scholarly journals Learning to predict pain: differences in people with persistent neck pain and pain-free controls

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9345
Author(s):  
Daniel S. Harvie ◽  
Jeroen D. Weermeijer ◽  
Nick A. Olthof ◽  
Ann Meulders

Background Learning to predict threatening events enables an organism to engage in protective behavior and prevent harm. Failure to differentiate between cues that truly predict danger and those that do not, however, may lead to indiscriminate fear and avoidance behaviors, which in turn may contribute to disability in people with persistent pain. We aimed to test whether people with persistent neck pain exhibit contingency learning deficits in predicting pain relative to pain-free, gender-and age-matched controls. Method We developed a differential predictive learning task with a neck pain-relevant scenario. During the acquisition phase, images displaying two distinct neck positions were presented and participants were asked to predict whether these neck positions would lead to pain in a fictive patient with persistent neck pain (see fictive patient scenario details in Appendix A). After participants gave their pain-expectancy judgment in the hypothetical scenario, the verbal outcome (PAIN or NO PAIN) was shown on the screen. One image (CS+) was followed by the outcome “PAIN”, while another image (CS−) was followed by the outcome “NO PAIN”. During the generalization phase, novel but related images depicting neck positions along a continuum between the CS+ and CS− images (generalization stimuli; GSs) were introduced to assess the generalization of acquired predictive learning to the novel images; the GSs were always followed by the verbal outcome “NOTES UNREADABLE” to prevent extinction learning. Finally, an extinction phase was included in which all images were followed by “NO PAIN” assessing the persistence of pain-expectancy judgments following disconfirming information. Results Differential pain-expectancy learning was reduced in people with neck pain relative to controls, resulting from patients giving significantly lower pain-expectancy judgments for the CS+, and significantly higher pain-expectancy judgments for the CS−. People with neck pain also demonstrated flatter generalization gradients relative to controls. No differences in extinction were noted. Discussion The results support the hypothesis that people with persistent neck pain exhibit reduced differential pain-expectancy learning and flatter generalization gradients, reflecting deficits in predictive learning. Contrary to our hypothesis, no differences in extinction were found. These findings may be relevant to understanding behavioral aspects of chronic pain.

Author(s):  
Tanja C. Hamacher-Dang ◽  
Harald Engler ◽  
Manfred Schedlowski ◽  
Oliver T. Wolf

2020 ◽  
Author(s):  
Jonas Zaman ◽  
Jessica C. Lee

When novel stimuli trigger a previously learned response, this can be due to failure to perceive the novel stimulus as different from the trained stimulus (perception), or active extrapolation of learned properties from the trained stimulus (induction). To date, there has been little investigation of how individual differences in perceptual ability relate to differences in induction. In this paper, we perform cluster analysis in six datasets (four published datasets and two unpublished datasets, N = 992 total) to examine the relationship between individual differences in perception and induction, as well as the utility of perception in predicting generalization gradients. The datasets were obtained from predictive learning tasks where participants learned associations between different colored cues and the presence or absence of a hypothetical outcome. In these datasets, stimulus perception and response generalization (expectancy ratings) were assessed in separate phases. Using cluster analyses, we identified similar subgroups of good and bad perceivers in all six datasets, with distinct patterns of response generalization between these subgroups. Based on the differences in stimulus perception, we could predict where across the stimulus range generalized responses would differ between subgroups as well as the direction of the difference. Furthermore, participants classified as good perceivers were more likely to report a similarity generalization rule than a relational or linear rule, providing evidence that individual differences in perception predict differences in induction. These findings suggest that greater consideration should be given to inter-individual variability in perception and induction and their relationship in explaining response generalization.


2016 ◽  
Vol 124 ◽  
pp. 66-73 ◽  
Author(s):  
José A. Aristizabal ◽  
Manuel M. Ramos-Álvarez ◽  
José E. Callejas-Aguilera ◽  
Juan M. Rosas

2018 ◽  
Vol 21 ◽  
Author(s):  
A. Matías Gámez ◽  
Rodolfo Bernal-Gamboa

AbstractOne of the most relevant phenomena both from a theoretical and clinical perspective is extinction. In particular, several researchers are interested in the response recovery effects from extinction. Reinstatement is an effect that has been proposed as a laboratory model to study relapse from extinction-based therapeutic treatments. We designed two experiments with humans to evaluate the reinstatement effect in a predictive learning task. In both experiments, participants learned a specific relationship between two cues (X and Y) and two outcomes (O1 and O2) during the first phase. Throughout extinction, both cues were presented without outcomes. After an exposure to the original outcomes, reinstatement of the first-learned information was observed during testing in both experiments. However, we found that the reinstatement effect was contextual modulated (Experiment 1; ηp2 = .78, 90% CI [.48, .86], p < .0001). Furthermore, in Experiment 2 we showed a reduction of reinstatement when an extinction reminder was used ηp2 = .45, 90% CI [.07, .65], p = .012. Theoretical implications are discussed, and some potential uses are mentioned.


2012 ◽  
Vol 24 (4) ◽  
pp. 794-808 ◽  
Author(s):  
David Luque ◽  
Francisco J. López ◽  
Josep Marco-Pallares ◽  
Estela Càmara ◽  
Antoni Rodríguez-Fornells

Feedback-related negativity (FRN) is an ERP component that distinguishes positive from negative feedback. FRN has been hypothesized to be the product of an error signal that may be used to adjust future behavior. In addition, associative learning models assume that the trial-to-trial learning of cue–outcome mappings involves the minimization of an error term. This study evaluated whether FRN is a possible electrophysiological correlate of this error term in a predictive learning task where human subjects were asked to learn different cue–outcome relationships. Specifically, we evaluated the sensitivity of the FRN to the course of learning when different stimuli interact or compete to become a predictor of certain outcomes. Importantly, some of these cues were blocked by more informative or predictive cues (i.e., the blocking effect). Interestingly, the present results show that both learning and blocking affect the amplitude of the FRN component. Furthermore, independent analyses of positive and negative feedback event-related signals showed that the learning effect was restricted to the ERP component elicited by positive feedback. The blocking test showed differences in the FRN magnitude between a predictive and a blocked cue. Overall, the present results show that ERPs that are related to feedback processing correspond to the main predictions of associative learning models.


2011 ◽  
Vol 42 (1) ◽  
pp. 84-98 ◽  
Author(s):  
Samuel P. León ◽  
María J.F. Abad ◽  
Juan M. Rosas

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