Subunit models for characterizing responses of sensory neurons

On July 28th, I presented the following paper in lab meeting:

• Efficient and direct estimation of a neural subunit model for sensory coding,
  Vintch, Zaharia, Movshon, & Simoncelli, NIPS 2012

This paper proposes a new method for characterizing the multi-dimensional stimulus selectivity of sensory neurons. The main idea is that, instead of thinking of neurons as projecting high-dimensional stimuli into an arbitrary low-dimensional feature space (the view underlying characterization methods like STA, STC, iSTAC, GQM, MID, and all their rosy-cheeked cousins), it might be more useful / parsimonious to think of neurons as performing a projection onto convolutional subunits. That is, rather than characterizing stimulus selectivity in terms of a bank of arbitrary linear filters, it might be better to consider a subspace defined by translated copies of a single linear filter.

new paper in PLoS Comp Bio

Our paper came out online today!

Receptive Field Inference with Localized Priors
M. Park & J.W. Pillow
PLoS Comput Biol 7(10).  (2011).

Great to see it in print.  Strangely, PLoS CB doesn’t send galley proofs, and they introduced a small error in one of the figs. Hopefully they’ll agree to fix it…