Research MSc in Cognitive and Clinical Neuroscience - Neuroeconomics
About This Masters Degree
Neuroeconomics is a truly interdisciplinary endeavor aiming at understanding human individual and social decision making by investigating their neuronal basis and underlying psychological processes. Neuroeconomics combines theoretical and empirical research methods and techniques from neuroscience, economics and psychology into a unified approach, aimed at an integrative understanding of human decision making.
The specialisation Neuroeconomics is jointly organised by the Faculty of Psychology and Neuroscience (FPN) and the Economics Departments of the School of Business and Economics (SBE). You will follow courses at SBE as well as FPN and you will receive an in-depth training in quantitative theoretical and empirical methods in economics and cognitive neuroscience as well as extensive hands-on training in all aspects of experimental and neuroscience research.
The research in Neuroeconomics is conducted by an international and multidisciplinary group of researchers with diverse backgrounds including economics, neuroscience, psychology, mathematics, and computer science, who are members of the Graduate School of Business and Economics (GSBE) and the Maastricht Brain Imaging Centre (M-BIC), respectively.
GSBE offers a fully equipped state-of-the-art experimental laboratory and M-BIC offers a unique research infrastructure with the newest ultra-high field imaging facilities. You will be fully integrated in this research team and will participate in cutting edge neuroeconomics research unravelling the psychological and neurophysiological processes underlying human decisions using rigorous economic and game theoretical modelling, behavioural experiments, functional Magnetic Resonance Imaging (fMRI), functional Near-Infrared Spectroscopy (fNIRS), Transcranial Magnetic Stimulation (TMS), Transcranial direct current stimulation (tDCS) and other state-of-the-art methods in neuroscience.
Examples of research currently carried out by the research group are the investigation of the relation between intertemporal choices and impulsiveness, the neuronal basis of prosocial behaviour and reciprocity, abstract value calculation, if and how neuronal data can be used to predict choices across different decision domains, and whether specific brain processes can explain the different behaviours of men and women in competitive situations.
The local state-of-the-art research infrastructure and the multidisciplinary team provide a large international research network in all involved research fields. The fact that the local researchers have backgrounds in economics, neuroscience and psychology gives access to institutes in all three subfields as well as to institutes specializing in neuroeconomics. This offers unique opportunities for internships at some of the most prestigious research institutes around the globe (including California Institute of Technology, University of Southern California Dornsife, Science Research Center Berlin).
Internship research topics can vary from studying individual and social human behavior to the the neural roots of creativity. decisions to exploring social human behaviour and research methods range from behavioural research to fMRI and TMS.
The specialisation in Neuroeconomics provides an optimal basis for a career in fundamental and applied neuroeconomics and decision neuroscience. Graduates in this specialisation are expected to continue their careers as PhD candidates at research institutes specializing in behavioural economics and decision neuroscience and will as well be able to use their acquired expertise as consultants and advisors in decision making and conflict resolution.
Is this programme right for me?
The specialisation Neuroeconomics aims at students interested in an academic career in this rapidly developing field and who are willing to take up the challenge to do research that demands multidisciplinary methods and talents. Students with undergraduate backgrounds as diverse as economics, mathematics, psychology, biology, computer science, physics, and engineering are suited for the programme, provided they are willing to learn and apply high level mathematical models and statistical methods.