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 2.03, 119 KB)

References: Yu et al., J Neurophysiol, 2009; Churchland et al., Nat Neurosci, 2010


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.

DataHigh webpage

Reference: Cowley et al., JNE, 2013