
Abstract
Human frontocentral event-related potentials (FC-ERPs) are ubiquitous neural correlates of cognition and control, but their generating multiscale mechanisms remain mostly unknown. We used the Human Neocortical Neurosolver's biophysical model of a canonical neocortical circuit under exogenous thalamic and cortical drive to simulate the cell and circuit mechanisms underpinning the P2, N2, and P3 features of the FC-ERP observed after Stop-Signals in the Stop-Signal task (SST; N = 234 humans, 137 female). We demonstrate that a sequence of simulated external thalamocortical and corticocortical drives can produce the FC-ERP, similar to what has been shown for primary sensory cortices. We used this model of the FC-ERP to examine likely circuit-mechanisms underlying FC-ERP features that distinguish between successful and failed action-stopping. We also tested their adherence to the predictions of the horse-race model of the SST, with specific hypotheses motivated by theoretical links between the P3 and Stop process. These simulations revealed that a difference in P3 onset between successful and failed Stops is most likely due to a later arrival of thalamocortical drive in failed Stops, rather than, for example, a difference in the effective strength of the input. In contrast, the same model predicted that early thalamocortical drives underpinning the P2 and N2 differed in both strength and timing across stopping accuracy conditions. Overall, this model generates novel testable predictions of the thalamocortical dynamics underlying FC-ERP generation during action-stopping. Moreover, it provides a detailed cellular and circuit-level interpretation that supports links between these macroscale signatures and predictions of the behavioral race model.
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Affiliation(s)
- Darcy A Diesburg
- Department of Neuroscience, Brown University, Providence, Rhode Island 02912
| | - Jan R Wessel
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa 52242
- Department of Neurology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa 52242
| | - Stephanie R Jones
- Department of Neuroscience, Brown University, Providence, Rhode Island 02912
- Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, Providence, Rhode Island 02908
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3
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Barbas H, Garcia-Cabezas MA, John Y, Bautista J, McKee A, Zikopoulos B. Cortical circuit principles predict patterns of trauma induced tauopathy in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.02.592271. [PMID: 38746103 PMCID: PMC11092596 DOI: 10.1101/2024.05.02.592271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Connections in the cortex of diverse mammalian species are predicted reliably by the Structural Model for direction of pathways and signal processing (reviewed in 1,2). The model is rooted in the universal principle of cortical systematic variation in laminar structure and has been supported widely for connection patterns in animals but has not yet been tested for humans. Here, in postmortem brains of individuals neuropathologically diagnosed with chronic traumatic encephalopathy (CTE) we studied whether the hyperphosphorylated tau (p-tau) pathology parallels connection sequence in time by circuit mechanisms. CTE is a progressive p-tau pathology that begins focally in perivascular sites in sulcal depths of the neocortex (stages I-II) and later involves the medial temporal lobe (MTL) in stages III-IV. We provide novel quantitative evidence that the p-tau pathology in MTL A28 and nearby sites in CTE stage III closely follows the graded laminar patterns seen in homologous cortico-cortical connections in non-human primates. The Structural Model successfully predicted the laminar distribution of the p-tau neurofibrillary tangles and neurites and their density, based on the relative laminar (dis)similarity between the cortical origin (seed) and each connection site. The findings were validated for generalizability by a computational progression model. By contrast, the early focal perivascular pathology in the sulcal depths followed local columnar connectivity rules. These findings support the general applicability of a theoretical model to unravel the direction and progression of p-tau pathology in human neurodegeneration via a cortico-cortical mechanism. Cortical pathways converging on medial MTL help explain the progressive spread of p-tau pathology from focal cortical sites in early CTE to widespread lateral MTL areas and beyond in later disease stages.
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Affiliation(s)
- Helen Barbas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA 022152
- Graduate Program in Neuroscience, Boston Univ. and School of Medicine
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA
- Center for Systems Neuroscience, Boston University, Boston, MA
| | - Miguel Angel Garcia-Cabezas
- Departamento de Anatomía, Histología y Neurociencia, Facultad de Medicina, Universidad Autónoma de Madrid, Madrid, Spain
| | - Yohan John
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA 022152
| | - Julied Bautista
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA 022152
| | - Ann McKee
- Veterans Affairs (VA) Boston Healthcare System, US Department of Veteran Affairs, Boston, Massachusetts
- Alzheimer’s Disease Research Center and Chronic Traumatic Encephalopathy Center, Chobanian and Avedisian School of Medicine, Boston University, Boston, Massachusetts
| | - Basilis Zikopoulos
- Graduate Program in Neuroscience, Boston Univ. and School of Medicine
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA
- Center for Systems Neuroscience, Boston University, Boston, MA
- Human Systems Neuroscience Laboratory, Department of Health Sciences, Boston University
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4
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Magrou L, Joyce MKP, Froudist-Walsh S, Datta D, Wang XJ, Martinez-Trujillo J, Arnsten AFT. The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition. Cereb Cortex 2024; 34:bhae174. [PMID: 38771244 PMCID: PMC11107384 DOI: 10.1093/cercor/bhae174] [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: 01/31/2024] [Revised: 03/29/2024] [Accepted: 04/08/2024] [Indexed: 05/22/2024] Open
Abstract
The recent publications of the inter-areal connectomes for mouse, marmoset, and macaque cortex have allowed deeper comparisons across rodent vs. primate cortical organization. In general, these show that the mouse has very widespread, "all-to-all" inter-areal connectivity (i.e. a "highly dense" connectome in a graph theoretical framework), while primates have a more modular organization. In this review, we highlight the relevance of these differences to function, including the example of primary visual cortex (V1) which, in the mouse, is interconnected with all other areas, therefore including other primary sensory and frontal areas. We argue that this dense inter-areal connectivity benefits multimodal associations, at the cost of reduced functional segregation. Conversely, primates have expanded cortices with a modular connectivity structure, where V1 is almost exclusively interconnected with other visual cortices, themselves organized in relatively segregated streams, and hierarchically higher cortical areas such as prefrontal cortex provide top-down regulation for specifying precise information for working memory storage and manipulation. Increased complexity in cytoarchitecture, connectivity, dendritic spine density, and receptor expression additionally reveal a sharper hierarchical organization in primate cortex. Together, we argue that these primate specializations permit separable deconstruction and selective reconstruction of representations, which is essential to higher cognition.
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Affiliation(s)
- Loïc Magrou
- Department of Neural Science, New York University, New York, NY 10003, United States
| | - Mary Kate P Joyce
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Sean Froudist-Walsh
- School of Engineering Mathematics and Technology, University of Bristol, Bristol, BS8 1QU, United Kingdom
| | - Dibyadeep Datta
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Xiao-Jing Wang
- Department of Neural Science, New York University, New York, NY 10003, United States
| | - Julio Martinez-Trujillo
- Departments of Physiology and Pharmacology, and Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 3K7, Canada
| | - Amy F T Arnsten
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
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Benavides-Piccione R, Blazquez-Llorca L, Kastanauskaite A, Fernaud-Espinosa I, Tapia-González S, DeFelipe J. Key morphological features of human pyramidal neurons. Cereb Cortex 2024; 34:bhae180. [PMID: 38745556 PMCID: PMC11094408 DOI: 10.1093/cercor/bhae180] [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: 01/03/2024] [Revised: 04/01/2024] [Accepted: 04/18/2024] [Indexed: 05/16/2024] Open
Abstract
The basic building block of the cerebral cortex, the pyramidal cell, has been shown to be characterized by a markedly different dendritic structure among layers, cortical areas, and species. Functionally, differences in the structure of their dendrites and axons are critical in determining how neurons integrate information. However, within the human cortex, these neurons have not been quantified in detail. In the present work, we performed intracellular injections of Lucifer Yellow and 3D reconstructed over 200 pyramidal neurons, including apical and basal dendritic and local axonal arbors and dendritic spines, from human occipital primary visual area and associative temporal cortex. We found that human pyramidal neurons from temporal cortex were larger, displayed more complex apical and basal structural organization, and had more spines compared to those in primary sensory cortex. Moreover, these human neocortical neurons displayed specific shared and distinct characteristics in comparison to previously published human hippocampal pyramidal neurons. Additionally, we identified distinct morphological features in human neurons that set them apart from mouse neurons. Lastly, we observed certain consistent organizational patterns shared across species. This study emphasizes the existing diversity within pyramidal cell structures across different cortical areas and species, suggesting substantial species-specific variations in their computational properties.
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Affiliation(s)
- Ruth Benavides-Piccione
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
| | - Lidia Blazquez-Llorca
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
- Departamento de Tecnología Fotónica y Bioingeniería, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040, Spain
| | - Asta Kastanauskaite
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
| | - Isabel Fernaud-Espinosa
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
| | - Silvia Tapia-González
- Laboratorio de Neurofisiología Celular, Facultad de Medicina, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
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6
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Billot A, Kiran S. Disentangling neuroplasticity mechanisms in post-stroke language recovery. BRAIN AND LANGUAGE 2024; 251:105381. [PMID: 38401381 PMCID: PMC10981555 DOI: 10.1016/j.bandl.2024.105381] [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: 07/20/2023] [Revised: 11/28/2023] [Accepted: 01/12/2024] [Indexed: 02/26/2024]
Abstract
A major objective in post-stroke aphasia research is to gain a deeper understanding of neuroplastic mechanisms that drive language recovery, with the ultimate goal of enhancing treatment outcomes. Subsequent to recent advances in neuroimaging techniques, we now have the ability to examine more closely how neural activity patterns change after a stroke. However, the way these neural activity changes relate to language impairments and language recovery is still debated. The aim of this review is to provide a theoretical framework to better investigate and interpret neuroplasticity mechanisms underlying language recovery in post-stroke aphasia. We detail two sets of neuroplasticity mechanisms observed at the synaptic level that may explain functional neuroimaging findings in post-stroke aphasia recovery at the network level: feedback-based homeostatic plasticity and associative Hebbian plasticity. In conjunction with these plasticity mechanisms, higher-order cognitive control processes dynamically modulate neural activity in other regions to meet communication demands, despite reduced neural resources. This work provides a network-level neurobiological framework for understanding neural changes observed in post-stroke aphasia and can be used to define guidelines for personalized treatment development.
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Affiliation(s)
- Anne Billot
- Center for Brain Recovery, Boston University, Boston, USA; Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Swathi Kiran
- Center for Brain Recovery, Boston University, Boston, USA.
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7
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Wright J, Bourke P. Markov Blankets and Mirror Symmetries-Free Energy Minimization and Mesocortical Anatomy. ENTROPY (BASEL, SWITZERLAND) 2024; 26:287. [PMID: 38667842 PMCID: PMC11049374 DOI: 10.3390/e26040287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 03/21/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024]
Abstract
A theoretical account of development in mesocortical anatomy is derived from the free energy principle, operating in a neural field with both Hebbian and anti-Hebbian neural plasticity. An elementary structural unit is proposed, in which synaptic connections at mesoscale are arranged in paired patterns with mirror symmetry. Exchanges of synaptic flux in each pattern form coupled spatial eigenmodes, and the line of mirror reflection between the paired patterns operates as a Markov blanket, so that prediction errors in exchanges between the pairs are minimized. The theoretical analysis is then compared to the outcomes from a biological model of neocortical development, in which neuron precursors are selected by apoptosis for cell body and synaptic connections maximizing synchrony and also minimizing axonal length. It is shown that this model results in patterns of connection with the anticipated mirror symmetries, at micro-, meso- and inter-arial scales, among lateral connections, and in cortical depth. This explains the spatial organization and functional significance of neuron response preferences, and is compatible with the structural form of both columnar and noncolumnar cortex. Multi-way interactions of mirrored representations can provide a preliminary anatomically realistic model of cortical information processing.
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Affiliation(s)
- James Wright
- Centre for Brain Research, and Department of Psychological Medicine, School of Medicine, University of Auckland, Auckland 1010, New Zealand
| | - Paul Bourke
- School of Social Sciences, Faculty of Arts, Business, Law and Education, University of Western Australia, Perth, WA 6009, Australia
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8
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Teckentrup V, Kroemer NB. Mechanisms for survival: vagal control of goal-directed behavior. Trends Cogn Sci 2024; 28:237-251. [PMID: 38036309 DOI: 10.1016/j.tics.2023.11.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/01/2023] [Accepted: 11/02/2023] [Indexed: 12/02/2023]
Abstract
Survival is a fundamental physiological drive, and neural circuits have evolved to prioritize actions that meet the energy demands of the body. This fine-tuning of goal-directed actions based on metabolic states ('allostasis') is deeply rooted in our brain, and hindbrain nuclei orchestrate the vital communication between the brain and body through the vagus nerve. Despite mounting evidence for vagal control of allostatic behavior in animals, its broader function in humans is still contested. Based on stimulation studies, we propose that the vagal afferent pathway supports transitions between survival modes by gating the integration of ascending bodily signals, thereby regulating reward-seeking. By reconceptualizing vagal signals as catalysts for goal-directed behavior, our perspective opens new avenues for theory-driven translational work in mental disorders.
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Affiliation(s)
- Vanessa Teckentrup
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, 72076 Tübingen, Germany; School of Psychology and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
| | - Nils B Kroemer
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, 72076 Tübingen, Germany; Section of Medical Psychology, Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Bonn, 53127 Bonn, Germany; German Center for Mental Health (DZPG), 72076 Tübingen, Germany.
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9
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Fang M, Huang H, Yang J, Zhang S, Wu Y, Huang CC. Changes in microstructural similarity of hippocampal subfield circuits in pathological cognitive aging. Brain Struct Funct 2024; 229:311-321. [PMID: 38147082 DOI: 10.1007/s00429-023-02721-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 10/02/2023] [Indexed: 12/27/2023]
Abstract
The hippocampal networks support multiple cognitive functions and may have biological roles and functions in pathological cognitive aging (PCA) and its associated diseases, which have not been explored. In the current study, a total of 116 older adults with 39 normal controls (NC) (mean age: 52.3 ± 13.64 years; 16 females), 39 mild cognitive impairment (MCI) (mean age: 68.15 ± 9.28 years, 14 females), and 38 dementia (mean age: 73.82 ± 8.06 years, 8 females) were included. The within-hippocampal subfields and the cortico-hippocampal circuits were assessed via a micro-structural similarity network approach using T1w/T2w ratio and regional gray matter tissue probability maps, respectively. An analysis of covariance was conducted to identify between-group differences in structural similarities among hippocampal subfields. The partial correlation analyses were performed to associate changes in micro-structural similarities with cognitive performance in the three groups, controlling the effect of age, sex, education, and cerebral small-vessel disease. Compared with the NC, an altered T1w/T2w ratio similarity between left CA3 and left subiculum was observed in the mild cognitive impairment (MCI) and dementia. The left CA3 was the most impaired region correlated with deteriorated cognitive performance. Using these regions as seeds for GM similarity comparisons between hippocampal subfields and cortical regions, group differences were observed primarily between the left subiculum and several cortical regions. By utilizing T1w/T2w ratio as a proxy measure for myelin content, our data suggest that the imbalanced synaptic weights within hippocampal CA3 provide a substrate to explain the abnormal firing characteristics of hippocampal neurons in PCA. Furthermore, our work depicts specific brain structural characteristics of normal and pathological cognitive aging and suggests a potential mechanism for cognitive aging heterogeneity.
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Affiliation(s)
- Min Fang
- Department of Neurology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Huanghuang Huang
- Department of Neurology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jie Yang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Shuying Zhang
- School of Medicine, Tongji University, Shanghai, China
| | - Yujie Wu
- Changning Mental Health Center, Shanghai, China
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China.
- Changning Mental Health Center, Shanghai, China.
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10
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Garcia-Marin V, Kelly JG, Hawken MJ. Neuronal composition of processing modules in human V1: laminar density for neuronal and non-neuronal populations and a comparison with macaque. Cereb Cortex 2024; 34:bhad512. [PMID: 38183210 PMCID: PMC10839852 DOI: 10.1093/cercor/bhad512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 12/07/2023] [Accepted: 12/08/2023] [Indexed: 01/07/2024] Open
Abstract
The neuronal composition of homologous brain regions in different primates is important for understanding their processing capacities. Primary visual cortex (V1) has been widely studied in different members of the catarrhines. Neuronal density is considered to be central in defining the structure-function relationship. In human, there are large variations in the reported neuronal density from prior studies. We found the neuronal density in human V1 was 79,000 neurons/mm3, which is 35% of the neuronal density previously determined in macaque V1. Laminar density was proportionally similar between human and macaque. In V1, the ocular dominance column (ODC) contains the circuits for the emergence of orientation preference and spatial processing of a point image in many mammalian species. Analysis of the total neurons in an ODC and of the full number of neurons in macular vision (the central 15°) indicates that humans have 1.3× more neurons than macaques even though the density of neurons in macaque is 3× the density in human V1. We propose that the number of neurons in a functional processing unit rather than the number of neurons under a mm2 of cortex is more appropriate for cortical comparisons across species.
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Affiliation(s)
| | - Jenna G Kelly
- Center for Neural Science, New York University, New York City, NY 10003, United States
| | - Michael J Hawken
- Center for Neural Science, New York University, New York City, NY 10003, United States
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11
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Rolls ET, Deco G, Huang CC, Feng J. The connectivity of the human frontal pole cortex, and a theory of its involvement in exploit versus explore. Cereb Cortex 2024; 34:bhad416. [PMID: 37991264 DOI: 10.1093/cercor/bhad416] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 11/23/2023] Open
Abstract
The frontal pole is implicated in humans in whether to exploit resources versus explore alternatives. Effective connectivity, functional connectivity, and tractography were measured between six human frontal pole regions and for comparison 13 dorsolateral and dorsal prefrontal cortex regions, and the 360 cortical regions in the Human Connectome Project Multi-modal-parcellation atlas in 171 HCP participants. The frontal pole regions have effective connectivity with Dorsolateral Prefrontal Cortex regions, the Dorsal Prefrontal Cortex, both implicated in working memory; and with the orbitofrontal and anterior cingulate cortex reward/non-reward system. There is also connectivity with temporal lobe, inferior parietal, and posterior cingulate regions. Given this new connectivity evidence, and evidence from activations and damage, it is proposed that the frontal pole cortex contains autoassociation attractor networks that are normally stable in a short-term memory state, and maintain stability in the other prefrontal networks during stable exploitation of goals and strategies. However, if an input from the orbitofrontal or anterior cingulate cortex that expected reward, non-reward, or punishment is received, this destabilizes the frontal pole and thereby other prefrontal networks to enable exploration of competing alternative goals and strategies. The frontal pole connectivity with reward systems may be key in exploit versus explore.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, United Kingdom
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Brain and Cognition, Pompeu Fabra University, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200602, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 200602, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
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12
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Kotlarz P, Lankinen K, Hakonen M, Turpin T, Polimeni JR, Ahveninen J. Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.23.573208. [PMID: 38187540 PMCID: PMC10769454 DOI: 10.1101/2023.12.23.573208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. A neuroscience example is the hierarchy of connections between different cortical depths or "lamina". This hierarchy is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We then compared networks where the inter-regional connections were limited to a single cortical depth only ("layer-by-layer matrices") to those considering all possible connections between regions and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes such as network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial aspects of the cortex dominated information transfer and deeper aspects clustering. These differences were largest in frontotemporal and limbic brain regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information. Multilayer connectomics could provide a methodological framework for studies on how information flows across this hierarchy.
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Affiliation(s)
- Parker Kotlarz
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Kaisu Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Maria Hakonen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | | | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
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Kenwood MM, Souaiaia T, Kovner R, Fox AS, French DA, Oler JA, Roseboom PH, Riedel MK, Mueller SAL, Kalin NH. Gene expression in the primate orbitofrontal cortex related to anxious temperament. Proc Natl Acad Sci U S A 2023; 120:e2305775120. [PMID: 38011550 DOI: 10.1073/pnas.2305775120] [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: 05/26/2023] [Accepted: 10/13/2023] [Indexed: 11/29/2023] Open
Abstract
Anxiety disorders are among the most prevalent psychiatric disorders, causing significant suffering and disability. Relative to other psychiatric disorders, anxiety disorders tend to emerge early in life, supporting the importance of developmental mechanisms in their emergence and maintenance. Behavioral inhibition (BI) is a temperament that emerges early in life and, when stable and extreme, is linked to an increased risk for the later development of anxiety disorders and other stress-related psychopathology. Understanding the neural systems and molecular mechanisms underlying this dispositional risk could provide insight into treatment targets for anxiety disorders. Nonhuman primates (NHPs) have an anxiety-related temperament, called anxious temperament (AT), that is remarkably similar to BI in humans, facilitating the design of highly translational models for studying the early risk for stress-related psychopathology. Because of the recent evolutionary divergence between humans and NHPs, many of the anxiety-related brain regions that contribute to psychopathology are highly similar in terms of their structure and function, particularly with respect to the prefrontal cortex. The orbitofrontal cortex plays a critical role in the flexible encoding and regulation of threat responses, in part through connections with subcortical structures like the amygdala. Here, we explore individual differences in the transcriptional profile of cells within the region, using laser capture microdissection and single nuclear sequencing, providing insight into the molecules underlying individual differences in AT-related function of the pOFC, with a particular focus on previously implicated cellular systems, including neurotrophins and glucocorticoid signaling.
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Affiliation(s)
- Margaux M Kenwood
- Neuroscience Training Program, University of Wisconsin, Madison, WI 53705
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | - Tade Souaiaia
- Department of Cell Biology, State University of New York Downstate, New York, NY 11228
| | - Rothem Kovner
- Yale School of Medicine, Yale University, New Haven, CT 06510
| | - Andrew S Fox
- Department of Psychology and California National Primate Research Center, University of California, Davis, CA 95616
| | - Delores A French
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | - Jonathan A Oler
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | | | - Marissa K Riedel
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
| | | | - Ned H Kalin
- Neuroscience Training Program, University of Wisconsin, Madison, WI 53705
- Department of Psychiatry, University of Wisconsin, Madison, WI 53719
- Wisconsin National Primate Research Center, University of Wisconsin, Madison, WI 53715
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14
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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: 7] [Impact Index Per Article: 7.0] [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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15
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Bautista J, García-Cabezas MÁ, Medalla M, Rosene DL, Zikopoulos B, Barbas H. Pattern of ventral temporal lobe interconnections in rhesus macaques. J Comp Neurol 2023; 531:1963-1986. [PMID: 37919833 PMCID: PMC11142421 DOI: 10.1002/cne.25550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 07/26/2023] [Accepted: 10/13/2023] [Indexed: 11/04/2023]
Abstract
The entorhinal cortex (EC, A28) is linked through reciprocal pathways with nearby perirhinal and visual, auditory, and multimodal association cortices in the temporal lobe, in pathways associated with the flow of information for memory processing. The density and laminar organization of these pathways is not well understood in primates. We studied interconnections within the ventral temporal lobe in young adult rhesus monkeys of both sexes with the aid of neural tracers injected in temporal areas (Ts1, Ts2, TE1, area 36, temporal polar area TPro, and area 28) to determine the density and laminar distribution of projection neurons within the temporal lobe. These temporal areas can be categorized into three different cortical types based on their laminar architecture: the sensory association areas Ts1, Ts2, and TE1 have six layers (eulaminate); the perirhinal limbic areas TPro and area 36 have an incipient layer IV (dysgranular); and area 28 lacks layer IV (agranular). We found that (1) temporal areas that are similar in laminar architecture by cortical type are strongly interconnected, and (2) the laminar pattern of connections is dependent on the difference in cortical laminar structure between linked areas. Thus, agranular A28 is more strongly connected with other agranular/dysgranular areas than with eulaminate cortices. Further, A28 predominantly projected via feedback-like pathways that originated in the deep layers, and received feedforward-like projections from areas of greater laminar differentiation, which emanated from the upper layers. Our results are consistent with the Structural Model, which relates the density and laminar distribution of connections to the relationship of the laminar structure between the linked areas. These connections were viewed in the context of the inhibitory microenvironment of A28, which is the key recipient of pathways from the cortex and of the output of hippocampus. Our findings revealed a higher population of calretinin (CR)-expressing neurons in EC, with a significantly higher density in its lateral division. Medial EC had a higher density of CR neurons in the deep layers, particularly in layer Va. In contrast, parvalbumin (PV) neurons were more densely distributed in the deep layers of the lateral subdivisions of rostral EC, especially in layer Va, whereas the densities of calbindin (CB) neurons in the medial and lateral EC were comparable in all layers, except for layer IIIa, in which medial EC had a higher CB population than the lateral. The pattern of connections in the inhibitory microenvironment of EC, which sends and receives input from the hippocampus, may shed light on signal propagation in this network associated with diverse aspects of memory, and disruptions in neurologic and psychiatric diseases that affect this region.
