Research goals - NTNU Cyborg
Through our research, major conceptual and methodological advances are expected in the following areas:
Hybrid biological-artificial computers, cyborg technology, and brain-machine/computer interfaces. For example, the inclusion of morphogenetic principles into computer architecture may decrease energy consumption. In systems with limited energy availability, i.e. drones and robots, principles from small plastic networks may allow complex computation.
Regenerative and translational neuroscience, modelling and understanding damage and repair processes applicable to trauma or neurodegenerative disease, and developing novel approaches in nanomedicine and personalized medicine. Being able to elucidate how biological neural networks self-organize and grow may provide a stepping stone towards novel neuro-rehabilitation techniques.
Basic issues around neuronal functions are investigated. In the long term, studying the mechanism of memory, learning, concept formation, and neuronal model building of the external world may lead to a better understanding of the emergence of consciousness.