Fast Multigroup Gaussian Process Factor Models.

ABSTRACT: Gaussian processes are now commonly used in dimensionality reduction approaches tailored to neuroscience, especially to describe changes in high-dimensional neural activity over time. As recording capabilities expand to include neuronal populations across multiple brain areas, cortical layers, and cell types, interest in extending gaussian process factor models to characterize multipopulation interactions has grown. However, the cubic runtime scaling of current methods with the length of experimental trials and the number of recorded populations (groups) precludes their application to large-scale multipopulation recordings. Here, we improve this scaling from cubic to linear in both trial length and group number. We present two approximate approaches to fitting multigroup gaussian process f

SUBMITTER: Gokcen E 

PROVIDER: S-EPMC12313100 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature