Identification of stimulus-response relations for cultured neuronal networks using features of multiple temporal resolution levels
Authors: 
Muqi Yin, Wei Zhang, You Wang, Guang LiAuthors Info & Claims
Pages 11 - 18
Abstract
In recent years cultured neuronal networks have been used with the aim of unraveling how biological information transmits between neurons. Investigating the evoked activities of cultured neuronal networks helps acquire a better understanding of neural decoding. However, it is still challenging to quantitatively describe and predict evoked patterns for them. This study focuses on evoked patterns of cultured neuronal networks and aims to identify stimulus-response relations with extracted feature sets including spike-based and rate-based features. The majority of neural information is encoded in evoked activities of the post-stimulus intervals. By partitioning post-stimulus intervals, features with multiple temporal resolution levels were constructed. This study investigates the impact of temporal resolution level on accuracy in recognizing stimulus-response relations.
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Published In
January 2022
551 pages
ISBN:9781450395755
DOI:10.1145/3523286
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Published: 31 May 2022
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BIC 2022
BIC 2022: 2022 2nd International Conference on Bioinformatics and Intelligent Computing
January 21 - 23, 2022
Harbin, China
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