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Eye Movements and EEG During Reading as Markers of Interest

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Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics (Intercognsci 2020)

Abstract

Interest as a positive emotion is closely related to the ability to process new information and/or better consolidate the information which has already been perceived, increase in attention to what one is interested in, and indicators of processing, learning, and motivation [1]. Here we aim to identify oculomotor and electroencephalographic correlates, which could serve as predictors of a locus of interest based on the travel locations perception. Thirty-eight (38) healthy volunteers took part in the study (people aged between 18 and 27, the average age was 22 ± 0.4 years, 14 males and 24 females). Eye movements were registered simultaneously with monopolar EEG using a standard 10/20 system (O1, O2, T3, T4, P3, P4, C3, C4, F3, F4). Participants were watching at the slides describing eight different places of interest in Russia. After seeing each slide, volunteers said whether the information shown to them arouse their interest or not. As each text was shown twice in different forms, statistical analysis, taking into account changes in answers about interest, was conducted. The fixation during the first demonstration was longer in case of interest, and doubts in answers also made the fixation duration longer. Saccade amplitudes showed the opposite trend. The electrical activity in the theta-band in frontal channels increased, compared to resting state in case of interest; however, if a participant said that he or she was not interested, there was an even larger increase. Therefore, eye movement and EEG characteristics reflect a subjective assessment of interest when reading information.

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Correspondence to Victor Anisimov .

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Shedenko, K., Anisimov, V., Kovaleva, A., Latanov, A. (2021). Eye Movements and EEG During Reading as Markers of Interest. In: Velichkovsky, B.M., Balaban, P.M., Ushakov, V.L. (eds) Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics. Intercognsci 2020. Advances in Intelligent Systems and Computing, vol 1358. Springer, Cham. https://doi.org/10.1007/978-3-030-71637-0_18

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