Orthogonal neural representations support perceptual judgments of natural stimuli

In natural visually guided behavior, observers must separate relevant information from a barrage of irrelevant information. Many studies have investigated the neural underpinnings of this ability using artificial stimuli presented on blank backgrounds. Natural images, however, contain task-irrelevant background elements that might interfere with the perception of object features. Recent studies suggest that visual feature estimation can be modeled through the linear decoding of task-relevant information from visual cortex. So, if the representations of task-relevant and irrelevant features are not orthogonal in the neural population, then variation in the task-irrelevant features would impair task performance. We tested this hypothesis using human psychophysics and monkey neurophysiology combined with parametrically variable naturalistic stimuli. We demonstrate that (1) the neural representation of one feature (the position of an object) in visual area V4 is orthogonal to those of several background features, (2) the ability of human observers to precisely judge object position was largely unaffected by those background features, and (3) many features of the object and the background (and of objects from a separate stimulus set) are orthogonally represented in V4 neural population responses. Our observations are consistent with the hypothesis that orthogonal neural representations can support stable perception of object features despite the richness of natural visual scenes.

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Publication Details

Journal
Scientific Reports
Published
2025-02-12
DOI
https://doi.org/10.1038/s41598-025-88910-8
Citations
2
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
2.86

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article

Orthogonal neural representations support perceptual judgments of natural stimuli

Amy M. Ni, David H. Brainard, Ramanujan Srinath, Marlene R. Cohen et al.
2 citations
Scientific Reports
Neural dynamics and brain function
2.86
article

Orthogonal neural representations support perceptual judgments of natural stimuli

Amy M. Ni, David H. Brainard, Ramanujan Srinath, Marlene R. Cohen, Claire Marucci
article en
2 citations

Abstract

In natural visually guided behavior, observers must separate relevant information from a barrage of irrelevant information. Many studies have investigated the neural underpinnings of this ability using artificial stimuli presented on blank backgrounds. Natural images, however, contain task-irrelevant background elements that might interfere with the perception of object features. Recent studies suggest that visual feature estimation can be modeled through the linear decoding of task-relevant information from visual cortex. So, if the representations of task-relevant and irrelevant features are not orthogonal in the neural population, then variation in the task-irrelevant features would impair task performance. We tested this hypothesis using human psychophysics and monkey neurophysiology combined with parametrically variable naturalistic stimuli. We demonstrate that (1) the neural representation of one feature (the position of an object) in visual area V4 is orthogonal to those of several background features, (2) the ability of human observers to precisely judge object position was largely unaffected by those background features, and (3) many features of the object and the background (and of objects from a separate stimulus set) are orthogonally represented in V4 neural population responses. Our observations are consistent with the hypothesis that orthogonal neural representations can support stable perception of object features despite the richness of natural visual scenes.

Scientific ReportsVol. 15(1)
University of Chicago (US), University of Pennsylvania (US), Philadelphia University (US)
Simons Foundation, National Institutes of Health
Openalex Percentile: Top 12%
Neural dynamics and brain function
2.86
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Orthogonal neural representations support perceptual judgments of natural stimuli — Amy M. Ni, David H. Brainard, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS