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Yamakawa H, Fukawa A, Yairi IE, Matsuo Y. Brain-consistent architecture for imagination. Front Syst Neurosci 2024; 18:1302429. [PMID: 39229305 PMCID: PMC11368743 DOI: 10.3389/fnsys.2024.1302429] [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: 09/26/2023] [Accepted: 07/29/2024] [Indexed: 09/05/2024] Open
Abstract
Background Imagination represents a pivotal capability of human intelligence. To develop human-like artificial intelligence, uncovering the computational architecture pertinent to imaginative capabilities through reverse engineering the brain's computational functions is essential. The existing Structure-Constrained Interface Decomposition (SCID) method, leverages the anatomical structure of the brain to extract computational architecture. However, its efficacy is limited to narrow brain regions, making it unsuitable for realizing the function of imagination, which involves diverse brain areas such as the neocortex, basal ganglia, thalamus, and hippocampus. Objective In this study, we proposed the Function-Oriented SCID method, an advancement over the existing SCID method, comprising four steps designed for reverse engineering broader brain areas. This method was applied to the brain's imaginative capabilities to design a hypothetical computational architecture. The implementation began with defining the human imaginative ability that we aspire to simulate. Subsequently, six critical requirements necessary for actualizing the defined imagination were identified. Constraints were established considering the unique representational capacity and the singularity of the neocortex's modes, a distributed memory structure responsible for executing imaginative functions. In line with these constraints, we developed five distinct functions to fulfill the requirements. We allocated specific components for each function, followed by an architectural proposal aligning each component with a corresponding brain organ. Results In the proposed architecture, the distributed memory component, associated with the neocortex, realizes the representation and execution function; the imaginary zone maker component, associated with the claustrum, accomplishes the dynamic-zone partitioning function; the routing conductor component, linked with the complex of thalamus and basal ganglia, performs the manipulation function; the mode memory component, related to the specific agranular neocortical area executes the mode maintenance function; and the recorder component, affiliated with the hippocampal formation, handles the history management function. Thus, we have provided a fundamental cognitive architecture of the brain that comprehensively covers the brain's imaginative capacities.
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Affiliation(s)
- Hiroshi Yamakawa
- School of Engineering, The University of Tokyo, Tokyo, Japan
- The Whole Brain Architecture Initiative, Tokyo, Japan
| | - Ayako Fukawa
- The Whole Brain Architecture Initiative, Tokyo, Japan
- Graduate School of Science and Technology, Sophia University, Tokyo, Japan
| | - Ikuko Eguchi Yairi
- Graduate School of Science and Technology, Sophia University, Tokyo, Japan
| | - Yutaka Matsuo
- School of Engineering, The University of Tokyo, Tokyo, Japan
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2
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Fotiadis P, Cieslak M, He X, Caciagli L, Ouellet M, Satterthwaite TD, Shinohara RT, Bassett DS. Myelination and excitation-inhibition balance synergistically shape structure-function coupling across the human cortex. Nat Commun 2023; 14:6115. [PMID: 37777569 PMCID: PMC10542365 DOI: 10.1038/s41467-023-41686-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 09/08/2023] [Indexed: 10/02/2023] Open
Abstract
Recent work has demonstrated that the relationship between structural and functional connectivity varies regionally across the human brain, with reduced coupling emerging along the sensory-association cortical hierarchy. The biological underpinnings driving this expression, however, remain largely unknown. Here, we postulate that intracortical myelination and excitation-inhibition (EI) balance mediate the heterogeneous expression of structure-function coupling (SFC) and its temporal variance across the cortical hierarchy. We employ atlas- and voxel-based connectivity approaches to analyze neuroimaging data acquired from two groups of healthy participants. Our findings are consistent across six complementary processing pipelines: 1) SFC and its temporal variance respectively decrease and increase across the unimodal-transmodal and granular-agranular gradients; 2) increased myelination and lower EI-ratio are associated with more rigid SFC and restricted moment-to-moment SFC fluctuations; 3) a gradual shift from EI-ratio to myelination as the principal predictor of SFC occurs when traversing from granular to agranular cortical regions. Collectively, our work delivers a framework to conceptualize structure-function relationships in the human brain, paving the way for an improved understanding of how demyelination and/or EI-imbalances induce reorganization in brain disorders.
