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Research Projects

Animal nervous systems are the most exquisitely engineered computational mechanisms in the known universe. Despite considerable advances in the science of computing and in the processing capacity and speed of computing hardware, the efficiencies and capabilities of today's artificial computational systems pale beside those of naturally evolved computational systems. This observation has persuaded many leading researchers that if our ultimate aim is to engineer artificially intelligent systems, one of our best approaches is to 'reverse engineer' naturally evolved thinking systems.

Computational neuroscience is a multidisciplinary research enterprise that seeks to understand, model, and ultimately copy biological computational systems. The disciplines that are relevant to this pursuit are:

• Cognitive Science - Brings conceptual understanding of the nature of representation and computation in biological thinking systems
• Cognitive Psychology - Models the computational processes that are responsible for perception and cognition
• Neurophysiology - Permits the modelling of the physical and chemical properties and processes of neural networks as a key to deducing the algorithms employed
• Computer Vision - Constructs algorithms for real-time implementation of perceptual and cognitive processes
• Electronic Engineering - Supplies the tools for simulating and constructing biomimetic (copies of biological) circuits to implement real-time computing
• Molecular and Cellular Neurobiology - Provides the theoretical understanding for exploring the possibility of interfacing silicon circuitry and neural tissue

By bringing together researchers in these different disciplines, the CRNC will pursue interdisciplinary research projects which further our understanding of the computational processes implemented in biological systems.

There are two immensely important potential technological outcomes from research collaborations of this kind. The first is that through a process of reverse engineering animal nervous systems it may be possible to develop new computational technologies for application in a wide range of areas, especially where perceptual and cognitive processes are required. The second is that through a process of exploring the potential interfacing between neural tissue and silicon circuitry, it may be possible to develop new medical technologies for application in a wide range of cases where neurological impairment exists. Examples include brain damage resulting from stroke, trauma and neurodegenerative diseases that result in localised, specific lesions. In such cases, external or internally implanted artificial 'neural' processors have the potential to take over the computational role of the missing brain region, providing the major challenges in interfacing such systems can be overcome.

The research projects currently underway within the CNRC are as follows:

Biomedical Engineering

• Biologically inspired electronics
• Electronic circuits that behave like neurons (neuro-MOS circuits)
• Computational models of stochastic resonance
• T-ray imaging, including the detection of neurological diseases
• Biofeedback signal applications and analysis of electroencephalograph data
• Complex systems and evolutionary computation for studying redundancy and pleiotrophy
• CNRC Bionic Vision project

Cognitive Science

• Computation and representation in neural networks
• Neural network simulations
• Neurocomputational models of consciousness
• The neural basis of delusions and psychopathologies

Computer Vision

• Computer vision and its possible interaction with biological systems
• Vision applications including motion vision, stereovision, shape reconstruction, intelligent video surveillance and unmanned aerial vehicle video surveillance
• Methodological issues in artificial intelligence and the limits of computation

Human Cognition and Applied Decision Making

• Human memory, language, learning and decision making
• Mathematical modeling of data related to understand these systems and predict behaviour
• Psycholinguistics, computational linguistics and information retrieval and extraction
• Machine learning and intelligence

Neurological Development and Disease

• Stroke prevention related to genetic risk factors and transient ischaemic attacks (TIAs)
• Repair following stroke, genes related to stem cell integration and proliferation
• Gene function related to development and to neurodegenerative diseases
• Neuropharmacology

Pathology/Neurological Diseases and Injury

• Improvement of function following central nervous system injury
• Patient monitoring
• Diagnostic equipment

Sensory Neurophysiology

• Insect vision
• Oral neurophysiology