I am a research associate with a PhD in Economics at University College London in the Affective Brain Lab where I am working with Tali Sharot on the concept of intrinsic rewards.
Before, I was working in the Rutledge lab with Robb Rutledge, on mood dynamics and their link with decision-making. I used computational models (e.g., mood models, reinforcement learning models), lab, smartphone and online data to study mood dynamics and their relation to decision-making. I notably showed that understanding the world may be more important for well-being than reward. We recently released a smartphone app I co-developed (https://thehappinessproject.app/).
I prepared my PhD at Paris 1 Panthéon-Sorbonne University under the co-supervision of Mathias Pessiglione and Guillaume Hollard. The topic of my research was the link between cognitive fatigue and decision-making: How does cognitive fatigue, occurring after several hours of cognitive work (e.g., a workday) alters economical decision making (e.g., the consumption-saving trade-off).
Between 2013 and 2018, I was teaching a Master degree Neuroeconomics class (Eco&Psycho, Paris 1 Panthéon-Sorbonne) since 2013.
I also worked as an associate consultant for Influence at Work. I am currently also a freelance consultant (for example, I worked with a global firm to tackle fare evasion in public transportation using behavioural and data science, I wrote reports about decision-making or cognitive fatigue for various companies).
Cognitive fatigue has been studied for decades. It refers to the evolution of accuracy with time while one performs cognitive tasks (like when one uses working memory to recall a piece of information or when one switches between two tasks, e.g., between social media and the document one is working on).
Yet, studying the evolution of accuracy did not bring to any clear predictions. This is because accuracy depends on many factors like motivation, stress, etc. I established new behavioural and neurocomputational markers of cognitive fatigue: performing cognitive tasks for a while or following an overload of physical exercise increase choice impulsivity and decrease the neural activity of a specific brain area in the lateral prefrontal cortex.
The published research (PNAS, Current Biology) has been widely cited and downloaded over 6,000 times and received large substantial media attention (e.g., the National Public Radio in the US, French Prime Time News).
Extrinsically rewarding stimuli (e.g. food, water) and activities (e.g. fornicating) are shaped by evolution, guiding the organism to select actions that increase survival and reproduction.
Yet, many activities are pleasurable in their own right. They are undertaken even when they do not lead to an external reward that is important for survival and reproduction: they are intrinsically rewarding. Playing, problem solving, exploring nature are a few such examples. Despite the importance of intrinsic rewards for well-being we do not know how to characterise or quantify them, nor do we understand the mechanisms that govern our responses to them.
Using computational modelling, I showed that learning may be more important than reward for happiness. I also established that individual preferences related to intrinsic and extrinsic rewards can be quantified using computational modelling of happiness and strongly relate to the brain valuation system. This work suggest that measuring mood ratings and analysing them using computational modelling could be a tool measuring preference implicitly.
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