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Neural Information Processing (BMEN90002)
Graduate courseworkPoints: 12.5On Campus (Parkville)
For information about the University’s phased return to campus and in-person activity in Winter and Semester 2, please refer to the on-campus subjects page.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 2
Email: aburkitt@unimelb.edu.au
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
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
On completion of this subject the student is expected to:
- Describe the structure and function of the nervous system
- Calculate equilibrium neural properties
- Describe the types and properties of synapses
- Describe the membrane mechanisms underlying the generation of action potentials
- Interpret neural responses in terms of point processes (Poisson)
- Evaluate neural processing using information theoretic measures
- Implement and analyse the input-output characteristics of simple and biologically-detailed neural models
- Describe the principles underlying the analysis of biological neural signals
- Describe the mechanisms underlying learning in the brain and nervous system
- 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)
Semester 1 (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 | Not available in 2024 |
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
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Description | Timing | Percentage |
---|---|---|
One mid-semester test. ILOs 1, 2, 3, 4, 5, 6, 8, 9 and 10 are assessed in the mid-semester test.
| Mid semester | 10% |
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.
| From Week 4 to Week 12 | 40% |
One examination. ILOs 1, 2, 3, 4, 5, 6, 8, 9 and 10 are assessed in the final written exam.
| End of semester | 50% |
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 3 August 2020 to 1 November 2020 Last self-enrol date 14 August 2020 Census date 21 September 2020 Last date to withdraw without fail 16 October 2020 Assessment period ends 27 November 2020 Semester 2 contact information
Email: aburkitt@unimelb.edu.au
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
None
- 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 Specialisation (formal) Biomedical - 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.
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
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 3 November 2022