Tag: Receptive field

• Non-negative matrix factorization for receptive field analysis

  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…

  April 1, 2014

• Tips on using crcns datasets

  I’ve mentioned before that the CRCNS web site has a number of neural datasets available for download. To save you some time, here’s some tips to get you up and running for specific datasets. V2-1 data Jack Gallant’s V2 dataset is really interesting; I think it’s fair to say that we know very little about…

  March 29, 2014

• GLMs and Hidden Markov models for single neurons

  I posted recently about modeling neurons with continuous state-space dynamics. It’s also possible to model neurons with Hidden Markov models (HMMs), which are state-space models with discrete rather than continuous states. In this post I’m going to focus on the application of HMMs to single neuron data. Single neurons with simple states Suppose that a…

  October 21, 2011

• Using the SVD to estimate receptive fields

  Spatio-temporal receptive fields can be hard to visualize. They can also be quite noisy. Thus, it’s desirable to find a low-dimensional approximation to the RF that is both easier to visualize and less noisy. The SVD is frequently used in neurophysiology for this purpose. Reading the Wikipedia page on the SVD, you might have trouble…

  September 20, 2011

• In the eyes of a cat

  U of C grad student and former undergrad minion of mine Kyler Brown has a demonstration of the “Cat Cam” data over at Bytes and Spikes. The movie was created by attaching a camera to a freely roaming cat in a natural environment and playing it back to an eye-tracked cat. So you get both…

  September 19, 2011