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Affiliation(s)
- Panagiotis Fotiadis
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Matthew Cieslak
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Xiaosong He
- Department of Psychology, University of Science and Technology of China, Hefei, Anhui, 230026, China
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mathieu Ouellet
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Center for Biomedical Image Computing & Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Santa Fe Institute, Santa Fe, NM, 87501, USA.
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3
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Shine JM, Lewis LD, Garrett DD, Hwang K. The impact of the human thalamus on brain-wide information processing. Nat Rev Neurosci 2023; 24:416-430. [PMID: 37237103 DOI: 10.1038/s41583-023-00701-0] [Citation(s) in RCA: 43] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/30/2023] [Indexed: 05/28/2023]
Abstract
The thalamus is a small, bilateral structure in the diencephalon that integrates signals from many areas of the CNS. This critical anatomical position allows the thalamus to influence whole-brain activity and adaptive behaviour. However, traditional research paradigms have struggled to attribute specific functions to the thalamus, and it has remained understudied in the human neuroimaging literature. Recent advances in analytical techniques and increased accessibility to large, high-quality data sets have brought forth a series of studies and findings that (re-)establish the thalamus as a core region of interest in human cognitive neuroscience, a field that otherwise remains cortico-centric. In this Perspective, we argue that using whole-brain neuroimaging approaches to investigate the thalamus and its interaction with the rest of the brain is key for understanding systems-level control of information processing. To this end, we highlight the role of the thalamus in shaping a range of functional signatures, including evoked activity, interregional connectivity, network topology and neuronal variability, both at rest and during the performance of cognitive tasks.
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Affiliation(s)
- James M Shine
- Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Laura D Lewis
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Douglas D Garrett
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Kai Hwang
- Cognitive Control Collaborative, Department of Psychological and Brain Sciences, The University of Iowa, Iowa City, IA, USA.
- Department of Psychiatry, The University of Iowa, Iowa City, IA, USA.
- Iowa Neuroscience Institute, The University of Iowa, Iowa City, IA, USA.
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4
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Shamir I, Assaf Y. Expanding connectomics to the laminar level: A perspective. Netw Neurosci 2023; 7:377-388. [PMID: 37397881 PMCID: PMC10312257 DOI: 10.1162/netn_a_00304] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 12/15/2022] [Indexed: 11/10/2023] Open
Abstract
Despite great progress in uncovering the complex connectivity patterns of the human brain over the last two decades, the field of connectomics still experiences a bias in its viewpoint of the cerebral cortex. Due to a lack of information regarding exact end points of fiber tracts inside cortical gray matter, the cortex is commonly reduced to a single homogenous unit. Concurrently, substantial developments have been made over the past decade in the use of relaxometry and particularly inversion recovery imaging for exploring the laminar microstructure of cortical gray matter. In recent years, these developments have culminated in an automated framework for cortical laminar composition analysis and visualization, followed by studies of cortical dyslamination in epilepsy patients and age-related differences in laminar composition in healthy subjects. This perspective summarizes the developments and remaining challenges of multi-T1 weighted imaging of cortical laminar substructure, the current limitations in structural connectomics, and the recent progress in integrating these fields into a new model-based subfield termed 'laminar connectomics'. In the coming years, we predict an increased use of similar generalizable, data-driven models in connectomics with the purpose of integrating multimodal MRI datasets and providing a more nuanced and detailed characterization of brain connectivity.
