Xie, Siying, Kaiser, Daniel orcid.org/0000-0002-9007-3160 and Cichy, Radoslaw M (2020) Visual Imagery and Perception Share Neural Representations in the Alpha Frequency Band. Current Biology. ISSN 0960-9822
Abstract
To behave adaptively with sufficient flexibility, biological organisms must cognize beyond immediate reaction to a physically present stimulus. For this, humans use visual mental imagery [1, 2], the ability to conjure up a vivid internal experience from memory that stands in for the percept of the stimulus. Visually imagined contents subjectively mimic perceived contents, suggesting that imagery and perception share common neural mechanisms. Using multivariate pattern analysis on human electroencephalography (EEG) data, we compared the oscillatory time courses of mental imagery and perception of objects. We found that representations shared between imagery and perception emerged specifically in the alpha frequency band. These representations were present in posterior, but not anterior, electrodes, suggesting an origin in parieto-occipital cortex. Comparison of the shared representations to computational models using representational similarity analysis revealed a relationship to later layers of deep neural networks trained on object representations, but not auditory or semantic models, suggesting representations of complex visual features as the basis of commonality. Together, our results identify and characterize alpha oscillations as a cortical signature of representations shared between visual mental imagery and perception.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Author(s). |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Psychology (York) |
Depositing User: | Pure (York) |
Date Deposited: | 22 Jun 2020 16:20 |
Last Modified: | 16 Oct 2024 16:41 |
Published Version: | https://doi.org/10.1016/j.cub.2020.04.074 |
Status: | Published online |
Refereed: | Yes |
Identification Number: | 10.1016/j.cub.2020.04.074 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:162199 |
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