Reduction to 2 dimensions: Exploiting similarities

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

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

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

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

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

Explores the Generalized Integrate-and-Fire Model and the Nonlinear Integrate-and-Fire Model.

Explores the behavior of a 2D neuron model with constant input.

Covers computational neuroscience basics, single neuron models, synapses, and neural variability.

Covers modeling electrophysiology at different scales, discussing ion channels, single neurons, and microcircuits.

Explores the study of single neurons, challenges in classification, and obtaining high-resolution data.