Tutorials with code and exercises
Crash course in scientific Python (created for the IBRO-Simons Computational Neuroscience Imbizo)
The joy of random processes (created for the IBRO-Simons Computational Neuroscience Imbizo)
Working with spikes in computational neuroscience (created for the IBRO-Simons Computational Neuroscience Imbizo)
Video tutorials
Neuroscience – Tuning curves (10:00)
Probablity – Gaussians (30:32)
Probability – 2-dimensional distributions (13:36)
Probability – Entropy (26:00)
Probability – Information theory (16:37)
Linear algebra – Changing basis (18:57)
Linear algebra – Functions are vectors (30:02)
Linear algebra – Eigenvalues and eigenvectors (24:14)
Dynamical systems – 1-dimensional systems (11:39)
Dynamical systems – 2-dimensional system (13:11)
Signal processing – Convolutions and linear systems (16:16)
Optimization – Gradient ascent (15:49)
Code examples (in Python)
Leaky integrate-and-fire neuron (under construction)
Chaos in random networks (under construction)
Exponential filtering in a linear differential equation
Power spectral density computation
Power law emergence from random-walk first-passage times
Algorithms
Infotaxis math and demo (based on Vergassola, Villermaux, Shraiman 2007)