Tutorial on how to perform multi-scale simulation of Alzheimer's disease on The Virtual Brain Simulation Platform. Authors: L. Stefanovski, P. Triebkorn, M.A. Diaz-Cortes, A. Solodkin, V. Jirsa, A.R. McIntosh, P. Ritter
A brief overview of the Python programming language, with an emphasis on tools relevant to data scientists. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.
Jake Vogel gives a hands-on, Jupyter-notebook-based tutorial to apply machine learning in Python to brain-imaging data.
The lesson was presented in the context of the BrainHack School 2020.
As a part of NeuroHackademy 2020, Elizabeth DuPre gives a lecture on "Nilearn", a python package that provides flexible statistical and machine-learning tools for brain volumes by leveraging the scikit-learn Python toolbox for multivariate statistics. This includes predictive modelling, classification, decoding, and connectivity analysis.
This video is courtesy of the University of Washington eScience Institute.
Colt Steele provides a comprehensive introduction to the command line and 50 popular Linux commands. This is a long course (nearly 5 hours) but well worth it if you are going to spend a good part of your career working from a terminal, which is likely if you are interested in flexibility, power, and reproducibility in neuroscience research.
This lesson is courtesy of freeCodeCamp.