Figure 1. A hidden Markov model of ensemble activity during PBEs.
A hidden Markov model of ensemble activity during PBEs. (a) Examples of three PBEs and a run epoch. (b) Spikes during seven example PBEs (top) and their associated (30 state HMM-decoded) latent space distributions (bottom). The place cells are ordered by their place fields on the track, whereas the non-place cells are unordered. The latent states are ordered according to the peak densities of the lsPFs (lsPFs, see Materials and methods). (c) The transition matrix models the dynamics of the unobserved internally-generated state. The sparsity and banded-diagonal shape are suggestive of sequential dynamics. (d) The observation model of our HMM is a set of Poisson probability distributions (one for each neuron) for each hidden state. Looking across columns (states), the mean firing rate is typically elevated for only a few of the neurons and individual neurons have elevated firing rates for only a few states.