This repository is meant to encompass how I've personally been introduced to computational neuroscience.
It's primarily evidence of what I've worked with in completion of coursework. This is structured in four practicals:
- Integrate and Fire model of single neurons | MATLAB
- Here I've expanded the coursework with an introduction to attractor dynamics in neuronal networks.
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Spike-Time Histogram with simulated neuronal spike data | MATLAB
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Reverse Correlation using Spike-Triggered averaging | MATLAB
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Nonlinear Neuronal Networks | PYTHON
- A self-led exploration of artificial neural networks (including my first implementation of backpropagation gradient descent)