Which cue to ‘want’? Opioid stimulation of central amygdala makes goal-trackers show stronger goal-tracking, just as sign-trackers show stronger sign-tracking
- 25 February 2012
- journal article
- Published by Elsevier BV in Behavioural Brain Research
- Vol. 230 (2), 399-408
- https://doi.org/10.1016/j.bbr.2012.02.032
Abstract
Pavlovian cues that have been paired with reward can gain incentive salience. Drug addicts find drug cues motivationally attractive and binge eaters are attracted by food cues. But the level of incentive salience elicited by a cue re-encounter still varies across time and brain states. In an animal model, cues become attractive and ‘wanted’ in an ‘autoshaping’ paradigm, where different targets of incentive salience emerge for different individuals. Some individuals (sign-trackers) find a predictive discrete cue attractive while others find a reward contiguous goal cue more attractive (location where reward arrives: goal-trackers). Here we assessed whether central amygdala mu opioid receptor stimulation enhances the phasic incentive salience of the goal-cue for goal-trackers during moments of predictive cue presence (expressed in both approach and consummatory behaviors to goal cue), just as it enhances the attractiveness of the predictive cue target for sign-trackers. Using detailed video analysis we measured the approaches, nibbles, sniffs, and bites directed at their preferred target for both sign-trackers and goal-trackers. We report that DAMGO microinjections in central amygdala made goal-trackers, like sign-trackers, show phasic increases in appetitive nibbles and sniffs directed at the goal-cue expressed selectively whenever the predictive cue was present. This indicates enhancement of incentive salience attributed by both goal trackers and sign-trackers, but attributed in different directions: each to their own target cue. For both phenotypes, amygdala opioid stimulation makes the individual's prepotent cue into a stronger motivational magnet at phasic moments triggered by a CS that predicts the reward UCS.Keywords
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