-
More neural datasets from CRCNS
From its humble beginnings about 5 years ago, the CRCNS data sharing website has grown into a very useful resource for modelers looking to test out their theories and algorithms on neural datasets. Vision-wise, the dataset includes: eye tracking data fMRI with natural images mouse LGN cat, primate primary visual cortex with natural images, gratings
-
GPU computing: which card should you get?
Running number-crunching code on a top-of-the-line graphics card can be 10x faster than on a comparably high-end CPU. Not every application will see a 10x benefit – Monte Carlo simulations, image processing, matrix-vector-product-heavy code are excellent candidates. Thanks to general-purpose linear-algebra-on-the-GPU classes – like gpuarray, gnumpy and Data.Array.Accelerate – it’s possible to run high-level Matlab, Python
-
Fast 1D and 2D data binning in Matlab & Python
I needed a fast method of binning 1D and 2D data in Matlab – that is, to compute the mean of z conditional on x being in a given range (1d binning) or the mean z of conditional on x and y being in given ranges (2d binning). I stumbled upon a clever method using
-
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
-
NIPS 2013 papers
Fresh off the presses, NIPS 2013 conference papers are here. Here’s a nice visualization complete with PDF preview, keyword analysis and categorization – via LDA, appropriately enough. Topic 6 appears to be neuroscience. Via Nuit Blanche.
-
Category information in the brain
The Gallant lab have a new paper out in Neuron using fMRI to study the brain’s representation of visual scene categories. It’s a slick little paper, using some fun machine learning algorithms (Latent Dirichlet allocation) that shows that there’s a substantial amount of latent semantic information available at the fMRI macroscale – raising the question
xcorr: AI & neuro 