Explores the variability of spike trains in computational neuroscience, covering experiments, sources of variability, and stochastic spike arrival and firing.
Explores the application of computational neuroscience in neuroprosthetics, focusing on predicting intended arm movements based on spike times and the importance of systematic parameter optimization.
Explores the stationary mean-field concept in computational neuroscience to predict neuronal activity based on population and single neuron firing rates.
By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Explores detailed modeling of ion channels and neuronal morphologies in in silico neuroscience, covering neuron classification, ion channel kinetics, and experimental observations.
