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Computational Neuroscience Research Team
One of the most important scientific challenges of the 21st century is to understand the biological brain. This challenge entails knowledge of brain structure, function and dynamics on many different levels all the way from molecules to neurons up to networks and beyond. How the various parts of the brain interact dynamically to produce cognition and behavior is still an unsolved problem.
Understanding the brain has significant implications for society ranging from industry and commerce to education and healthcare.  A direct application from understanding the brain's computational capabilities is the advancement of beyond state-of-the-art intelligent systems. In terms of mental health, clinical depression, age related dementia and Alzheimer's disease are major societal problems that affect millions of people worldwide, with substantial economic cost and catastrophic impact on both sufferers and caregivers. Alzheimer's disease is the most common cause of dementia, affecting more than 5 million people in Europe and predicted to increase to 106 million by 2050. In parallel, recent reviews put the total cost of depression to the economy of England in the year 2000 at over £9 billion, and major depressive disorder is the single greatest burden of all human diseases in Europe. Locally, N. Ireland has the world's highest post traumatic stress disorder, and prevalence of stress-induced mental disorders. Belfast has UK's highest dementia diagnosis rate. Clearly understanding the normal and dysfunctional brain is critically important for the development of effective drugs and therapies as well as ways to enhance and preserve cognitive and brain function.
 The brain is a complex system consisting of about 100 billion neurons. A massive amount of data from many different sources on many different levels is now available in part due to advanced measurement techniques and evermore sophisticated technology. The computer has become an indispensible tool for acquiring, analyzing and mining data. In turn, theoretical and computational modelling offers a way to organize new data and extract meaningful information. Theoretical modelling is also necessary to generate experimentally testable hypotheses about how the brain works, and thus is a crucial accompaniment to data collection and analysis. Computational neuroscience is a relatively new field of study that uses computational modelling, simulation, and theoretical analysis to uncover the principles and mechanisms that underlie how the brain performs cognitive functions and produces overt behavior.
Computational Neuroscience Research Team (CNRT): The CNRT is a relatively recent initiative of the Intelligent Systems Research Centre. The project was initially funded under the Northern Ireland Department for Employment and Learning, through its "Strengthening the all-Island Research Base" initiative. CNRT brings together a substantial team of talented researchers dedicated to computational modelling and analysis of the nervous system and the information processing functions it performs. Although CNRT's research is grounded in basic neuroscience, a long term goal is multi-scale modelling of cognitive disorder and specific clinical conditions such as clinical depression and Alzheimer's disease. The aim is to develop accurate computational models of brain regions and their associated circuitry, especially those known to be affected during the course of depression and AD. Such models are critical also for studies of the neural dynamics of development, learning and aging including neurodegenerative processes. Currently, the team consists of researchers who are experts in the areas of computational neuroimaging and computational modelling.
The CNRT initiative brings together the skill sets of two prominent and complementary research centres - the Intelligent Systems Research Centre, at the University of Ulster and Trinity College Institute of Neuroscience (TCIN), at Trinity College Dublin.
Some Current Research Themes
- Brain signal (e.g. fMRI, DTI) analysis and computational modelling of the ageing brain and Alzheimer's disease. In collaboration with TCIN.
- Computational modelling of brain systems implicated in cognitive-affective processing, mood disorders, and clinical depression. In collaboration with the Biomedical Sciences Research Institute, University of Ulster.
- Brain signal (e.g. EEG) and behavioural analysis of social interaction and coordination. In collaboration with the Center for Complex Systems and Brain Sciences, Florida Atlantic University, USA.
- Development of advanced theoretical and computational techniques for brain signal processing.
Team Members
Academic Staffs
Dr. Sonya Coleman
Dr. Damien Coyle
Professor Scott Kelso (Visiting Professor)
Professor Liam P. Maguire
Professor T. Martin McGinnity
Professor Girijesh Prasad
Dr. KongFatt Wong-Lin
Research Staffs
Dr. Min Jing (Research Associate)
Dr. Xingfeng Li (Research Fellow)
Dr. Naeem Muhammad (Research Associate)
Dr. John Wade (Research Assistant)
Dr. David Watson (Research Fellow)
Research Students
Mr. Kamal Abuhassan
Mr. Gaurav Garg
Mr. Alok Joshi
Mr. Anthony Laviale
Mr. Vahab Youssofzadeh
Previous Members
Dr. Basabdatta Sen Bhattacharya (Research Associate)
Dr. Olivier Coenen (Research Fellow)
Dr. Huaizhong Zhang (Research Assistant)
Dr. Feng Zhao (Research Associate)
Dr. Xin Zou (Research Associate)
Relevant Journal Publications (since 2008)
News and Announcements
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