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Neural Coding and Computation

This code deals with simulating biological neurons to understand how data is encoded in the brain and the larger scope of neuronal dynamics. Neuron models such as the RC circuit model and Hodgkin-Huxley model are developed and tested. The models are then extended to include synapses and short term synaptic plasticity.

Neuronal signals are processed as "spike trains."

As part of the AMATH 342 class at the University of Washington, the HW 8 file introduces machine learning through neural networks, building on biological principles.

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