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Use of artificial intelligence for study of the visual perception
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Paper Abstract

In this report we propose an approach based on artificial neural networks for the classification and recognition of various states of the human brain associated with the spatial perception of ambiguous images. Based on the developed numerical methodology and analysis of the experimental multi-channel EEG data, we create and optimize an artificial neural network to ensure the accuracy of the classification of EEG states of the brain in visual perception close to 100%. Different interpretations of ambiguous images produce different oscillatory patterns in the EEG of a person with similar characteristics for each interpretation.

Paper Details

Date Published: 3 June 2019
PDF: 6 pages
Proc. SPIE 11067, Saratov Fall Meeting 2018: Computations and Data Analysis: from Nanoscale Tools to Brain Functions, 1106704 (3 June 2019); doi: 10.1117/12.2527705
Show Author Affiliations
Anastasiya Runnova, Innopolis Univ. (Russian Federation)
Saratov State Technical Univ. (Russian Federation)
Vladimir Maksimenko, Innopolis Univ. (Russian Federation)
Maksim Zhuravlev, Innopolis Univ. (Russian Federation)
Saratov State Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 11067:
Saratov Fall Meeting 2018: Computations and Data Analysis: from Nanoscale Tools to Brain Functions
Dmitry Engelevich Postnov, Editor(s)

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