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      Brain-wide functional architecture remodeling by alcohol dependence and abstinence

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          Significance

          Visualizing functional changes in brain networks that are produced by alcohol use and alcohol dependence is a critical step in our understanding of the consequences of drinking alcohol. Because of technical limitations, visualizing changes throughout the whole brain at single-cell resolution has not been possible. The present study used a single-cell whole-brain imaging approach in mice to assess whether alcohol abstinence alters functional architecture of the brain. Compared with nondrinkers and casual drinkers, alcohol-dependent mice exhibited widespread increases in coordinated brain activity during abstinence and a decrease in modularity. We also identified target brain regions for future research and provide a single-cell whole-brain atlas that may be used to better understand the consequences of alcohol use, dependence, and abstinence.

          Abstract

          Alcohol abuse and alcohol dependence are key factors in the development of alcohol use disorder, which is a pervasive societal problem with substantial economic, medical, and psychiatric consequences. Although our understanding of the neurocircuitry that underlies alcohol use has improved, novel brain regions that are involved in alcohol use and novel biomarkers of alcohol use need to be identified. The present study used a single-cell whole-brain imaging approach to 1) assess whether abstinence from alcohol in an animal model of alcohol dependence alters the functional architecture of brain activity and modularity, 2) validate our current knowledge of the neurocircuitry of alcohol abstinence, and 3) discover brain regions that may be involved in alcohol use. Alcohol abstinence resulted in the whole-brain reorganization of functional architecture in mice and a pronounced decrease in modularity that was not observed in nondependent moderate drinkers. Structuring of the alcohol abstinence network revealed three major brain modules: 1) extended amygdala module, 2) midbrain striatal module, and 3) cortico-hippocampo-thalamic module, reminiscent of the three-stage theory. Many hub brain regions that control this network were identified, including several that have been previously overlooked in alcohol research. These results identify brain targets for future research and demonstrate that alcohol use and dependence remodel brain-wide functional architecture to decrease modularity. Further studies are needed to determine whether the changes in coactivation and modularity that are associated with alcohol abstinence are causal features of alcohol dependence or a consequence of excessive drinking and alcohol exposure.

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          Most cited references83

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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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            Scale-free networks: a decade and beyond.

            For decades, we tacitly assumed that the components of such complex systems as the cell, the society, or the Internet are randomly wired together. In the past decade, an avalanche of research has shown that many real networks, independent of their age, function, and scope, converge to similar architectures, a universality that allowed researchers from different disciplines to embrace network theory as a common paradigm. The decade-old discovery of scale-free networks was one of those events that had helped catalyze the emergence of network science, a new research field with its distinct set of challenges and accomplishments.
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              Identification and Classification of Hubs in Brain Networks

              Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                28 January 2020
                14 January 2020
                : 117
                : 4
                : 2149-2159
                Affiliations
                [1] aDepartment of Psychiatry, School of Medicine, University of California San Diego , La Jolla, CA 92093;
                [2] bHelen Wills Neuroscience Institute, University of California, Berkeley , CA 94720;
                [3] cBeckman Institute, California Institute of Technology , Pasadena, CA 91125;
                [4] dDepartment of Molecular Medicine, The Scripps Research Institute , La Jolla, CA 92037
                Author notes
                1To whom correspondence may be addressed. Email: olgeorge@ 123456ucsd.edu .

                Edited by Huda Akil, University of Michigan, Ann Arbor, MI, and approved December 16, 2019 (received for review June 10, 2019)

                Author contributions: A.K. and O.G. designed research; A.K., A.C., M.K., H.S., G.C.M., and C.C. performed research; D.J.L. and M.D. contributed new reagents/analytic tools; A.K., D.J.L., M.D., and C.C. analyzed data; and A.K. and O.G. wrote the paper.

                Author information
                http://orcid.org/0000-0001-9434-4987
                Article
                PMC6994986 PMC6994986 6994986 201909915
                10.1073/pnas.1909915117
                6994986
                31937658
                b3faf5f5-6b7d-45c6-97ad-1d283941ed43
                Copyright @ 2020

                Published under the PNAS license.

                History
                Page count
                Pages: 11
                Funding
                Funded by: HHS | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA) 100000027
                Award ID: AA006420
                Award Recipient : Adam Kimbrough Award Recipient : Candice Contet Award Recipient : Olivier George
                Funded by: HHS | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA) 100000027
                Award ID: AA026081
                Award Recipient : Adam Kimbrough Award Recipient : Candice Contet Award Recipient : Olivier George
                Funded by: HHS | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA) 100000027
                Award ID: AA022977
                Award Recipient : Adam Kimbrough Award Recipient : Candice Contet Award Recipient : Olivier George
                Funded by: HHS | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA) 100000027
                Award ID: AA026685
                Award Recipient : Adam Kimbrough Award Recipient : Candice Contet Award Recipient : Olivier George
                Funded by: HHS | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA) 100000027
                Award ID: AA024198
                Award Recipient : Adam Kimbrough Award Recipient : Candice Contet Award Recipient : Olivier George
                Funded by: HHS | NIH | National Institute of Neurological Disorders and Stroke (NINDS) 100000065
                Award ID: NS079698
                Award Recipient : Mark D'Esposito
                Funded by: HHS | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA) 100000027
                Award ID: AA027301
                Award Recipient : Adam Kimbrough Award Recipient : Candice Contet Award Recipient : Olivier George
                Funded by: HHS | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA) 100000027
                Award ID: AA007456
                Award Recipient : Adam Kimbrough Award Recipient : Candice Contet Award Recipient : Olivier George
                Categories
                PNAS Plus
                Biological Sciences
                Neuroscience
                PNAS Plus

                graph theory,Fos,iDISCO,network analysis,dependence
                graph theory, Fos, iDISCO, network analysis, dependence

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