Neural Information Processing (BMEN90002)
Graduate courseworkPoints: 12.5On Campus (Parkville)
Overview
| Availability | Semester 2 |
|---|---|
| Fees | Look up fees |
AIMS
This subject introduces students to the basic mechanisms of information processing and learning in the brain and nervous system. The subject builds upon signals and systems modelling approaches to demonstrate the application of mathematical and computation modelling to understanding and simulating neural systems. Aspects of neural modelling that are introduced include: membrane potential, action potentials, neural coding, neural models and neural learning. The application of neural information processing is demonstrated in areas such as: electrophysiology, and neuroprostheses. Material is reinforced through MATLAB and/or NEURON based laboratories.
INDICATIVE CONTENT
Topics include:
Neural information processing analysed using information theoretic measures; generation and propagation of action potentials (spikes); Hodgkin-Huxley equations; coding and transmission of neural information (spiking rate, correlation and synchronisation); neural models (binary, rate based, integrate & fire, Hodgkin-Huxley, and multicompartmental); synaptic plasticity and learning in biological neural systems (synaptic basis of learning, short term, medium term and long term, and rate based Hebbian learning models); spike-timing dependent plasticity (STDP) of synapses; higher order neural pathways and systems (cortical structure and circuits).
Intended learning outcomes
INTENDED LEARNING OUTCOMES (ILOs)
On successful completion of this subject, students should be able to:
1 - describe the structure and function of the nervous system;
2 - calculate equilibrium neural properties;
3 - describe the types and properties of synapses;
4 - describe the membrane mechanisms underlying the generation of action potentials;
5 - interpret neural responses in terms of point processes (Poisson);
6 - evaluate neural processing using information theoretic measures;
7 - implement and analyse the input-output characteristics of simple and biologically-detailed neural models;
8 - describe the principles underlying the analysis of biological neural signals;
9 - describe the mechanisms underlying learning in the brain and nervous system;
10 - describe higher-order neural pathways and systems.
Generic skills
On completion of this subject, students should have developed the following generic skills:
- Ability to apply knowledge of science and engineering fundamentals.
- Ability to undertake problem identification, formulation, and solution.
- Ability to utilise a systems approach to complex problems and to design and operational performance.
- Ability to conduct an engineering project.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Prerequisite for this subject is:
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| BMEN30006 | Circuits and Systems | Semester 1 (On Campus - Parkville) |
12.5 |
(prior to 2015 BMEN30006 Fundamentals of Biosignals)
OR
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| ELEN30012 | Signals and Systems |
Semester 2 (On Campus - Parkville)
Winter Term (On Campus - Parkville)
|
12.5 |
OR
equivalent
Corequisites
None
Non-allowed subjects
Anti-requisites for this subject are:
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| BMEN90004 | Advanced Neural Information Processing | Semester 1 (On Campus - Parkville) |
12.5 |
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Additional details
- One mid-semester test of one hour duration (10%). ILOs 1, 2, 3, 4, 5, 6, 8, 9 and 10 are assessed in the mid-semester test.
- Four laboratory classes in Weeks 4 to 12, each with a written assignment of approximately 1000 words and requiring approximately 13-15 hours of work including preparation (10% each). ILOs 2, 5, 6 and 7 are assessed in the submitted laboratory reports.
- One end-of-semester examination of two hours duration (50%). ILOs 1, 2, 3, 4, 5, 6, 8, 9 and 10 are assessed in the final written exam.
Hurdle requirement: Students must pass the end of semester examination to pass the subject.
Last updated: 3 November 2022
Dates & times
- Semester 2
Principal coordinator Anthony Burkitt Mode of delivery On Campus (Parkville) Contact hours 3 hours lecture, one hour tutorial per week and up to 24 hours of laboratories. Total time commitment 200 hours Teaching period 24 July 2017 to 22 October 2017 Last self-enrol date 4 August 2017 Census date 31 August 2017 Last date to withdraw without fail 22 September 2017 Assessment period ends 17 November 2017 Semester 2 contact information
Email: aburkitt@unimelb.edu.au
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
- Subject notes
LEARNING AND TEACHING METHODS
The subject is delivered through lectures, tutorials and computer laboratory classes.
INDICATIVE KEY LEARNING RESOURCES
Students are provided with lecture slides, tutorials and worked solutions, laboratory sheets, and reference text lists.
CAREERS / INDUSTRY LINKS
Exposure to neural information processing in industry is provided through research laboratory visits to medical research institutes and guest lectures by representatives of industry, hospitals and research institutes.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Ph.D.- Engineering Specialisation (formal) Biomedical with Business Informal specialisation Master of Engineering (Biomedical) Specialisation (formal) Biomedical Informal specialisation Master of Engineering (Biomedical with Business) - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
Last updated: 3 November 2022