Welcome to the Computational Memory Lab at Princeton University!
Our lab uses neural decoding methods, applied to fMRI and EEG data, to test the predictions of computational models of learning and memory.
Click on the Publications link to access our publications online. The rest of this site is under construction.
We are looking for a postdoc! For more info, check out this PDF.
Come see us at SfN 2016! Here is an itinerary of our poster sessions.
We have developed a Matlab toolbox (P-CIT) that can be used to estimate the shape of the curve relating a predictor variable (e.g., fMRI classifier estimates of memory activation) to a dependent variable (e.g., subsequent memory recall). The toolbox can also be used to estimate the posterior probability that the curve meets some (arbitrarily defined) set of criteria. The toolbox and documentation can be found here: P-CIT.
Mike Adelson has created software for running experiments using the emotiv EEG headset. The software and documentation can be found here: Emotiv.