Dr Tyagi is a Lecturer in the division of Nursing. He is a neuroscientist and an engineer by training. He has a bachelor’s degree in bio-technology and a master’s degree in information technology (specialization in bioinformatics) from Indian Institute of Information Technology.
- Research Interests
- Research Publications
Dr. Tyagi has received a formal training in cognitive neuroscience and psychology and has contributed to the research in studying human behaviour. He has previously completed a project which involved collecting functional MRI data (magnetic resonance imaging of the brain). His doctoral thesis in psychology from the University of Plymouth investigated social aspects of creativity. As a post-doctoral research fellow, he worked with a team of researchers on developing and testing a new questionnaire. He specializes in analyzing large quantitative datasets (such as survey data) and neuroimaging data and often employs coding and algorithms in his data analyses.
Dr. Tyagi’s broad areas of research are Risk taking and Creativity. He is specifically interested in investigating the behavioural and neuroscientific aspects of social risk taking. This involves studying the neural and environmental factors that drive us to interact with other people especially in socially risky situations. These situations can range from mildly discomforting situations (such as disagreeing with your supervisor) to potentially dangerous situations (such as marching in a protest). Dr. Tyagi’s doctoral research has found a strong positive link between social risk taking and creativity.
As a research fellow at Queen Margaret University, he is helping a team of researchers understand the social and environmental factors that lead to reduced participation in school children.
Active research interests:
Social risk taking, Creativity, Right-wing authoritarianism, School participation
Behavioural data, Large survey data, Neuroimaging, Advanced statistical analyses and Psychometrics such as Item response theory analyses and Structural Equation Modeling.