MSc Neuroimaging for Clinical & Cognitive Neuroscience / Course details

This module will provide theoretical background and practical instruction on a number of key advanced methods in neuroimaging analysis, including connectivity, multivariate pattern analysis, advanced diffusion and PET methods, and M/EEG source estimation.

Lectures will focus on the theoretical issues underlying the methodology such as anatomical, functional, and effective connectivity; pattern-information mapping vs. mass-univariate modelling; parametric vs. non-parametric statistical methods; and Bayesian approaches to inverse problems. Practical sessions will apply the theory introduced in lectures and provide introductory hands-on training in a number of advanced analysis methods. The course builds on the Image Analysis unit by exploring recent developments in neuroimaging analysis techniques and proposed solutions to specific problems and challenges.

• To provide students with an introduction to, and a working knowledge of, a selection of advanced neuroimaging techniques, focusing on both acquisition and analysis methodology.
• To provide some advanced mathematical, statistical, and neurophysiological background to these methods.

At the end of this unit students will:

• have a solid grasp of a selection of advanced neuroimaging techniques and how they can be used to contribute to research;
• understand some of the mathematical, statistical and neurophysiological factors underlying these advanced methods;
• understand the neurophysiological issues that need to be addressed by the advanced techniques;
• be able to evaluate the use of advanced neuroimaging analysis techniques to answer specific questions about brain function;
• be able to select the most appropriate technique to address the question in hand;
• be able to discuss some of the mathematical and statistical models and assumptions that underlie the methods;
• have some specialised analysis skills.
   

The course will be taught through a combination of linked lectures and lab sessions; 12 x two-hour sessions over six weeks. Teaching will be complemented by the availability of notes, slides and recommended reading.

• Two lab reports each worth 50% of the overall mark.

No information available