Neural correlates of appetitive extinction in humans. Issue 1 (31st October 2016)

• Record Type: Journal Article
• Authors: Kruse, Onno; Tapia León, Isabell; Stark, Rudolf; Klucken, Tim
• Is Part Of: Social cognitive and affective neuroscience. Volume 12:Issue 1(2017)
• Page Start: 106
• Page End: 115
• Publication Date: 2016-10-31
• Subjects: fMRI -- reward -- conditioning -- extinction -- nucleus accumbens -- amygdala; Neurosciences -- Periodicals; Cognitive neuroscience -- Periodicals; Neuropsychology -- Periodicals; 612.8205
• DOI: 10.1093/scan/nsw157
• Languages: English
• ISSNs: 1749-5016

Abstract

Abstract: Appetitive extinction receives attention as an important model for the treatment of psychiatric disorders. However, in humans, its underlying neural correlates remain unknown. To close this gap, we investigated appetitive acquisition and extinction with fMRI in a 2-day monetary incentive delay paradigm. During appetitive conditioning, one stimulus (CS+) was paired with monetary reward, while another stimulus (CS−) was never rewarded. Twenty-four hours later, subjects underwent extinction, in which neither CS was reinforced. Appetitive conditioning elicited stronger skin conductance responses to the CS+ as compared with the CS−. Regarding subjective ratings, the CS+ was rated more pleasant and arousing than the CS− after conditioning. Furthermore, fMRI-results (CS+ − CS−) showed activation of the reward circuitry including amygdala, midbrain and striatal areas. During extinction, conditioned responses were successfully extinguished. In the early phase of extinction, we found a significant activation of the caudate, the hippocampus, the dorsal and ventral anterior cingulate cortex (dACC and vACC). In the late phase, we found significant activation of the nucleus accumbens (NAcc) and the amygdala. Correlational analyses with subjective ratings linked extinction success to the vACC and the NAcc, while associating the dACC with reduced extinction. The results reveal neural correlates of appetitive extinction in humans and extend assumptions from models for human extinction learning.