EEG based topography analysis in string recognition task

Xiaofei Ma, Xiaolin Huang, Yuxiaotong Shen, Zike Qin, Yun Ge, Ying Chen and Xinbao Ning

Physica A: Statistical Mechanics and its Applications, 2017, vol. 469, issue C, 531-539

Abstract: Vision perception and recognition is a complex process, during which different parts of brain are involved depending on the specific modality of the vision target, e.g. face, character, or word. In this study, brain activities in string recognition task compared with idle control state are analyzed through topographies based on multiple measurements, i.e. sample entropy, symbolic sample entropy and normalized rhythm power, extracted from simultaneously collected scalp EEG. Our analyses show that, for most subjects, both symbolic sample entropy and normalized gamma power in string recognition task are significantly higher than those in idle state, especially at locations of P4, O2, T6 and C4. It implies that these regions are highly involved in string recognition task. Since symbolic sample entropy measures complexity, from the perspective of new information generation, and normalized rhythm power reveals the power distributions in frequency domain, complementary information about the underlying dynamics can be provided through the two types of indices.

Keywords: EEG; String recognition; Symbolic sample entropy; Normalized rhythm power (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:469:y:2017:i:c:p:531-539

DOI: 10.1016/j.physa.2016.11.105

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