PYM0FM-fMRI Data Analysis

Module Provider: Psychology
Number of credits: 10 [5 ECTS credits]
Terms in which taught: Spring term module
Non-modular pre-requisites:
Modules excluded:
Module version for: 2017/8

Module Convenor: Dr Etienne Roesch


Summary module description:
The purpose of this module is to provide students with practical experience of analysing fMRI data. Each session will begin with a lecture providing theoretical background. The second part of each session will be devoted to hands-on experience of data processing. Student’s will first familiarize themselves with the most common sequence of processing steps that are applied to fMRI data, and then explore alternative approaches by comparing two or more approaches to the same data set. The software package used will be FSL (


Assessable learning outcomes:
By the end of the course, students should be able to:

1)Understanding theoretical issues in fMRI data analysis (e.g., haemodynamic response, motion and other artifacts in the time series, the multiple statistical comparisons problem)
2)Understand and perform preprocessing of fMRI time series (e.g., realignment, registration to standard space, spatial smoothing)
3)Set up a general linear model capturing experimental and nuisance effects in data and try out one or more ways of fitting the model to the data
4)Understand and navigate coordinate system for reporting activations (stereotaxic space)
5)Make statistical comparison of activation level across the brain between two experimental conditions (contrasts, t-test) for a single subject
6)Compare activation in two experimental conditions at the group level

Additional outcomes:
This module will provide a valuable introduction to methods of analysis in brain imaging research. It will thus serve as a suitable foundation for students looking to carry out brain imaging experiments in postgraduate studies, or seeking research-based positions in brain imaging laboratories.

Outline content:
This module covers the analysis of FMRI data at both the theoretical
and practical levels. Topics covered include MRI Physics, what FMRI
is actually measuring, preprocessing of FMRI data, and modelling of
FMRI data.

Brief description of teaching and learning methods:
Theoretical content is delivered by a lecture at the start of each
session. In the second part of each session students learn to use to
use FSL software to analyse example data sets.

Contact hours:
  Autumn Spring Summer
Seminars 7.5
Practicals classes and workshops 7.5
Guided independent study 85
Total hours by term 100.00
Total hours for module 100.00

Summative Assessment Methods:
Method Percentage
Report 100

Other information on summative assessment:
Students will be provided with a data set to independently analyze and report on. The reported analysis should include systematic variation of some processing stages (e.g. degree of spatial smoothing, or comparing different methods of model fitting), and some reporting of relevant methodological literature.

Formative assessment methods:
Students will be able to improve their performance through practical components of the module.

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information:

Length of examination:

Requirements for a pass:

Reassessment arrangements:
Failing assessments may be retaken in consultation with the Course Director.

Additional Costs (specified where applicable):
1) Required text books:
2) Specialist equipment or materials:
3) Specialist clothing, footwear or headgear:
4) Printing and binding:
5) Computers and devices with a particular specification:
6) Travel, accommodation and subsistence:

Last updated: 31 March 2017

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