Category: Receptive field estimation

SFN 2014 poster – converging encoding strategies in dorsal and ventral visual streams

November 14, 2014

I have a poster session on Sunday afternoon at SFN 2014 in DC. It’s on a spiffy new method I’ve been working on for estimating the nonlinear transformation performed by an ensemble of sensory neurons, and its application to understanding visual representation in the dorsal and ventral visual streams. Some background: there’s a growing consensus … More SFN 2014 poster – converging encoding strategies in dorsal and ventral visual streams

PhD thesis – Parametric Models of Visual Cortex at Multiple Scales

April 2, 2014

*Updated Sun April 6th* Well it’s done! I successfully defended my thesis on April 3rd. I now have what I’ve been longing for all these years – an obnoxious title that I can remind people of whenever I’m about to lose an argument. Unfortunately, this only works when erguing with non-PhDs. Entitled Parametric Models of … More PhD thesis – Parametric Models of Visual Cortex at Multiple Scales

Non-negative matrix factorization for receptive field analysis

April 1, 2014

Using Non-negative matrix factorization instead of SVD Sujay, a labmate of mine came to me with an interesting analysis problem. He’s looking at perisaccadic changes in receptive fields in V4. The saccade-triggered receptive fields shows two activations: an initial one at the pre-saccadic location, and a later one at the remapped location. Basically, the activation … More Non-negative matrix factorization for receptive field analysis

Workshop on statistical challenges in neuroscience

January 22, 2014

My old buddy Simon Barthelmé as well as Nicolas Chopin and Adam Johansen are organizing a 3-day workshop in Warwick, UK in September on statistical challenges in neuroscience. Some of the invited speakers include J.D. Victor, Robert Kass and Aapo Hyvärinen. Great chance to discuss and present your latest methods-heavy research. Here’s the pitch: Workshop … More Workshop on statistical challenges in neuroscience