TY - JOUR
T1 - Reinforcement learning detuned in addiction
T2 - integrative and translational approaches
AU - Groman, Stephanie M.
AU - Thompson, Summer L.
AU - Lee, Daeyeol
AU - Taylor, Jane R.
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022/2
Y1 - 2022/2
N2 - Suboptimal decision-making strategies have been proposed to contribute to the pathophysiology of addiction. Decision-making, however, arises from a collection of computational components that can independently influence behavior. Disruptions in these different components can lead to decision-making deficits that appear similar behaviorally, but differ at the computational, and likely the neurobiological, level. Here, we discuss recent studies that have used computational approaches to investigate the decision-making processes underlying addiction. Studies in animal models have found that value updating following positive, but not negative, outcomes is predictive of drug use, whereas value updating following negative, but not positive, outcomes is disrupted following drug self-administration. We contextualize these findings with studies on the circuit and biological mechanisms of decision-making to develop a framework for revealing the biobehavioral mechanisms of addiction.
AB - Suboptimal decision-making strategies have been proposed to contribute to the pathophysiology of addiction. Decision-making, however, arises from a collection of computational components that can independently influence behavior. Disruptions in these different components can lead to decision-making deficits that appear similar behaviorally, but differ at the computational, and likely the neurobiological, level. Here, we discuss recent studies that have used computational approaches to investigate the decision-making processes underlying addiction. Studies in animal models have found that value updating following positive, but not negative, outcomes is predictive of drug use, whereas value updating following negative, but not positive, outcomes is disrupted following drug self-administration. We contextualize these findings with studies on the circuit and biological mechanisms of decision-making to develop a framework for revealing the biobehavioral mechanisms of addiction.
KW - amygdala
KW - decision-making
KW - dopamine
KW - mGlu5
KW - nucleus accumbens
KW - orbitofrontal cortex
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U2 - 10.1016/j.tins.2021.11.007
DO - 10.1016/j.tins.2021.11.007
M3 - Review article
C2 - 34920884
AN - SCOPUS:85121272221
SN - 0166-2236
VL - 45
SP - 96
EP - 105
JO - Trends in neurosciences
JF - Trends in neurosciences
IS - 2
ER -