Abstract
Computational models can potentially be a very effective way to understand how the brain processes information. However, their power depends on the location of artificial features and errors of omission within the simulation, and on whether it is possible for the model to fail.
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References
Hodgkin, A. L., Huxley, A. F. A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. (Lond.) 117, 500–544 (1952).
Acknowledgements
I thank Garrett Kenyon and Javier Medina for comments. Supported by NIMH 46904 and 57051.
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Mauk, M. The potential effectiveness of simulations versus phenomenological models. Nat Neurosci 3, 649–651 (2000). https://doi.org/10.1038/76606
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DOI: https://doi.org/10.1038/76606
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