Pupil dilation and skin conductance as measures of prediction error in aversive learning

Stemerding, Lotte E.; Ast, Vanessa A. van; Gerlicher, Anna; Kindt, Merel

doi:10.1016/j.brat.2022.104164

Cited by 10 publications

(15 citation statements)

References 49 publications

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“…The US consisted of a 2 ms aversive electrical shock (Effting & Kindt, 2007; Krypotos et al, 2014, 2015; Starita et al, 2022; Stemerding et al, 2022) generated by a Digitimer Stimulator (Model DS7A, Digitimer Ltd., UK) and delivered to the participants' right wrist through pre‐gelled Ag/AgCl snapped electrodes (Friendship Medical, SEAg‐S‐15000/15 × 20). The US intensity ( M = 43.47 mA, SD = 22.41 mA) was calibrated for each participant to a level deemed “highly unpleasant, but not painful” using an ascending staircase procedure (Lonsdorf et al, 2017; Starita et al, 2016, 2022; Starita, Kroes, et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

Theta and alpha power track the acquisition and reversal of threat predictions and correlate with skin conductance response

et al. 2023

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The ability to flexibly adjust one's threat predictions to meet the current environmental contingencies is crucial to survival. Nevertheless, its neural oscillatory correlates remain elusive in humans. Here, we tested whether changes in theta and alpha brain oscillations mark the updating of threat predictions and correlate with response of the peripheral nervous system. To this end, electroencephalogram and electrodermal activity were recorded in a group of healthy adults, who completed a Pavlovian threat conditioning task that included an acquisition and a reversal phase. Both theta and alpha power discriminated between threat and safety, with each frequency band showing unique patterns of modulations during acquisition and reversal. While changes in midcingulate theta power may learn the timing of an upcoming danger, alpha power may reflect the preparation of the somato‐motor system. Additionally, ventromedial prefrontal cortex theta may play a role in the inhibition of previously acquired threat responses, when they are no longer appropriate. Finally, theta and alpha power correlated with skin conductance response, establishing a direct relationship between activation of the central and peripheral nervous systems. Taken together these results highlight the existence of multiple oscillatory systems that flexibly regulate their activity for the successful expression of threat responses in an ever‐changing environment.

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Section: Methodsmentioning

confidence: 99%

Theta and alpha power track the acquisition and reversal of threat predictions and correlate with skin conductance response

et al. 2023

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“…Cooper et al ( 25 ) observed only rare pupil responses to auditory omissions in paralyzed cats [but note that the relationship between subcortical activity and pupil responses differs substantially between species, e.g., ( 18 , 26 )]. Stemmerding et al ( 27 ) observed responses to the omission of fear stimuli in the skin conductance response but not in the PDR. Damsma and Van Rijn ( 28 ) observed an amplified PDR only for omission of the most salient sound on the first beat of a drum sequence but not for the second beat or hi-hat sounds.…”

Section: Introductionmentioning

confidence: 99%

“…An important difference between pupillometry and EEG omission studies is the condition to which the omission is compared. In pupillometry studies, unexpected omissions have typically been compared to standard stimuli ( 27 – 29 ), while in EEG studies, unexpected omissions are compared to expected omissions. This reintroduces stimulus-specific confounds to pupillometry studies and may have contributed to inconsistent results in the past.…”

Section: Introductionmentioning

confidence: 99%

Salient omissions—pupil dilation in response to unexpected omissions of sound and touch

2023

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IntroductionRecent theories describe perception as an inferential process based on internal predictive models adjusted by means of prediction violations (prediction error). To study and demonstrate predictive processing in the brain the use of unexpected stimulus omissions has been suggested as a promising approach as the evoked brain responses are uncontaminated by responses to stimuli. Here, we aimed to investigate the pupil’s response to unexpected stimulus omissions in order to better understand surprise and orienting of attention resulting from prediction violation. So far only few studies have used omission in pupillometry research and results have been inconsistent.MethodsThis study adapted an EEG paradigm that has been shown to elicit omission responses in auditory and somatosensory modalities. Healthy adults pressed a button at their own pace, which resulted in the presentation of sounds or tactile stimuli in either 88%, 50% or 0% (motor-control) of cases. Pupil size was recorded continuously and averaged to analyze the pupil dilation response associated with each condition.ResultsResults revealed that omission responses were observed in both modalities in the 88%-condition compared to motor-control. Similar pupil omission responses were observed between modalities, suggesting modality-unspecific activation of the underlying brain circuits.DiscussionIn combination with previous omission studies using EEG, the findings demonstrate predictive models in brain processing and point to the involvement of subcortical structures in the omission response. Our pupillometry approach is especially suitable to study sensory prediction in vulnerable populations within the psychiatric field.

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“…To date, work examining the correspondence of task-evoked pupillary responses with probabilistic surprise has focused on associative learning and perceptual inference [22,27,31].…”

Section: Introductionmentioning

confidence: 99%

Task-evoked pupillary responses track precision-weighted prediction errors and learning rate during interceptive visuomotor actions

Harris¹,

Arthur²,

Vine³

et al. 2022

Preprint

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In this study we examined the relationship between physiological encoding of surprise and the learning of anticipatory eye movements. Active inference portrays perception and action as interconnected inference processes driven by the imperative to minimise the surprise of sensory observations. To examine this characterisation of oculomotor learning during a hand-eye coordination task, we tested whether anticipatory eye movements were updated in accordance with Bayesian principles and whether learning rates tracked pupil dilation as a marker of ‘surprise’. Forty-four participants completed an interception task in immersive virtual reality that required them to hit bouncing balls with either expected or unexpected bounce profiles. We recorded anticipatory eye movements known to index participants’ beliefs about likely ball bounce trajectories. By fitting a hierarchical Bayesian inference model to the trial-wise trajectories of these predictive eye movements, we were able to estimate each individual’s expectations about bounce trajectories, rates of belief updating, and precision-weighted prediction errors. We found that the task-evoked pupil response tracked prediction errors and learning rates but not beliefs about ball bounciness or environmental volatility. These findings are partially consistent with active inference accounts and shed light on how encoding of surprise may shape the control of action.

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Pupil dilation and skin conductance as measures of prediction error in aversive learning

Cited by 10 publications

References 49 publications

Theta and alpha power track the acquisition and reversal of threat predictions and correlate with skin conductance response

Theta and alpha power track the acquisition and reversal of threat predictions and correlate with skin conductance response

Salient omissions—pupil dilation in response to unexpected omissions of sound and touch

Task-evoked pupillary responses track precision-weighted prediction errors and learning rate during interceptive visuomotor actions

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