Experimental Data Techniques: Caveats and Summary

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Single Neuron Data Collection Techniques

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Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

Models and data

Covers the optimization of neuron models for coding and decoding in computational neuroscience.

Dendrite as a Cable

Discusses dendrites as cables, covering the cable equation derivation and current conservation in coupled compartments.

Leaky Integrate-and-Fire Model

Explores the Leaky Integrate-and-Fire Model in computational neuroscience, emphasizing single neuron dynamics.

Neuronal Dynamics: Aims and Challenges

Explores the aims and challenges in computational neuroscience, focusing on neuronal dynamics of cognition and mean-field arguments.

Computational Neuroscience: Biophysics & Modeling

Covers the fundamentals of computational neuroscience, focusing on biophysics and modeling.

Reduction to 2 dimensions: Exploiting similarities

Explores reducing the Hodgkin-Huxley model to 2 dimensions by exploiting similarities between variables and discussing the nonlinear integrate-and-fire model.

Neurosciences I: Molecular Neuroscience and Neurodegeneration

Covers molecular neuroscience, neurodegeneration, cell types, neuron structure, and history of neuroscience breakthroughs.