Biological neuron model

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Related lectures (32)

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Generalized Integrate-and-Fire Models

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

Attractor Networks and Spiking Neurons

Explores attractor networks, spiking neurons, memory data, and realistic networks in neural dynamics.

Three definitions of rate code

Discusses three definitions of rate code in computational neuroscience, emphasizing temporal averaging, interspike intervals, and FANO factor.

AdEx: Adaptive exponential integrate-and-fire

Covers the AdEx model, firing patterns, adaptation, and parameter estimation.

Computational Neuroscience: Biophysics & Modeling

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

Neuronal Dynamics: D2 Transients

Explores transients in neuronal dynamics, including the Spike Response Model and simulations of neuron populations.

Neural Signals and Signal Processing: Modeling and Simulation

Covers the fundamentals of neural signals and signal processing, focusing on modeling and simulation of neural systems.

Neurons and Synapses: Overview

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

Quality of Integrate-and-Fire Models

Explores the quality of Integrate-and-Fire models in computational neuroscience through comparisons with experimental data and mathematical predictions.

Biophysical Models: Ion Channels

Explores the zoo of ion channels and their functional roles in biophysical neuron models.