Understanding how drugs of abuse alter the computational properties of neural populations has been characterized as a "necessary intermediary" to identify how cellular-level changes in neurobiology, induced by the drug, manifest altered behavioral phenotypes commonly observed in addiction (Kalivas, 2005). While numerous neurotransmitter systems play a role in encoding reward-related information and guiding motivated behavior, overwhelming evidence identifies the mesocorticolimbic dopamine system as particularly important in these processes. Furthermore, multiple drugs of abuse, including alcohol, evoke persistent neuroadaptations in the dopamine system that are thought to be a primary biological feature that underlies the expression of the addicted phenotype. Drugs of abuse, such as opiates and psychostimulants, have received considerable attention in modeling studies as their clear pharmacological mechanism of action on ventral tegmental area dopamine (DA) neurons provides a computationally tractable target. An understanding of alcohols pharmacological and physiological effects on the DA system are improving, but understanding the specific mechanisms by which alcohol modulates ventral tegmental area microcircuits and specifically GABA-DA dynamics are still largely a mystery. Considering alcohol use disorders are the most pervasive of all addiction spectrum disorders and alcohol abuse is estimated to be responsible to 2.5 million deaths world-wide annually, understanding how alcohol alters DA signaling represents a currently unmet and critical medical need. The immediate goal of this France-USA collaboration is to quantify the acute effects of alcohol on the dynamics of GABA-DA crosstalk and ultimately the integrative and computational properties of this neural system. A balance between intrinsic conductances and synaptic inputs mediates both pacemaking and burst firing in the DA neuron, which ultimately controls tonic and phasic release of DA. Our hypothesis is 1) alcohol modifies intrinsic conductances, which have the net effect of increasing the dynamic range of DA neuron activity and 2) in parallel, this is boosted by changes in GABA release onto DA neurons allowing for increased bursting. To test these hypotheses, we will combine single cell and network biophysical models of DA and GABA neurons to motivate in vitro and in vivo experiments to assess synaptic and network function. Our goal is to build a toolbox able to drive and predict experimental approaches that allow for the changes induced by alcohol on DA dynamics to be quantified. The models will be developed together by the USA and French theoretical teams. The French and USA experimental teams will perform in vitro and in vivo experiments, respectively, using cutting edge electrophysiological techniques. Our overall goal is to clarify the key biophysical mechanisms by which alcohol usurps the function of dopaminergic circuits in the ventral tegmentum and thus motivational signals. Intellectual merit: This proposal aims to model and characterize alcohol-induced effects in the dopamine system, notably the ventral tegmental area. As such, our work will provide experimental data and computational tools to understand the neuronal and circuit level effects of alcohol on DA and GABA neuronal circuits. Notably, the models of DA and GABA neuron spiking and their local circuit interactions proposed herein are not currently available. Developing these model have application beyond this project and would be easily incorporated into high-level models of reward-based learning and behavior. Furthermore, the tools developed can be used to study the biophysics of reward signaling for other drugs of abuse and understand the basic biological mechanisms of motivated behavior. Broader Impact: Our project will provide data and modeling tools that can potentially identify the key site of actin and mechanism for alcohols initial effects on motivational signaling. These data will also provide the necessary framework to understand how alcohol's actions on motivational circuits are altered in populations genetically vulnerable to alcohol use disorders. Moreover, these data will provide a critical first step to develop computational models that trace the progressive changes in cellular and circuit level signaling by chronic alcohol. Potential therapeutic targets to treat alcoholism could be modeled, leading to the discovery or development of novel translational approaches to treat this disease. Furthermore, the computational tools developed will set the stage to understand the biophysics of co-morbidity between alcohol and nicotine, another highly addictive substance. In summary we believe the outcomes of this project will have a broad translational impact. In terms of educational impact, this project initiates a consortium between US and French institutions and provides funding for two postdoctoral trainees, will provide training opportunities for at least one graduate student, and three undergraduate students. Moreover, this project will stimulate a robust collaborative program between the participating institutions that is certain to stimulate novel projects and collaborative science beyond the currently proposed studies.

National Institute of Health (NIH)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Matochik, John A
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Indiana University-Purdue University at Indianapolis
Biostatistics & Other Math Sci
Schools of Arts and Sciences
United States
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