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Affiliation(s)
- Ittai Shamir
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yaniv Assaf
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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5
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Shamir I, Tomer O, Krupnik R, Assaf Y. Modelling the laminar connectome of the human brain. Brain Struct Funct 2022; 227:2153-2165. [DOI: 10.1007/s00429-022-02513-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/22/2022] [Indexed: 12/20/2022]
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6
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Homologous organization of cerebellar pathways to sensory, motor, and associative forebrain. Cell Rep 2021; 36:109721. [PMID: 34551311 PMCID: PMC8506234 DOI: 10.1016/j.celrep.2021.109721] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 06/06/2021] [Accepted: 08/25/2021] [Indexed: 12/31/2022] Open
Abstract
Cerebellar outputs take polysynaptic routes to reach the rest of the brain, impeding conventional tracing. Here, we quantify pathways between the cerebellum and forebrain by using transsynaptic tracing viruses and a whole-brain analysis pipeline. With retrograde tracing, we find that most descending paths originate from the somatomotor cortex. Anterograde tracing of ascending paths encompasses most thalamic nuclei, especially ventral posteromedial, lateral posterior, mediodorsal, and reticular nuclei. In the neocortex, sensorimotor regions contain the most labeled neurons, but we find higher densities in associative areas, including orbital, anterior cingulate, prelimbic, and infralimbic cortex. Patterns of ascending expression correlate with c-Fos expression after optogenetic inhibition of Purkinje cells. Our results reveal homologous networks linking single areas of the cerebellar cortex to diverse forebrain targets. We conclude that shared areas of the cerebellum are positioned to provide sensory-motor information to regions implicated in both movement and nonmotor function. Pisano et al. use transsynaptic tracing and whole-brain light-sheet microscopy to quantitatively map cerebellar paths to and from the forebrain, including relatively dense projections to the prefrontal neocortex. Divergence of paths from single injection sites suggests that a single cerebellar region can influence multiple thalamic and neocortical targets at once.
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7
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Zhao K, Zheng Q, Che T, Dyrba M, Li Q, Ding Y, Zheng Y, Liu Y, Li S. Regional radiomics similarity networks (R2SNs) in the human brain: Reproducibility, small-world properties and a biological basis. Netw Neurosci 2021; 5:783-797. [PMID: 34746627 PMCID: PMC8567836 DOI: 10.1162/netn_a_00200] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 05/08/2021] [Indexed: 12/13/2022] Open
Abstract
A structural covariance network (SCN) has been used successfully in structural magnetic resonance imaging (sMRI) studies. However, most SCNs have been constructed by a unitary marker that is insensitive for discriminating different disease phases. The aim of this study was to devise a novel regional radiomics similarity network (R2SN) that could provide more comprehensive information in morphological network analysis. R2SNs were constructed by computing the Pearson correlations between the radiomics features extracted from any pair of regions for each subject (AAL atlas). We further assessed the small-world property of R2SNs, and we evaluated the reproducibility in different datasets and through test-retest analysis. The relationships between the R2SNs and general intelligence/interregional coexpression of genes were also explored. R2SNs could be replicated in different datasets, regardless of the use of different feature subsets. R2SNs showed high reproducibility in the test-retest analysis (intraclass correlation coefficient > 0.7). In addition, the small-word property (σ > 2) and the high correlation between gene expression (R = 0.29, p < 0.001) and general intelligence were determined for R2SNs. Furthermore, the results have also been repeated in the Brainnetome atlas. R2SNs provide a novel, reliable, and biologically plausible method to understand human morphological covariance based on sMRI.
