Nonlinear demixed component analysis for neural population data as a low-rank kernel regression problem

1 code implementation • 19 Dec 2018 • Kenneth W. Latimer

Here I introduce an extension to demixed principal component analysis (dPCA), a linear dimensionality reduction technique for analyzing the activity of neural populations, to the case of nonlinear components.

Dimensionality Reduction regression

Inferring synaptic conductances from spike trains with a biophysically inspired point process model

no code implementations • NeurIPS 2014 • Kenneth W. Latimer, E.J. Chichilnisky, Fred Rieke, Jonathan W. Pillow

We show that the model fit to extracellular spike trains can predict excitatory and inhibitory conductances elicited by novel stimuli with nearly the same accuracy as a model trained directly with intracellular conductances.