Note: This is an archived Handbook entry from 2008.Search for this in the current handbook
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2008:Semester 2, - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: Twenty-four hours of lectures, 12 hours of tutorials and 12 hours of laboratory work. |
Total Time Commitment: Not available
|Prerequisites:||431-202 Engineering Analysis B or equivalent and 421-286 Bioengineering Systems Modelling 2 or 431-221 Fundamentals of Signals and Systems and 431-325 Stochastic Signals and Systems|
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorDr David Grayden
|Subject Overview:||This subject introduces students to the basic mechanisms of information processing and learning in the brain and nervous system. Topics include: neural properties underlying information processing in neurons; generation and propagation of action potentials (spikes); Hodgkin-Huxley equations; coding and transmission of neural information (spiking rate, correlation and synchronisation); simplified neural models (binary, rate-based, integrate & fire and Hodgkin-Huxley); 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). |
On Successful completion of this subject, students should be able 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 process (Poisson); calculate the key measures of neural information based upon spike timing information; implement and analyse the input-output characteristics of simplified neural models; describe the mechanisms underlying learning in the brain and nervous system. Material will be reinforced through MATLAB based tutorials and laboratories.
|Assessment:||One written examination of three hours (60%), Matlab based laboratory work(40%).|
|Recommended Texts:|| |
Information Not Available
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
|Generic Skills:|| |
Bachelor of Engineering (Biomedical)Biosignals |
Bachelor of Engineering (Electrical Engineering)
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