Module PPP-4021:
Intro Neuroimaging Analysis
Introduction to Neuroimaging Analysis 2022-23
PPP-4021
2022-23
School Of Human And Behavioural Sciences
Module - Semester 1
10 credits
Module Organiser:
Paul Mullins
Overview
1) Physical and practical principles of MRI imaging, Methods for image pre-processing (e.g. image registration etc.) and basic handling of imaging data; 2) Practicalities associated with the physiology of MRI contrast in the brain, with a focus on measures of cerebral metabolism and blood flow; 3) Principles and practical methodologies for measurement of changes in cerebral metabolism; 5) Practicalities of statistical analyses of functional imaging time-series; 6) Experimental design for functional imaging; 7) The safety and ethical issues that arise in regards to neuroimaging research and how they apply to the researcher, participants and the wider community.
Assessment Strategy
-threshold -Links to C gradesKnowledge of key areas/principles only • Limited evidence of background study • Answer only poorly focused on ques3on & with some irrelevantmaterial & poor structure • AQempts to present relevant and coherent arguments • Has several factual/computa3onal errors • No original interpreta3on • Only major links between topic are described • Limited problem solving • Many weaknesses in presenta3on & accuracy
-good -Links to B gradesStrong Knowledge • Understands most but not all of subject area • Evidence of background study • Focused answer with good structure • Arguments presented coherently • Mostly free of factual/computa3onal errors • Some limited original interpreta3on • Well known links described between topics • Problems addressed by exis3ng methods/approaches • Good presenta3on, accurate communica3on
-excellent -Links to A gradesComprehensive knowledge • Detailed understanding of the subject area • Extensive background study • Highly focused answer & well-structured • Logically presented & defended arguments • No factual/computa3onal errors • Original interpreta3on • New links to topic are presented • New approach to a problem • Excellent presenta3on with very accurate communica3on
Learning Outcomes
- 1. Understand modern neuroimaging data formats and solid data management and hygiene practices
- 3. Use this knowledge of the GLM to design a good fMRI study
- 4. Be able to pre-process and analyze MRI and fMRI data.
- 5. Be able to report and interpret the results of fMRI studies.
- 6. A thorough understanding of MRI safety
- 7. An understanding of the ethical issues associated with handling modern neuroimaging data.
- Have a solid understanding of practical application of the general linear model (GLM) to analysis of neuroimaging data
Assessment type
Crynodol
Description
Lab Book Week 2
Weighting
5%
Due date
11/10/2021
Assessment type
Crynodol
Description
Lab Book Week 11
Weighting
5%
Assessment type
Crynodol
Description
Lab Book Week 8
Weighting
5%
Due date
22/11/2021
Assessment type
Crynodol
Description
Lab Book Week 4
Weighting
5%
Due date
25/10/2021
Assessment type
Crynodol
Description
Lab Book Week 10
Weighting
5%
Due date
06/12/2021
Assessment type
Crynodol
Description
Lab Book Week 1
Weighting
5%
Due date
04/10/2021
Assessment method
Coursework
Assessment type
Crynodol
Description
Lab Book Week 9
Weighting
5%
Due date
29/11/2021
Assessment type
Crynodol
Description
Lab Book Week 3
Weighting
5%
Due date
18/10/2021
Assessment type
Crynodol
Description
Lab Book Week 7
Weighting
5%
Due date
15/11/2021
Assessment method
Coursework
Assessment type
Crynodol
Description
Final Project
Weighting
50%
Due date
10/01/2022
Assessment method
Coursework
Assessment type
Crynodol
Description
Lab Book Week 5
Weighting
5%
Due date
01/11/2021