For many decades, psychology has studied motivation via self-report questionnaires. Many theories of motivation have been developed, but few go beyond studying the effects of rewards, and many theories are tailored for very specific purposes such as to increase worker’s motivation in organizational psychology, rendering difficulty in generalization. Only in the last 10 years that scientists start to establish precise behavioural quantification of motivation using an overarching cost-benefit framework via decision making tasks. This attracted much attention in the neuroscience community, leading to significant advancement in the neurobiology of motivation, including the brain, as well as peripheral nervous systems (such as autonomic arousal). The recent emergence of eyetracking device helps this surge of research, because it allows us to read out in which arousal state the brain is. We do this by recording the size of the pupil in the eye. Put simply, based on the pupil size, we could tell apart a drowsy brain from a brain at peak level of alertness.
This project is a timely continuation of such maturing neuro-computational account of motivation and the burgeoning empirical work on pupillometry and decision making. During this fellowship at the Zurich Center for Neuroeconomics (ZNE), I was able to implement my skills and expertise in neuroimaging and behavioral quantification of motivation and dopamine, and combine these with newly acquired skills and expertise in pupillometry and noradrenergic arousal. To the best my knowledge, the data acquired in this fellowship is the first demonstration that the phasic signal for pupil-linked arousal is sensitive towards anticipated effort levels, extending previous findings of pupil signaling of currently exerted physical effort. Our findings therefore show that measurement of pupil signals during decision making about potentially effortful options (rather than exertion of physical effort) can already reveal motivation, i.e. how much effort the decision maker is willing to accept. Results from these data will significantly contribute to the wealth of empirical results in this field.
The translational value of this project has bolstered the capability of neuroeconomics research in EU to deliver applied science that is directly borne out of basic science, with the potential to improve the lives of individuals in EU and worldwide. This project cemented the overarching cost-benefit theoretical framework to study motivation that is universal and can be transplanted into many other concrete dilemmas that occur in real life. In addition, I have made two funding research proposals with applied questions that were born directly out of current findings, aimed at developing arousal regulation techniques such as mental simulation and biofeedback to increase motivation. I have also engaged with external labs in ETH, Zurich who are interested in building a start-up spin-off company on pupil biofeedback.
No website has been developed for the project.