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Affiliation(s)
- Julied Bautista
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, USA
| | - Miguel Á. García-Cabezas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, USA
| | - Maria Medalla
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts, USA
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts, USA
| | - Douglas L. Rosene
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts, USA
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts, USA
| | - Basilis Zikopoulos
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts, USA
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts, USA
- Human Systems Neuroscience Laboratory, Boston University, Boston, Massachusetts, USA
| | - Helen Barbas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, USA
- Graduate Program in Neuroscience, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts, USA
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts, USA
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16
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DiNicola LM, Sun W, Buckner RL. Side-by-side regions in dorsolateral prefrontal cortex estimated within the individual respond differentially to domain-specific and domain-flexible processes. J Neurophysiol 2023; 130:1602-1615. [PMID: 37937340 PMCID: PMC11068361 DOI: 10.1152/jn.00277.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/06/2023] [Accepted: 10/28/2023] [Indexed: 11/09/2023] Open
Abstract
A recurring debate concerns whether regions of primate prefrontal cortex (PFC) support domain-flexible or domain-specific processes. Here we tested the hypothesis with functional MRI (fMRI) that side-by-side PFC regions, within distinct parallel association networks, differentially support domain-flexible and domain-specialized processing. Individuals (N = 9) were intensively sampled, and all effects were estimated within their own idiosyncratic anatomy. Within each individual, we identified PFC regions linked to distinct networks, including a dorsolateral PFC (DLPFC) region coupled to the medial temporal lobe (MTL) and an extended region associated with the canonical multiple-demand network. We further identified an inferior PFC region coupled to the language network. Exploration in separate task data, collected within the same individuals, revealed a robust functional triple dissociation. The DLPFC region linked to the MTL was recruited during remembering and imagining the future, distinct from juxtaposed regions that were modulated in a domain-flexible manner during working memory. The inferior PFC region linked to the language network was recruited during sentence processing. Detailed analysis of the trial-level responses further revealed that the DLPFC region linked to the MTL specifically tracked processes associated with scene construction. These results suggest that the DLPFC possesses a domain-specialized region that is small and easily confused with nearby (larger) regions associated with cognitive control. The newly described region is domain specialized for functions traditionally associated with the MTL. We discuss the implications of these findings in relation to convergent anatomical analysis in the monkey.NEW & NOTEWORTHY Competing hypotheses link regions of prefrontal cortex (PFC) to domain-flexible or domain-specific processes. Here, using a precision neuroimaging approach, we identify a domain-specialized region in dorsolateral PFC, coupled to the medial temporal lobe and recruited for scene construction. This region is juxtaposed to, but distinct from, broader PFC regions recruited flexibly for cognitive control. Region distinctions align with broader network differences, suggesting that PFC regions gain dissociable processing properties via segregated anatomical projections.
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Affiliation(s)
- Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Wendy Sun
- Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts, United States
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
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Saberi A, Paquola C, Wagstyl K, Hettwer MD, Bernhardt BC, Eickhoff SB, Valk SL. The regional variation of laminar thickness in the human isocortex is related to cortical hierarchy and interregional connectivity. PLoS Biol 2023; 21:e3002365. [PMID: 37943873 PMCID: PMC10684102 DOI: 10.1371/journal.pbio.3002365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 11/28/2023] [Accepted: 10/06/2023] [Indexed: 11/12/2023] Open
Abstract
The human isocortex consists of tangentially organized layers with unique cytoarchitectural properties. These layers show spatial variations in thickness and cytoarchitecture across the neocortex, which is thought to support function through enabling targeted corticocortical connections. Here, leveraging maps of the 6 cortical layers based on 3D human brain histology, we aimed to quantitatively characterize the systematic covariation of laminar structure in the cortex and its functional consequences. After correcting for the effect of cortical curvature, we identified a spatial pattern of changes in laminar thickness covariance from lateral frontal to posterior occipital regions, which differentiated the dominance of infra- versus supragranular layer thickness. Corresponding to the laminar regularities of cortical connections along cortical hierarchy, the infragranular-dominant pattern of laminar thickness was associated with higher hierarchical positions of regions, mapped based on resting-state effective connectivity in humans and tract-tracing of structural connections in macaques. Moreover, we show that regions with similar laminar thickness patterns have a higher likelihood of structural connections and strength of functional connections. In sum, here we characterize the organization of laminar thickness in the human isocortex and its association with cortico-cortical connectivity, illustrating how laminar organization may provide a foundational principle of cortical function.
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Affiliation(s)
- Amin Saberi
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Casey Paquola
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
| | - Konrad Wagstyl
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Meike D. Hettwer
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Max Planck School of Cognition, Leipzig, Germany
| | - Boris C. Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Simon B. Eickhoff
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sofie L. Valk
- Otto Hahn Research Group for Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neurosciences and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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18
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Diesburg DA, Wessel JR, Jones SR. Biophysical modeling of frontocentral ERP generation links circuit-level mechanisms of action-stopping to a behavioral race model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.25.564020. [PMID: 37961333 PMCID: PMC10634895 DOI: 10.1101/2023.10.25.564020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Human frontocentral event-related potentials (FC-ERPs) are ubiquitous neural correlates of cognition and control, but their generating multiscale mechanisms remain mostly unknown. We used the Human Neocortical Neurosolver(HNN)'s biophysical model of a canonical neocortical circuit under exogenous thalamic and cortical drive to simulate the cell and circuit mechanisms underpinning the P2, N2, and P3 features of the FC-ERP observed after Stop-Signals in the Stop-Signal task (SST). We demonstrate that a sequence of simulated external thalamocortical and cortico-cortical drives can produce the FC-ERP, similar to what has been shown for primary sensory cortices. We used this model of the FC-ERP to examine likely circuit-mechanisms underlying FC-ERP features that distinguish between successful and failed action-stopping. We also tested their adherence to the predictions of the horse-race model of the SST, with specific hypotheses motivated by theoretical links between the P3 and Stop process. These simulations revealed that a difference in P3 onset between successful and failed Stops is most likely due to a later arrival of thalamocortical drive in failed Stops, rather than, for example, a difference in effective strength of the input. In contrast, the same model predicted that early thalamocortical drives underpinning the P2 and N2 differed in both strength and timing across stopping accuracy conditions. Overall, this model generates novel testable predictions of the thalamocortical dynamics underlying FC-ERP generation during action-stopping. Moreover, it provides a detailed cellular and circuit-level interpretation that supports links between these macroscale signatures and predictions of the behavioral race model.
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Affiliation(s)
| | - Jan R. Wessel
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, USA
- Department of Neurology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, USA
| | - Stephanie R. Jones
- Department of Neuroscience, Brown University, Providence, RI, USA
- Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, RI, USA
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Skandalakis GP, Barrios-Martinez J, Kazim SF, Rumalla K, Courville EN, Mahto N, Kalyvas A, Yeh FC, Hadjipanayis CG, Schmidt MH, Kogan M. The anatomy of the four streams of the prefrontal cortex. Preliminary evidence from a population based high definition tractography study. Front Neuroanat 2023; 17:1214629. [PMID: 37942215 PMCID: PMC10628325 DOI: 10.3389/fnana.2023.1214629] [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: 04/30/2023] [Accepted: 10/11/2023] [Indexed: 11/10/2023] Open
Abstract
The model of the four streams of the prefrontal cortex proposes 4 streams of information: motor through Brodmann area (BA) 8, emotion through BA 9, memory through BA 10, and emotional-related sensory through BA 11. Although there is a surge of functional data supporting these 4 streams within the PFC, the structural connectivity underlying these neural networks has not been fully clarified. Here we perform population-based high-definition tractography using an averaged template generated from data of 1,065 human healthy subjects acquired from the Human Connectome Project to further elucidate the structural organization of these regions. We report the structural connectivity of BA 8 with BA 6, BA 9 with the insula, BA 10 with the hippocampus, BA 11 with the temporal pole, and BA 11 with the amygdala. The 4 streams of the prefrontal cortex are subserved by a structural neural network encompassing fibers of the anterior part of the superior longitudinal fasciculus-I and II, corona radiata, cingulum, frontal aslant tract, and uncinate fasciculus. The identified neural network of the four streams of the PFC will allow the comprehensive analysis of these networks in normal and pathological brain function.
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Affiliation(s)
- Georgios P. Skandalakis
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, United States
| | | | - Syed Faraz Kazim
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, United States
| | - Kavelin Rumalla
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, United States
| | - Evan N. Courville
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, United States
| | - Neil Mahto
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, United States
| | - Aristotelis Kalyvas
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Fang-Cheng Yeh
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA, United States
| | | | - Meic H. Schmidt
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, United States
| | - Michael Kogan
- Department of Neurosurgery, University of New Mexico Hospital, Albuquerque, NM, United States
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Theriault JE, Shaffer C, Dienel GA, Sander CY, Hooker JM, Dickerson BC, Barrett LF, Quigley KS. A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments. Neurosci Biobehav Rev 2023; 153:105373. [PMID: 37634556 PMCID: PMC10591873 DOI: 10.1016/j.neubiorev.2023.105373] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/28/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.
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Affiliation(s)
- Jordan E Theriault
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| | - Clare Shaffer
- Northeastern University, Department of Psychology, Boston, MA, USA
| | - Gerald A Dienel
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, USA; Department of Cell Biology and Physiology, University of New Mexico, Albuquerque, NM, USA
| | - Christin Y Sander
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Jacob M Hooker
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Bradford C Dickerson
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Lisa Feldman Barrett
- Northeastern University, Department of Psychology, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Karen S Quigley
- Northeastern University, Department of Psychology, Boston, MA, USA; VA Bedford Healthcare System, Bedford, MA, USA
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Tan PK, Tang C, Herikstad R, Pillay A, Libedinsky C. Distinct Lateral Prefrontal Regions Are Organized in an Anterior-Posterior Functional Gradient. J Neurosci 2023; 43:6564-6572. [PMID: 37607819 PMCID: PMC10513068 DOI: 10.1523/jneurosci.0007-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 08/13/2023] [Accepted: 08/15/2023] [Indexed: 08/24/2023] Open
Abstract
The dorsolateral prefrontal cortex (dlPFC) is composed of multiple anatomically defined regions involved in higher-order cognitive processes, including working memory and selective attention. It is organized in an anterior-posterior global gradient where posterior regions track changes in the environment, whereas anterior regions support abstract neural representations. However, it remains unknown if such a global gradient results from a smooth gradient that spans regions or an emergent property arising from functionally distinct regions, that is, an areal gradient. Here, we recorded single neurons in the dlPFC of nonhuman primates trained to perform a memory-guided saccade task with an interfering distractor and analyzed their physiological properties along the anterior-posterior axis. We found that these physiological properties were best described by an areal gradient. Further, population analyses revealed that there is a distributed representation of spatial information across the dlPFC. Our results validate the functional boundaries between anatomically defined dlPFC regions and highlight the distributed nature of computations underlying working memory across the dlPFC.SIGNIFICANCE STATEMENT Activity of frontal lobe regions is known to possess an anterior-posterior functional gradient. However, it is not known whether this gradient is the result of individual brain regions organized in a gradient (like a staircase), or a smooth gradient that spans regions (like a slide). Analysis of physiological properties of individual neurons in the primate frontal regions suggest that individual regions are organized as a gradient, rather than a smooth gradient. At the population level, working memory was more prominent in posterior regions, although it was also present in anterior regions. This is consistent with the functional segregation of brain regions that is also observed in other systems (i.e., the visual system).
