Gaussian Process Factor Analysis (GPFA)
GPFA extracts low-d latent trajectories from noisy, high-d time series data. It combines linear dimensionality reduction (factor analysis) with Gaussian-process temporal smoothing in a unified probabilistic framework. GPFA is particularly useful for exploratory analysis of spike trains recorded simultaneously from multiple neurons on individual experimental trials.
Matlab codepack (version 2.02, 108 KB)
DataHigh is a Matlab-based graphical user interface to visualize and interact with high-dimensional neural population activity. DataHigh has built-in tools to perform dimensionality reduction on raw spike trains, and includes a suite of visualization tools tailored for neural data analysis.
Reference: Cowley et al., JNE, 2013