Behavioral Neuroscience

by haloperidol, participants learned slower and earned less money compared to the control group. Interestingly, no shift of the learning curves was observed when participants were in the loss condition, which suggests that other processes are involved in aversive learning. In a separate study using the Iowa gambling task, an activation of the ventral striatum has also been shown by fMRI (Li et al., 2010). The effect of DA on learning can be explained by a modulation of the mesocorticolimbic system of circuits involved in action planning and decision-making. In many mammals, at least two systems exist to predict the value of an action: the planning or explicit system, which takes a given situation, predicts an outcome and evaluates that outcome; and the habit or implicit system, which takes a given situation and identifies the best remembered action to take (Redish et al., 2008). The flexible planning system involves the ventral and dorsomedial striatum, the prelimbic medial prefrontal cortex and the orbitofrontal cortex, as well as the entorhinal cortex and hippocampus, with an involvement of DA inputs from the VTA. The habit system involves the dorsolateral striatum, the infralim-bic medial prefrontal cortex as well as the parietal cortex, with an involvement of DA inputs from the pars compacta of the substantia nigra (SNc; Redish et al., 2008). The mesocorticolimbic system thus has a central role in evaluating the value of predicted outcomes during decision-making and planning. An over-evaluation of a predicted value by the DA system might alter the decision system leading to addictive behaviors (Redish et al., 2008). Another mechanism leading to automatic decision-making and even addiction could be the recruitment of the habit system by the NAc via feedback loops to the dorsal striatum (Koob and Volkow, 2010). Understanding how modulation of DA can alter valuation and decision-processing therefore has profound implication for understanding motivated