PSY3310 - Introduction to computational neuroscience - 2017

6 points, SCA Band 1, 0.125 EFTSL

Undergraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Medicine, Nursing and Health Sciences

Organisational Unit

School of Psychological Sciences

Coordinator(s)

Associate Professor Jeroen Van Boxtel

Unit guides

Offered

Clayton

  • First semester 2017 (Day)

Synopsis

Computational neuroscience bridges several disciplines such as neuroscience, cognitive science, psychology, electrical engineering, computer science, mathematics, and physics.

This unit introduces several key concepts and techniques that are useful in understanding computational neuroscience and the applications to real experimental data.

The unit will focus on theoretical aspects of commonly encountered computational problems in cognitive neuroscience (e.g. Fourier analysis and graph theory), as well as practicing modelling skills on the computer.

These theoretical topics will be linked to common applications: e.g., EEG analysis, neuronal activity analysis, and brain connectivity analysis.

At the end of this unit, students will have a basic set of computational skills through hands on programming that will prepare them to perform work in the field of cognitive neuroscience.

Outcomes

Upon successful completion of this unit, students should be able to:

  1. Explain core theoretical concepts in computational neuroscience, especially as they relate to cognitive neuroscience.
  2. Critically evaluate the contribution of contemporary research findings and theories in key areas of computational neuroscience.
  3. Evaluate the use of a range of computational tools and paradigms used within different domains of neuroscientific research.
  4. Translate a theoretical neuroscience question into a computational approach
  5. Code and perform an analysis of brain data

Assessment

  • Examination (MCQ) (2 hours) (35%)
  • Essay (2,000 words) (30%)
  • 5 x Computer projects (400 - 500 words each) (35%)

Workload requirements

One x 2 hour lectures each week and one 2 hour workshop every fortnight.

For each week during the semester that students are not engaged in a workshop, students will be expected to independently complete the equivalent of 2 hours independent study that is linked to their workshop activities. Attendance is not monitored; students are assessed on their answers provided for each computer project.

For each week during the semester, students will be expected to complete the equivalent of 2 hours preparation for each lecture, 2 hours preparation for each workshop and 4 hours of research work/independent study (total = 12 hours study).

See also Unit timetable information

Chief examiner(s)

This unit applies to the following area(s) of study

Prerequisites