Variation in the geometry of concept manifolds across human visual cortex.

ABSTRACT: Brain activity patterns in high-level visual cortex support accurate linear classification of visual concepts (e.g., objects or scenes). It has long been appreciated that the accuracy of linear classification in any brain area depends on the geometry of its concept manifolds-sets of brain activity patterns that encode images of a concept. However, it is unclear how the geometry of concept manifolds differs between regions of visual cortex that support accurate classification and those that don't, or how it differs between visual cortex and deep neural networks (DNNs). We estimated geometric properties of concept manifolds that, per a recent theory, directly determine the accuracy of simple "few-shot" linear classifiers. Using a large fMRI dataset, we show that variation in classification a

SUBMITTER: St-Yves G 

PROVIDER: S-EPMC12445742 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature