Format

Send to

Choose Destination
Prog Brain Res. 2014;211:31-77. doi: 10.1016/B978-0-444-63425-2.00003-9.

The role of learning-related dopamine signals in addiction vulnerability.

Author information

1
Translational Neuromodeling Unit, Department of Biomedical Engineering, ETH Zürich and University of Zürich, Zürich, Switzerland; Department of Psychiatry, Psychosomatics and Psychotherapy, Hospital of Psychiatry, University of Zürich, Zürich, Switzerland. Electronic address: qhuys@cantab.net.
2
Department of Economics, Laboratory for Social and Neural Systems Research, University of Zürich, Zürich, Switzerland.
3
Department of Psychiatry, University of Bern, Bern, Switzerland.
4
Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA.

Abstract

Dopaminergic signals play a mathematically precise role in reward-related learning, and variations in dopaminergic signaling have been implicated in vulnerability to addiction. Here, we provide a detailed overview of the relationship between theoretical, mathematical, and experimental accounts of phasic dopamine signaling, with implications for the role of learning-related dopamine signaling in addiction and related disorders. We describe the theoretical and behavioral characteristics of model-free learning based on errors in the prediction of reward, including step-by-step explanations of the underlying equations. We then use recent insights from an animal model that highlights individual variation in learning during a Pavlovian conditioning paradigm to describe overlapping aspects of incentive salience attribution and model-free learning. We argue that this provides a computationally coherent account of some features of addiction.

KEYWORDS:

addiction; dopamine; incentive salience; model-free; prediction error; reinforcement learning; sign-tracking

[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center