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      Long-range inputome of cortical neurons containing corticotropin-releasing hormone

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          Abstract

          Dissection of the neural circuits of the cerebral cortex is essential for studying mechanisms underlying brain function. Herein, combining a retrograde rabies tracing system with fluorescent micro-optical sectional tomography, we investigated long-range input neurons of corticotropin-releasing hormone containing neurons in the six main cortical areas, including the prefrontal, somatosensory, motor, auditory, and visual cortices. The whole brain distribution of input neurons showed similar patterns to input neurons distributed mainly in the adjacent cortical areas, thalamus, and basal forebrain. Reconstruction of continuous three-dimensional datasets showed the anterior and middle thalamus projected mainly to the rostral cortex whereas the posterior and lateral projected to the caudal cortex. In the basal forebrain, immunohistochemical staining showed these cortical areas received afferent information from cholinergic neurons in the substantia innominata and lateral globus pallidus, whereas cholinergic neurons in the diagonal band nucleus projected strongly to the prefrontal and visual cortex. Additionally, dense neurons in the zona incerta and ventral hippocampus were found to project to the prefrontal cortex. These results showed general patterns of cortical input circuits and unique connection patterns of each individual area, allowing for valuable comparisons among the organisation of different cortical areas and new insight into cortical functions.

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          A mesoscale connectome of the mouse brain.

          Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.
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            A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex.

            A key obstacle to understanding neural circuits in the cerebral cortex is that of unraveling the diversity of GABAergic interneurons. This diversity poses general questions for neural circuit analysis: how are these interneuron cell types generated and assembled into stereotyped local circuits and how do they differentially contribute to circuit operations that underlie cortical functions ranging from perception to cognition? Using genetic engineering in mice, we have generated and characterized approximately 20 Cre and inducible CreER knockin driver lines that reliably target major classes and lineages of GABAergic neurons. More select populations are captured by intersection of Cre and Flp drivers. Genetic targeting allows reliable identification, monitoring, and manipulation of cortical GABAergic neurons, thereby enabling a systematic and comprehensive analysis from cell fate specification, migration, and connectivity, to their functions in network dynamics and behavior. As such, this approach will accelerate the study of GABAergic circuits throughout the mammalian brain. Copyright © 2011 Elsevier Inc. All rights reserved.
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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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                Author and article information

                Contributors
                huigong@mail.hust.edu.cn
                lixiangning@mail.hust.edu.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                22 July 2020
                22 July 2020
                2020
                : 10
                : 12209
                Affiliations
                [1 ]ISNI 0000 0004 0368 7223, GRID grid.33199.31, Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, , Huazhong University of Science and Technology, ; Wuhan, 430074 China
                [2 ]HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, 215123 China
                [3 ]ISNI 0000000119573309, GRID grid.9227.e, CAS Center for Excellence in Brain Science and Intelligence Technology, , Chinese Academy of Science, ; Shanghai, 200031 China
                Article
                68115
                10.1038/s41598-020-68115-x
                7376058
                32699360
                b05ddd1e-9e8e-41c2-bdec-913329073c1e
                © The Author(s) 2020

                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
                : 10 March 2020
                : 12 June 2020
                Funding
                Funded by: NSFC projects
                Award ID: 61721092
                Award ID: 91749209
                Award ID: 61890953
                Award ID: 31871088
                Funded by: WNLO
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                neural circuits,cellular neuroscience
                Uncategorized
                neural circuits, cellular neuroscience

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