NS2003 - Computational Neuroscience
|* The offering term is subject to change without prior notice|
Brain computation is one of the important topics for scientists and engineers. Through understanding brain cells and synapses, many mathematical models for neurons and synapses are proposed. In addition, interesting dynamic pictures of networks of neurons show their potential for computations. For scientists, numerical exploration is an essential tool to understand how interactions of neurons support brain computations and functionalities. For engineers, understanding how the brain computes will be helpful for innovations. This course will begin with a brief introduction to differential equations and numerical methods. After that, this course will cover a collection of neuronal models and synaptic models. Then, the course will introduce techniques to construct random networks. Also, this course will include how artificial neuronal networks perform machine learning tasks. In addition, other computational issues related to Neuroscience, e.g., data analysis, will also be covered.
Assessment (Indicative only, please check the detailed course information)
Continuous Assessment: 60%
Examination Duration: 2 hours
Detailed Course Information
|Department of Neuroscience|