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Updated: Jan 31, 2026

Directed Dopaminergic Neuron Differentiation from Human Pluripotent Stem Cells
Published on: September 15, 2014
Cell-type and projection-specific dopaminergic encoding of aversive stimuli in addiction
Kimberly C Thibeault1, Munir Gunes Kutlu2, Christina Sanders2
1Vanderbilt Center for Addiction Research, Vanderbilt University School of Medicine, Nashville, TN 37232, USA; Vanderbilt Brain Institute, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Abstract:
Drug addiction is a major public health concern across the world for which there are limited treatment options. In order to develop new therapies to correct the behavioral deficits that result from repeated drug use, we need to understand the neural circuit dysfunction that underlies the pathophysiology of the disorder. Because the initial reinforcing effects of drugs are dependent on increases in dopamine in reward-related brain regions such as the mesolimbic dopamine pathway, a large focus of addiction research has centered on the dysregulation of this system and its control of positive reinforcement and motivation. However, in addition to the processing of positive, rewarding stimuli, there are clear deficits in the encoding and valuation of information about potential negative outcomes and how they control decision making and motivation. Further, aversive stimuli can motivate or suppress behavior depending on the context in which they are encountered. We propose a model where rewarding and aversive information guides the execution of specific motivated actions through mesocortical and mesolimbic dopamine acting on D1- and D2- receptor containing neuronal populations. Volitional drug exposure alters the processing of rewarding and aversive stimuli through remodeling of these dopaminergic circuits, causing maladaptive drug seeking, self-administration in the face of negative consequences, and drug craving. Together, this review discusses the dysfunction of the circuits controlling different types of aversive learning as well as how these guide specific discrete behaviors, and provides a conceptual framework for how they should be considered in preclinical addiction models.
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