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Affiliation(s)
- Pin Kwang Tan
- Institute of Neuroscience, University of Texas at Austin, Austin, Texas 78712
| | - Cheng Tang
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
| | - Roger Herikstad
- The N1 Institute for Health, National University of Singapore, Singapore 117456
| | - Arunika Pillay
- Department of Psychology, Royal Holloway University of London, Egham TW20 OEX, United Kingdom
| | - Camilo Libedinsky
- The N1 Institute for Health, National University of Singapore, Singapore 117456
- Department of Psychology, National University of Singapore, Singapore 117570
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, National University of Singapore, Singapore 138632
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22
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Royer J, Larivière S, Rodriguez-Cruces R, Cabalo DG, Tavakol S, Auer H, Ngo A, Park BY, Paquola C, Smallwood J, Jefferies E, Caciagli L, Bernasconi A, Bernasconi N, Frauscher B, Bernhardt BC. Cortical microstructural gradients capture memory network reorganization in temporal lobe epilepsy. Brain 2023; 146:3923-3937. [PMID: 37082950 PMCID: PMC10473569 DOI: 10.1093/brain/awad125] [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] [Revised: 02/21/2023] [Accepted: 03/23/2023] [Indexed: 04/22/2023] Open
Abstract
Temporal lobe epilepsy (TLE), one of the most common pharmaco-resistant epilepsies, is associated with pathology of paralimbic brain regions, particularly in the mesiotemporal lobe. Cognitive dysfunction in TLE is frequent, and particularly affects episodic memory. Crucially, these difficulties challenge the quality of life of patients, sometimes more than seizures, underscoring the need to assess neural processes of cognitive dysfunction in TLE to improve patient management. Our work harnessed a novel conceptual and analytical approach to assess spatial gradients of microstructural differentiation between cortical areas based on high-resolution MRI analysis. Gradients track region-to-region variations in intracortical lamination and myeloarchitecture, serving as a system-level measure of structural and functional reorganization. Comparing cortex-wide microstructural gradients between 21 patients and 35 healthy controls, we observed a reorganization of this gradient in TLE driven by reduced microstructural differentiation between paralimbic cortices and the remaining cortex with marked abnormalities in ipsilateral temporopolar and dorsolateral prefrontal regions. Findings were replicated in an independent cohort. Using an independent post-mortem dataset, we observed that in vivo findings reflected topographical variations in cortical cytoarchitecture. We indeed found that macroscale changes in microstructural differentiation in TLE reflected increased similarity of paralimbic and primary sensory/motor regions. Disease-related transcriptomics could furthermore show specificity of our findings to TLE over other common epilepsy syndromes. Finally, microstructural dedifferentiation was associated with cognitive network reorganization seen during an episodic memory functional MRI paradigm and correlated with interindividual differences in task accuracy. Collectively, our findings showing a pattern of reduced microarchitectural differentiation between paralimbic regions and the remaining cortex provide a structurally-grounded explanation for large-scale functional network reorganization and cognitive dysfunction characteristic of TLE.
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Affiliation(s)
- Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Bo-yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
- Department of Data Science, Inha University, Incheon 22212, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 34126, Republic of Korea
| | - Casey Paquola
- Multiscale Neuroanatomy Lab, INM-1, Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Jonathan Smallwood
- Department of Psychology, Queen’s University, Kingston, ON, K7L 3N6, Canada
| | | | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, MA 19104, USA
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, H3A 2B4, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, H3A 2B4, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
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23
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Hansen JY, Shafiei G, Voigt K, Liang EX, Cox SML, Leyton M, Jamadar SD, Misic B. Integrating multimodal and multiscale connectivity blueprints of the human cerebral cortex in health and disease. PLoS Biol 2023; 21:e3002314. [PMID: 37747886 PMCID: PMC10553842 DOI: 10.1371/journal.pbio.3002314] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 10/05/2023] [Accepted: 08/28/2023] [Indexed: 09/27/2023] Open
Abstract
The brain is composed of disparate neural populations that communicate and interact with one another. Although fiber bundles, similarities in molecular architecture, and synchronized neural activity all reflect how brain regions potentially interact with one another, a comprehensive study of how all these interregional relationships jointly reflect brain structure and function remains missing. Here, we systematically integrate 7 multimodal, multiscale types of interregional similarity ("connectivity modes") derived from gene expression, neurotransmitter receptor density, cellular morphology, glucose metabolism, haemodynamic activity, and electrophysiology in humans. We first show that for all connectivity modes, feature similarity decreases with distance and increases when regions are structurally connected. Next, we show that connectivity modes exhibit unique and diverse connection patterns, hub profiles, spatial gradients, and modular organization. Throughout, we observe a consistent primacy of molecular connectivity modes-namely correlated gene expression and receptor similarity-that map onto multiple phenomena, including the rich club and patterns of abnormal cortical thickness across 13 neurological, psychiatric, and neurodevelopmental disorders. Finally, to construct a single multimodal wiring map of the human cortex, we fuse all 7 connectivity modes and show that the fused network maps onto major organizational features of the cortex including structural connectivity, intrinsic functional networks, and cytoarchitectonic classes. Altogether, this work contributes to the integrative study of interregional relationships in the human cerebral cortex.
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Affiliation(s)
- Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Katharina Voigt
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Emma X. Liang
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | | | - Marco Leyton
- Montréal Neurological Institute, McGill University, Montréal, Canada
- Department of Psychiatry, McGill University, Montréal, Canada
| | - Sharna D. Jamadar
- Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, Canada
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24
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [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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25
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Cano-Astorga N, Plaza-Alonso S, DeFelipe J, Alonso-Nanclares L. 3D synaptic organization of layer III of the human anterior cingulate and temporopolar cortex. Cereb Cortex 2023; 33:9691-9708. [PMID: 37455478 PMCID: PMC10472499 DOI: 10.1093/cercor/bhad232] [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: 04/11/2023] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
The human anterior cingulate and temporopolar cortices have been proposed as highly connected nodes involved in high-order cognitive functions, but their synaptic organization is still basically unknown due to the difficulties involved in studying the human brain. Using Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) to study the synaptic organization of the human brain obtained with a short post-mortem delay allows excellent results to be obtained. We have used this technology to analyze layer III of the anterior cingulate cortex (Brodmann area 24) and the temporopolar cortex, including the temporal pole (Brodmann area 38 ventral and dorsal) and anterior middle temporal gyrus (Brodmann area 21). Our results, based on 6695 synaptic junctions fully reconstructed in 3D, revealed that Brodmann areas 24, 21 and ventral area 38 showed similar synaptic density and synaptic size, whereas dorsal area 38 displayed the highest synaptic density and the smallest synaptic size. However, the proportion of the different types of synapses (excitatory and inhibitory), the postsynaptic targets, and the shapes of excitatory and inhibitory synapses were similar, regardless of the region examined. These observations indicate that certain aspects of the synaptic organization are rather homogeneous, whereas others show specific variations across cortical regions.
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Affiliation(s)
- Nicolás Cano-Astorga
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, 28002 Madrid, Spain
- PhD Program in Neuroscience, Autonoma de Madrid University - Cajal Institute, 28029 Madrid, Spain
| | - Sergio Plaza-Alonso
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, 28002 Madrid, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, 28002 Madrid, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, 28031 Madrid, Spain
| | - Lidia Alonso-Nanclares
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, 28002 Madrid, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, 28031 Madrid, Spain
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26
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Long J, Li J, Xie B, Jiao Z, Shen G, Liao W, Song X, Le H, Xia J, Wu S. Morphometric similarity network alterations in COVID-19 survivors correlate with behavioral features and transcriptional signatures. Neuroimage Clin 2023; 39:103498. [PMID: 37643521 PMCID: PMC10474075 DOI: 10.1016/j.nicl.2023.103498] [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: 04/17/2023] [Revised: 07/24/2023] [Accepted: 08/15/2023] [Indexed: 08/31/2023]
Abstract
OBJECTIVES To explore the differences in the cortical morphometric similarity network (MSN) between COVID-19 survivors and healthy controls, and the correlation between these differences and behavioralfeatures and transcriptional signatures. MATERIALS & METHODS 39 COVID-19 survivors and 39 age-, sex- and education years-matched healthy controls (HCs) were included. All participants underwent MRI and behavioral assessments (PCL-17, GAD-7, PHQ-9). MSN analysis was used to compute COVID-19 survivors vs. HCs differences across brain regions. Correlation analysis was used to determine the associations between regional MSN differences and behavioral assessments, and determine the spatial similarities between regional MSN differences and risk genes transcriptional activity. RESULTS COVID-19 survivors exhibited decreased regional MSN in insula, precuneus, transverse temporal, entorhinal, para-hippocampal, rostral middle frontal and supramarginal cortices, and increased regional MSN in pars triangularis, lateral orbitofrontal, superior frontal, superior parietal, postcentral, and inferior temporal cortices. Regional MSN value of lateral orbitofrontal cortex was positively associated with GAD-7 and PHQ-9 scores, and rostral middle frontal was negatively related to PHQ-9 scores. The analysis of spatial similarities showed that seven risk genes (MFGE8, MOB2, NUP62, PMPCA, SDSL, TMEM178B, and ZBTB11) were related to regional MSN values. CONCLUSION The MSN differences were associated with behavioral and transcriptional signatures, early psychological counseling or intervention may be required to COVID-19 survivors. Our study provided a new insight into understanding the altered coordination of structure in COVID-19 and may offer a new endophenotype to further investigate the brain substrate.
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Affiliation(s)
- Jia Long
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Jiao Li
- School of Life Science and Technology, University of Electronic Science and Technology of China Chengdu, 610054, PR China
| | - Bing Xie
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Zhuomin Jiao
- Department of Neurology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Guoqiang Shen
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Wei Liao
- School of Life Science and Technology, University of Electronic Science and Technology of China Chengdu, 610054, PR China
| | - Xiaomin Song
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China
| | - Hongbo Le
- Department of Radiology, South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China.
| | - Jun Xia
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen 518035, PR China.
| | - Song Wu
- South China Hospital, Medical School, Shenzhen University, Shenzhen 518116, PR China.
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27
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Lee HM, Hong SJ, Gill R, Caldairou B, Wang I, Zhang JG, Deleo F, Schrader D, Bartolomei F, Guye M, Cho KH, Barba C, Sisodiya S, Jackson G, Hogan RE, Wong-Kisiel L, Cascino GD, Schulze-Bonhage A, Lopes-Cendes I, Cendes F, Guerrini R, Bernhardt B, Bernasconi N, Bernasconi A. Multimodal mapping of regional brain vulnerability to focal cortical dysplasia. Brain 2023; 146:3404-3415. [PMID: 36852571 PMCID: PMC10393418 DOI: 10.1093/brain/awad060] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 01/17/2023] [Accepted: 02/02/2023] [Indexed: 03/01/2023] Open
Abstract
Focal cortical dysplasia (FCD) type II is a highly epileptogenic developmental malformation and a common cause of surgically treated drug-resistant epilepsy. While clinical observations suggest frequent occurrence in the frontal lobe, mechanisms for such propensity remain unexplored. Here, we hypothesized that cortex-wide spatial associations of FCD distribution with cortical cytoarchitecture, gene expression and organizational axes may offer complementary insights into processes that predispose given cortical regions to harbour FCD. We mapped the cortex-wide MRI distribution of FCDs in 337 patients collected from 13 sites worldwide. We then determined its associations with (i) cytoarchitectural features using histological atlases by Von Economo and Koskinas and BigBrain; (ii) whole-brain gene expression and spatiotemporal dynamics from prenatal to adulthood stages using the Allen Human Brain Atlas and PsychENCODE BrainSpan; and (iii) macroscale developmental axes of cortical organization. FCD lesions were preferentially located in the prefrontal and fronto-limbic cortices typified by low neuron density, large soma and thick grey matter. Transcriptomic associations with FCD distribution uncovered a prenatal component related to neuroglial proliferation and differentiation, likely accounting for the dysplastic makeup, and a postnatal component related to synaptogenesis and circuit organization, possibly contributing to circuit-level hyperexcitability. FCD distribution showed a strong association with the anterior region of the antero-posterior axis derived from heritability analysis of interregional structural covariance of cortical thickness, but not with structural and functional hierarchical axes. Reliability of all results was confirmed through resampling techniques. Multimodal associations with cytoarchitecture, gene expression and axes of cortical organization indicate that prenatal neurogenesis and postnatal synaptogenesis may be key points of developmental vulnerability of the frontal lobe to FCD. Concordant with a causal role of atypical neuroglial proliferation and growth, our results indicate that FCD-vulnerable cortices display properties indicative of earlier termination of neurogenesis and initiation of cell growth. They also suggest a potential contribution of aberrant postnatal synaptogenesis and circuit development to FCD epileptogenicity.
