MSc Neuroimaging for Clinical & Cognitive Neuroscience / Course details

Year of entry: 2021

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Course unit details:
Image Analysis

Unit code BIOL62121
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Offered by School of Biological Sciences
Available as a free choice unit? No

Overview

This unit will explore the image analyses aspects of a number of neuroimaging techniques covering both theoretical and practical perspectives. Students will gain valuable hands-on experience with a number of analysis packages, with the aim of consolidating and building upon their knowledge of image analysis theory.

In turn, gaining a comprehensive knowledge and understanding of the various stages of analysing neuroimaging and electrophysiological data will provide a firm foundation upon which any future image analysis package can be learnt, with relative ease.

The unit will also explore the relative strengths and weaknesses of selecting various imaging parameters and the resulting inferences that can be drawn.

Aims

The course aims to provide students with a comprehensive knowledge of functional and structural neuroimaging and electrophysiological methodologies. The unit focuses on the image analyses aspects of a number of techniques including fMRI, EEG and ERP.

In addition to gaining knowledge of image analysis theory, students will learn how to conduct various aspects of image analysis through hands-on experience with analyses packages.

Learning outcomes

By the end of the course, students will be able to:

  • have comprehensive understanding of each stage of image analysis;
  • have a well-developed knowledge of the advantages and disadvantages of each analysis parameter;
  • draw appropriate inferences based on the image analysis employed;
  • evaluate the appropriateness of using a particular neuroimage analysis method;
  • consider the various strengths and weaknesses of different analyses techniques;
  • gain experience of and expertise with all the stages of preprocessing neuroimaging data;
  • perform both participant- and group-level statistics on neuroimaging data;
  • analyse neuroimaging data for various designs, such as blocked, event-related and mixed designs.

Teaching and learning methods

The course will be taught through a combination of linked lectures and lab sessions (12 x two hours over six weeks). Additional lab sessions and lab support will be available for students.

The course will be supported by a dedicated e-learning package providing step-by-step training and assessment. Students will be required to keep an online diary of their progress for monitoring and assessment.

Teaching will be complemented by the availability of notes, slides and recommended reading.

Assessment methods

Method Weight
Written exam 50%
Report 50%

Feedback methods

Formative feedback available.

Study hours

Scheduled activity hours
Lectures 24
Independent study hours
Independent study 126

Teaching staff

Staff member Role
Cheryl Capek Unit coordinator

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