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Psychophysiological Outcome Responses in Human Pavlovian Fear Conditioning: A Prediction Error Analysis.

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Bibliographic Details
Title: Psychophysiological Outcome Responses in Human Pavlovian Fear Conditioning: A Prediction Error Analysis.
Authors: Liu, Huaiyu (AUTHOR), Linnell, Josie (AUTHOR), Bach, Dominik R. (AUTHOR)
Source: Psychophysiology. Apr2026, Vol. 63 Issue 4, p1-12. 12p.
Subjects: Associative learning, Psychophysiology, Pupillary reflex, Classical conditioning, Galvanic skin response
Abstract: Prediction errors (PE) are thought to drive associative learning. While neural signals consistent with PE encoding have been identified, the expression of PE in psychophysiological indices remains debated. Here, we sought to fill this gap by investigating responses to unconditioned stimulus (US) occurrence and probability in skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), and respiration amplitude responses (RAR). Data set 1 consisted of eight published studies (N1 = 264) using differential fear conditioning with partial reinforcement (50%), and novel data set 2 (N2 = 29) parametrically varied US probability (20%/50%/80%). Across both data sets, all modalities showed differential responses to the US compared to US omission. In data set 1, there was evidence for responses to unexpected as compared to expected US omission in all modalities, but no responses were consistent with signed or unsigned PE encoding. Similarly, data set 2 provided no evidence that US or US omission responses monotonically related to outcome probability, which is incompatible with both signed and unsigned PE encoding. In conclusion, all recorded psychophysiological signals responded strongly to US and less strongly to unexpected US omission, with no evidence of either signed or unsigned PE encoding. Impact Statement: Pavlovian reward learning is driven by prediction errors (PE), but it remains unclear whether this is also the case for aversive learning, and to what extent PE are expressed in physiological indices. Here, we examined responses to outcome magnitude and probability to assess the expression of PE across four psychophysiological indices (SCR, PSR, HPR, RAR). Results replicated the well‐known US response in all modalities; however, we found clear evidence against signed PE encoding and no evidence for unsigned PE encoding. These findings may inform future work on computational modeling of fear learning and reconsolidation‐based clinical interventions. [ABSTRACT FROM AUTHOR]
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Database: Psychology and Behavioral Sciences Collection
Description
Abstract:Prediction errors (PE) are thought to drive associative learning. While neural signals consistent with PE encoding have been identified, the expression of PE in psychophysiological indices remains debated. Here, we sought to fill this gap by investigating responses to unconditioned stimulus (US) occurrence and probability in skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), and respiration amplitude responses (RAR). Data set 1 consisted of eight published studies (N1 = 264) using differential fear conditioning with partial reinforcement (50%), and novel data set 2 (N2 = 29) parametrically varied US probability (20%/50%/80%). Across both data sets, all modalities showed differential responses to the US compared to US omission. In data set 1, there was evidence for responses to unexpected as compared to expected US omission in all modalities, but no responses were consistent with signed or unsigned PE encoding. Similarly, data set 2 provided no evidence that US or US omission responses monotonically related to outcome probability, which is incompatible with both signed and unsigned PE encoding. In conclusion, all recorded psychophysiological signals responded strongly to US and less strongly to unexpected US omission, with no evidence of either signed or unsigned PE encoding. Impact Statement: Pavlovian reward learning is driven by prediction errors (PE), but it remains unclear whether this is also the case for aversive learning, and to what extent PE are expressed in physiological indices. Here, we examined responses to outcome magnitude and probability to assess the expression of PE across four psychophysiological indices (SCR, PSR, HPR, RAR). Results replicated the well‐known US response in all modalities; however, we found clear evidence against signed PE encoding and no evidence for unsigned PE encoding. These findings may inform future work on computational modeling of fear learning and reconsolidation‐based clinical interventions. [ABSTRACT FROM AUTHOR]
ISSN:00485772
DOI:10.1111/psyp.70300