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Papers of the Week

Papers: 7 Mar 2020 - 13 Mar 2020


Human Studies

2020 Mar 05


Learning mechanisms in nocebo hyperalgesia: the role of conditioning and extinction processes.


Thomaidou M A, Veldhuijzen D S, Peerdeman K J, Sifra Wiebing N Z, Blythe J S, Maria Evers A W
Pain. 2020 Mar 05.
PMID: 32149863.


Nocebo hyperalgesia is a clinically relevant phenomenon and may be formed as a result of associative learning, implemented by classical conditioning. This study explored for the first time distinct nocebo conditioning methods and their consequences for nocebo attenuation methods. Healthy participants (N = 140) were recruited and randomized to the following nocebo hyperalgesia induction groups: conditioning with continuous reinforcement (CRF), conditioning with partial reinforcement (PRF), and a sham-conditioning control group. In the attenuation phase, counterconditioning was compared to extinction. During induction, participants experienced increased thermal pain in 100% of nocebo trials in the CRF groups, while in only 70% of nocebo trials in the PRF groups. During evocation, pain stimulation was equivalent across all trials. During attenuation, pain stimulation was decreased on nocebo trials relative to control trials for the counterconditioning groups, while pain remained equivalent across all trials for the extinction groups. Results showed that both PRF and CRF significantly induced nocebo hyperalgesia, but CRF was a more potent nocebo induction method, as compared to PRF. Counterconditioning was more effective than extinction in attenuating nocebo hyperalgesia. Neither CRF nor PRF resulted in resistance to extinction. However, compared to CRF, conditioning with PRF resulted in more resistance to counterconditioning. These findings demonstrate that the more ambiguous learning method of PRF can induce nocebo hyperalgesia and may potentially explain the treatment resistance and chronification seen in clinical practice. Further research is required to establish whether attenuation with counterconditioning is generalizable to clinical settings.