Prof. Chetwyn Chan, Director of UBSN discussed how it enables PolyU researchers from different disciplines to collaboratively apply neuroscientific methods to answer important theoretical and applied questions.
1. Does neuroscience have anything to do with the society?
Let’s take the example of the study of the mechanisms underlying multi-sensory learning. To understand how learning can be maximised using both visual and audial senses, we tested the phenomenon in individuals with blindness and in rats using electrophysiology, electroencephalography and brain imaging. The parietal cortex was found to play a very significant role in the audiovisual learning, and this learning was associated with changes in the neural networks that had survived deficiencies in the brain.
Understanding this mechanism enabled us to design intervention protocols to assist people with blindness to navigate around the environment, and to explore how multi-sensory learning applies in improving the motor and cognitive functions of older people and patients with neurocognitive disorders.
2. How does the UBSN create research synergies among experts from different fields?
The primary role of the UBSN is to provide state-of-the-art equipment and technological platforms for neuroscientists to conduct high impact studies and train research students. Cross-species and cross-modality research are the key to the UBSN’s success. Cross-species research undertakes invasive animal studies to reveal underlying neural mechanisms, and this knowledge is then combined with translational methods to test the findings on human subjects. The ultimate goal is to enable researchers to create and apply knowledge to solve real-life problems in areas such as ageing, child development, neurological rehabilitation, language development and mental health.
3. What are the interesting developments in neuroscience to unveil how the brain works?
A particular area of interest among PolyU’s rehabilitation researchers is to explore three-dimensional activities of the brain among both clinical and normal populations. The extremely precise spatial and temporal resolutions help researchers to understand and resolve complex human behaviours such as cognitive roles of the motor-related cortices, emotion regulation in patients with mental illnesses, learning capacity in patients with brain injuries, and neuro-degeneration and protection in older individuals. These and other advancements in data science and information technology pave the way for constructing machine learning protocols that mimic human thinking processes.