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Affiliation(s)
- Kun Zhao
- School of Biological Science & Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Qiang Zheng
- School of Computer and Control Engineering, Yantai University, Yantai, China
| | - Tongtong Che
- School of Biological Science & Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Qiongling Li
- School of Biological Science & Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Yanhui Ding
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Yuanjie Zheng
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Shuyu Li
- School of Biological Science & Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
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8
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Yamakawa H. Revealing the Computational Meaning of Neocortical Interarea Signals. Front Comput Neurosci 2020; 14:74. [PMID: 33013340 PMCID: PMC7461790 DOI: 10.3389/fncom.2020.00074] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 07/13/2020] [Indexed: 11/13/2022] Open
Abstract
To understand the function of the neocortex, which is a hierarchical distributed network, it is useful giving meaning to the signals transmitted between these areas from the computational viewpoint. The overall anatomical structure or organs related to this network, including the neocortex, thalamus, and basal ganglia, has been roughly revealed, and much physiological knowledge, though often fragmentary, is being accumulated. The computational theories involving the neocortex have also been developed considerably. By introducing the assumption “The signals transmitted by interarea axonal projections of pyramidal cells in the neocortex carry different meanings for each cell type, common to all areas,” derived from its nature as a distributed network in the neocortex, allows us to specify the computational meanings of interarea signals. In this paper, first, the types of signals exchanged between neocortical areas are investigated, taking into account biological constraints, and employing theories such as predictive coding, reinforcement learning, representation emulation theory, and BDI logic as theoretical starting points, two types of feedforward signals (observation and deviation) and three types of feedback signals (prediction, plan, and intention) are identified. Next, based on the anatomical knowledge of the neocortex and thalamus, the pathways connecting the areas are organized and summarized as three corticocortical pathways and two thalamocortical pathways. Using this summation as preparation, this paper proposes a hypothesis that gives meaning to each type of signals transmitted in the different pathways in the neocortex, from the viewpoint of their functions. This hypothesis reckons that the feedforward corticocortical pathway transmits observation signals, the feedback corticocortical pathway transmits prediction signals, and the corticothalamic pathway mediated by core relay cells transmits deviation signals. The thalamocortical pathway, which is mediated by matrix relay cells, would be responsible for transmitting the signals that activate a part of prediction signals as intentions, due to the reason that the nature of the other available feedback pathways are not sufficient for conveying plans and intentions as signals. The corticocortical pathway, which is projected from various IT cells to the first layer, would be responsible for transmitting signals that activate a part of prediction signals as plans.
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Affiliation(s)
- Hiroshi Yamakawa
- University of Tokyo, Tokyo, Japan.,The Whole Brain Architecture Initiative, Edogawa-ku, Japan
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9
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Shamir I, Assaf Y. An MRI-Based, Data-Driven Model of Cortical Laminar Connectivity. Neuroinformatics 2020; 19:205-218. [PMID: 32949346 DOI: 10.1007/s12021-020-09491-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/07/2020] [Indexed: 01/19/2023]
Abstract
Over the past two centuries, great scientific efforts have been spent on deciphering the structure and function of the cerebral cortex using a wide variety of methods. Since the advent of MRI neuroimaging, significant progress has been made in imaging of global white matter connectivity (connectomics), followed by promising new studies regarding imaging of grey matter laminar compartments. Despite progress in both fields, there still lacks mesoscale information regarding cortical laminar connectivity that could potentially bridge the gap between the current resolution of connectomics and the relatively higher resolution of cortical laminar imaging. Here, we systematically review a sample of prominent published articles regarding cortical laminar connectivity, in order to offer a simplified data-driven model that integrates white and grey matter MRI datasets into a novel way of exploring whole-brain tissue-level connectivity. Although it has been widely accepted that the cortex is exceptionally organized and interconnected, studies on the subject display a variety of approaches towards its structural building blocks. Our model addresses three principal cortical building blocks: cortical layer definitions (laminar grouping), vertical connections (intraregional, within the cortical microcircuit and subcortex) and horizontal connections (interregional, including connections within and between the hemispheres). While cortical partitioning into layers is more widely accepted as common knowledge, certain aspects of others such as cortical columns or microcircuits are still being debated. This study offers a broad and simplified view of histological and microscopical knowledge in laminar research that is applicable to the limitations of MRI methodologies, primarily regarding specificity and resolution.
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Affiliation(s)
- Ittai Shamir
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
| | - Yaniv Assaf
- Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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10
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Grydeland H, Vértes PE, Váša F, Romero-Garcia R, Whitaker K, Alexander-Bloch AF, Bjørnerud A, Patel AX, Sederevicius D, Tamnes CK, Westlye LT, White SR, Walhovd KB, Fjell AM, Bullmore ET. Waves of Maturation and Senescence in Micro-structural MRI Markers of Human Cortical Myelination over the Lifespan. Cereb Cortex 2020; 29:1369-1381. [PMID: 30590439 PMCID: PMC6373687 DOI: 10.1093/cercor/bhy330] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 11/30/2018] [Indexed: 11/13/2022] Open
Abstract
Seminal human brain histology work has demonstrated developmental waves of myelination. Here, using a micro-structural magnetic resonance imaging (MRI) marker linked to myelin, we studied fine-grained age differences to deduce waves of growth, stability, and decline of cortical myelination over the life-cycle. In 484 participants, aged 8–85 years, we fitted smooth growth curves to T1- to T2-weighted ratio in each of 360 regions from one of seven cytoarchitectonic classes. From the first derivatives of these generally inverted-U trajectories, we defined three milestones: the age at peak growth; the age at onset of a stable plateau; and the age at the onset of decline. Age at peak growth had a bimodal distribution comprising an early (pre-pubertal) wave of primary sensory and motor cortices and a later (post-pubertal) wave of association, insular and limbic cortices. Most regions reached stability in the 30-s but there was a second wave reaching stability in the 50-s. Age at onset of decline was also bimodal: in some right hemisphere regions, the curve declined from the 60-s, but in other left hemisphere regions, there was no significant decline from the stable plateau. These results are consistent with regionally heterogeneous waves of intracortical myelinogenesis and age-related demyelination.
