Measurement, Data, and Analytics in Cognitive Neuroscience
36 Hours + Blended
One Semester or equivalent
Hawthorn
Available to incoming Study Abroad and Exchange students
Overview
This unit provides instruction in signal acquisition and processing for Psychophysiology & Cognitive Neuroscience. Students will gain experience in acquiring data with biomedical tools, minimising interference, applying signal processing algorithms, and using statistics to interpret time-varying biological signals linked to psychological constructs and behaviours. Students will gain practical experience working with data from various modalities including MRI, EEG, MEG, and psychophysiology.
Requisites
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
Unit learning outcomes
Students who successfully complete this unit will be able to:
- Apply appropriate preprocessing and processing techniques to minimise noise and extract measures of interest across different imaging applications
- Use appropriate statistical approaches for comparisons in signal and image analysis to test hypotheses
- Write code using appropriate open source software packages for analysing and managing data
- Describe key principles of automated data processing and machine learning in Cognitive Neuroscience
- Organise and manage data and metadata, including ethical sharing of data, and produce interactive data visualisations
- Critically analyse data processing methods used in cognitive neuroscience research
Teaching methods
All applicable locations
| Activity Type | Activity | Total Hours | Number of Weeks | Hours Per Week | Venue Type and Activity Detail |
|---|---|---|---|---|---|
| Live Online | Lecture | 12 | 12 weeks | 1 | |
| On-campus | Lab | 24 | 12 weeks | 2 | |
| Specified Activities | Various | 48 | 12 weeks | 4 | Laboratory homework, Reading |
| Unspecified Activities | Independent Learning | 66 | 12 weeks | 5.5 | Independent study, Assignment preparation |
| Total Hours: | 150 | Total Hours (per week): | 12.5 | ||
Assessment
| Type | Task | Weighting | ULOs |
|---|---|---|---|
| Article Analysis | Individual | 40% | 6 |
| Laboratory Tutorial Quizzes | Individual | 30% | 1,2,3,4 |
| Project Report | Individual/Group | 30% | 1,2,5 |
Hurdle
Nil
Content
- Signals & Data acquisition
- Signal Processing: time-domain
- Signal Processing: frequency-domain
- Imaging: the spatial dimension
- Signal & imaging statistics
- Representations, machine learning & AI
- Graduate Attribute – Communication 2- Communicating using different media
- Graduate Attribute - Teamwork 1- Collaboration and negotiation
- Graduate Attribute – Digital Literacies 1- Information literacy
- Graduate Attribute – Digital Literacies 2- Technical literacy
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.