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Unit of study_
PHYS4015: The Physics of Complex Systems
2025 unit information
What is the neural code How do neural circuits communicate information What happens in our brain when we make a decision Computational modelling and theoretical analysis are important tools for addressing these fundamental questions and for determining the functioning mechanisms of the brain. This interdisciplinary unit will provide a thorough and up-to-date introduction to the fields of computational neuroscience and neurophysics. You will learn to develop basic models of how neurons process information and perform quantitative analyses of real neural circuits in action. These models include neural activity dynamics at many different scales, including the biophysical, the circuit and the system levels. Basic data analytics of neural recordings at these levels will also be explored. In addition, you will become familiar with the computational principles underlying perception and cognition, and algorithms of neural adaptation and learning, which will provide knowledge for building-inspired artificial intelligence. Your theoretical learning will be complemented by inquiry-led practical classes that reinforce the above concepts. By doing this unit, you will develop essential modelling and quantitative analysis skills for studying how the brain works.
Unit details and rules
Managing faculty or University school:
Science
| Study level | Undergraduate |
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| Academic unit | Physics Academic Operations |
| Credit points | 6 |
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Prerequisites:
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144 credit points of units including (MATH1X01 or MATH1X21 or MATH1906 or MATH1931) and MATH1X02 |
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Corequisites:
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None |
| Prohibitions:
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None |
| Assumed knowledge:
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First- and second-year physics |
At the completion of this unit, you should be able to:
- LO1. Demonstrate an understanding of key concepts in neural dynamics and computation.
- LO2. Apply these concepts to develop models, and to solve qualitative and quantitative problems in scientific contexts, using appropriate mathematical and computing techniques as necessary.
- LO3. Design brain-inspired algorithms to solve problems.
- LO4. Develop models to explain neurophysiological and/or psychophysical data.
- LO5. Communicate scientific information appropriately, through written work.
- LO6. Analyse the dynamical process of brain functions such as decision making and develop appropriate quantitative methods for solving them.
- LO7. Demonstrate a sense of responsibility, ethical behaviour, and independence as a learner and as a scientist.
Unit availability
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
There are no availabilities for this year.
| Session | MoA ? | Location | Outline ? |
|---|---|---|---|
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Semester 2 2025
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Normal day | Camperdown/Darlington, Sydney |
Outline unavailable
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Modes of attendance (MoA)
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