Code to fit spike trains with the Conductance-based encoding model.
Contains Python and Matlab implementations of the analyses found in Latimer et al. 2014.
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From command line:
git clone git@github.com:pillowlab/CBEM.git -
In browser: click to Download ZIP and then unzip archive
Open exampleScript.m to see it in action using a small simulated dataset
The pyCBEM code uses a Python + Jax implementation of the CBEM for retinal ganglion cells. The notebook "exampleCBEMfitting.ipynb" shows how to use this.
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K. W. Latimer, F. Rieke, & J. W. Pillow (2019) Inferring synaptic inputs from spikes with a conductance-based neural encoding model eLife 8 (2019): e47012.
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K. W. Latimer, E. J. Chichilnisky, F. Rieke, & J. W. Pillow (2014). Inferring synaptic conductances from spike trains with a biophysically inspired point process model Advances in Neural Information Processings Systems 27, 954-962.