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Course materials for PSYC 132: Introduction to Programming for Psychological Scientists
A lightweight package to plot brain surfaces with Python.
Voxelwise modeling tutorial from the Gallantlab.
This repository contains the code to run the analyses from our paper on vmPFC dynamics.
A d3 layout for creating XKCD style narrative charts
A repo for the pre-course work at home exercises
Declarative statistical visualization library for Python
Interactive Data Visualization in the browser, from Python
A Python toolbox for gaining geometric insights into high-dimensional data
Princeton Handbook for Reproducible Neuroimaging
Code and tutorials to visualise your data that is both beautiful *and* statistically valid
The data and code for our IJCAI-ECAI 2018 paper: Constructing Narrative Event Evolutionary Graph for Script Event Prediction
Handout for the tutorial "Creating publication-quality figures with matplotlib"
NYU PSYCH-GA 3405.002 / DS-GS 3001.006 : Computational cognitive modeling
Data and code for the paper "Geometric models reveal behavioural and neural signatures of transforming naturalistic experiences into episodic memories" by Andrew C. Heusser, Paxton C. Fitzpatrick, …
Materials for Neurohackademy 2018 lectures, tutorials, etc.
Materials for my Mixed Model Workshop
Tutorials on how to use pandas effectively to do data analysis
An Introduction to Programming for Psychologists & Neuroscientists Course at Dartmouth PBS
Materials for Methods in Neuroscience at Dartmouth (MIND) 2017 Summer School on Network Dynamics
Data, stimuli, materials, and code for Tarantola et al, Prior preferences beneficially influence social and non-social learning. Nature Communications (2017)