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      Organization of the inputs and outputs of the mouse superior colliculus

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          Abstract

          The superior colliculus (SC) receives diverse and robust cortical inputs to drive a range of cognitive and sensorimotor behaviors. However, it remains unclear how descending cortical input arising from higher-order associative areas coordinate with SC sensorimotor networks to influence its outputs. Here, we construct a comprehensive map of all cortico-tectal projections and identify four collicular zones with differential cortical inputs: medial (SC.m), centromedial (SC.cm), centrolateral (SC.cl) and lateral (SC.l). Further, we delineate the distinctive brain-wide input/output organization of each collicular zone, assemble multiple parallel cortico-tecto-thalamic subnetworks, and identify the somatotopic map in the SC that displays distinguishable spatial properties from the somatotopic maps in the neocortex and basal ganglia. Finally, we characterize interactions between those cortico-tecto-thalamic and cortico-basal ganglia-thalamic subnetworks. This study provides a structural basis for understanding how SC is involved in integrating different sensory modalities, translating sensory information to motor command, and coordinating different actions in goal-directed behaviors.

          Abstract

          The superior colliculus (SC) receives diverse cortical inputs to drive many behaviors. Here, based on comprehensive mapping of cortico-tectal projections, the authors refined the superior colliculus into medial, centromedial, centrolateral, and lateral zones, and characterized the input-output connectivity and morphology of neurons in each zone that serve the role of SC in goal-directed behaviors.

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          Most cited references97

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          Fast unfolding of communities in large networks

          Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008
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            Neural networks of the mouse neocortex.

            Numerous studies have examined the neuronal inputs and outputs of many areas within the mammalian cerebral cortex, but how these areas are organized into neural networks that communicate across the entire cortex is unclear. Over 600 labeled neuronal pathways acquired from tracer injections placed across the entire mouse neocortex enabled us to generate a cortical connectivity atlas. A total of 240 intracortical connections were manually reconstructed within a common neuroanatomic framework, forming a cortico-cortical connectivity map that facilitates comparison of connections from different cortical targets. Connectivity matrices were generated to provide an overview of all intracortical connections and subnetwork clusterings. The connectivity matrices and cortical map revealed that the entire cortex is organized into four somatic sensorimotor, two medial, and two lateral subnetworks that display unique topologies and can interact through select cortical areas. Together, these data provide a resource that can be used to further investigate cortical networks and their corresponding functions. Copyright © 2014 Elsevier Inc. All rights reserved.
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              AAV-Mediated Anterograde Transsynaptic Tagging: Mapping Corticocollicular Input-Defined Neural Pathways for Defense Behaviors.

              To decipher neural circuits underlying brain functions, viral tracers are widely applied to map input and output connectivity of neuronal populations. Despite the successful application of retrograde transsynaptic viruses for identifying presynaptic neurons of transduced neurons, analogous anterograde transsynaptic tools for tagging postsynaptically targeted neurons remain under development. Here, we discovered that adeno-associated viruses (AAV1 and AAV9) exhibit anterograde transsynaptic spread properties. AAV1-Cre from transduced presynaptic neurons effectively and specifically drives Cre-dependent transgene expression in selected postsynaptic neuronal targets, thus allowing axonal tracing and functional manipulations of the latter input-defined neuronal population. Its application in superior colliculus (SC) reveals that SC neuron subpopulations receiving corticocollicular projections from auditory and visual cortex specifically drive flight and freezing, two different types of defense behavior, respectively. Together with an intersectional approach, AAV-mediated anterograde transsynaptic tagging can categorize neurons by their inputs and molecular identity, and allow forward screening of distinct functional neural pathways embedded in complex brain circuits.
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                Author and article information

                Contributors
                hongweid@mednet.ucla.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                28 June 2021
                28 June 2021
                2021
                : 12
                : 4004
                Affiliations
                [1 ]GRID grid.42505.36, ISNI 0000 0001 2156 6853, Neuroscience Graduate Program, , University of Southern California, ; Los Angeles, CA USA
                [2 ]GRID grid.42505.36, ISNI 0000 0001 2156 6853, Stevens Neuroimaging and Informatics Institute, Laboratory of Neuro Imaging, Keck School of Medicine, , University of Southern California, ; Los Angeles, CA USA
                [3 ]GRID grid.116068.8, ISNI 0000 0001 2341 2786, McGovern Institute for Brain Research, , Massachusetts Institute of Technology, ; Cambridge, MA USA
                [4 ]GRID grid.22448.38, ISNI 0000 0004 1936 8032, Krasnow Institute for Advanced Study, , George Mason University, ; Fairfax, VA USA
                [5 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Present Address: UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, ; Los Angeles, CA USA
                Author information
                http://orcid.org/0000-0002-7754-0991
                http://orcid.org/0000-0002-8231-8893
                http://orcid.org/0000-0002-5516-8607
                http://orcid.org/0000-0001-9972-3177
                Article
                24241
                10.1038/s41467-021-24241-2
                8239028
                34183678
                cb2d82d4-131a-4cf5-88c6-5479905b8a2b
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 March 2021
                : 2 June 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000025, U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH);
                Award ID: MH094360
                Award ID: MH114829
                Award ID: MH114821
                Award ID: MH114821
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
                Funded by: FundRef https://doi.org/10.13039/100000054, U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI);
                Award ID: CA198932-01
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
                Funded by: NIH/NIMH
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                network models,neural circuits
                Uncategorized
                network models, neural circuits

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