Technical content for MSc Cognitive and Computational Neuroscience
The MSc Cognitive and Computational Neuroscience courses uses mathematical concepts, and a large amount of teaching time is devoted to equipping you with the skills and techniques you need. The main thing we ask for is a willingness to learn as you study topics such as:
- Probability theory, probability density functions, Bayes' theorem and maximum likelihood estimation;
- Calculus, differential equations, and finding extrema of functions;
- The general linear model for regression and parameter estimation;
- Programming MatLab to test computational models.
To give you an understanding of the sort of technical knowledge you'll be aiming to have by the end of your training, we've included some documents below:
- Mathematics for computational neuroscience and imaging (PDF, 1.3MB)
- Single neuron models (PDF, 6.3MB)
- Vectors (PDF, 1.3MB)
You can find out more about the course by visiting the University of Sheffield's online prospectus:
Find a postgraduate course
A masters from Sheffield means in-depth knowledge, advanced skills and the confidence to achieve your ambitions.