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Neural Information Processing (BMEN90002)
Graduate courseworkPoints: 12.5On Campus (Parkville)
To learn more, visit 2023 Course and subject delivery.
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
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: 31 January 2024
Eligibility and requirements
Prerequisites
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
BMEN30006 | Circuits and Systems | Semester 1 (On Campus - Parkville) |
12.5 |
ELEN30012 | Signals and Systems |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
BMEN30006 Fundamentals of Biosignals (Prior to 2015)
Or equivalent
Corequisites
None
Non-allowed subjects
Code | Name | Teaching period | Credit Points |
---|---|---|---|
BMEN90004 | Advanced Neural Information Processing | No longer available |
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: 31 January 2024
Assessment
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% |
End of semester Written Exam. ILOs 1, 2, 3, 4, 5, 6, 8, 9 and 10 are assessed in the final written exam.
| During the examination period | 50% |
Last updated: 31 January 2024
Dates & times
- Semester 2
Principal coordinator Anthony Burkitt Mode of delivery On Campus (Parkville) Contact hours A 3-hour lecture and a 1-hour tutorial per week, and four 3-hour workshop laboratory classes. Total time commitment 200 hours Teaching period 24 July 2023 to 22 October 2023 Last self-enrol date 4 August 2023 Census date 31 August 2023 Last date to withdraw without fail 22 September 2023 Assessment period ends 17 November 2023 Semester 2 contact information
Email: aburkitt@unimelb.edu.au
Time commitment details
200 hours
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 31 January 2024
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: 31 January 2024