Сибирский федеральный университет

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Scientific Conference on Applied Physics, Information Technologies and Engineering, APITECH-III 2021

Год издания: 2021

Идентификатор DOI: 10.1088/1742-6596/2094/3/032041

Аннотация: The study is concerned with the comparison of two methods for identification of stimulus received by artificial neural network using neural activity pattern that corresponds to the period of storing information about this stimulus in the working memory. We used simple recurrent neural networks learned to pass the delayed matching-to-sample test. Neural activity was detected at the period of pause between receiving stimuli. The analysis of neural excitation patterns showed that neural networks encoded variables that were relevant for the task during the delayed matching-to-sample test, and their activity patterns were dynamic. The method of centroids allowed identifying the type of the received stimuli with efficiency up to 75% while the method of neural network-based decoder showed 100% efficiency. In addition, this method was applied to determine the minimal set of neurons whose activity was the most significant for stimulus recognition. © 2021 Institute of Physics Publishing. All rights reserved.

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 2094, Is. 3

Номера страниц: 32041

ISSN журнала: 17426588

Издатель: IOP Publishing Ltd

• Bartsev S.I. (Institute of Biophysics SB RAS, Federal Research Center, Krasnoyarsk Scientific Center SB RAS, 50, Akademgorodok, Krasnoyarsk, 660036, Russian Federation, Siberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, Russian Federation)
• Markova G.M. (Siberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, Russian Federation)

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