EEE 482 Computational Neuroscience

Mathematical techniques for analysis and modeling of neural systems. Neural encoding: reverse-correlation and regression, receptive-field models. Representation: Hebbian learning (PCA), sparse coding (ICA). Cortical maps: clustering, dimensionality reduction, manifold models. Neural decoding: classification, identification, Bayesian inference. Connectomics: structural and functional connectivity. Credit units: 3 ECTS Credit units: 6, Prerequisite: MATH 220 or MATH 225 or MATH 241.

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