Supplementary Material: Estimating Fluctuations in Neural Representations of Uncertain Environments

In the framework specified in section 2.2, we use a first-order Markov chain with two states as our Figure S1: For four different cells, the posterior distribution function is computed and depicted. Here, we concentrate only on trials within original environments, where we know the correct environment and hence can assess how well is the decoding. In this approach, instead of using a state-space structure, we use the likelihoods given by Eq. (1) of Each plot shows a histogram of the average probability (over time) of correctly decoding the trials within unambiguous environments. Fig. S3 shows the decoded environment for a few sample trials based on the neural activity of the whole population. In some trials (e. g. trials 65 & 25) we observe few fluctuations, while in other In Eq. 6, we use a history dependent, gamma-distributed generalized linear model with identity link.