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Homeostatic Reinforcement Learning Theory, and its implications in cocaine addiction

Principal investigators: Boris Gutkin, Mehdi Keramati

In this project, we try to understand the neurobiological algorithms with which, animals' behavior is responsive not only to external events, but also to the internal physiological state of the animal. Our theoretical approach investigates the interaction between the hypothalamic nuclei and the brain reward circuitry, as the neural substrates of homeostatic regulation and reinforcement learning systems, respectively. We integrate these two systems by proposing a unified normative theory that gives a physiological definition for reward. This integrative framework gives normative explanations to several behavioral and neurobiological evidence, including temporal discounting of reward, anticipatory responding, extinction burst, modulation of midbrain dopaminergic activity by hypothalamic signals, etc.

Furthermore, within this theoretical framework, we try to understand cocaine addiction as a pathological state of the homeostatic reinforcement learning system. We show that hijacking of the dopamine signaling in the striatum by cocaine results in a maladaptive allostatic mechanism and thus, leads to a whole set of addiction-like behaviors reported in animal models of addiction.

INSERM ENS