Bayesian inference for model selection centres on comparing competing hypotheses by evaluating how well each model explains observed data, accounting for prior beliefs about parameters. The ...

A Bayesian particle Gibbs framework enables unbiased spike time inference with millisecond resolution and jointly estimates uncertainties in both spike timing and model parameters from fast calcium ...