research overview teaching nyuconcats resoures/code     - PyPsyExp     - SUSTAIN publications by year by category people - everyone - location map In the spirit of academic exchange and to avoid the unnecessary duplication of effort, we've collected a set of resources which may be helpful to other researchers. If you use our code in something the leads to a publication, please let us know. Also, we're open and receptive to bug finding/suggestions. PyPsyExp System - a simple, no hassle way to build experiments for higher-level cognition (where very precise timing and display control are less important relative to the ability to make flexible, dynamic interfaces and displays). The code provided here is generally implemented in Python. SUSTAIN - The Supervised and Unsupervised Stratified Incremental Network (more coming soon) Complex systems simulations (developed for teaching purposes and based on some things Rob Goldstone did): Game of Life - a simple python implementation of Conway's Game of Life Hebbian Learning - simple neural network simulator (could form the basis of additional code) Using R for analyzing experiments - a simple introduction to R. Software we like (mostly mac based): Web stuff we use in the lab:      Copyright 2009 - Todd Gureckis - New York University