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Graphic patterns of cortical functional connectivity of depressed patients on the basis of EEG measurements

conference contribution
posted on 03.08.2016, 11:00 by Yu Sun, Sijung HuSijung Hu, Jonathon Chambers, Yisheng Zhu, Shanbao Tong
Considerable evidences have shown a decrease of neu-ronal activity in the left frontal lobe of depressed patients, but the underlying cortical network is still unclear. The present study intends to investigate the conscious-state brain network patterns in depressed patients compared with control individuals. Cortical functional connectivity is quantified by the partial directed coherence (PDC) analysis of multichannel EEG signals from 12 depressed patients and 12 healthy volunteers. The corresponding PDC matrices are first converted into unweighted graphs by applying a threshold to obtain the topographic property in-degree (K in). A significantly larger K in in the left hemisphere is identified in depressed patients, while a symmetric pattern is found in the control group. Another two topographic measures, i.e., clustering coefficients (C) and characteristic path length (L), are obtained from the original weighted PDC digraphs. Compared with control individuals, significantly smaller C and L are revealed in the depression group, indicating a random network-like architecture due to affective disorder. This study thereby provides further support for the presence of a hemispheric asymmetry syndrome in the depressed patients. More importantly, we present evidence that depression is characterized by a loss of optimal small-world network characteristics in conscious state.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Pages

1419 - 1422

Citation

SUN, Y. ... et al., 2011. Graphic patterns of cortical functional connectivity of depressed patients on the basis of EEG measurements. IN: Proceedings of 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEMBS 2011), Boston, United States, 30 August-3 September 2011, pp.1419-1422.

Publisher

© IEEE

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2011

Notes

Closed access.

ISBN

9781424441211;9781424441228

ISSN

1557-170X

Language

en