Clinical & Experimental Applications of Neuroimaging
36 Hours + Blended
One Semester or equivalent
Hawthorn
Available to incoming Study Abroad and Exchange students
Overview
This unit exposes students to the applications of neuroimaging techniques in Cognitive Neuroscience. Students will explore how methods like MRI, EEG, PET, and MEG index brain function in both experimental and clinical settings. The unit aims to illustrate how neuroimaging aids in clinical diagnosis, treatment planning, and experimental research, enhancing our understanding of brain functions in health and disease.
Requisites
Prerequisites
NEU10002
NeurosciencePSY10009 Methods of Cognitive Neuroscience
Rules
NEU10002 Neuroscience v1
AND
PSY10009 Methods of Cognitive Neuroscience v1
Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
02-March-2026
31-May-2026
31-May-2026
Last self-enrolment date
15-March-2026
Census date
31-March-2026
Last withdraw without fail date
21-April-2026
Results released date
07-July-2026
Semester 1
Location
Hawthorn
Start and end dates
01-March-2027
30-May-2027
30-May-2027
Last self-enrolment date
14-March-2027
Census date
30-March-2027
Last withdraw without fail date
20-April-2027
Results released date
06-July-2027
Unit learning outcomes
Students who successfully complete this unit will be able to:
- Explain how neuroimaging methods are used in clinical contexts, understanding their role in diagnosing, monitoring, and planning treatments for neurological disorders
- Interpret and critically analyse neuroimaging data, linking brain activity patterns to cognitive functions and behaviour
- Apply understanding of ethical considerations to the use of neuroimaging in research and clinical practice
- Perform basic signal processing of multi-dimensional datasets
- Implement preprocessing and analysis algorithms for neuroimaging data
Teaching methods
All applicable locations
| Activity Type | Activity | Total Hours | Number of Weeks | Hours Per Week | Venue Type and Activity Detail |
|---|---|---|---|---|---|
| Online | Lecture | 12 | 12 weeks | 1 | Asynchronous |
| On-campus | Lab | 12 | 6 weeks | 2 | |
| On-campus | Class | 12 | 12 weeks | 1 | Non-lab tutorials |
| Specified Activities | Various | 36 | 12 weeks | 3 | Reading and workbook activities |
| Unspecified Activities | Independent Learning | 78 | 12 weeks | 6.5 | Independent study, Assignment preparation, Revision |
| Total Hours: | 150 | Total Hours (per week): | 13.5 | ||
Assessment
| Type | Task | Weighting | ULOs |
|---|---|---|---|
| Written Assignment | Individual | 35% | 1,3 |
| Laboratory Practicals | Individual | 35% | 2,4,5 |
| Final-Semester Test | Individual | 30% | 1,2 |
Hurdle
Nil
Content
- Applications of Magnetic Resonance Imaging (MRI), Electroencephalography (EEG), Positron Emission Tomography (PET), and Magnetoencephalography (MEG) as measures of cognitive function
- Applications of Magnetic Resonance Imaging (MRI), Electroencephalography (EEG), Positron Emission Tomography (PET), and Magnetoencephalography (MEG) to clinical testing, particularly epilepsy, multiple sclerosis, tumours, and brain damage
- Training in modern open-source tools for analysing neural data (Python, R)
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.