Objetivo
The mesocorticolimbic (MCL) system, extending from the ventral tegmental area (VTA) to the nucleus accumbens and prefrontal cortex, comprises a dopamine (DA) projection implicated in reinforcement learning. The MCL system is the target of addictive substances and of drug-evoked synaptic plasticity, a cellular mechanism that may underlie the adaptive, pathological behaviors that occur after repeated drug exposure. While most previous work has focused on excitatory transmission, recent studies suggest that inhibitory transmission may play a crucial role in mediating specific functions of the MCL system. However the identity of the inhibitory synapses and circuits and the plasticity mechanisms underlying these forms of normal and pathological learning remain elusive.
We hypothesize that distinct inhibitory circuits in the MCL system mediate specific behaviors and that adaptive synaptic plasticity of these circuits are fundamental to both normal reward learning and addictive behaviors.
We will test this hypothesis using optogenetic projection targeting to characterize specific inhibitory projections, to selectively change the activity of these neurons in freely behaving animals to explore their behavioral relevance, and to identify precise circuit changes that underlie behavioral alterations after drug exposure. Taken together, the experiments we propose will not only identify the specific circuits and basic role of inhibition in mediating reward-related behaviors, but will allow us to understand how the alteration of these circuits after drugs can result in pathological behavior. Ultimately, our results will establish the importance of inhibitory synaptic transmission in the MCL system, are likely to fundamentally change current views of this important modulatory system, and will allow us to design strategies to interfere with drug-evoked synaptic plasticity to revert addictive behavior.
Ámbito científico (EuroSciVoc)
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural.
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural.
- ciencias naturalesinformática y ciencias de la informacióninteligencia artificialaprendizaje automáticoaprendizaje por refuerzo
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Convocatoria de propuestas
ERC-2012-ADG_20120314
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Régimen de financiación
ERC-AG - ERC Advanced GrantInstitución de acogida
1211 Geneve
Suiza