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Graphic patterns of cortical functional connectivity of depressed patients on the basis of EEG measurements
conference contribution
posted on 2016-08-03, 11:00 authored by Yu Sun, Sijung HuSijung Hu, Jonathon Chambers, Yisheng Zhu, Shanbao TongConsiderable 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, EMBSPages
1419 - 1422Citation
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
© IEEEVersion
- 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
2011Notes
Closed access.ISBN
9781424441211;9781424441228ISSN
1557-170XPublisher version
Language
- en