Amy J. Tindell

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The ventral pallidum (VP) is a key structure in brain mesocorticolimbic reward circuits that mediate "liking" reactions to sensory pleasures. Do firing patterns in VP actually code sensory pleasure? Strong evidence for hedonic coding requires showing that neural signals track positive increases in sensory pleasure or even reversals from bad to good. A(More)
In recent years the ventral pallidum has become a focus of great research interest as a mechanism of reward and incentive motivation. As a major output for limbic signals, the ventral pallidum was once associated primarily with motor functions rather than regarded as a reward structure in its own right. However, ample evidence now suggests that ventral(More)
Incentive salience is a motivational property with 'magnet-like' qualities. When attributed to reward-predicting stimuli (cues), incentive salience triggers a pulse of 'wanting' and an individual is pulled toward the cues and reward. A key computational question is how incentive salience is generated during a cue re-encounter, which combines both learning(More)
Neurons in ventral pallidum fire to reward and its predictive cues. We tested mesolimbic activation effects on neural reward coding. Rats learned that a Pavlovian conditioned stimulus (CS+1 tone) predicted a second conditioned stimulus (CS+2 feeder click) followed by an unconditioned stimulus (UCS sucrose reward). Some rats were sensitized to amphetamine(More)
We recorded neural activity in the ventral pallidum (VP) while rats learned a pavlovian reward association. Rats learned to distinguish a tone that predicted sucrose pellets (CS+) from a different tone that predicted nothing (CS-). Many VP units became responsive to CS+, but few units responded to CS-. When two CS+ were encountered sequentially, the(More)
Pavlovian cues for rewards become endowed with incentive salience, guiding "wanting" to their learned reward. Usually, cues are "wanted" only if their rewards have ever been "liked," but here we show that mesocorticolimbic systems can recompute "wanting" de novo by integrating novel physiological signals with a cue's preexisting associations to an outcome(More)
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