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Voluntary control of semantic neural representations by imagery with conflicting visual stimulation.

Ryohei FukumaTakufumi YanagisawaShinji NishimotoHidenori SuganoKentaro TamuraShota YamamotoYasushi IimuraYuya FujitaSatoru OshinoNaoki TaniNaoko Koide-MajimaYukiyasu KamitaniHaruhiko Kishima
Published in: Communications biology (2022)
Neural representations of visual perception are affected by mental imagery and attention. Although attention is known to modulate neural representations, it is unknown how imagery changes neural representations when imagined and perceived images semantically conflict. We hypothesized that imagining an image would activate a neural representation during its perception even while watching a conflicting image. To test this hypothesis, we developed a closed-loop system to show images inferred from electrocorticograms using a visual semantic space. The successful control of the feedback images demonstrated that the semantic vector inferred from electrocorticograms became closer to the vector of the imagined category, even while watching images from different categories. Moreover, modulation of the inferred vectors by mental imagery depended asymmetrically on the perceived and imagined categories. Shared neural representation between mental imagery and perception was still activated by the imagery under semantically conflicting perceptions depending on the semantic category.
Keyphrases
  • working memory
  • deep learning
  • mental health
  • convolutional neural network
  • optical coherence tomography
  • physical activity
  • healthcare
  • social support
  • primary care
  • machine learning
  • neural network