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Designing experiments which utilise magnetic resonance imaging of people, data analysis and interpretation. Use of basic computer coding and application of statistics, interactive neuroimaging software for scientific communication.
This course will suit students interested in postgraduate research who would like to study the structure and function of the human brain using magnetic resonance imaging (MRI). Students will be given an overview of the methods commonly used and is designed for beginners to the field of neuroimaging. The topics include experimental design, image acquisition, data analysis, localisation/anatomy and data interpretation.
| Paper title | Special Topic: Magnetic Resonance Imaging in Neuroscience |
|---|---|
| Paper code | NEUR471 |
| Subject | Neuroscience |
| EFTS | 0.1667 |
| Points | 20 points |
| Teaching period | Semester 1 (On campus) |
| Domestic Tuition Fees (NZD) | $1,673.50 |
| International Tuition Fees (NZD) | $6,508.13 |
- Recommended Preparation
- STAT 210 or STAT 310 and STAT 210 or STAT 310
- Eligibility
The course is intended for science majors, especially neuroscience majors, possibly with limited programming experience. A computer science or statistics paper would be advantageous but not essential.
- Contact
Associate Professor Bruce Russell, bruce.russell@otago.ac.nz
- Teaching staff
- Paper Structure
The first part of the course is composed of series of lectures that covers the fundamental aspects of functional human neuroimaging coupled with guided practical sessions. This is followed by journal club presentations with additional lectures considering possible applications of MRI to health and disease. Students will then be guided through how to develop and simulate experimental protocols with hands-on support.
The course briefly covers the analysis of other neuroimaging modalities (resting state, structural and diffusion imaging), aspects of which students can choose to incorporate into an experimental design project of their choice. Students are required to present their experimental design to their peers for further discussion.
- Teaching Arrangements
We will use the FSL software package from the University of Oxfords FMRIB. Students are expected to have their own laptop (<5 years old). Lectures are followed by a guided practical session.
- Textbooks
Textbooks are not required for this paper. Readings will be supplied.
- Graduate Attributes Emphasised
Critical thinking, Information literacy, Scholarship, Research
View more information about Otago's graduate attributes.- Learning Outcomes
Students who successfully complete the paper will:
- Understand how brain activity and connectivity are assessed using functional neuroimaging, and why this is important within neuroscience Be able to write computer code to simulate biophysical, dynamical and statistical models of neurons and neural systems
- Acquire a basic understanding of how mathematical models in neuroimaging are derived and applied, and what can and cannot be inferred regarding underlying neural systems when using these modelling techniques.
- Learn that effective collaboration between neuroimagers, statistical modelers and study participants requires each to have some understanding of the other approaches and perspectives, what is known and what is possible. Students will feel confident in their knowledge of MRI analysis and understand the basics of neuroimaging research.
- Learn basic coding, documentation and version control using FSL software which is now a common tool used in neuroimaging.
- Learn to use graphics, animation and interactive software tools to communicate analysis of complex systems to non-specialists.
