Fits a multi-dimensional LNP-Integrator model to behavioral data.
- Feature extraction: time-varying stimulus is processed by LN models
- Integration: output of each LN ('firing rate') is integrated to yield a feature value ('spike count')
- Weighing: Feature values of multiple LN models are linearly combined to yield behavioral response value
Some tweaks to optimize performance:
- filter is represented in a raised-cosine basis
- nonlinearity is parameterized (sigmoidal)
- GPU implementation of the model for faster evaluation during fitting (using Matlab's GPU capabilities).
load('demo/demo.mat')% loading stimulus and response
p.bee = Behave(stim, resp, ..);
pGa = GA(p);This should produce the following Figure:
Jan Clemens, Bernhard Ronacher
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