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Affiliation(s)
- Håkon Grydeland
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Petra E Vértes
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - František Váša
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Rafael Romero-Garcia
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Kirstie Whitaker
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.,The Alan Turing Institute, British Library, London, UK
| | | | - Atle Bjørnerud
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway.,Department of Radiology and Nuclear Medicine, University of Oslo, Oslo, Norway
| | - Ameera X Patel
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Donatas Sederevicius
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Christian K Tamnes
- Department of Psychology, University of Oslo, Oslo, Norway.,Department of Psychiatry, Diakonhjemmet Hospital, Oslo, Norway
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Simon R White
- MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge University, Cambridge, UK
| | - Kristine B Walhovd
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway.,Department of Radiology and Nuclear Medicine, University of Oslo, Oslo, Norway
| | - Anders M Fjell
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway.,Department of Radiology and Nuclear Medicine, University of Oslo, Oslo, Norway
| | - Edward T Bullmore
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.,Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, UK.,Immuno-Inflammation Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage, UK
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11
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Hilgetag CC, Beul SF, van Albada SJ, Goulas A. An architectonic type principle integrates macroscopic cortico-cortical connections with intrinsic cortical circuits of the primate brain. Netw Neurosci 2019; 3:905-923. [PMID: 31637331 PMCID: PMC6777964 DOI: 10.1162/netn_a_00100] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 06/07/2019] [Indexed: 12/31/2022] Open
Abstract
The connections linking neurons within and between cerebral cortical areas form a multiscale network for communication. We review recent work relating essential features of cortico-cortical connections, such as their existence and laminar origins and terminations, to fundamental structural parameters of cortical areas, such as their distance, similarity in cytoarchitecture, defined by lamination or neuronal density, and other macroscopic and microscopic structural features. These analyses demonstrate the presence of an architectonic type principle. Across species and cortices, the essential features of cortico-cortical connections vary consistently and strongly with the cytoarchitectonic similarity of cortical areas. By contrast, in multivariate analyses such relations were not found consistently for distance, similarity of cortical thickness, or cellular morphology. Gradients of laminar cortical differentiation, as reflected in overall neuronal density, also correspond to regional variations of cellular features, forming a spatially ordered natural axis of concerted architectonic and connectional changes across the cortical sheet. The robustness of findings across mammalian brains allows cross-species predictions of the existence and laminar patterns of projections, including estimates for the human brain that are not yet available experimentally. The architectonic type principle integrates cortical connectivity and architecture across scales, with implications for computational explorations of cortical physiology and developmental mechanisms.