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Affiliation(s)
- Hyo M Lee
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Seok-Jun Hong
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Montreal, Canada
- Center for Neuroscience Imaging, Research Institute for Basic Science, Department of Global Biomedical Engineering, SungKyunKwan University, Suwon, KoreaSuwon, Korea
| | - Ravnoor Gill
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Irene Wang
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jian-guo Zhang
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Francesco Deleo
- Epilepsy Unit, Fondazione IRCCS Istituto Neurologico C. Besta, Milano, Italy
| | - Dewi Schrader
- Department of Pediatrics, British Columbia Children’s Hospital, Vancouver, Canada
| | - Fabrice Bartolomei
- Aix Marseille Univ, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, 13005, France
| | - Maxime Guye
- Aix Marseille University, CNRS, CRMBM UMR 7339, Marseille, France
| | - Kyoo Ho Cho
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Carmen Barba
- Meyer Children's Hospital IRCCS, Florence, Italy
- University of Florence, 50121 Florence, Italy
| | - Sanjay Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Graeme Jackson
- The Florey Institute of Neuroscience and Mental Health and The University of Melbourne, Victoria, Australia
| | - R Edward Hogan
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | | | | | | | - Iscia Lopes-Cendes
- Department of Translational Medicine, School of Medical Sciences, University of Campinas (UNICAMP) and the Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas SP, Brazil
| | - Fernando Cendes
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), and the Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas SP, Brazil
| | - Renzo Guerrini
- Meyer Children's Hospital IRCCS, Florence, Italy
- University of Florence, 50121 Florence, Italy
| | - Boris Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Montreal, Canada
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28
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Sebenius I, Seidlitz J, Warrier V, Bethlehem RAI, Alexander-Bloch A, Mallard TT, Garcia RR, Bullmore ET, Morgan SE. Robust estimation of cortical similarity networks from brain MRI. Nat Neurosci 2023; 26:1461-1471. [PMID: 37460809 PMCID: PMC10400419 DOI: 10.1038/s41593-023-01376-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 06/08/2023] [Indexed: 08/05/2023]
Abstract
Structural similarity is a growing focus for magnetic resonance imaging (MRI) of connectomes. Here we propose Morphometric INverse Divergence (MIND), a new method to estimate within-subject similarity between cortical areas based on the divergence between their multivariate distributions of multiple MRI features. Compared to the prior approach of morphometric similarity networks (MSNs) on n > 11,000 scans spanning three human datasets and one macaque dataset, MIND networks were more reliable, more consistent with cortical cytoarchitectonics and symmetry and more correlated with tract-tracing measures of axonal connectivity. MIND networks derived from human T1-weighted MRI were more sensitive to age-related changes than MSNs or networks derived by tractography of diffusion-weighted MRI. Gene co-expression between cortical areas was more strongly coupled to MIND networks than to MSNs or tractography. MIND network phenotypes were also more heritable, especially edges between structurally differentiated areas. MIND network analysis provides a biologically validated lens for cortical connectomics using readily available MRI data.
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Affiliation(s)
- Isaac Sebenius
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK.
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Richard A I Bethlehem
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Travis T Mallard
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Rafael Romero Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla/CIBERSAM, ISCIII, Dpto. de Fisiología Médica y Biofísica, Barcelona, Spain
| | | | - Sarah E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- Alan Turing Institute, London, UK
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29
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Watakabe A, Skibbe H, Nakae K, Abe H, Ichinohe N, Rachmadi MF, Wang J, Takaji M, Mizukami H, Woodward A, Gong R, Hata J, Van Essen DC, Okano H, Ishii S, Yamamori T. Local and long-distance organization of prefrontal cortex circuits in the marmoset brain. Neuron 2023; 111:2258-2273.e10. [PMID: 37196659 PMCID: PMC10789578 DOI: 10.1016/j.neuron.2023.04.028] [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: 10/31/2022] [Revised: 03/13/2023] [Accepted: 04/25/2023] [Indexed: 05/19/2023]
Abstract
The prefrontal cortex (PFC) has dramatically expanded in primates, but its organization and interactions with other brain regions are only partially understood. We performed high-resolution connectomic mapping of the marmoset PFC and found two contrasting corticocortical and corticostriatal projection patterns: "patchy" projections that formed many columns of submillimeter scale in nearby and distant regions and "diffuse" projections that spread widely across the cortex and striatum. Parcellation-free analyses revealed representations of PFC gradients in these projections' local and global distribution patterns. We also demonstrated column-scale precision of reciprocal corticocortical connectivity, suggesting that PFC contains a mosaic of discrete columns. Diffuse projections showed considerable diversity in the laminar patterns of axonal spread. Altogether, these fine-grained analyses reveal important principles of local and long-distance PFC circuits in marmosets and provide insights into the functional organization of the primate brain.
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Affiliation(s)
- Akiya Watakabe
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Laboratory for Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan.
| | - Henrik Skibbe
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan.
| | - Ken Nakae
- Integrated Systems Biology Laboratory, Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto, Kyoto 606-8501, Japan; Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Okazaki, Aichi 444-8787, Japan
| | - Hiroshi Abe
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Laboratory for Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Noritaka Ichinohe
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Department of Ultrastructural Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-0031, Japan
| | - Muhammad Febrian Rachmadi
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Faculty of Computer Science, Universitas Indonesia, Depok, Jawa Barat 16424, Indonesia
| | - Jian Wang
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Masafumi Takaji
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Laboratory for Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Hiroaki Mizukami
- Division of Genetic Therapeutics, Center for Molecular Medicine, Jichi Medical University, Shimotsuke, Tochigi 329-0498, Japan
| | - Alexander Woodward
- Connectome Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Rui Gong
- Connectome Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
| | - Junichi Hata
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo 116-8551, Japan
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Department of Physiology, Keio University School of Medicine, Tokyo 108-8345, Japan
| | - Shin Ishii
- Integrated Systems Biology Laboratory, Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto, Kyoto 606-8501, Japan
| | - Tetsuo Yamamori
- Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Laboratory for Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan; Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan.
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30
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Valk SL, Kanske P, Park BY, Hong SJ, Böckler A, Trautwein FM, Bernhardt BC, Singer T. Functional and microstructural plasticity following social and interoceptive mental training. eLife 2023; 12:e85188. [PMID: 37417306 PMCID: PMC10414971 DOI: 10.7554/elife.85188] [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: 11/25/2022] [Accepted: 07/01/2023] [Indexed: 07/08/2023] Open
Abstract
The human brain supports social cognitive functions, including Theory of Mind, empathy, and compassion, through its intrinsic hierarchical organization. However, it remains unclear how the learning and refinement of social skills shapes brain function and structure. We studied if different types of social mental training induce changes in cortical function and microstructure, investigating 332 healthy adults (197 women, 20-55 years) with repeated multimodal neuroimaging and behavioral testing. Our neuroimaging approach examined longitudinal changes in cortical functional gradients and myelin-sensitive T1 relaxometry, two complementary measures of cortical hierarchical organization. We observed marked changes in intrinsic cortical function and microstructure, which varied as a function of social training content. In particular, cortical function and microstructure changed as a result of attention-mindfulness and socio-cognitive training in regions functionally associated with attention and interoception, including insular and parietal cortices. Conversely, socio-affective and socio-cognitive training resulted in differential microstructural changes in regions classically implicated in interoceptive and emotional processing, including insular and orbitofrontal areas, but did not result in functional reorganization. Notably, longitudinal changes in cortical function and microstructure predicted behavioral change in attention, compassion and perspective-taking. Our work demonstrates functional and microstructural plasticity after the training of social-interoceptive functions, and illustrates the bidirectional relationship between brain organisation and human social skills.
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Affiliation(s)
- Sofie Louise Valk
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- INM-7, FZ JülichJülichGermany
| | - Philipp Kanske
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität DresdenDresdenGermany
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Bo-yong Park
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
- Department of Data Science, Inha UniversityIncheonRepublic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic ScienceSuwonRepublic of Korea
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic ScienceSuwonRepublic of Korea
- Center for the Developing Brain, Child Mind InstituteNew YorkUnited States
- Department of Biomedical Engineering, Sungkyunkwan UniversitySuwonRepublic of Korea
| | - Anne Böckler
- Department of Psychology, Wurzburg UniversityWurzburgGermany
| | - Fynn-Mathis Trautwein
- Department of Psychosomatic Medicine and Psychotherapy, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgFreiburgGermany
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Tania Singer
- Social Neuroscience Lab, Max Planck SocietyBerlinGermany
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31
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Sancha-Velasco A, Uceda-Heras A, García-Cabezas MÁ. Cortical type: a conceptual tool for meaningful biological interpretation of high-throughput gene expression data in the human cerebral cortex. Front Neuroanat 2023; 17:1187280. [PMID: 37426901 PMCID: PMC10323436 DOI: 10.3389/fnana.2023.1187280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 05/31/2023] [Indexed: 07/11/2023] Open
Abstract
The interpretation of massive high-throughput gene expression data requires computational and biological analyses to identify statistically and biologically significant differences, respectively. There are abundant sources that describe computational tools for statistical analysis of massive gene expression data but few address data analysis for biological significance. In the present article we exemplify the importance of selecting the proper biological context in the human brain for gene expression data analysis and interpretation. For this purpose, we use cortical type as conceptual tool to make predictions about gene expression in areas of the human temporal cortex. We predict that the expression of genes related to glutamatergic transmission would be higher in areas of simpler cortical type, the expression of genes related to GABAergic transmission would be higher in areas of more complex cortical type, and the expression of genes related to epigenetic regulation would be higher in areas of simpler cortical type. Then, we test these predictions with gene expression data from several regions of the human temporal cortex obtained from the Allen Human Brain Atlas. We find that the expression of several genes shows statistically significant differences in agreement with the predicted gradual expression along the laminar complexity gradient of the human cortex, suggesting that simpler cortical types may have greater glutamatergic excitability and epigenetic turnover compared to more complex types; on the other hand, complex cortical types seem to have greater GABAergic inhibitory control compared to simpler types. Our results show that cortical type is a good predictor of synaptic plasticity, epigenetic turnover, and selective vulnerability in human cortical areas. Thus, cortical type can provide a meaningful context for interpreting high-throughput gene expression data in the human cerebral cortex.
