Neurodynamics

The course provides a dynamical framework to study the brain using mathematical models and computer simulations with the aim of illustrating fundamental principles in Neuroscience. The aim of the course is two folds (a) to introduce students to standard mathematical models of individual neurons (with particular emphasis on Hodgkin Huxley framework for neuron modeling) and the synaptic events by which neurons communicate (b) to introduce students to macroscopic models for ensembles of neuron populations, i.e., mean field models, that allow for simulation of EEG dynamics.

The course is designed for advanced undergraduate and graduate students in engineering, mathematics, and biological sciences and will be primarily centered on the application of tools from dynamical systems to analyze models that mimic brain function. Time permitting we will also discuss plasticity in biological networks and its important function in emerging network properties of networks of neurons. The important goal of the course is to help prepare students to work in an interdisciplinary environment that includes both biological and mathematical scientists.

 

Credits: 
3
Type: 
BME Core Elective Courses
Course Number: 
BME 6938
Semester: 
Spring

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