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Updated: Jun 2, 2025

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
Published on: August 1, 2018
Retinotopic biases in contextual feedback signals to V1 for object and scene processing
Matthew A Bennett1,2, Lucy S Petro2,3, Clement Abbatecola2,3
1Institute of Neuroscience, Université Catholique de Louvain, Place Cardinal Mercier 10/L3.05.01, 1348, Louvain-la-Neuve, Belgium.
Abstract:
Identifying the objects embedded in natural scenes relies on recurrent processing between lower and higher visual areas. How is cortical feedback information related to objects and scenes organised in lower visual areas? The spatial organisation of cortical feedback converging in early visual cortex during object and scene processing could be retinotopically specific as it is coded in V1, or object centred as coded in higher areas, or both. Here, we characterise object and scene-related feedback information to V1. Participants identified foreground objects or background scenes in images with occluded central and peripheral subsections, allowing us to isolate feedback activity to foveal and peripheral regions of V1. Using fMRI and multivoxel pattern classification, we found that background scene information is projected to both foveal and peripheral V1 but can be disrupted in the fovea by a sufficiently demanding object discrimination task, during which we found evidence of foveal object decoding when using naturalistic stimuli. We suggest that the feedback connections during scene perception project back to earlier visual areas an automatic sketch of occluded information to the predicted retinotopic location. In the case of a cognitive task however, feedback pathways project content to foveal retinotopic space, potentially for introspection, functioning as a cognitive active blackboard and not necessarily predicting the object's location. This feedback architecture could reflect the internal mapping in V1 of the brain's endogenous models of the visual environment that are used to predict perceptual inputs.
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