Implementation of Kiah Hardcastle's Linear-Nonlinear model from Hardcastle et al., 2017..
- Refactors code to make it more modular
- Implements some bug-fixes
- Incorporates model into RatCatcher architecture.
Code implements the LN model used to describe spike trains of MEC neurons based on the animal's position, head direction, speed, and theta phase information. Used in Hardcastle et al., 2017.
Run_me.m is the main script. This will load the data from a single cell, fit the 15 LN models (as described in Hardcastle et al., 2017), select the best model according to a forward search procedure, and then plot the results. Details for each step can be found in run_me.m, and the scripts listed within run_me.m.
Questions can be directed to [email protected]