A central and unified role of corticocortical feedback in parsing visual scenes
Abstract Visual scene analysis in the brain involves diverse grouping and segmentation processes mediated by intra- and inter-areal interactions, but the role of feedback from higher to lower visual cortices has remained largely speculative, relying mostly on indirect evidence. In this study with be...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-62279-8 |
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| Summary: | Abstract Visual scene analysis in the brain involves diverse grouping and segmentation processes mediated by intra- and inter-areal interactions, but the role of feedback from higher to lower visual cortices has remained largely speculative, relying mostly on indirect evidence. In this study with behaving monkeys, we investigated the causal impact of V4-to-V1 feedback on different figure-ground perceptual tasks employing distinct contextual cues. We compared neuronal responses in the primary visual cortex (V1) and the behavioral performance before and after silencing a higher-order visual area (V4). Our results reveal that V4-to-V1 feedback comprises dissociable facilitatory and inhibitory components that differ in their spatial distribution, onset time, modulatory polarity, and magnitude. This feedback is essential for, and consistent across, distinct grouping and segmentation processes, operating independently of V1 neurons’ selectivity for local features and primarily modifying the late phases of neuronal responses. These findings highlight fundamental differences between the mechanisms underlying global, feature-independent figure-ground organization and local, feature-dependent contextual analysis. Moreover, while the feedback modifies correlated variability in neural responses, this effect does not alter the neural population code. Our study underscores the central and unified role of corticocortical feedback in integrating and interpreting visual scenes, with implications for circuit-level mechanisms. |
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| ISSN: | 2041-1723 |