Spike-triggered mixture of gaussians

  Nice new paper out from Matthias Bethge’s group on neural systems identification. The proposed method can be considered an extension of the spike-triggered average/spike-triggered covariance approaches. In STA/STC, you’re characterizing the spike-triggered stimulus ensemble and comparing it to the baseline stimulus ensemble. Assuming for a moment that the baseline ensemble is iid Gaussian, then … More Spike-triggered mixture of gaussians

Why second-order methods can be futile in non-convex problems

I’ve been working on fitting a convolutional model of neurons in primary and intermediate visual cortex. A non-convex optimization problem must be solved to estimate the parameters of the model. It has a form similar to: There are some shared weights to further complicate things, but the most salient features is that it’s a 3-layer … More Why second-order methods can be futile in non-convex problems

Learning about GLMs and GAMs in neuroscience

During my lecture on Wednesday, a few students asked me where they could learn more about generalized linear and additive models (GLMs and GAMs) and their applications to systems identification in neuroscience. Unfortunately, there are few textbooks in computational neuroscience, and most cover systems identification to some degree, most notably Marmarelis’ latest. To the best … More Learning about GLMs and GAMs in neuroscience