Statistical Neuroscience

NEUR 2110 S01 [CRN: 16066]

A lecture and computing lab course for senior undergraduate and graduate students with background in either systems neuroscience or applied math/biomedical engineering on the statistical analysis and modeling of neural data, with hands-on Matlab(Octave)/Python-based applications to real and simulated data. Topics will include signal processing, hypothesis testing and statistical inference, modeling of multivariate time series and stochastic processes in neuroscience and neuroengineering, neural point processes, time and spectral domain analyses, and state-space models. Example datasets include neuronal spike trains, local field potentials, ECoG/EEG, and fMRI. Sign-up sheet in Sidney Frank Hall, Room 315 beginning on the first day of registration. Instructor permission required.
Fall 2020
Credit Hours
Maximum Enrollment
Primary Instructor
17:00 - 19:00 Tue, Wed - from Sep 9, 2020 to Dec 21, 2020
Exam Group Code