Reward-related cues elicit phasic changes in activity in ventral pallidum neurons, which predict and functionally contribute to the speed of behaviors trained on the basis of act-outcome, but not stimulus-outcome, contingencies.

In vivo deconstruction of reward-related behaviors with circuit and pharmacological specificity using designer, light-controllable nicotinic acetylcholine receptors.

Excitatory output neurons in dorsomedial prefrontal cortex display heterogeneously specialized coding properties that evolve during cue-reward learning and predict cue-driven reward seeking.

Serotonin-releasing neurons show tonic firing-rate changes correlating with global reward value in addition to phasic firing-rate changes correlating with local task events.

Risk of punishment during reward seeking behavior is associated with a functional "disconnection" of the PFC-VTA circuit due to a transient loss of VTA-driven theta oscillation.

The anticipation of rewards turns out to have its own hedonic value, on top of that of the reward itself; a wide range of behavioral and neurophysiological data suggest that this anticipation is boosted by prediction errors.

A two-part neural network models reward-based training and provides a unified framework in which to study diverse computations that can be compared to electrophysiological recordings from behaving animals.

Rodent model of context-dependent discrimination reveals sex-biased tradeoff between speed of acquisition and robustness of contextual control over cue-elicited reward seeking, linked to orbitofrontal cortex activation.

A customizable open-source hardware and software platform for conducting diverse behavioral experiments in head-fixed mice.

Inhibiting ventral tegmental dopamine neurons, or their inputs to nucleus accumbens, disrupts cue-motivated reward seeking in a manner that depends on the microstructure of behavior.