Statistics of natural scenes shape contextual modulation in the visual cortex

Vision is context dependent, with neuronal responses shaped not only by local features but also by surrounding visual input. While classical studies, using grating stimuli, show that iso-oriented surrounds suppress responses more than orthogonal surrounds, the role of contextual modulation under natural stimulus conditions remains less clear. Using recordings from mouse primary visual cortex (V1), we trained convolutional neural network models to predict neuronal responses to natural images and synthesized surround stimuli that selectively suppressed or facilitated responses to optimal center inputs. In vivo experiments confirmed these predictions. Facilitatory surrounds resembled naturalistic continuations of the optimal center stimulus, consistent with natural image statistics, whereas suppressive surrounds deviated from these predictions. Applying the same approach to macaque V1 revealed similar principles across species. Both models accurately predicted responses to classical grating stimuli. We formalize these results in a normative Bayesian model, showing that neuronal activity for preferred center features reflects posterior beliefs about likely center-surround configurations.

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Publication Details

Journal
Neuron
Published
2026-03-01
DOI
https://doi.org/10.1016/j.neuron.2026.02.022
Primary Topic
Visual perception and processing mechanisms
Type
article
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article

Statistics of natural scenes shape contextual modulation in the visual cortex

Stelios Papadopoulos, Ján Antolík, Zhuokun Ding, Jiakun Fu et al.
Neuron
Visual perception and processing mechanisms
article

Statistics of natural scenes shape contextual modulation in the visual cortex

Stelios Papadopoulos, Ján Antolík, Zhuokun Ding, Jiakun Fu, Nikos Karantzas, Kayla Ponder, Jacob Reimer, Rachel Froebe, Lydia Ntanavara, Luca Baroni, Fabian H. Sinz, Andreas S. Tolias, Suhas Shrinivasan, Taliah Muhammad, Ralf M. Haefner, Dat Tran, Xaq Pitkow, Konstantin F. Willeke, Eric Wang, Paweł A. Pierzchlewicz, Katrin Franke, Zhiwei Ding, Paul G. Fahey, Saumil Patel, Alexander S. Ecker
article en

Abstract

Vision is context dependent, with neuronal responses shaped not only by local features but also by surrounding visual input. While classical studies, using grating stimuli, show that iso-oriented surrounds suppress responses more than orthogonal surrounds, the role of contextual modulation under natural stimulus conditions remains less clear. Using recordings from mouse primary visual cortex (V1), we trained convolutional neural network models to predict neuronal responses to natural images and synthesized surround stimuli that selectively suppressed or facilitated responses to optimal center inputs. In vivo experiments confirmed these predictions. Facilitatory surrounds resembled naturalistic continuations of the optimal center stimulus, consistent with natural image statistics, whereas suppressive surrounds deviated from these predictions. Applying the same approach to macaque V1 revealed similar principles across species. Both models accurately predicted responses to classical grating stimuli. We formalize these results in a normative Bayesian model, showing that neuronal activity for preferred center features reflects posterior beliefs about likely center-surround configurations.

Neuron
Salk Institute for Biological Studies (US), Baylor College of Medicine (US), Neurosciences Institute (US), Charles University (CZ), Max Planck Institute for Dynamics and Self-Organization (DE), European Neuroscience Institute Göttingen (DE), University of Rochester (US), University of Göttingen (DE), Carnegie Mellon University (US), Stanford University (US)
Openalex Percentile: Top 11%
Visual perception and processing mechanisms
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