State-space GLMs for neural data: a simple example

State space methods are a very broad class of methods to analyze temporal data. At its most basic, you assume that your temporal data is generated by a model with underlying parameters. The parameters are time-varying, and usually it’s assumed that the temporal variation is generated through Markovian dynamics. That is, at every time-step, the… More State-space GLMs for neural data: a simple example