Brain-guided convolutional neural networks reveal task-specific representations in scene processing.

ABSTRACT: Scene categorization is the dominant proxy for visual understanding, yet humans can perform a large number of visual tasks within any scene. Consequently, we know little about how different tasks change how a scene is processed, represented, and its features ultimately used. Here, we developed a novel brain-guided convolutional neural network (CNN) where each convolutional layer was separately guided by neural responses taken at different time points while observers performed a pre-cued object detection task or a scene affordance task on the same set of images. We then reconstructed each layer's activation maps via deconvolution to spatially assess how different features were used within each task. The brain-guided CNN made use of image features that human observers identified as being cru

SUBMITTER: Hansen BC 

PROVIDER: S-EPMC12000445 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature