Tag: Bayesian inference

Bayesian mixed effects model to estimate experimental parameters
I ran into a tricky problem while analyzing a series of experiments we recently performed with Scanbox. We’re trying to estimate the angle of the objective with respect to the cortical surface. The way we approach this is by scanning at a given depth, going down a little bit, scanning again, and so on. By […]

Spike identification through Gibbs sampling #1
Multiunit activity (MUA) is usually derived by highpass filtering a raw wideband signal, thresholding with a low threshold or rectifying, and subsequently using a lowpass filter. The intuition I think is correct, in that spikes from far away neurons will cause transient blips in the wideband signal which can be amplified by thresholding. The usual […]