latent manifold tuning model
The old name of the model is Poisson-Gaussian process latent variable model (P-GPLVM).
Description: Estimate latent variables and tuning curves from spike train using P-GPLVM.
As shown in Gaussian process based nonlinear latent structure discovery in multivariate spike train data Wu et al 2017.
-
Launch matlab and cd into the directory containing the code (e.g.
cd code/poisson-gplvm/). -
Examine the demo scripts for annotated example analyses of simulated datasets:
demo1_1DGP.m- Tutorial script illustrating P-GPLVM for 1-dimensional latent variable with tuning curves generated from 1D Gaussian Process.demo2_1DBump.m- Tutorial script illustrating P-GPLVM for 1-dimensional latent variable with tuning curves generated from 1D Gaussian bumps.demo3_2DBump.m- Tutorial script illustrating P-GPLVM for 2-dimensional latent variable with tuning curves generated from 2D Gaussian bumps.
demo_*_ref.m are the new demos with a reference implementation. The new implementation works for multi-trial data with aligned time points.