NDLI: Multi-domain feature analysis for depression: A study of N170 in time, frequency and spatial domains simultaneously

Content Provider	IEEE Xplore Digital Library
Author	Qiangfeng Zhao Junfeng Sun Fengyu Cong Shan Chen Yingying Tang Shanbao Tong
Copyright Year	2013
Description	Author affiliation: Dept. of Math. Inf. Technol., Univ. of Jyvaskyla, Jyvaskyla, Finland (Fengyu Cong) \|\| Dept. of EEG Source Imaging, Shanghai Jiao Tong Univ., Shanghai, China (Yingying Tang) \|\| Sch. of Biomed. Eng., Shanghai Jiao Tong Univ., Shanghai, China (Qiangfeng Zhao; Junfeng Sun; Shan Chen; Shanbao Tong)
Abstract	This study investigated the differences in event-related potentials (ERPs) between depression and normal control groups by using the cue-target paradigm with facial expressions as stimuli. Conventional ERPs analysis did not show a significant difference in the N170 amplitude or latency between the two groups. However, the multi-domain feature analysis of N170 by nonnegative tensor factorization (NTF) indicated that N170 in depression group had lower power compared with the normal control group for all three different emotional (i.e., happy, neutral, and sad) facial stimuli (Q ≤ 0.05). The results revealed the perceptual early-stage dysfunction in face processing for depression.
Starting Page	5986
Ending Page	5989
File Size	497534
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6610916
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Face Tensile stress Electroencephalography Time-frequency analysis Analysis of variance Educational institutions
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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