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Affiliation(s)
- Ariadna Sancha-Velasco
- Department of Anatomy, Histology and Neuroscience, School of Medicine, Autonomous University of Madrid, Madrid, Spain
- Master Program in Neuroscience, Autonomous University of Madrid, Madrid, Spain
| | - Alicia Uceda-Heras
- Master Program in Neuroscience, Autonomous University of Madrid, Madrid, Spain
- Ph.D. Program in Neuroscience UAM-Cajal, Autonomous University of Madrid, Madrid, Spain
| | - Miguel Ángel García-Cabezas
- Department of Anatomy, Histology and Neuroscience, School of Medicine, Autonomous University of Madrid, Madrid, Spain
- Master Program in Neuroscience, Autonomous University of Madrid, Madrid, Spain
- Ph.D. Program in Neuroscience UAM-Cajal, Autonomous University of Madrid, Madrid, Spain
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
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32
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Karolis VR, Fitzgibbon SP, Cordero-Grande L, Farahibozorg SR, Price AN, Hughes EJ, Fetit AE, Kyriakopoulou V, Pietsch M, Rutherford MA, Rueckert D, Hajnal JV, Edwards AD, O'Muircheartaigh J, Duff EP, Arichi T. Maturational networks of human fetal brain activity reveal emerging connectivity patterns prior to ex-utero exposure. Commun Biol 2023; 6:661. [PMID: 37349403 PMCID: PMC10287667 DOI: 10.1038/s42003-023-04969-x] [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: 10/05/2022] [Accepted: 05/23/2023] [Indexed: 06/24/2023] Open
Abstract
A key feature of the fetal period is the rapid emergence of organised patterns of spontaneous brain activity. However, characterising this process in utero using functional MRI is inherently challenging and requires analytical methods which can capture the constituent developmental transformations. Here, we introduce a novel analytical framework, termed "maturational networks" (matnets), that achieves this by modelling functional networks as an emerging property of the developing brain. Compared to standard network analysis methods that assume consistent patterns of connectivity across development, our method incorporates age-related changes in connectivity directly into network estimation. We test its performance in a large neonatal sample, finding that the matnets approach characterises adult-like features of functional network architecture with a greater specificity than a standard group-ICA approach; for example, our approach is able to identify a nearly complete default mode network. In the in-utero brain, matnets enables us to reveal the richness of emerging functional connections and the hierarchy of their maturational relationships with remarkable anatomical specificity. We show that the associative areas play a central role within prenatal functional architecture, therefore indicating that functional connections of high-level associative areas start emerging prior to exposure to the extra-utero environment.
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Affiliation(s)
- Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Sean P Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Lucilio Cordero-Grande
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, Madrid, Spain
| | - Seyedeh-Rezvan Farahibozorg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Emer J Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Ahmed E Fetit
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
- UKRI CDT in Artificial Intelligence for Healthcare, Department of Computing, Imperial College London, London, UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Maximilian Pietsch
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
- Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Eugene P Duff
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- Paediatric Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK
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Wang XJ, Jiang J, Pereira-Obilinovic U. Bifurcation in space: Emergence of function modularity in the neocortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.04.543639. [PMID: 37333347 PMCID: PMC10274618 DOI: 10.1101/2023.06.04.543639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
How does functional modularity emerge in a multiregional cortex made with repeats of a canonical local circuit architecture? We investigated this question by focusing on neural coding of working memory, a core cognitive function. Here we report a mechanism dubbed "bifurcation in space", and show that its salient signature is spatially localized "critical slowing down" leading to an inverted V-shaped profile of neuronal time constants along the cortical hierarchy during working memory. The phenomenon is confirmed in connectome-based large-scale models of mouse and monkey cortices, offering an experimentally testable prediction to assess whether working memory representation is modular. Many bifurcations in space could explain the emergence of different activity patterns potentially deployed for distinct cognitive functions, This work demonstrates that a distributed mental representation is compatible with functional specificity as a consequence of macroscopic gradients of neurobiological properties across the cortex, suggesting a general principle for understanding brain's modular organization.
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Affiliation(s)
- Xiao-Jing Wang
- Center for Neural Science, New York University, 4 Washington Place, New York 10003, USA
| | - Junjie Jiang
- Center for Neural Science, New York University, 4 Washington Place, New York 10003, USA
- Present address: The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Research Center for Brain-inspired Intelligence, Xi’an Jiaotong University, No.28, West Xianning Road, Xi’an, 710049, Shaanxi, P. R. China
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Schirner M, Deco G, Ritter P. Learning how network structure shapes decision-making for bio-inspired computing. Nat Commun 2023; 14:2963. [PMID: 37221168 DOI: 10.1038/s41467-023-38626-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 05/10/2023] [Indexed: 05/25/2023] Open
Abstract
To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that we used to build personalized brain network models for 650 Human Connectome Project participants. We found that participants with higher intelligence scores took more time to solve difficult problems, and that slower solvers had higher average functional connectivity. With simulations we identified a mechanistic link between functional connectivity, intelligence, processing speed and brain synchrony for trading accuracy with speed in dependence of excitation-inhibition balance. Reduced synchrony led decision-making circuits to quickly jump to conclusions, while higher synchrony allowed for better integration of evidence and more robust working memory. Strict tests were applied to ensure reproducibility and generality of the obtained results. Here, we identify links between brain structure and function that enable to learn connectome topology from noninvasive recordings and map it to inter-individual differences in behavior, suggesting broad utility for research and clinical applications.
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Affiliation(s)
- Michael Schirner
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany.
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany.
| | - Gustavo Deco
- Department of Information and Communication Technologies, Center for Brain and Cognition, Computational Neuroscience Group, University of Pompeu Fabra, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, Melbourne, VIC, Australia
| | - Petra Ritter
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany.
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany.
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Draganov M, Galiano-Landeira J, Doruk Camsari D, Ramírez JE, Robles M, Chanes L. Noninvasive modulation of predictive coding in humans: causal evidence for frequency-specific temporal dynamics. Cereb Cortex 2023:7156779. [PMID: 37154618 DOI: 10.1093/cercor/bhad127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 03/17/2023] [Accepted: 03/18/2023] [Indexed: 05/10/2023] Open
Abstract
Increasing evidence indicates that the brain predicts sensory input based on past experiences, importantly constraining how we experience the world. Despite a growing interest on this framework, known as predictive coding, most of such approaches to multiple psychological domains continue to be theoretical or primarily provide correlational evidence. We here explored the neural basis of predictive processing using noninvasive brain stimulation and provide causal evidence of frequency-specific modulations in humans. Participants received 20 Hz (associated with top-down/predictions), 50 Hz (associated with bottom-up/prediction errors), or sham transcranial alternating current stimulation on the left dorsolateral prefrontal cortex while performing a social perception task in which facial expression predictions were induced and subsequently confirmed or violated. Left prefrontal 20 Hz stimulation reinforced stereotypical predictions. In contrast, 50 Hz and sham stimulation failed to yield any significant behavioral effects. Moreover, the frequency-specific effect observed was further supported by electroencephalography data, which showed a boost of brain activity at the stimulated frequency band. These observations provide causal evidence for how predictive processing may be enabled in the human brain, setting up a needed framework to understand how it may be disrupted across brain-related conditions and potentially restored through noninvasive methods.
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Affiliation(s)
- Metodi Draganov
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
| | - Jordi Galiano-Landeira
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
| | - Deniz Doruk Camsari
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, United States
| | - Jairo-Enrique Ramírez
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
| | - Marta Robles
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
- Department of Psychiatry and Psychotherapy, Medical Faculty, LMU Munich, Munich 80336, Germany
| | - Lorena Chanes
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
- Institut de Neurociències, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
- Serra Húnter Programme, Generalitat de Catalunya, Barcelona 08002, Spain
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Moore TL, Medalla M, Ibañez S, Wimmer K, Mojica CA, Killiany RJ, Moss MB, Luebke JI, Rosene DL. Neuronal properties of pyramidal cells in lateral prefrontal cortex of the aging rhesus monkey brain are associated with performance deficits on spatial working memory but not executive function. GeroScience 2023:10.1007/s11357-023-00798-2. [PMID: 37106282 PMCID: PMC10400510 DOI: 10.1007/s11357-023-00798-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 04/11/2023] [Indexed: 04/29/2023] Open
Abstract
Age-related declines in cognitive abilities occur as early as middle-age in humans and rhesus monkeys. Specifically, performance by aged individuals on tasks of executive function (EF) and working memory (WM) is characterized by greater frequency of errors, shorter memory spans, increased frequency of perseverative responses, impaired use of feedback and reduced speed of processing. However, how aging precisely differentially impacts specific aspects of these cognitive functions and the distinct brain areas mediating cognition are not well understood. The prefrontal cortex (PFC) is known to mediate EF and WM and is an area that shows a vulnerability to age-related alterations in neuronal morphology. In the current study, we show that performance on EF and WM tasks exhibited significant changes with age, and these impairments correlate with changes in biophysical properties of layer 3 (L3) pyramidal neurons in lateral LPFC (LPFC). Specifically, there was a significant age-related increase in excitability of L3 LPFC pyramidal neurons, consistent with previous studies. Further, this age-related hyperexcitability of LPFC neurons was significantly correlated with age-related decline on a task of WM, but not an EF task. The current study characterizes age-related performance on tasks of WM and EF and provides insight into the neural substrates that may underlie changes in both WM and EF with age.
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Affiliation(s)
- Tara L Moore
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, 700 Albany Street, W701, MA, 02118, Boston, USA.
- Center for Systems Neuroscience, Boston University, MA, 02115, Boston, USA.
| | - Maria Medalla
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, 700 Albany Street, W701, MA, 02118, Boston, USA
- Center for Systems Neuroscience, Boston University, MA, 02115, Boston, USA
| | - Sara Ibañez
- Centre de Recerca Matemàtica, Edifici C, Campus Bellaterra, 08193, Bellaterra, Spain
| | - Klaus Wimmer
- Centre de Recerca Matemàtica, Edifici C, Campus Bellaterra, 08193, Bellaterra, Spain
| | - Chromewell A Mojica
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, 700 Albany Street, W701, MA, 02118, Boston, USA
| | - Ronald J Killiany
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, 700 Albany Street, W701, MA, 02118, Boston, USA
- Center for Systems Neuroscience, Boston University, MA, 02115, Boston, USA
| | - Mark B Moss
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, 700 Albany Street, W701, MA, 02118, Boston, USA
- Center for Systems Neuroscience, Boston University, MA, 02115, Boston, USA
| | - Jennifer I Luebke
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, 700 Albany Street, W701, MA, 02118, Boston, USA
- Center for Systems Neuroscience, Boston University, MA, 02115, Boston, USA
| | - Douglas L Rosene
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, 700 Albany Street, W701, MA, 02118, Boston, USA
- Center for Systems Neuroscience, Boston University, MA, 02115, Boston, USA
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37
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Katsumi Y, Zhang J, Chen D, Kamona N, Bunce JG, Hutchinson JB, Yarossi M, Tunik E, Dickerson BC, Quigley KS, Barrett LF. Correspondence of functional connectivity gradients across human isocortex, cerebellum, and hippocampus. Commun Biol 2023; 6:401. [PMID: 37046050 PMCID: PMC10097701 DOI: 10.1038/s42003-023-04796-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/03/2023] [Indexed: 04/14/2023] Open
Abstract
Gradient mapping is an important technique to summarize high dimensional biological features as low dimensional manifold representations in exploring brain structure-function relationships at various levels of the cerebral cortex. While recent studies have characterized the major gradients of functional connectivity in several brain structures using this technique, very few have systematically examined the correspondence of such gradients across structures under a common systems-level framework. Using resting-state functional magnetic resonance imaging, here we show that the organizing principles of the isocortex, and those of the cerebellum and hippocampus in relation to the isocortex, can be described using two common functional gradients. We suggest that the similarity in functional connectivity gradients across these structures can be meaningfully interpreted within a common computational framework based on the principles of predictive processing. The present results, and the specific hypotheses that they suggest, represent an important step toward an integrative account of brain function.
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Affiliation(s)
- Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
| | - Jiahe Zhang
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Danlei Chen
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Nada Kamona
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Jamie G Bunce
- Department of Biology, Northeastern University, Boston, MA, 02115, USA
| | | | - Mathew Yarossi
- Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, 02115, USA
- Department of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, Boston, MA, 02115, USA
| | - Eugene Tunik
- Department of Physical Therapy, Movement, and Rehabilitation Science, Northeastern University, Boston, MA, 02115, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Karen S Quigley
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
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38
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Hanganu-Opatz IL, Klausberger T, Sigurdsson T, Nieder A, Jacob SN, Bartos M, Sauer JF, Durstewitz D, Leibold C, Diester I. Resolving the prefrontal mechanisms of adaptive cognitive behaviors: A cross-species perspective. Neuron 2023; 111:1020-1036. [PMID: 37023708 DOI: 10.1016/j.neuron.2023.03.017] [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: 11/04/2022] [Revised: 02/15/2023] [Accepted: 03/10/2023] [Indexed: 04/08/2023]
Abstract
The prefrontal cortex (PFC) enables a staggering variety of complex behaviors, such as planning actions, solving problems, and adapting to new situations according to external information and internal states. These higher-order abilities, collectively defined as adaptive cognitive behavior, require cellular ensembles that coordinate the tradeoff between the stability and flexibility of neural representations. While the mechanisms underlying the function of cellular ensembles are still unclear, recent experimental and theoretical studies suggest that temporal coordination dynamically binds prefrontal neurons into functional ensembles. A so far largely separate stream of research has investigated the prefrontal efferent and afferent connectivity. These two research streams have recently converged on the hypothesis that prefrontal connectivity patterns influence ensemble formation and the function of neurons within ensembles. Here, we propose a unitary concept that, leveraging a cross-species definition of prefrontal regions, explains how prefrontal ensembles adaptively regulate and efficiently coordinate multiple processes in distinct cognitive behaviors.
