Category: Decoding
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SFN 2014 poster – converging encoding strategies in dorsal and ventral visual streams
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…
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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…
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Adam Kohn on population coding
Adam delivered a pretty intense lecture at CSHL on population coding, correlations and phase-locking. Consider myself mindfucked. Mainen & Sejnowski (1995) showed that single neurons have very reliable responses to current injections. Nevertheless, cortical neurons seem to have Poisson or supra-Poisson variability. It’s possible to find a bound on decodability using the Fisher information matrix (Sompolinsky…
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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…
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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…
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Decoding fMRI activity evoked by natural movies
The Gallant lab have just published a new paper in Current Biology about decoding visual activity in fMRI evoked through natural movies. TryNerdy has a very high level overview of the paper. Here I’m more interested in the nitty gritty computational/statistical details. The idea is to train an encoding model using fMRI responses during natural…