Faculty of Medicine, Nursing and Health Sciences

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This unit entry is for students who completed this unit in 2016 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

Monash University

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.


Medicine, Nursing and Health Sciences

Organisational Unit

School of Psychological Sciences


Associate Professor Jeroen Van Boxtel



  • First semester 2016 (Day)


Computational neuroscience bridges several disciplines such as neuroscience, cognitive science, psychology, electrical engineering, computer science, mathematics, and physics. Brain function is studied with a focus on the information processing properties. This unit introduces several key concepts and techniques that are necessary to understand computational neuroscience. Specifically, it aims to endow the students with an understanding of existing basic computational models in neuroscience.

There will be a 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 (e.g. numerical modelling, ordinary differential equations). These theoretical topics will be linked to common applications: e.g., integrate-and-fire neuronal modelling, connectivity analysis.

At the end of the unit, students are expected to understand the main concepts and have a basic set of computational skills through hands-on programming of simple models. It is expected that the students will be better prepared for understanding and performing work in the field cognitive neuroscience which is increasingly dependent on computational tools, and be less apprehensive of research in general.


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. Describe the use of a range of computational tools and paradigms used within different domains of neuroscientific research.
  4. Translate a theoretical question into a computational approach, e.g. a computational model.
  5. Explain and apply basic neuroscience knowledge within a modelling approach.


Examination (MCQ) (2 hours) (30%)
Essay (1,500 words) (25%)
6 x Computer projects (400 - 500 words each) (45%)

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