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Affiliation(s)
- Ileana L Hanganu-Opatz
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
| | - Thomas Klausberger
- Center for Brain Research, Division of Cognitive Neurobiology, Medical University of Vienna, Vienna, Austria
| | - Torfi Sigurdsson
- Institute of Neurophysiology, Goethe University, Frankfurt, Germany
| | - Andreas Nieder
- Animal Physiology Unit, Institute of Neurobiology, University of Tübingen, 72076 Tübingen, Germany
| | - Simon N Jacob
- Translational Neurotechnology Laboratory, Department of Neurosurgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Marlene Bartos
- Institute for Physiology I, Medical Faculty, University of Freiburg, Freiburg im Breisgau, Germany
| | - Jonas-Frederic Sauer
- Institute for Physiology I, Medical Faculty, University of Freiburg, Freiburg im Breisgau, Germany
| | - Daniel Durstewitz
- Department of Theoretical Neuroscience, Central Institute of Mental Health & Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Christian Leibold
- Faculty of Biology, Bernstein Center Freiburg, BrainLinks-BrainTools, University of Freiburg, Freiburg im Breisgau, Germany
| | - Ilka Diester
- Optophysiology - Optogenetics and Neurophysiology, IMBIT // BrainLinks-BrainTools, University of Freiburg, Freiburg im Breisgau, Germany.
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Barbas H, Hilgetag CC. From Circuit Principles to Human Psychiatric Disorders. Biol Psychiatry 2023; 93:388-390. [PMID: 36114040 DOI: 10.1016/j.biopsych.2022.08.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 07/23/2022] [Accepted: 08/09/2022] [Indexed: 02/07/2023]
Affiliation(s)
- Helen Barbas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts; Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, Massachusetts.
| | - Claus C Hilgetag
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts; Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany
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Wang Y, Royer J, Park BY, Vos de Wael R, Larivière S, Tavakol S, Rodriguez-Cruces R, Paquola C, Hong SJ, Margulies DS, Smallwood J, Valk SL, Evans AC, Bernhardt BC. Long-range functional connections mirror and link microarchitectural and cognitive hierarchies in the human brain. Cereb Cortex 2023; 33:1782-1798. [PMID: 35596951 PMCID: PMC9977370 DOI: 10.1093/cercor/bhac172] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 03/30/2022] [Accepted: 04/01/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Higher-order cognition is hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, it is unknown how computational advantages of long-range connections reflect cortical microstructure and microcircuitry. METHODS We investigated this question by (i) profiling long-range cortical connectivity using resting-state functional magnetic resonance imaging (MRI) and cortico-cortical geodesic distance mapping, (ii) assessing how long-range connections reflect local brain microarchitecture, and (iii) examining the microarchitectural similarity of regions connected through long-range connections. RESULTS Analysis of 2 independent datasets indicated that sensory/motor areas had more clustered short-range connections, while transmodal association systems hosted distributed, long-range connections. Meta-analytical decoding suggested that this topographical difference mirrored shifts in cognitive function, from perception/action towards emotional/social processing. Analysis of myelin-sensitive in vivo MRI as well as postmortem histology and transcriptomics datasets established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Notably, long-range connections were found to link spatially remote regions of association cortex with an unexpectedly similar microarchitecture. CONCLUSIONS By mapping covarying topographies of long-range functional connections and cortical microcircuits, the current work provides insights into structure-function relations in human neocortex.
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Affiliation(s)
- Yezhou Wang
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Bo-Yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Department of Data Science, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, South Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Casey Paquola
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea
| | - Daniel S Margulies
- Cognitive Neuroanatomy Lab, Integrative Neuroscience and Cognition Centre, University of Paris and CRNS, INCC - UMR 8002, Rue des Saint-Pères 75006, Paris
| | - Jonathan Smallwood
- Department of Psychology, Queen's University, 62 Arch Street, Humphrey Hall, Room 232 Kingston, Ontario K7L 3N6, Canada
| | - Sofie L Valk
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.,Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A. Leipzig D-04103, Germany.,Institute of Systems Neuroscience, Heinrich Heine University, Moorenstr. 5, Düsseldorf 40225, Germany
| | - Alan C Evans
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
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Moore TL, Medalla M, Iba Ez S, Wimmer K, Mojica CA, Killiany RJ, Moss MB, Luebke JI, Rosene DL. Neuronal properties of pyramidal cells in lateral prefrontal cortex of the aging rhesus monkey brain are associated with performance deficits on spatial working memory but not executive function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.07.527321. [PMID: 36798388 PMCID: PMC9934587 DOI: 10.1101/2023.02.07.527321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Age-related declines in cognitive abilities occur as early as middle-age in humans and rhesus monkeys. Specifically, performance by aged individuals on tasks of executive function (EF) and working memory (WM) is characterized by greater frequency of errors, shorter memory spans, increased frequency of perseverative responses, impaired use of feedback and reduced speed of processing. However, how aging precisely differentially impacts specific aspects of these cognitive functions and the distinct brain areas mediating cognition are not well understood. The prefrontal cortex (PFC) is known to mediate EF and WM and is an area that shows a vulnerability to age-related alterations in neuronal morphology. In the current study, we show that performance on EF and WM tasks exhibited significant changes with age and these impairments correlate with changes in biophysical properties of L3 pyramidal neurons in lateral LPFC (LPFC). Specifically, there was a significant age-related increase in excitability of Layer 3 LPFC pyramidal neurons, consistent with previous studies. Further, this age-related hyperexcitability of LPFC neurons was significantly correlated with age-related decline on a task of WM, but not an EF task. The current study characterizes age-related performance on tasks of WM and EF and provides insight into the neural substrates that may underlie changes in both WM and EF with age.
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Zong X, Zhang J, Li L, Yao T, Ma S, Kang L, Zhang N, Nie Z, Liu Z, Zheng J, Duan X, Hu M, Hu M. Virtual histology of morphometric similarity network after risperidone monotherapy and imaging-epigenetic biomarkers for treatment response in first-episode schizophrenia. Asian J Psychiatr 2023; 80:103406. [PMID: 36586357 DOI: 10.1016/j.ajp.2022.103406] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 11/29/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Antipsychotic treatment has been conceived to alter brain connectivity, but it is unclear how the changes of network phenotypes relate to the underlying transcriptomics. Given DNA methylation (DNAm) may alter transcriptional levels, we further integrated an imaging-transcriptomic-epigenetic analysis to explore multi-omics treatment response biomarkers. METHODS Forty-two treatment-naive first-episode schizophrenia patients were scanned by TI weighted (T1W) imaging and DTI before and after 8-week risperidone monotherapy, and their peripheral blood genomic DNAm values were examined in parallel with MRI scanning. Morphometric similarity network (MSN) quantified with DTI and T1W data were used as a marker of treatment-related alterations in interareal cortical connectivity. We utilized partial least squares (PLS) to examine spatial associations between treatment-related MSN variations and cortical transcriptomic data obtained from the Allen Human Brain Atlas. RESULTS Longitudinal MSN alterations were related to treatment response on cognitive function and general psychopathology symptoms, while DNAm values of 59 PLS1 genes were on negative and positive symptoms. Virtual-histology transcriptomic analysis linked the MSN alterations with the neurobiological, cellular and metabolic pathways or processes, and assigned MSN-related genes to multiple cell types, specifying neurons and glial cells as contributing most to the transcriptomic associations of longitudinal changes in MSN. CONCLUSIONS We firstly reveal how brain-wide transcriptional levels and cell classes capture molecularly validated cortical connectivity alterations after antipsychotic treatment. Our findings represent a vital step towards the exploration of treatment response biomarkers on the basis of multiple omics rather than a single omics type as a strategy for advancing precise care.
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Affiliation(s)
- Xiaofen Zong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Jiangbo Zhang
- The High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Lei Li
- The High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Tao Yao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Simeng Ma
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Lijun Kang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Nan Zhang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Zhaowen Nie
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China; Taikang center for life and medical sciences, Wuhan University, Wuhan, Hubei, China.
| | - Junjie Zheng
- The Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China; The Functional Brain Imaging Institute, Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Xujun Duan
- The High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.
| | - Maolin Hu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
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Lankinen K, Ahlfors SP, Mamashli F, Blazejewska AI, Raij T, Turpin T, Polimeni JR, Ahveninen J. Cortical depth profiles of auditory and visual 7 T functional MRI responses in human superior temporal areas. Hum Brain Mapp 2023; 44:362-372. [PMID: 35980015 PMCID: PMC9842898 DOI: 10.1002/hbm.26046] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 07/06/2022] [Accepted: 07/16/2022] [Indexed: 02/02/2023] Open
Abstract
Invasive neurophysiological studies in nonhuman primates have shown different laminar activation profiles to auditory vs. visual stimuli in auditory cortices and adjacent polymodal areas. Means to examine the underlying feedforward vs. feedback type influences noninvasively have been limited in humans. Here, using 1-mm isotropic resolution 3D echo-planar imaging at 7 T, we studied the intracortical depth profiles of functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) signals to brief auditory (noise bursts) and visual (checkerboard) stimuli. BOLD percent-signal-changes were estimated at 11 equally spaced intracortical depths, within regions-of-interest encompassing auditory (Heschl's gyrus, Heschl's sulcus, planum temporale, and posterior superior temporal gyrus) and polymodal (middle and posterior superior temporal sulcus) areas. Effects of differing BOLD signal strengths for auditory and visual stimuli were controlled via normalization and statistical modeling. The BOLD depth profile shapes, modeled with quadratic regression, were significantly different for auditory vs. visual stimuli in auditory cortices, but not in polymodal areas. The different depth profiles could reflect sensory-specific feedforward versus cross-sensory feedback influences, previously shown in laminar recordings in nonhuman primates. The results suggest that intracortical BOLD profiles can help distinguish between feedforward and feedback type influences in the human brain. Further experimental studies are still needed to clarify how underlying signal strength influences BOLD depth profiles under different stimulus conditions.
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Affiliation(s)
- Kaisu Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Seppo P. Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Fahimeh Mamashli
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Anna I. Blazejewska
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Tommi Raij
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Tori Turpin
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Division of Health Sciences and TechnologyMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
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Sherif MA, Khalil MZ, Shukla R, Brown JC, Carpenter LL. Synapses, predictions, and prediction errors: A neocortical computational study of MDD using the temporal memory algorithm of HTM. Front Psychiatry 2023; 14:976921. [PMID: 36911109 PMCID: PMC9995817 DOI: 10.3389/fpsyt.2023.976921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 01/16/2023] [Indexed: 02/25/2023] Open
Abstract
INTRODUCTION Synapses and spines play a significant role in major depressive disorder (MDD) pathophysiology, recently highlighted by the rapid antidepressant effect of ketamine and psilocybin. According to the Bayesian brain and interoception perspectives, MDD is formalized as being stuck in affective states constantly predicting negative energy balance. To understand how spines and synapses relate to the predictive function of the neocortex and thus to symptoms, we used the temporal memory (TM), an unsupervised machine-learning algorithm. TM models a single neocortical layer, learns in real-time, and extracts and predicts temporal sequences. TM exhibits neocortical biological features such as sparse firing and continuous online learning using local Hebbian-learning rules. METHODS We trained a TM model on random sequences of upper-case alphabetical letters, representing sequences of affective states. To model depression, we progressively destroyed synapses in the TM model and examined how that affected the predictive capacity of the network. We found that the number of predictions decreased non-linearly. RESULTS Destroying 50% of the synapses slightly reduced the number of predictions, followed by a marked drop with further destruction. However, reducing the synapses by 25% distinctly dropped the confidence in the predictions. Therefore, even though the network was making accurate predictions, the network was no longer confident about these predictions. DISCUSSION These findings explain how interoceptive cortices could be stuck in limited affective states with high prediction error. Connecting ketamine and psilocybin's proposed mechanism of action to depression pathophysiology, the growth of new synapses would allow representing more futuristic predictions with higher confidence. To our knowledge, this is the first study to use the TM model to connect changes happening at synaptic levels to the Bayesian formulation of psychiatric symptomatology. Linking neurobiological abnormalities to symptoms will allow us to understand the mechanisms of treatments and possibly, develop new ones.
