JEB1444H Neural Engineering

Streams

Clinical Engineering

Sessions

Winter

Description

Neural Engineering is an emerging field of research at the crossroads of neuroscience, electrophysiology, signal processing, computer science and nonlinear science. Neural Systems exhibit an amazing variety of instabilities, fluctuations, richness of forms and structures. They can be modeled at the micro and macro levels using parametric and nonparametric methods that are based on differential and integral equations, respectively. Topics covered in the course include the following: (i) A general perspective of neurobiology and neural engineering. (ii) Parametric neural models described by nonlinear rate processes. (iii) Nonparametric neural models described by the Volterra-Wiener approach. (iv) Applications to neural systems. 

Two computer-based projects, dealing with a parametric and a non-parametric neural model, provide hands on experiences to supplement the lectures.

Prerequisites

Undergraduate engineering background covering electrical fundamentals and digital signal processing

Components

Lecture

Restrictions

None