Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in...
Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task
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Author / Creator
Tian, Yin , Zhang, Huiling , Xu, Wei , Zhang, Haiyong , Yang, Li , Zheng, Shuxing and Shi, Yupan
Publisher
Switzerland: Frontiers Research Foundation
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Language
English
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Publisher
Switzerland: Frontiers Research Foundation
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Contents
Spectral entropy, which was generated by applying the Shannon entropy concept to the power distribution of the Fourier-transformed electroencephalograph (EEG), was utilized to measure the uniformity of power spectral density underlying EEG when subjects performed the working memory tasks twice, i.e., before and after training. According to Signed R...
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Full title
Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task
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TN_cdi_doaj_primary_oai_doaj_org_article_3c929a8a5c5241d4be1c0bba4bb4e802
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_3c929a8a5c5241d4be1c0bba4bb4e802
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ISSN
1662-5161
E-ISSN
1662-5161
DOI
10.3389/fnhum.2017.00437
