Multiscale entropy as a new feature for EEG and fNIRS analysis

Thanate Angsuwatanakul, Jamie O'Reilly, Kajornvut Ounjai, Boonserm Kaewkamnerdpong, Keiji Iramina

研究成果: Contribution to journalArticle査読

3 被引用数 (Scopus)

抄録

The present study aims to apply multiscale entropy (MSE) to analyse brain activity in terms of brain complexity levels and to use simultaneous electroencephalogram and functional near-infrared spectroscopy (EEG/fNIRS) recordings for brain functional analysis. A memory task was selected to demonstrate the potential of this multimodality approach since memory is a highly complex neurocognitive process, and the mechanisms governing selective retention of memories are not fully understood by other approaches. In this study, 15 healthy participants with normal colour vision participated in the visual memory task, which involved the making the executive decision of remembering or forgetting the visual stimuli based on his/her own will. In a continuous stimulus set, 250 indoor/outdoor scenes were presented at random, between periods of fixation on a black background. The participants were instructed to make a binary choice indicating whether they wished to remember or forget the image; both stimulus and response times were stored for analysis. The participants then performed a scene recognition test to confirm whether or not they remembered the images. The results revealed that the participants intentionally memorising a visual scene demonstrate significantly greater brain complexity levels in the prefrontal and frontal lobe than when purposefully forgetting a scene; p < 0.05 (two-tailed). This suggests that simultaneous EEG and fNIRS can be used for brain functional analysis, and MSE might be the potential indicator for this multimodality approach.

本文言語英語
論文番号189
ジャーナルEntropy
22
2
DOI
出版ステータス出版済み - 2 1 2020

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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