Fig. 1: Application of the state-space kinetic Ising model to two simulated neurons.
A A schematic of the time-dependent kinetic Ising model for two neurons with field and coupling parameters. The links between the nodes represent the neurons' causal interactions with arrows indicating the time evolution from the past to the present. B Raster plots for the two neurons. The vertical axis represents the number of trials, and the horizontal axis shows the number of time bins. C The approximate marginal log-likelihood as a function of the iteration steps of the EM algorithm. D The optimized hyperparameter Qi for neuron 1 (left) and neuron 2 (right). E (top) Estimated and true time-dependent field parameters. The solid lines represent the MAP estimates of the field (first-order) parameters obtained from the smoothing posterior, θt∣T. The shaded areas show the 95% credible intervals derived from the diagonal elements of the smoothed covariance matrix, Wt∣T. The dotted lines are the field parameters from true θt used to generate the data. (middle, bottom) Estimated and true time-dependent coupling (second-order) parameters.
