Introduction to recurrent neural networks and their application to modeling and understanding real neural circuits.
Taught by: Larry Abbott, Columbia University
- Learning in recurrent neural networks (1:16:39)
- Notes on Boerlin, Machens and Deneve (learning in recurrent spiking network) - Larry Abbott's notes
- Recursive Least-Squares Algorithm - Larry Abbott's notes
- Sompolinsky, H., Crisanti, A. & Sommers, H. J. (1988) Chaos in random neural networks, Physical Review Letters 61:259.
- Rajan, K., Abbott, L. F. & Sompolinsky, H. (2010) Stimulus-dependent suppression of chaos in recurrent neural networks, Physical Review E 82:011903.
- Sussillo, D. & Abbott, L. F. (2009) Generating coherent patterns of activity from chaotic neural networks, Neuron 63:544-557.
- Boerlin, M., Machens, C. K. & Deneve, S. (2013) Predictive coding of dynamic variables in balanced spiking networks, PLoS Computational Biology 9:e1003258.