dSCA: Demixed shared component analysis

Y Takagi^*, SW Kennerley, J Hirayama⁺, LT Hunt⁺
Demixed shared component analysis of neuralpopulation data from multiple brain areas
NeurIPS 2020, selected as spotlight presentation
(arXiv link: https://arxiv.org/abs/2006.10212)

Overview of dSCA

dSCA decomposes population activity into a few components, such that the shared components capture the maximum amount of shared information across brain regions while also depending on relevant task parameters. This yields interpretable components that express which variables are shared between different brain regions and when this information is shared across time.

Example Usage

Before running dSCA, please download dPCA (demixed PCA) package from here. Running simulation.m provides a simulation results and plotting the results.

Support

Email yutakagi322@gmail.com with any questions.

MIT license. Contributions welcome.