Data Analysis in Neuroimaging - PSY00109M

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  • Department: Psychology
  • Credit value: 20 credits
  • Credit level: M
  • Academic year of delivery: 2025-26

Module will run

Occurrence Teaching period
A Semester 2 2025-26

Module aims

The aim of this module is to provide hands-on practical experience in the analysis of neuroimaging data, and how to describe experiments and analyses in scientific reports. Students will learn to explain, report and critically evaluate experiments using fMRI and MEG, identifying the relative merits of these different cognitive neuroscience methods.

Module learning outcomes

  • Demonstrate the ability to independently perform neuroimaging analyses in fMRI and MEG
  • Demonstrate a critical understanding of the relative merits of fMRI and MEG as tools for cognitive and behavioural neuroscience
  • To write a scientific report in the format used in the field of cognitive neuroscience
  • Describe and explain the use of fMRI and MEG methods in typical experimental paradigms
  • Report and critically evaluate the results of fMRI and MEG analyses

Module content

  • Lecture: Introduction to Data Analysis in Neuroimaging
  • Practical: Visualising & Characterising fMRI Data
  • Practical: Single Subject fMRI Analysis
  • Practical: Group fMRI Analysis
  • Practical: fMRI ROI Analysis
  • Lecture: Describing Neuroimaging Methods & Results
  • Practical: Preprocessing MEG Data
  • Practical: Individual Level MEG Analysis
  • Practical: MEG Source Localisation
  • Practical: MEG Group Level Analysis & Statistics
  • Lecture: Writing Neuroimaging Discussions & Assessment session

Indicative assessment

Task % of module mark
Essay/coursework 100

Special assessment rules

None

Indicative reassessment

Task % of module mark
Essay/coursework 100

Module feedback

The marks on all assessed work will be provided on e-vision.

Indicative reading

Functional Magnetic Resonance Imaging by Huettel, Song, McCarthy (3rd edition)

Magnetoencephalography. Elizabeth W. Pang (Ed). InTech