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      Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability

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          Abstract

          The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability.

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          Emotional processing in anterior cingulate and medial prefrontal cortex.

          Negative emotional stimuli activate a broad network of brain regions, including the medial prefrontal (mPFC) and anterior cingulate (ACC) cortices. An early influential view dichotomized these regions into dorsal-caudal cognitive and ventral-rostral affective subdivisions. In this review, we examine a wealth of recent research on negative emotions in animals and humans, using the example of fear or anxiety, and conclude that, contrary to the traditional dichotomy, both subdivisions make key contributions to emotional processing. Specifically, dorsal-caudal regions of the ACC and mPFC are involved in appraisal and expression of negative emotion, whereas ventral-rostral portions of the ACC and mPFC have a regulatory role with respect to limbic regions involved in generating emotional responses. Moreover, this new framework is broadly consistent with emerging data on other negative and positive emotions. Published by Elsevier Ltd.
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            Comparing correlated correlation coefficients.

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              Small-world anatomical networks in the human brain revealed by cortical thickness from MRI.

              An important issue in neuroscience is the characterization for the underlying architectures of complex brain networks. However, little is known about the network of anatomical connections in the human brain. Here, we investigated large-scale anatomical connection patterns of the human cerebral cortex using cortical thickness measurements from magnetic resonance images. Two areas were considered anatomically connected if they showed statistically significant correlations in cortical thickness and we constructed the network of such connections using 124 brains from the International Consortium for Brain Mapping database. Significant short- and long-range connections were found in both intra- and interhemispheric regions, many of which were consistent with known neuroanatomical pathways measured by human diffusion imaging. More importantly, we showed that the human brain anatomical network had robust small-world properties with cohesive neighborhoods and short mean distances between regions that were insensitive to the selection of correlation thresholds. Additionally, we also found that this network and the probability of finding a connection between 2 regions for a given anatomical distance had both exponentially truncated power-law distributions. Our results demonstrated the basic organizational principles for the anatomical network in the human brain compatible with previous functional networks studies, which provides important implications of how functional brain states originate from their structural underpinnings. To our knowledge, this study provides the first report of small-world properties and degree distribution of anatomical networks in the human brain using cortical thickness measurements.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                23 January 2018
                2018
                : 12
                : 2
                Affiliations
                Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University , Chongqing, China
                Author notes

                Edited by: Xiaolin Zhou, Peking University, China

                Reviewed by: Wei Liao, University of Electronic Science and Technology of China, China; Bruno Bonaz, Grenoble Faculty of Medicine and Hospital, France

                *Correspondence: Guo-Rong Wu, gronwu@ 123456gmail.com Hong Chen, chenhg@ 123456swu.edu.cn
                Article
                10.3389/fnhum.2018.00002
                5838315
                29545744
                a9a3b0b2-64df-4656-bad3-c87f9b40321e
                Copyright © 2018 Wei, Chen and Wu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 04 November 2017
                : 03 January 2018
                Page count
                Figures: 3, Tables: 3, Equations: 2, References: 89, Pages: 11, Words: 0
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 61403312
                Categories
                Neuroscience
                Original Research

                Neurosciences
                amygdala,heart rate variability,central autonomic network,structural covariance network,prefrontal-amygdala pathways

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