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Related lectures (32)
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Likelihood of Spike Train in GLM
Covers the Generalized Linear Model (GLM) in computational neuroscience.
Parameter estimation
Explores parameter estimation in neuron models, focusing on quadratic optimization and linear fit.
Scientific Computing in Neuroscience
Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.
Generalized Integrate-and-Fire Models
Explores the Generalized Integrate-and-Fire Model and the Nonlinear Integrate-and-Fire Model.
In Silico Neuroscience: Ion Channels and Neuronal Models
Explores detailed modeling of ion channels and neuronal morphologies in in silico neuroscience, covering neuron classification, ion channel kinetics, and experimental observations.
Leaky Integrate-and-Fire Model
Explores the Leaky Integrate-and-Fire Model in computational neuroscience, emphasizing single neuron dynamics.
Spike Response Model (SRM)
Covers the Spike Response Model (SRM) in computational neuroscience and its relation to the adaptive leaky integrate-and-fire model.
Modeling in vitro data
Explores modeling in vitro data for computational neuroscience, including predicting subthreshold voltage and spike times.
AdEx model: Firing patterns and phase plane analysis
Explores the AdEx neuron model, analyzing firing patterns and phase planes.
Three definitions of rate code
Discusses three definitions of rate code in computational neuroscience, emphasizing temporal averaging, interspike intervals, and FANO factor.
