NeuroEngineering is closely related to the fields of experimental and computational neuroscience.
Experimental neuroscience is the study of neural systems in different forms of life, at the molecular, cellular, systems and cognitive levels. Computational neuroscience refers to the development of mathematical models and computational analyses of these neural systems. Computational Neuroscience complements experimental neuroscience by helping to integrate, and provide a deeper analysis of, different experimental results. The formal theory and methods developed through the combination of experimental and computational neuroscience provide the framework with which neuroengineers can develop technology.
In general terms the aim of our NeuroEngineering research lab is to address two questions:
- How does the brain learn, control behaviour, and give rise to the mind?
- How can we use our understanding of the brain to develop technology that can interact with or emulate brain function?
Core research interests
- Audition, speech and bionic ear design
- Bionic eye design and vision
- Computational neuroscience
- Neuroimaging and neuroinformatics
Research in these areas overlap with ideas from fields in electrical engineering, computer science, mathematics, and physics. This overlap includes theory on machine learning, pattern recognition, signal processing, nonlinear dynamical systems, stochastic processes, statistical mechanics, and many more.