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Topic: cortical topographies

Seminar
1 seminar

In Brain Imaging and Computational Neuroscience

Seminar · Computational Neuroscience

Hyperalignment: Modeling shared information encoded in idiosyncratic cortical topographies

James Haxby · Dartmouth College

Fri, Jun 26, 2020 · 14:30 UTC

Information that is shared across brains is encoded in idiosyncratic fine-scale functional topographies. Hyperalignment jointly models shared information and idiosyncratic topographies. Pattern vectors for neural responses and connectivities are projected into a common, high-dimensional information space, rather than being aligned in a canonical anatomical space. Hyperalignment calculates individual transformation matrices that preserve the geometry of pairwise dissimilarities between pattern vectors. Individual cortical topographies are modeled as mixtures of overlapping, individual-specific