What motivates the choices we make? Human decisions are frequently explained as the balancing of potential rewards and punishments, such as food, money, or lost time. However, rational models of decision making based on this idea have gloriously failed to accurately predict human behavior for decades. Some research suggests however that humans and other animals base decisions on value attribution that is often not clearly linked to extrinsic outcomes. For example, humans prefer opportunities to choose, even when these have no impact on future rewards or punishments. Thus, choice can be viewed as intrinsically motivating, i.e., an autonomous form of motivation that invigorates an agent to perform behavior in and of itself.
We seek to understand how extrinsic and intrinsic motivations act together to generate natural behavior, and to map out the neural mechanisms underlying this integration. More specifically we are designing and testing imagery and behavioral experiments to characterize primate (human and monkey) preference for intrinsic reward and measure their relative value using quantitative computational models of decision-making behavior. We then seek to pinpoint specific neural and behavioral impairments in patients with dysfunctions of hypothesized circuits, including the dopaminergic system and prefrontal cortices involved in processing rewarding experiences. Finally, we are investigating the neural circuit and its associated neurotransmitters involved in the motivation for intrinsic reward. To do so, in monkeys, we implement state-of-the-art neurophysiology techniques including multi-site high-density electrophysiological recordings, calcium-imaging, and causal manipulation techniques targeting specifically the dopaminergic system.
Using this multimodal approach, our preliminary results suggest healthy subjects can give up extrinsic reward (e.g. money) for the opportunity to choose freely. By contrast, Parkinson’s disease patients lose this preference in conditions that diminish the quantity of dopamine in their brains or by reducing the activation of medial prefrontal cortical areas via deep brain stimulation. Computational investigation also suggest that these behaviors can be predicted by reinforcement learning algorithms which identify several decision and risk attitude across individual subjects. Importantly, we also achieved specific expression of the dopaminergic neurons in wildtype monkey by injecting a cocktail of virus. This proof of concept will allow us to manipulate specifically the dopaminergic system in primates
Taken together, this translational project could significantly advance our understanding of the neurocognitive determinants of intrinsic reward and its interplay with general motivational and learning processes. Importantly this could unmask motivational mechanisms associated with behavioral impairments observed in many neuropsychiatric disorders that involved the dopaminergic system such as Parkinson’s diseases, schizophrenia, obsessive control disorders or Gilles de la Tourette syndrome.