Literature DB >> 22173012

Interindividual reaction time variability is related to resting-state network topology: an electroencephalogram study.

G Zhou1, P Liu, J He, M Dong, X Yang, B Hou, K M Von Deneen, W Qin, J Tian.   

Abstract

Both anatomical and functional brain network studies have drawn great attention recently. Previous studies have suggested the significant impacts of brain network topology on cognitive function. However, the relationship between non-task-related resting-state functional brain network topology and overall efficiency of sensorimotor processing has not been well identified. In the present study, we investigated the relationship between non-task-related resting-state functional brain network topology and reaction time (RT) in a Go/Nogo task using an electroencephalogram (EEG). After estimating the functional connectivity between each pair of electrodes, graph analysis was applied to characterize the network topology. Two fundamental measures, clustering coefficient (functional segregation) and characteristic path length (functional integration), as well as "small-world-ness" (the ratio between the clustering coefficient and characteristic path length) were calculated in five frequency bands. Then, the correlations between the network measures and RT were evaluated in each band separately. The present results showed that increased overall functional connectivity in alpha and gamma frequency bands was correlated with a longer RT. Furthermore, shorter RT was correlated with a shorter characteristic path length in the gamma band. This result suggested that human RTs were likely to be related to the efficiency of the brain integrating information across distributed brain regions. The results also showed that a longer RT was related to an increased gamma clustering coefficient and decreased small-world-ness. These results provided further evidence of the association between the resting-state functional brain network and cognitive function.
Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 22173012     DOI: 10.1016/j.neuroscience.2011.11.048

Source DB:  PubMed          Journal:  Neuroscience        ISSN: 0306-4522            Impact factor:   3.590


  9 in total

1.  The graph theoretical analysis of the SSVEP harmonic response networks.

Authors:  Yangsong Zhang; Daqing Guo; Kaiwen Cheng; Dezhong Yao; Peng Xu
Journal:  Cogn Neurodyn       Date:  2015-01-11       Impact factor: 5.082

2.  COMT polymorphism modulates the resting-state EEG alpha oscillatory response to acute nicotine in male non-smokers.

Authors:  H Bowers; D Smith; S de la Salle; J Choueiry; D Impey; T Philippe; H Dort; A Millar; M Daigle; P R Albert; A Beaudoin; V Knott
Journal:  Genes Brain Behav       Date:  2015-07-15       Impact factor: 3.449

Review 3.  High-frequency neural activity and human cognition: past, present and possible future of intracranial EEG research.

Authors:  Jean-Philippe Lachaux; Nikolai Axmacher; Florian Mormann; Eric Halgren; Nathan E Crone
Journal:  Prog Neurobiol       Date:  2012-06-26       Impact factor: 11.685

4.  Pro-cognitive drug effects modulate functional brain network organization.

Authors:  Carsten Giessing; Christiane M Thiel
Journal:  Front Behav Neurosci       Date:  2012-08-28       Impact factor: 3.558

5.  Rifle Shooting Performance Correlates with Electroencephalogram Beta Rhythm Network Activity during Aiming.

Authors:  Anmin Gong; Jianping Liu; Changhao Jiang; Yunfa Fu
Journal:  Comput Intell Neurosci       Date:  2018-11-11

6.  Relationships between the resting-state network and the P3: Evidence from a scalp EEG study.

Authors:  Fali Li; Tiejun Liu; Fei Wang; He Li; Diankun Gong; Rui Zhang; Yi Jiang; Yin Tian; Daqing Guo; Dezhong Yao; Peng Xu
Journal:  Sci Rep       Date:  2015-10-12       Impact factor: 4.379

7.  SSVEP response is related to functional brain network topology entrained by the flickering stimulus.

Authors:  Yangsong Zhang; Peng Xu; Yingling Huang; Kaiwen Cheng; Dezhong Yao
Journal:  PLoS One       Date:  2013-09-09       Impact factor: 3.240

8.  Single-Trial Recognition of Imagined Forces and Speeds of Hand Clenching Based on Brain Topography and Brain Network.

Authors:  Xin Xiong; Yunfa Fu; Jian Chen; Lijun Liu; Xiabing Zhang
Journal:  Brain Topogr       Date:  2018-12-31       Impact factor: 3.020

9.  Efficacy, Trainability, and Neuroplasticity of SMR vs. Alpha Rhythm Shooting Performance Neurofeedback Training.

Authors:  Anmin Gong; Wenya Nan; Erwei Yin; Changhao Jiang; Yunfa Fu
Journal:  Front Hum Neurosci       Date:  2020-03-20       Impact factor: 3.169

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.