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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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Sorting calcium imaging signals
Calcium imaging can record from several dozens of neurons at once. Analyzing this raw data is expensive, so one typically wants to define regions of interest corresponding to cell bodies and work with the average calcium signal within. Dario has a post on defining polygonal ROIs using the mean fluorescence image. Doing this manually is fairly time-consuming and it
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Off-the-shelf optimization functions in Matlab
Estimating a statistical model via maximum likelihood or MAP involves minimizing an error function – the negative log-likelihood or log-posterior. Generic functions built in to Matlab like fminunc and fmincon will often do the trick. There are many other free solvers available, which are often faster, or more powerful: Solvers by Mark Schmidt: there’s a huge collection of functions from Mark
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Non-rigid deformation for calcium imaging frame alignment
Following my PhD at McGill, I moved to LA to work in Dr. Dario Ringach’s lab at UCLA. We’ve been doing calcium imaging – GCamp6 – in mice via a custom-built microscope – you can read more about the microscope over at the Scanbox blog. If you’re used to working with single electrodes or multi-unit
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PhD thesis – Parametric Models of Visual Cortex at Multiple Scales
*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
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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
xcorr: AI & neuro 