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The AI Seminar is a weekly meeting at the University of Alberta where researchers interested in artificial intelligence (AI) can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics can be related in any way to artificial intelligence, from foundational theoretical work, to innovative applications of AI techniques, to new fields and problems.
On Sept. 13, Cory Efird — an MSc. student in the Computing Science Department at the University of Alberta — presented “Contrastive Decoding for Concepts in the Brain" at the AI Seminar.
Abstract:
Efird presents a novel data-driven method for identifying category-selective regions in the human brain that are consistent across multiple participants. By leveraging a massive fMRI dataset and a multi-modal (language and image) neural network (CLIP), researchers trained a highly accurate contrastive brain decoder to predict neural responses to naturalistic images in the human visual cortex. They then applied a novel adaptation of the DBSCAN clustering algorithm to identify clusters of voxels across multiple brains that decode similar concepts.
Watch the full presentation below:
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