Features

For estimating LN-type models from spiking data.

Model types include:

• standard STA and STC analysis
• STA and STC with a parametric information-theoretic objective
• wrapper for MID
• wrapper for sparse GLMs
• ML estimation of linear and quadratic models with regularization

Demo

load('demo.mat')% load sample spikeTimes and stim
resolution = 1;%ms
filterDuration = 64;%samples
sr = SpikeResp(spikeTimes, resolution);
sr.setStim(stim, resolution);
sf = FeaturesSTC(sr, filterDuration);
sf.getFeat();
plot(sf.STA);

Code base used in:

Jan Clemens, Sandra Wohlgemuth, Bernhard Ronacher
Nonlinear computations underlying temporal and population sparseness in the auditory system of the grasshopper
2012, Journal of Neuroscience, 32(29):10053-10062 | pdf

Jan Clemens, Olaf Kutzki, Bernhard Ronacher, Susanne Schreiber, Sandra Wohlgemuth
Efficient transformation of an auditory population code
2011, PNAS, 108:13812-13817 | pdf