Both Target and Distractor are Sampled Rhythmically in a Motion Detection Task

It has been shown that the visual system samples the attended information rhythmically. Does rhythmic sampling also apply to distracting information? How do attended information and distracting information compete temporally for neural representations? We recorded electroencephalography from participants who detected instances of coherent motion in a random dot kinematogram (RDK) (primary task) overlayed on different categories (pleasant, unpleasant, and neutral) of affective images from the IAPS library (distractor). The RDK was flicked at 4.29 Hz whereas the IAPS pictures at 6 Hz. From the SSVEP time series, the time course of the power at 4.29 Hz was extracted in a moving window approach, and its fluctuation was taken to index the temporal dynamics of attended information processing. The time course of the power at 6Hz was similarly extracted and support vector machine (SVM) was applied to decode different categories of affective images with the resulting fluctuating decoding accuracy taken to index the temporal dynamics of distracting information processing. We found that (1) both the 4.29 Hz power time course and the 6 Hz decoding accuracy time course exhibited rhythmicity at 1 Hz and (2) the phase difference between the two rhythmic time courses predicted task performance, i.e., phase difference close to pi corresponded to a higher rate of coherent motion detection whereas phase difference close to 0 corresponded to a lower rate of coherence motion detection. These results suggest that (1) both attended and distracting information were sampled rhythmically and (2) alternating the sampling between target and distractor reduces the adverse impact of distractor.

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Publication Details

Journal
Journal of Vision
Published
2024-09-15
DOI
https://doi.org/10.1167/jov.24.10.426
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
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article

Both Target and Distractor are Sampled Rhythmically in a Motion Detection Task

Mingzhou Ding, Changhao Xiong, Andreas Keil, Ke Bo et al.
Journal of Vision
EEG and Brain-Computer Interfaces
article

Both Target and Distractor are Sampled Rhythmically in a Motion Detection Task

Mingzhou Ding, Changhao Xiong, Andreas Keil, Ke Bo, Nathan M. Petro
article en

Abstract

It has been shown that the visual system samples the attended information rhythmically. Does rhythmic sampling also apply to distracting information? How do attended information and distracting information compete temporally for neural representations? We recorded electroencephalography from participants who detected instances of coherent motion in a random dot kinematogram (RDK) (primary task) overlayed on different categories (pleasant, unpleasant, and neutral) of affective images from the IAPS library (distractor). The RDK was flicked at 4.29 Hz whereas the IAPS pictures at 6 Hz. From the SSVEP time series, the time course of the power at 4.29 Hz was extracted in a moving window approach, and its fluctuation was taken to index the temporal dynamics of attended information processing. The time course of the power at 6Hz was similarly extracted and support vector machine (SVM) was applied to decode different categories of affective images with the resulting fluctuating decoding accuracy taken to index the temporal dynamics of distracting information processing. We found that (1) both the 4.29 Hz power time course and the 6 Hz decoding accuracy time course exhibited rhythmicity at 1 Hz and (2) the phase difference between the two rhythmic time courses predicted task performance, i.e., phase difference close to pi corresponded to a higher rate of coherent motion detection whereas phase difference close to 0 corresponded to a lower rate of coherence motion detection. These results suggest that (1) both attended and distracting information were sampled rhythmically and (2) alternating the sampling between target and distractor reduces the adverse impact of distractor.

Journal of VisionVol. 24(10)
University of Florida (US), Dartmouth Hospital (GB)
Openalex Percentile: Top 83%
EEG and Brain-Computer Interfaces
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