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Affiliation(s)
- Mohamed A Sherif
- Lifespan Physician Group, Department of Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Carney Institute for Brain Science, Norman Prince Neurosciences Institute, Providence, RI, United States
| | - Mostafa Z Khalil
- Department of Psychiatry and Behavioral Health, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA, United States
| | - Rammohan Shukla
- Department of Neurosciences, The University of Toledo College of Medicine and Life Sciences, Toledo, OH, United States
| | - Joshua C Brown
- Department of Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Butler Hospital, Providence, RI, United States
| | - Linda L Carpenter
- Department of Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Butler Hospital, Providence, RI, United States
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Petanjek Z, Banovac I, Sedmak D, Hladnik A. Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits. ADVANCES IN NEUROBIOLOGY 2023; 34:143-221. [PMID: 37962796 DOI: 10.1007/978-3-031-36159-3_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.
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Affiliation(s)
- Zdravko Petanjek
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia.
| | - Ivan Banovac
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Dora Sedmak
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ana Hladnik
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
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Parkes L, Kim JZ, Stiso J, Calkins ME, Cieslak M, Gur RE, Gur RC, Moore TM, Ouellet M, Roalf DR, Shinohara RT, Wolf DH, Satterthwaite TD, Bassett DS. Asymmetric signaling across the hierarchy of cytoarchitecture within the human connectome. SCIENCE ADVANCES 2022; 8:eadd2185. [PMID: 36516263 PMCID: PMC9750154 DOI: 10.1126/sciadv.add2185] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 11/10/2022] [Indexed: 05/30/2023]
Abstract
Cortical variations in cytoarchitecture form a sensory-fugal axis that shapes regional profiles of extrinsic connectivity and is thought to guide signal propagation and integration across the cortical hierarchy. While neuroimaging work has shown that this axis constrains local properties of the human connectome, it remains unclear whether it also shapes the asymmetric signaling that arises from higher-order topology. Here, we used network control theory to examine the amount of energy required to propagate dynamics across the sensory-fugal axis. Our results revealed an asymmetry in this energy, indicating that bottom-up transitions were easier to complete compared to top-down. Supporting analyses demonstrated that asymmetries were underpinned by a connectome topology that is wired to support efficient bottom-up signaling. Lastly, we found that asymmetries correlated with differences in communicability and intrinsic neuronal time scales and lessened throughout youth. Our results show that cortical variation in cytoarchitecture may guide the formation of macroscopic connectome topology.
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Affiliation(s)
- Linden Parkes
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jason Z. Kim
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jennifer Stiso
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Monica E. Calkins
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Matthew Cieslak
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Radiology, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Radiology, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Tyler M. Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mathieu Ouellet
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R. Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Russell T. Shinohara
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel H. Wolf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, University of Pennsylvania and Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dani S. Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Santa Fe Institute, Santa Fe, NM 87501, USA
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Bayrak Ş, de Wael RV, Schaare HL, Hettwer MD, Caldairou B, Bernasconi A, Bernasconi N, Bernhardt BC, Valk SL. Heritability of hippocampal functional and microstructural organisation. Neuroimage 2022; 264:119656. [PMID: 36183945 DOI: 10.1016/j.neuroimage.2022.119656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 09/18/2022] [Accepted: 09/28/2022] [Indexed: 01/07/2023] Open
Abstract
The hippocampus is a uniquely infolded allocortical structure in the medial temporal lobe that consists of the microstructurally and functionally distinct subregions: subiculum, cornu ammonis, and dentate gyrus. The hippocampus is a remarkably plastic region that is implicated in learning and memory. At the same time it has been shown that hippocampal subregion volumes are heritable, and that genetic expression varies along a posterior to anterior axis. Here, we studied how a heritable, stable, hippocampal organisation may support its flexible function in healthy adults. Leveraging the twin set-up of the Human Connectome Project with multimodal neuroimaging, we observed that the functional connectivity between hippocampus and cortex was heritable and that microstructure of the hippocampus genetically correlated with cortical microstructure. Moreover, both functional and microstructural organisation could be consistently captured by anterior-to-posterior and medial-to-lateral axes across individuals. However, heritability of functional, relative to microstructural, organisation was found reduced, suggesting individual variation in functional organisation may be explained by experience-driven factors. Last, we demonstrate that structure and function couple along an inherited macroscale organisation, suggesting an interplay of stability and plasticity within the hippocampus. Our study provides new insights on the heritability of the hippocampal of the structure and function within the hippocampal organisation.
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Affiliation(s)
- Şeyma Bayrak
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, FZ Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Cognitive Neurology, University Hospital Leipzig and Faculty of Medicine, University of Leipzig, Leipzig, Germany.
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - H Lina Schaare
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, FZ Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Meike D Hettwer
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, FZ Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Max Planck School of Cognition, Max Planck Institute of Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Sofie L Valk
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, FZ Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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48
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Katsumi Y, Theriault JE, Quigley KS, Barrett LF. Allostasis as a core feature of hierarchical gradients in the human brain. Netw Neurosci 2022; 6:1010-1031. [PMID: 38800458 PMCID: PMC11117115 DOI: 10.1162/netn_a_00240] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/11/2022] [Indexed: 05/29/2024] Open
Abstract
This paper integrates emerging evidence from two broad streams of scientific literature into one common framework: (a) hierarchical gradients of functional connectivity that reflect the brain's large-scale structural architecture (e.g., a lamination gradient in the cerebral cortex); and (b) approaches to predictive processing and one of its specific instantiations called allostasis (i.e., the predictive regulation of energetic resources in the service of coordinating the body's internal systems). This synthesis begins to sketch a coherent, neurobiologically inspired framework suggesting that predictive energy regulation is at the core of human brain function, and by extension, psychological and behavioral phenomena, providing a shared vocabulary for theory building and knowledge accumulation.
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Affiliation(s)
- Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Karen S. Quigley
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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49
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Ma S, Skarica M, Li Q, Xu C, Risgaard RD, Tebbenkamp AT, Mato-Blanco X, Kovner R, Krsnik Ž, de Martin X, Luria V, Martí-Pérez X, Liang D, Karger A, Schmidt DK, Gomez-Sanchez Z, Qi C, Gobeske KT, Pochareddy S, Debnath A, Hottman CJ, Spurrier J, Teo L, Boghdadi AG, Homman-Ludiye J, Ely JJ, Daadi EW, Mi D, Daadi M, Marín O, Hof PR, Rasin MR, Bourne J, Sherwood CC, Santpere G, Girgenti MJ, Strittmatter SM, Sousa AM, Sestan N. Molecular and cellular evolution of the primate dorsolateral prefrontal cortex. Science 2022; 377:eabo7257. [PMID: 36007006 PMCID: PMC9614553 DOI: 10.1126/science.abo7257] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The granular dorsolateral prefrontal cortex (dlPFC) is an evolutionary specialization of primates that is centrally involved in cognition. We assessed more than 600,000 single-nucleus transcriptomes from adult human, chimpanzee, macaque, and marmoset dlPFC. Although most cell subtypes defined transcriptomically are conserved, we detected several that exist only in a subset of species as well as substantial species-specific molecular differences across homologous neuronal, glial, and non-neural subtypes. The latter are exemplified by human-specific switching between expression of the neuropeptide somatostatin and tyrosine hydroxylase, the rate-limiting enzyme in dopamine production in certain interneurons. The above molecular differences are also illustrated by expression of the neuropsychiatric risk gene FOXP2, which is human-specific in microglia and primate-specific in layer 4 granular neurons. We generated a comprehensive survey of the dlPFC cellular repertoire and its shared and divergent features in anthropoid primates.
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Affiliation(s)
- Shaojie Ma
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Mario Skarica
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Qian Li
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Chuan Xu
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Ryan D. Risgaard
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
- Medical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Xoel Mato-Blanco
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Rothem Kovner
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Željka Krsnik
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Xabier de Martin
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Xavier Martí-Pérez
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Dan Liang
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Amir Karger
- IT-Research Computing, Harvard Medical School, Boston, MA, USA
| | - Danielle K. Schmidt
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Zachary Gomez-Sanchez
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Cai Qi
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Kevin T. Gobeske
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Sirisha Pochareddy
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Ashwin Debnath
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Cade J. Hottman
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Joshua Spurrier
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Neurology, Yale School of Medicine, New Haven, CT 06536, USA
| | - Leon Teo
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Anthony G. Boghdadi
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Jihane Homman-Ludiye
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - John J. Ely
- MAEBIOS, Alamogordo, NM 88310, USA
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
| | - Etienne W. Daadi
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Da Mi
- Tsinghua-Peking Center for Life Sciences, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Marcel Daadi
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
- Department of Cell Systems & Anatomy, Radiology, Long School of Medicine, UT Health San Antonio
- NeoNeuron LLC, Palo Alto, CA 94306, USA
| | - Oscar Marín
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| | - Patrick R. Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mladen-Roko Rasin
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - James Bourne
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
| | - Gabriel Santpere
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Matthew J. Girgenti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT 06510, USA
- National Center for PTSD, US Department of Veterans Affairs, White River Junction, VT, USA
| | - Stephen M. Strittmatter
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Neurology, Yale School of Medicine, New Haven, CT 06536, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - André M.M. Sousa
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Departments of Genetics and Comparative Medicine, Program in Cellular Neuroscience, Neurodegeneration and Repair, and Yale Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
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50
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Barbas H, Zikopoulos B, John YJ. The inevitable inequality of cortical columns. Front Syst Neurosci 2022; 16:921468. [PMID: 36203745 PMCID: PMC9532056 DOI: 10.3389/fnsys.2022.921468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 09/01/2022] [Indexed: 11/13/2022] Open
Abstract
The idea of columns as an organizing cortical unit emerged from physiologic studies in the sensory systems. Connectional studies and molecular markers pointed to widespread presence of modular label that necessitated revision of the classical concept of columns. The general principle of cortical systematic variation in laminar structure is at the core of cortical organization. Systematic variation can be traced to the phylogenetically ancient limbic cortices, which have the simplest laminar structure, and continues through eulaminate cortices that show sequential elaboration of their six layers. Connections are governed by relational rules, whereby columns or modules with a vertical organization represent the feedforward mode of communication from earlier- to later processing cortices. Conversely, feedback connections are laminar-based and connect later- with earlier processing areas; both patterns are established in development. Based on studies in primates, the columnar/modular pattern of communication appears to be newer in evolution, while the broadly based laminar pattern represents an older system. The graded variation of cortices entails a rich variety of patterns of connections into modules, layers, and mixed arrangements as the laminar and modular patterns of communication intersect in the cortex. This framework suggests an ordered architecture poised to facilitate seamless recruitment of areas in behavior, in patterns that are affected in diseases of developmental origin.
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Affiliation(s)
- Helen Barbas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Graduate Program in Neuroscience, Boston University and School of Medicine, Boston, MA, United States
- *Correspondence: Helen Barbas,
| | - Basilis Zikopoulos
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Graduate Program in Neuroscience, Boston University and School of Medicine, Boston, MA, United States
- Human Systems Neuroscience Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
| | - Yohan J. John
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
- Graduate Program in Neuroscience, Boston University and School of Medicine, Boston, MA, United States
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