PLoS Computational BiologyNeurosciencePeer-reviewed journal article
Unveiling functions of the visual cortex using task-specific deep neural networks
Kshitij DwivediiD, Michael BonneriD, Radoslaw Martin CichyiD, Gemma RoigiD
Abstract
The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities. Here, we introduce an AI-driven approach to discover the functional mapping of the visual cortex. We related human brain responses to scene images measured with functional MRI (fMRI) systematically to a diverse set of deep neural networks (DNNs) optimized to perform different scene perception tasks. We found a structured mapping between DNN tasks and brain regions along the ventral and dorsal visual streams. Low-level visual tasks mapped onto early brain regions, 3-dimensional scene perception tasks mapped onto the dorsal stream, and semantic tasks mapped onto the ventral stream. This mapping was of high fidelity, with more than 60% of the explainable variance in nine key regions being explained. Together, our results provide a novel functional mapping of the human visual cortex and demonstrate the power of the computational approach.
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- 52
- FWCI
- 4.87
- Field percentile
- top 4%
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