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Affiliation(s)
- Claus C Hilgetag
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Germany
| | - Sarah F Beul
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Germany
| | - Sacha J van Albada
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), and JARA-Institute of Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Germany
| | - Alexandros Goulas
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Germany
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12
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Boskovic Z, Meier S, Wang Y, Milne M, Onraet T, Tedoldi A, Coulson E. Regulation of cholinergic basal forebrain development, connectivity, and function by neurotrophin receptors. Neuronal Signal 2019; 3:NS20180066. [PMID: 32269831 PMCID: PMC7104233 DOI: 10.1042/ns20180066] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 01/15/2019] [Accepted: 01/15/2019] [Indexed: 12/11/2022] Open
Abstract
Cholinergic basal forebrain (cBF) neurons are defined by their expression of the p75 neurotrophin receptor (p75NTR) and tropomyosin-related kinase (Trk) neurotrophin receptors in addition to cholinergic markers. It is known that the neurotrophins, particularly nerve growth factor (NGF), mediate cholinergic neuronal development and maintenance. However, the role of neurotrophin signalling in regulating adult cBF function is less clear, although in dementia, trophic signalling is reduced and p75NTR mediates neurodegeneration of cBF neurons. Here we review the current understanding of how cBF neurons are regulated by neurotrophins which activate p75NTR and TrkA, B or C to influence the critical role that these neurons play in normal cortical function, particularly higher order cognition. Specifically, we describe the current evidence that neurotrophins regulate the development of basal forebrain neurons and their role in maintaining and modifying mature basal forebrain synaptic and cortical microcircuit connectivity. Understanding the role neurotrophin signalling plays in regulating the precision of cholinergic connectivity will contribute to the understanding of normal cognitive processes and will likely provide additional ideas for designing improved therapies for the treatment of neurological disease in which cholinergic dysfunction has been demonstrated.
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Affiliation(s)
- Zoran Boskovic
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- Clem Jones Centre for Ageing Dementia Research, The University of Queensland, Brisbane, Queensland, Australia
| | - Sonja Meier
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- Clem Jones Centre for Ageing Dementia Research, The University of Queensland, Brisbane, Queensland, Australia
| | - Yunpeng Wang
- Faculty of Medicine, School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, Australia
- College of Forensic Science, Xi’an Jiaotong University, Shaanxi, China
| | - Michael R. Milne
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- Clem Jones Centre for Ageing Dementia Research, The University of Queensland, Brisbane, Queensland, Australia
- Faculty of Medicine, School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, Australia
| | - Tessa Onraet
- Clem Jones Centre for Ageing Dementia Research, The University of Queensland, Brisbane, Queensland, Australia
| | - Angelo Tedoldi
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Elizabeth J. Coulson
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- Clem Jones Centre for Ageing Dementia Research, The University of Queensland, Brisbane, Queensland, Australia
- Faculty of Medicine, School of Biomedical Sciences, The University of Queensland, Brisbane, Queensland, Australia
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Seidlitz J, Váša F, Shinn M, Romero-Garcia R, Whitaker KJ, Vértes PE, Wagstyl K, Kirkpatrick Reardon P, Clasen L, Liu S, Messinger A, Leopold DA, Fonagy P, Dolan RJ, Jones PB, Goodyer IM, Raznahan A, Bullmore ET. Morphometric Similarity Networks Detect Microscale Cortical Organization and Predict Inter-Individual Cognitive Variation. Neuron 2017; 97:231-247.e7. [PMID: 29276055 DOI: 10.1016/j.neuron.2017.11.039] [Citation(s) in RCA: 239] [Impact Index Per Article: 34.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 10/05/2017] [Accepted: 11/22/2017] [Indexed: 12/22/2022]
Abstract
Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organization comprising modules and high-degree hubs. Human MSN modules recapitulate known cortical cytoarchitectonic divisions, and greater inter-regional morphometric similarity was associated with stronger inter-regional co-expression of genes enriched for neuronal terms. Comparing macaque MSNs with tract-tracing data confirmed that morphometric similarity was related to axonal connectivity. Finally, variation in the degree of human MSN nodes accounted for about 40% of between-subject variability in IQ. Morphometric similarity mapping provides a novel, robust, and biologically plausible approach to understanding how human cortical networks underpin individual differences in psychological functions.
