Category: GLMs

• Journal club express #1

  I’m introducing a new (hopefully recurring) feature on the blog: the Journal Club express. Lengthy discussions of papers are quite time-consuming to write, so instead I’ll periodically highlight a few recent papers I’ve read that I think could be interesting to regular readers. There’s a new Neuron paper from John Maunsell’s lab that shows an…

  February 29, 2012

• 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…

  February 20, 2012

• Lecture slides on Generalized Linear and Additive models

  I gave a lecture yesterday as part of Chris’ computational neuroscience class on generalized linear and additive models (GLMs and GAMs) and their application to neuroscience. A lot of the people in the class have little to no background in stats so I kept it very basic. I also have exercises involving the estimation of a…

  February 16, 2012

• Using a particle filter to decode place cells

  In the last post, I discussed using an extended Kalman filter to decode place cells, based on the algorithm published in Brown et al. (1998). The results looked pretty good. EKFs are certainly better than population vector approaches that don’t consider the sequential nature of the decoding task. The fact that the path of the…

  February 7, 2012

• Using an iterated extended Kalman filter to decode place cells

  Decoding neuronal activity is a powerful technique to study how information is encoded in a population and how it might be extracted by other brains areas. Hippocampal place cells are a prime example of a system that can be studied fruitfully from a decoding persepective. In a typical place cell decoding experiment, a population of…

  February 6, 2012

• Hierarchical processing of complex motion

  I’m thrilled to announce that our paper, Hierarchical processing of complex motion along the dorsal visual pathway, has been published in PNAS. In this work, we looked at the response properties of neurons in area MST (the medial superior temporal area). MST neurons are part of the dorsal visual pathway; they are strongly selective for…

  January 31, 2012