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      The impact of fasting on resting state brain networks in mice

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      1 , , 1 , 2
      Scientific Reports
      Nature Publishing Group UK

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          Abstract

          Fasting is known to influence learning and memory in mice and alter the neural networks that subserve these cognitive functions. We used high-resolution functional MRI to study the impact of fasting on resting-state functional connectivity in mice following 12 h of fasting. The cortex and subcortex were parcellated into 52 subregions and functional connectivity was measured between each pair of subregions in groups of fasted and non-fasted mice. Functional connectivity was globally increased in the fasted group compared to the non-fasted group, with the most significant increases evident between the hippocampus (bilateral), retrosplenial cortex (left), visual cortex (left) and auditory cortex (left). Functional brain networks in the non-fasted group comprised five segregated modules of strongly interconnected subregions, whereas the fasted group comprised only three modules. The amplitude of low frequency fluctuations (ALFF) was decreased in the ventromedial hypothalamus in the fasted group. Correlation in gamma oscillations derived from local field potentials was increased between the left visual and retrosplenial cortices in the fasted group and the power of gamma oscillations was reduced in the ventromedial hypothalamus. These results indicate that fasting induces profound changes in functional connectivity, most likely resulting from altered coupling of neuronal gamma oscillations.

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          Weight-conserving characterization of complex functional brain networks.

          Complex functional brain networks are large networks of brain regions and functional brain connections. Statistical characterizations of these networks aim to quantify global and local properties of brain activity with a small number of network measures. Important functional network measures include measures of modularity (measures of the goodness with which a network is optimally partitioned into functional subgroups) and measures of centrality (measures of the functional influence of individual brain regions). Characterizations of functional networks are increasing in popularity, but are associated with several important methodological problems. These problems include the inability to characterize densely connected and weighted functional networks, the neglect of degenerate topologically distinct high-modularity partitions of these networks, and the absence of a network null model for testing hypotheses of association between observed nontrivial network properties and simple weighted connectivity properties. In this study we describe a set of methods to overcome these problems. Specifically, we generalize measures of modularity and centrality to fully connected and weighted complex networks, describe the detection of degenerate high-modularity partitions of these networks, and introduce a weighted-connectivity null model of these networks. We illustrate our methods by demonstrating degenerate high-modularity partitions and strong correlations between two complementary measures of centrality in resting-state functional magnetic resonance imaging (MRI) networks from the 1000 Functional Connectomes Project, an open-access repository of resting-state functional MRI datasets. Our methods may allow more sound and reliable characterizations and comparisons of functional brain networks across conditions and subjects. Copyright © 2011 Elsevier Inc. All rights reserved.
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            Rat brains also have a default mode network.

            The default mode network (DMN) in humans has been suggested to support a variety of cognitive functions and has been implicated in an array of neuropsychological disorders. However, its function(s) remains poorly understood. We show that rats possess a DMN that is broadly similar to the DMNs of nonhuman primates and humans. Our data suggest that, despite the distinct evolutionary paths between rodent and primate brain, a well-organized, intrinsically coherent DMN appears to be a fundamental feature in the mammalian brain whose primary functions might be to integrate multimodal sensory and affective information to guide behavior in anticipation of changing environmental contingencies.
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              Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex.

              Astrocytes have long been thought to act as a support network for neurons, with little role in information representation or processing. We used two-photon imaging of calcium signals in the ferret visual cortex in vivo to discover that astrocytes, like neurons, respond to visual stimuli, with distinct spatial receptive fields and sharp tuning to visual stimulus features including orientation and spatial frequency. The stimulus-feature preferences of astrocytes were exquisitely mapped across the cortical surface, in close register with neuronal maps. The spatially restricted stimulus-specific component of the intrinsic hemodynamic mapping signal was highly sensitive to astrocyte activation, indicating that astrocytes have a key role in coupling neuronal organization to mapping signals critical for noninvasive brain imaging. Furthermore, blocking astrocyte glutamate transporters influenced the magnitude and duration of adjacent visually driven neuronal responses.
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                Author and article information

                Contributors
                tsurugizawa@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 February 2019
                27 February 2019
                2019
                : 9
                : 2976
                Affiliations
                [1 ]GRID grid.457334.2, NeuroSpin, Commissariat à l’Energie Atomique et aux Energies Alternatives, CEA Saclay, ; Gif-sur-Yvette, 91191 France
                [2 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, Melbourne Neuropsychiatry Centre and Department of Biomedical Engineering, , The University of Melbourne, ; Victoria, 3010 Australia
                Author information
                http://orcid.org/0000-0003-3194-578X
                Article
                39851
                10.1038/s41598-019-39851-6
                6393589
                30626917
                8ebd69db-ff09-457c-8278-f3b96ba0b635
                © The Author(s) 2019

                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
                : 18 May 2018
                : 4 February 2019
                Funding
                Funded by: L'Idex Paris Saclay
                Funded by: FundRef https://doi.org/10.13039/501100000925, Department of Health | National Health and Medical Research Council (NHMRC);
                Award ID: 1136649
                Award Recipient :
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