Invariant inter-subject relational structures in high order human visual cortex

Ofer Lipman, Shany Grossman, Doron Friedman, Yacov Hel-Or and Rafael Malach ()
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Ofer Lipman: Reichman University
Shany Grossman: University of Hamburg
Doron Friedman: Reichman University
Yacov Hel-Or: Reichman University
Rafael Malach: Weizmann Institute of Science

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract It is a fundamental of behavior that different individuals see the world in a largely similar manner. This is an essential basis for humans’ ability to cooperate and communicate. However, what are the neural properties that underlie these inter-subject commonalities of our visual world? Finding out what aspects of neural coding remain invariant across individuals’ brains will shed light not only on this fundamental question but will also point to the neural coding scheme at the basis of visual perception. Here, we address this question by obtaining intracranial recordings from three groups of patients taking part in a visual recognition task (overall 19 patients and 244 high-order visual contacts included in the analyses) and examining the neural coding scheme that was most consistent across individuals’ visual cortex. Our results highlight relational coding – expressed by the set of similarity distances between profiles of pattern activations—as the most consistent representation across individuals. Alternative coding schemes, such as activation pattern coding or linear coding, failed to achieve similar inter-subject consistency. Our results thus support relational coding as the central neural code underlying individuals’ shared perceptual content in the human brain.

Date: 2025
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DOI: 10.1038/s41467-025-62551-x

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