Decoding time-resolved neural representations of orientation ensemble perception.

Front Neurosci

Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.

Published: August 2024


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Article Abstract

The visual system can compute summary statistics of several visual elements at a glance. Numerous studies have shown that an ensemble of different visual features can be perceived over 50-200 ms; however, the time point at which the visual system forms an accurate ensemble representation associated with an individual's perception remains unclear. This is mainly because most previous studies have not fully addressed time-resolved neural representations that occur during ensemble perception, particularly lacking quantification of the representational strength of ensembles and their correlation with behavior. Here, we conducted orientation ensemble discrimination tasks and electroencephalogram (EEG) recordings to decode orientation representations over time while human observers discriminated an average of multiple orientations. We modeled EEG signals as a linear sum of hypothetical orientation channel responses and inverted this model to quantify the representational strength of orientation ensemble. Our analysis using this inverted encoding model revealed stronger representations of the average orientation over 400-700 ms. We also correlated the orientation representation estimated from EEG signals with the perceived average orientation reported in the ensemble discrimination task with adjustment methods. We found that the estimated orientation at approximately 600-700 ms significantly correlated with the individual differences in perceived average orientation. These results suggest that although ensembles can be quickly and roughly computed, the visual system may gradually compute an orientation ensemble over several hundred milliseconds to achieve a more accurate ensemble representation.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11325722PMC
http://dx.doi.org/10.3389/fnins.2024.1387393DOI Listing

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