Literature DB >> 32798679

Identifying the brain's connector hubs at the voxel level using functional connectivity overlap ratio.

Epifanio Bagarinao1, Hirohisa Watanabe2, Satoshi Maesawa3, Daisuke Mori4, Kazuhiro Hara5, Kazuya Kawabata5, Reiko Ohdake5, Michihito Masuda5, Aya Ogura5, Toshiyasu Kato5, Shuji Koyama1, Masahisa Katsuno5, Toshihiko Wakabayashi6, Masafumi Kuzuya7, Minoru Hoshiyama1, Haruo Isoda1, Shinji Naganawa8, Norio Ozaki9, Gen Sobue10.   

Abstract

Neuroimaging studies have shown that the brain is functionally organized into several large-scale brain networks. Within these networks are regions that are widely connected to several other regions within and/or outside the network. Regions that connect to several other networks, known as connector hubs, are believed to be crucial for information transfer and between-network communication within the brain. To identify regions with high between-network connectivity at the voxel level, we introduced a novel metric called functional connectivity overlap ratio (FCOR), which quantifies the spatial extent of a region's connection to a given network. Using resting state functional magnetic resonance imaging data, FCOR maps were generated for several well-known large-scale resting state networks (RSNs) and used to examine the relevant associations among different RSNs, identify connector hub regions in the cerebral cortex, and elucidate the hierarchical functional organization of the brain. Constructed FCOR maps revealed a strong association among the core neurocognitive networks (default mode, salience, and executive control) as well as among primary processing networks (sensorimotor, auditory, and visual). Prominent connector hubs were identified in the bilateral middle frontal gyrus, posterior cingulate, lateral parietal, middle temporal, dorsal anterior cingulate, and anterior insula, among others, regions mostly associated with the core neurocognitive networks. Finally, clustering the whole brain using FCOR features yielded a topological organization that arranges brain regions into a hierarchy of information processing systems with the primary processing systems at one end and the heteromodal systems comprising connector hubs at the other end.
Copyright © 2020. Published by Elsevier Inc.

Entities:  

Year:  2020        PMID: 32798679     DOI: 10.1016/j.neuroimage.2020.117241

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  6 in total

1.  Connectivity impairment of cerebellar and sensorimotor connector hubs in Parkinson's disease.

Authors:  Epifanio Bagarinao; Kazuya Kawabata; Hirohisa Watanabe; Kazuhiro Hara; Reiko Ohdake; Aya Ogura; Michihito Masuda; Toshiyasu Kato; Satoshi Maesawa; Masahisa Katsuno; Gen Sobue
Journal:  Brain Commun       Date:  2022-08-20

2.  Involvement of cerebellar and subcortical connector hubs in schizophrenia.

Authors:  Maeri Yamamoto; Epifanio Bagarinao; Masanori Shimamoto; Tetsuya Iidaka; Norio Ozaki
Journal:  Neuroimage Clin       Date:  2022-08-04       Impact factor: 4.891

3.  Transcranial magnetic stimulation treatment in Alzheimer's disease: a meta-analysis of its efficacy as a function of protocol characteristics and degree of personalization.

Authors:  Arianna Menardi; Lisa Dotti; Ettore Ambrosini; Antonino Vallesi
Journal:  J Neurol       Date:  2022-07-04       Impact factor: 6.682

4.  Aging Impacts the Overall Connectivity Strength of Regions Critical for Information Transfer Among Brain Networks.

Authors:  Epifanio Bagarinao; Hirohisa Watanabe; Satoshi Maesawa; Daisuke Mori; Kazuhiro Hara; Kazuya Kawabata; Noritaka Yoneyama; Reiko Ohdake; Kazunori Imai; Michihito Masuda; Takamasa Yokoi; Aya Ogura; Toshiaki Taoka; Shuji Koyama; Hiroki C Tanabe; Masahisa Katsuno; Toshihiko Wakabayashi; Masafumi Kuzuya; Minoru Hoshiyama; Haruo Isoda; Shinji Naganawa; Norio Ozaki; Gen Sobue
Journal:  Front Aging Neurosci       Date:  2020-10-28       Impact factor: 5.750

5.  Classification of Alzheimer's Disease Based on Abnormal Hippocampal Functional Connectivity and Machine Learning.

Authors:  Qixiao Zhu; Yonghui Wang; Chuanjun Zhuo; Qunxing Xu; Yuan Yao; Zhuyun Liu; Yi Li; Zhao Sun; Jian Wang; Ming Lv; Qiang Wu; Dawei Wang
Journal:  Front Aging Neurosci       Date:  2022-02-22       Impact factor: 5.750

6.  Network properties and regional brain morphology of the insular cortex correlate with individual pain thresholds.

Authors:  Lynn Neumann; Niklas Wulms; Vanessa Witte; Tamas Spisak; Matthias Zunhammer; Ulrike Bingel; Tobias Schmidt-Wilcke
Journal:  Hum Brain Mapp       Date:  2021-07-23       Impact factor: 5.038

  6 in total

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