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Swanson LW, Hahn JD, Sporns O. Neural network architecture of a mammalian brain. Proc Natl Acad Sci U S A 2024; 121:e2413422121. [PMID: 39288175 PMCID: PMC11441483 DOI: 10.1073/pnas.2413422121] [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: 07/04/2024] [Accepted: 08/14/2024] [Indexed: 09/19/2024] Open
Abstract
Connectomics research is making rapid advances, although models revealing general principles of connectional architecture are far from complete. Our analysis of 106 published connection reports indicates that the adult rat brain interregional connectome has about 76,940 of a possible 623,310 axonal connections between its 790 gray matter regions mapped in a reference atlas, equating to a network density of 12.3%. We examined the sexually dimorphic network using multiresolution consensus clustering that generated a nested hierarchy of interconnected modules/subsystems with three first-order modules and 157 terminal modules in females. Top-down hierarchy analysis suggests a mirror-image primary module pair in the central nervous system's rostral sector (forebrain-midbrain) associated with behavior control, and a single primary module in the intermediate sector (rhombicbrain) associated with behavior execution; the implications of these results are considered in relation to brain development and evolution. Bottom-up hierarchy analysis reveals known and unfamiliar modules suggesting strong experimentally testable hypotheses. Global network analyses indicate that all hubs are in the rostral module pair, a rich club extends through all three primary modules, and the network exhibits small-world attributes. Simulated lesions of all regions individually enabled ranking their impact on global network organization, and the visual path from the retina was used as a specific example, including the effects of cyclic connection weight changes from the endogenous circadian rhythm generator, suprachiasmatic nucleus. This study elucidates principles of interregional neuronal network architecture for a mammalian brain and suggests a strategy for modeling dynamic structural connectivity.
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Affiliation(s)
- Larry W Swanson
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089
| | - Joel D Hahn
- Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089
| | - Olaf Sporns
- Indiana University Network Science Institute, Indiana University, Bloomington, IN 47405
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405
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The brainstem connectome database. Sci Data 2022; 9:168. [PMID: 35414055 PMCID: PMC9005652 DOI: 10.1038/s41597-022-01219-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 02/25/2022] [Indexed: 11/29/2022] Open
Abstract
Connectivity data of the nervous system and subdivisions, such as the brainstem, cerebral cortex and subcortical nuclei, are necessary to understand connectional structures, predict effects of connectional disorders and simulate network dynamics. For that purpose, a database was built and analyzed which comprises all known directed and weighted connections within the rat brainstem. A longterm metastudy of original research publications describing tract tracing results form the foundation of the brainstem connectome (BC) database which can be analyzed directly in the framework neuroVIISAS. The BC database can be accessed directly by connectivity tables, a web-based tool and the framework. Analysis of global and local network properties, a motif analysis, and a community analysis of the brainstem connectome provides insight into its network organization. For example, we found that BC is a scale-free network with a small-world connectivity. The Louvain modularity and weighted stochastic block matching resulted in partially matching of functions and connectivity. BC modeling was performed to demonstrate signal propagation through the somatosensory pathway which is affected in Multiple sclerosis. Measurement(s) | brainstem | Technology Type(s) | tract tracing metastudy | Factor Type(s) | brain region | Sample Characteristic - Organism | Rattus rattus | Sample Characteristic - Environment | Experimental setup | Sample Characteristic - Location | Germany |
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Hahn JD, Swanson LW, Bowman I, Foster NN, Zingg B, Bienkowski MS, Hintiryan H, Dong HW. An open access mouse brain flatmap and upgraded rat and human brain flatmaps based on current reference atlases. J Comp Neurol 2020; 529:576-594. [PMID: 32511750 DOI: 10.1002/cne.24966] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 05/22/2020] [Accepted: 05/22/2020] [Indexed: 12/11/2022]
Abstract
Here we present a flatmap of the mouse central nervous system (CNS) (brain) and substantially enhanced flatmaps of the rat and human brain. Also included are enhanced representations of nervous system white matter tracts, ganglia, and nerves, and an enhanced series of 10 flatmaps showing different stages of rat brain development. The adult mouse and rat brain flatmaps provide layered diagrammatic representation of CNS divisions, according to their arrangement in corresponding reference atlases: Brain Maps 4.0 (BM4, rat) (Swanson, The Journal of Comparative Neurology, 2018, 526, 935-943), and the first version of the Allen Reference Atlas (mouse) (Dong, The Allen reference atlas, (book + CD-ROM): A digital color brain atlas of the C57BL/6J male mouse, 2007). To facilitate comparative analysis, both flatmaps are scaled equally, and the divisional hierarchy of gray matter follows a topographic arrangement used in BM4. Also included with the mouse and rat brain flatmaps are cerebral cortex atlas level contours based on the reference atlases, and direct graphical and tabular comparison of regional parcellation. To encourage use of the brain flatmaps, they were designed and organized, with supporting reference tables, for ease-of-use and to be amenable to computational applications. We demonstrate how they can be adapted to represent novel parcellations resulting from experimental data, and we provide a proof-of-concept for how they could form the basis of a web-based graphical data viewer and analysis platform. The mouse, rat, and human brain flatmap vector graphics files (Adobe Reader/Acrobat viewable and Adobe Illustrator editable) and supporting tables are provided open access; they constitute a broadly applicable neuroscience toolbox resource for researchers seeking to map and perform comparative analysis of brain data.
