NEUR2110 Statistical Neuroscience
An introduction to random dynamical systems and stochastic processes in neuroscience. This is a lecture and computing lab course for senior undergraduate and graduate students with a background in systems neuroscience and/or applied math/biomedical engineering on the modeling of stochastic neural dynamics, with hands-on Matlab/Julia/Python-based applications to real and simulated data. Topics include modeling of stochastic multivariate time series and point processes in neuroscience and neuroengineering, time and spectral domain analyses, state-space models, and signal processing. These topics are addressed in the contexts of modeling neural dynamics in ensembles of neurons and brain networks, neural population encoding and decoding, among others. Example datasets include neuronal spike trains, local field potentials, ECoG/EEG.
NEUR1930H Neurological Disorders: Neural Dynamics & Neurotechnology
This seminar course provides an introduction to neural dynamics in neurological and neuropsychiatric disorders, and an overview of current therapeutic approaches based on open-/closed-loop Brain-Computer Interfaces (BCIs) and adaptive neuromodulation, e.g. Deep Brain Stimulation (DBS). The lectures and discussion sections cover: (1) Disorders of consciousness: Primary and secondary generalized epileptic seizures; Multiscale neural dynamics in human epilepsy; Basics of open- and closed-loop neuromodulation and seizure prediction/control; Coma, medically induced coma and general anesthesia; Consciousness and integrated information theory; Consciousness neuromonitoring; (2) Sensory disorders: Auditory, visual and proprioceptive/somatosensory neuroprostheses; (3) Movement disorders: Paralysis and BCIs for restoring movement and communication; adaptive DBS for Parkinson’s disease and essential tremor. (4) Neuropsychiatric disorders: DBS for major depression and obsessive compulsive disorder. Computational approaches for tracking ongoing brain states/dynamics in BCIs and closed-loop neuromodulation/DBS will be reviewed. The course addresses concrete applications of mathematical and statistical approaches introduced in detail in the course NEUR2110, Statistical Neuroscience. Enrollment is capped at 20. Instructor permission required.