Collection of material for the course in Computational Neuroscience (LM-55).
Eugene M. Izhikevich, Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting The MIT Press, 2007 here
Dayan, P. (2005). Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems. MIT Press. here
Gerstner, Wulfram, et al. Neuronal dynamics: From single neurons to networks and models of cognition. Cambridge University Press, 2014. here
The slides of the course can be found at the following links:
Bassett, D. S., Zurn, P., and Gold, J. I. (2018). On the nature and use of models in network neuroscience. Nature Reviews Neuroscience 19(9):566-578. doi: 10.1038/s41583-018-0038-8
Blohm, G., Kording, K. P., and Schrater, P. R. (2020). A how-to-model guide for Neuroscience. Eneuro, 7(1). doi: 10.1523/ENEURO.0352-19.2019
Churchland, P. S., and Sejnowski, T. J. (1990). Neural representation and neural computation. Philosophical Perspectives 4: 343-382. doi: 10.2307/2214198
Cichy, R. M., and Kaiser, D. (2019). Deep neural networks as scientific models. Trends in cognitive sciences, 23(4), 305-317. doi: 10.1016/j.tics.2019.01.009
Feldman, J. (2016). The simplicity principle in perception and cognition. Wiley Interdisciplinary Reviews: Cognitive Science 7(5): 330-340. doi: 10.1002/wcs.1406
Goldstein, R. E. (2018). Point of View: Are theoretical results ‘Results’?. Elife 7: e40018. doi: 10.7554/elife.40018
Jonas, E., and Kording, K. P. (2017). Could a neuroscientist understand a microprocessor?. PLoS computational biology 13(1): e1005268. doi: 10.1371/journal.pcbi.1005268
Kording, K., Blohm, G., Schrater, P., and Kay, K. (2018). Appreciating diversity of goals in computational neuroscience. doi: 10.31219/osf.io/3vy69
Lee, M. D., Criss, A. H., Devezer, B., Donkin, C., Etz, A., Leite, F. P., ... and Vandekerckhove, J. (2019). Robust modeling in cognitive science. Computational Brain & Behavior 2(3): 141-153. doi: 10.31234/osf.io/dmfhk
Parker, W. S. (2012). Computer simulation and philosophy of science. Metascience, Vol. 21, pp. 111–114. doi: 10.1007/s11016-011-9567-8
Schrater, P., Kording, K., and Blohm, G. (2019). Modeling in Neuroscience as a Decision Process. OSF Preprints. url: osf.io/w56vt
Wilson, R. C., and Collins, A. G. (2019). Ten simple rules for the computational modeling of behavioral data. Elife 8: e49547. doi: 10.7554/eLife.49547