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The nucleus accumbens (NAc) contributes to behavioral inhibition and compulsions, but circuit mechanisms are unclear. Recent evidence suggests that amygdala and thalamic inputs exert opposing control over behavior, much like direct and indirect pathway output neurons. Accordingly, opponent processes between these NAc inputs or cell types may underlie efficient reward seeking. We assess the contributions of these circuit elements to mouse operant behavior during recurring conditions when reward is and is not available. Although direct pathway stimulation is rewarding and indirect pathway stimulation aversive, the activity of both cell types is elevated during periods of behavioral suppression, and the inhibition of either cell-type selectively increases unproductive reward seeking. Amygdala and thalamic inputs are also necessary for behavioral suppression, even though they both support self-stimulation and innervate different NAc subregions. These data suggest that efficient reward seeking relies on complementary activity across NAc cell types and inputs rather than opponent processes between them.

Cue-evoked midbrain dopamine (DA) neuron activity reflects expected value, but its influence on reward assessment is unclear. In mice performing a trial-based operant task, we test if bidirectional manipulations of cue or operant-associated DA neuron activity drive learning as a result of under- or overexpectation of reward value. We target optogenetic manipulations to different components of forced trials, when only one lever is presented, and assess lever biases on choice trials in the absence of photomanipulation. Although lever biases are demonstrated to be flexible and sensitive to changes in expected value, augmentation of cue or operant-associated DA signaling does not significantly alter choice behavior, and blunting DA signaling during any component of the forced trials reduces choice trial responses on the associated lever. These data suggest cue-evoked DA helps maintain cue-value associations but does not encode expected value as to set the benchmark against which received reward is judged.