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PSY6307   Computational Neuroscience 1: Biologically Grounded Models   (15 credits)

 
Year Running: 2017/2018
Credit level: F7
Additional Information   This unit can accept a total of up to 20 students, subject to space and resource limitations.Pre-requisite: A Levels Maths or equivalent

Description

This module starts with a primer on neuroscience and the role of computational neuroscience. The next part of the module covers abstract neuron models and introduce classic computational principles and learning rules related to neural networks. From there we move to more biologically grounded models and deal with single neuron models including leaky-integrate-and-fire and conductance-based neurons. Finally, we examine higher levels of description, in particular systems in context of reinforcement learning. While the emphasis throughout the module is on methodological issues, how models can be built, tested and validated at each level, we will also draw connections to specific brain regions to motivate and illustrate the models.

 

Reading List


Please click here for reading list.
 

Teaching Methods

Delivery Type Hours
Independent 113.0
Lab 6.0
Lecture 26.0
Seminar 2.0
 

Methods of assessment

Assessment Type Duration % of formal assessment Semester
Exam 3.0 100 % S1
 

Teaching methods and assessment displayed on this page are indicative for 2023-24.