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Published on: February 4, 2016
Motor activation in cue-guided behavior: Neural evidence from human Pavlovian-to-instrumental transfer (PIT)
Yulong Huang1, Chen Qu2, Valeria Gazzola3
1Department of Experimental Psychology, Ghent University, Henri Dunantlaan 2, 9000 Ghent, Belgium; Center for Studies of Psychological Application, School of Psychology, South China Normal University, 55 Zhongshan Avenue West, Tianhe District, Guangzhou 510631, China.
Abstract:
In everyday life, our behavior is often guided by environmental cues that predict rewarding or aversive outcomes. The Pavlovian-to-Instrumental Transfer (PIT) paradigm provides a framework for examining how conditioned stimuli (CS) influence instrumental actions (R) associated with specific outcomes (O). Two distinct mechanisms have been identified: specific PIT, where a cue selectively invigorates the action linked to the same outcome, and general PIT, where reward-predictive cues non-selectively enhance response vigor. Theoretical accounts propose that specific PIT depends on the reactivation of learned action representations by sensory-specific cues, yet it remains unclear whether such reactivation occurs during passive cue exposure (Pavlovian phase) and how it evolves across learning. Using fMRI (N = 31), we investigated cue-evoked neural activity during two Pavlovian learning phases, before and after instrumental learning, in a four-phase PIT paradigm. Behaviorally, participants showed robust specific and general PIT effects in the transfer phase. At the neural level, general PIT-related cues engaged occipito-temporal visual and associative regions early in learning, whereas specific PIT-related cues recruited fronto-parietal, premotor, sensorimotor and striatal regions (MFG, IPS, PMC/M1/S1, caudate, putamen) after instrumental learning. These findings indicate that Pavlovian cues dynamically engage motor and sensorimotor systems following action-outcome learning, consistent with outcome-mediated retrieval of learned action representations even in the absence of overt movement. Together, the results refine theoretical models of PIT by demonstrating learning-dependent modulation of corticostriatal circuits during passive cue processing.
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