Date: June 2, 2026 Time: 13:00 Location: Building 35 , 003 Title: Decoding Functional Networks for Visual Categories via GNNs Speaker: Shira Karmi Abstract: Understanding how large-scale brain networks represent visual categories is fundamental to linking perception and cortical organization. Using high-resolution 7T fMRI from the Natural Scenes Dataset, we construct parcel-level functional graphs and train a signed Graph Neural Network that models both positive and negative interactions, with a sparse edge mask and class-specific saliency. The model accurately decodes category-specific functional connectivity states sports, food,vehicles) and reveals reproducible, biologically meaningful subnetworks along the ventral and dorsal visual pathways. This framework bridges machine learning and neuroscience by extending voxel-level category selectivity to a connectivity-based representation of visual processing. Bio: Shira Karmi is Electrical Engineer MSc student supervised by Tammy Riklin Raviv and Galia Avidan