Neuron Models: Type I and Type II

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Covers neurophysiological data analysis, including AP detection, firing rate computation, and spectral analysis, with a focus on predicting cell classes.

Engineering Neurons: Light, Chemicals, Sound

Explores optogenetics, chemogenetics, and sonogenetics to engineer neural activity using light, chemicals, and sound.

Neuronal Morphologies: Global Features and Measurements

Covers neuronal morphologies, visualisation, measurements, and statistical tests.

Likelihood of Spike Train in GLM

Covers the Generalized Linear Model (GLM) in computational neuroscience.

MathDetour 1: Separation of time scales

Explores the concept of separation of time scales in computational neuroscience and the reduction of detail in two-dimensional neuron models.

Neuronal Dynamics: Random Networks

Explores the dynamics of neuronal populations, emphasizing random networks and mean-field arguments for connectivity.

Dendrite as a Cable

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

Interspike Intervals & Renewal Processes

Explores interspike intervals, renewal processes, and escape noise experiments in neuronal dynamics.

Neural Signals and Signal Processing

Explores neural signal modeling, nervous system structure, and fiber classification for understanding neural phenomena.

Computational Neuroscience: Biophysics

Covers modern neuroscience synthesis, biophysical modeling, and brain building blocks with practical applications.