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Affiliation(s)
- Jakob Seidlitz
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA.
| | - František Váša
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK
| | - Maxwell Shinn
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK
| | | | - Kirstie J Whitaker
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK
| | - Petra E Vértes
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK
| | - Konrad Wagstyl
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK
| | | | - Liv Clasen
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Siyuan Liu
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - David A Leopold
- Laboratory of Neuropsychology, National Institute of Mental Health, Bethesda, MD 20892, USA; Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA
| | - Peter Fonagy
- Research Department of Clinical, Educational and Health Psychology, University College London, London WC1E 6BT, UK
| | - Raymond J Dolan
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London WC1N 3BG, UK; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK
| | - Peter B Jones
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK
| | - Ian M Goodyer
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK
| | | | - Armin Raznahan
- Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Edward T Bullmore
- University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK; ImmunoPsychiatry, Immuno-Inflammation Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage SG1 2NY, UK
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14
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Marblestone AH, Wayne G, Kording KP. Toward an Integration of Deep Learning and Neuroscience. Front Comput Neurosci 2016; 10:94. [PMID: 27683554 PMCID: PMC5021692 DOI: 10.3389/fncom.2016.00094] [Citation(s) in RCA: 243] [Impact Index Per Article: 30.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2016] [Accepted: 08/24/2016] [Indexed: 01/22/2023] Open
Abstract
Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend to eschew precisely designed codes, dynamics or circuits in favor of brute force optimization of a cost function, often using simple and relatively uniform initial architectures. Two recent developments have emerged within machine learning that create an opportunity to connect these seemingly divergent perspectives. First, structured architectures are used, including dedicated systems for attention, recursion and various forms of short- and long-term memory storage. Second, cost functions and training procedures have become more complex and are varied across layers and over time. Here we think about the brain in terms of these ideas. We hypothesize that (1) the brain optimizes cost functions, (2) the cost functions are diverse and differ across brain locations and over development, and (3) optimization operates within a pre-structured architecture matched to the computational problems posed by behavior. In support of these hypotheses, we argue that a range of implementations of credit assignment through multiple layers of neurons are compatible with our current knowledge of neural circuitry, and that the brain's specialized systems can be interpreted as enabling efficient optimization for specific problem classes. Such a heterogeneously optimized system, enabled by a series of interacting cost functions, serves to make learning data-efficient and precisely targeted to the needs of the organism. We suggest directions by which neuroscience could seek to refine and test these hypotheses.
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Affiliation(s)
- Adam H. Marblestone
- Synthetic Neurobiology Group, Massachusetts Institute of Technology, Media LabCambridge, MA, USA
| | | | - Konrad P. Kording
- Rehabilitation Institute of Chicago, Northwestern UniversityChicago, IL, USA
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Stoos C, Nelsen L, Schissler KA, Elliott AJ, Kinney HC. Fetal alcohol syndrome and secondary schizophrenia: a unique neuropathologic study. J Child Neurol 2015; 30:601-5. [PMID: 24563476 PMCID: PMC8312346 DOI: 10.1177/0883073814520976] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We report the unique neuropathologic study of an adult brain of a patient with fetal alcohol syndrome who developed the well-recognized complication of schizophrenia in adolescence. The major finding was asymmetric formation of the lateral temporal lobes, with marked enlargement of the right superior temporal gyrus, suggesting that alcohol is preferentially toxic to temporal lobe patterning during gestation. Critical maturational changes unique to adolescence can unmask psychotic symptomatology mediated by temporal lobe pathology that has been clinically dormant since birth. Elucidating the neuropathologic basis of the secondary psychiatric disorders in fetal alcohol syndrome can help provide insight into their putative developmental origins.
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Affiliation(s)
- Catherine Stoos
- Department of Pathology, Sanford Health, Sioux Falls, SD, USA
| | - Laura Nelsen
- Department of Pathology, MaineGeneral Health, Augusta, MA, USA
| | - Kathryn A Schissler
- Department of Pathology, Boston Children's Hospital and Harvard Medical School, MA, USA
| | - Amy J Elliott
- Department of Pathology, Boston Children's Hospital and Harvard Medical School, MA, USA
| | - Hannah C Kinney
- Department of Pathology, Boston Children's Hospital and Harvard Medical School, MA, USA
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16
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Budd J, Kisvarday Z. How do you wire a brain? Front Neuroanat 2013; 7:14. [PMID: 23754989 PMCID: PMC3664766 DOI: 10.3389/fnana.2013.00014] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2013] [Accepted: 05/08/2013] [Indexed: 11/13/2022] Open
Affiliation(s)
- Julian Budd
- Department of Informatics, University of Sussex Brighton, UK
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