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Affiliation(s)
- Joel D Hahn
- Department of Biological Sciences, University of Southern California, California, Los Angeles, USA.,Center for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA
| | - Larry W Swanson
- Department of Biological Sciences, University of Southern California, California, Los Angeles, USA
| | - Ian Bowman
- Center for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA
| | - Nicholas N Foster
- Center for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA
| | - Brian Zingg
- Center for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA
| | - Michael S Bienkowski
- Center for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA
| | - Houri Hintiryan
- Center for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA
| | - Hong-Wei Dong
- Center for Integrated Connectomics (CIC), Keck School of Medicine of University of Southern California, University of Southern California Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA.,Department of Neurology, Keck School of Medicine of University of Southern California, Los Angeles, California, USA.,Department of Physiology and Neuroscience, and Zilkha Neurogenetic Institute, Keck School of Medicine of University of Southern California, Los Angeles, California, USA
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Swanson LW. Brain maps 4.0-Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps. J Comp Neurol 2018; 526:935-943. [PMID: 29277900 PMCID: PMC5851017 DOI: 10.1002/cne.24381] [Citation(s) in RCA: 175] [Impact Index Per Article: 29.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 12/13/2017] [Accepted: 12/14/2017] [Indexed: 12/11/2022]
Abstract
The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature tables that define and describe all parts of the rat nervous system within the framework of a strictly topographic system devised previously for the human nervous system. These tables constitute a global ontology for knowledge management systems dealing with neural circuitry. A second new feature is an aligned atlas of bilateral flatmaps illustrating rat nervous system development from the neural plate stage to the adult stage, where most gray matter regions, white matter tracts, ganglia, and nerves listed in the nomenclature tables are illustrated schematically. These flatmaps are convenient for future development of online applications analogous to "Google Maps" for systems neuroscience. The third new feature is a completely revised Atlas of the rat brain in spatially aligned transverse sections that can serve as a framework for 3-D modeling. Atlas parcellation is little changed from the preceding edition, but the nomenclature for rat is now aligned with an emerging panmammalian neuroanatomical nomenclature. All figures are presented in Adobe Illustrator vector graphics format that can be manipulated, modified, and resized as desired, and freely used with a Creative Commons license.
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Affiliation(s)
- Larry W. Swanson
- Department of Biological SciencesUniversity of Southern CaliforniaLos AngelesCalifornia
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Wiwanitkit S, Joob B, Wiwanitkit V. Cerebral malaria: An interactive brain mapping study. ASIAN PAC J TROP MED 2016; 9:823. [PMID: 27569898 DOI: 10.1016/j.apjtm.2016.06.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2016] [Revised: 06/16/2016] [Accepted: 06/21/2016] [Indexed: 11/24/2022] Open
Affiliation(s)
| | - Beuy Joob
- Sanitationl Medical Academic Center, Bangkok, Thailand
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Affiliation(s)
- Larry W. Swanson
- Department of Biological Sciences, University of Southern California, Los Angeles, California 90089;
| | - Jeff W. Lichtman
- Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, Massachusetts 02138;
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