P300 amplitude variations, prior probabilities, and likelihoods: A Bayesian ERP study

Kopp, Bruno; Seer, Caroline; Lange, Florian; Kluytmans, Anouck; Kolossa, Antonio; Fingscheidt, Tim; Hoijtink, Herbert

doi:10.3758/s13415-016-0442-3

Cited by 52 publications

(44 citation statements)

References 68 publications

(92 reference statements)

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“…A second interpretation in terms of Bayesian Brain theory is that the P3 reflects sensory representations that include the reliability of the percept (Kopp et al, 2016). This second view is consistent with classical interpretations of the P3 as update of working memory in response to task-relevant events (Donchin & Coles, 1988) or global broadcast of information within a neural global workspace (Sergent et al, 2005).…”

Section: Bayesian Accounts Of the Relation Between P3 And Confidencesupporting

confidence: 74%

Cognitive modelling reveals distinct electrophysiological markers of decision confidence and error monitoring

Rausch

Zehetleitner

Steinhauser

et al. 2019

Preprint

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Is confidence in perceptual decisions generated by the same brain processes as decision itself, or does confidence require metacognitive processes following up on the decision? In a masked orientation task with varying stimulus-onset-asynchrony, we used EEG and cognitive modelling to trace the timing of the neural correlates of confidence.Confidence as reported by observers increased with stimulus-onset-asynchrony in correct and to a lesser degree in incorrect trials, a pattern incompatible with established models of confidence. Electrophysiological activity in two different time periods was associated with confidence, namely, 350 -500 ms after stimulus onset and 250 -350 ms after the response.Cognitive modelling revealed that only the activity following on the stimulus exhibited the same statistical regularities as confidence, while the statistical pattern of the activity following the response was not compatible with confidence. It is argued that electrophysiological markers of decision confidence and error awareness are at least in parts distinct.

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Section: Bayesian Accounts Of the Relation Between P3 And Confidencesupporting

confidence: 74%

Cognitive modelling reveals distinct electrophysiological markers of decision confidence and error monitoring

Rausch

Zehetleitner

Steinhauser

et al. 2019

Preprint

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“…This oddball effect has often been conceived in terms of (subjective) probability (Duncan‐Johnson & Donchin, ; Johnson, ; Kopp et al, ; Mars et al, ), separable into global event probability and local probability, the latter being due to expectancies generated by specific preceding stimulus sequences (Squires, Wickens, Squires, & Donchin, ). See Section 4.2 for discussion of the expectancy construct.…”

Section: Experimental Variables: Effects Of Frequency and Relevancementioning

confidence: 99%

Effects of relevance and response frequency on P3b amplitudes: Review of findings and comparison of hypotheses about the process reflected by P3b

2020

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Diverse psychological correlates have been ascribed to “P300,” the conspicuous P3b component of event‐related potentials (ERPs) recorded in many laboratory tasks. Traditionally, hypotheses on P3b have conceived of this component being independent from implementing the response to the present stimulus. This has changed in the recent decade when P3b has been related to aspects of the decision process. The present review first focusses on effects of the classic variables stimulus frequency and relevance on P3b amplitude. It turns out that already these effects are related to response requirements because effects of stimulus frequency actually are effects of frequency of response‐defined stimulus categories and effects of relevance may be defined as effects of graduating the response requirements. Then, constructs and hypotheses on psychological functions reflected by P3b are evaluated for their abilities in explaining those effects. The tested constructs are information, relevance, and capacity, and the hypotheses are priming, cognitive processing, memory storage, context updating, closure, response facilitation, decision, stimulus–response (S–R) link reactivation, and conscious representations. S–R link reactivation hypothesis performed best, closely followed by memory storage and closure hypotheses. To make further progress, more studies should conduct tests between competing hypotheses.

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“…In the present study, we moved a step forward using electroencephalography (EEG) to overcome the poor temporal resolution of fMRI and to better describe the dynamics of neural processes of temporal updating and surprise. Following the EEG-based research on Bayesian belief updating (see Kopp et al, 2016, for an overview), we predicted to differentiate updating and surprise at the level of the P3 event-related potential (ERP) family (Donchin & Coles, 1988;Polich, 2007;Sutton et al, 1965). It is a well-replicable fact that P3 amplitudes are inversely related to stimulus probabilities (Donchin & Coles, 1988).…”

Section: Introductionmentioning

confidence: 99%

Electroencephalographic Correlates of Temporal Bayesian Belief Updating and Surprise

Visalli¹,

Capizzi²,

Ambrosini³

et al. 2020

Preprint

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The brain predicts the timing of forthcoming events to optimize responses to them. Temporal predictions have been formalized in terms of the hazard function, which integrates prior beliefs on the likely timing of stimulus occurrence with information conveyed by the passage of time. However, how the human brain updates prior temporal beliefs is still elusive. Here we investigated electroencephalographic (EEG) signatures associated with Bayes-optimal updating of temporal beliefs. Given that updating usually occurs in response to surprising events, we sought to disentangle EEG correlates of updating from those associated with surprise. Twenty-six participants performed a temporal foreperiod task, which comprised a subset of surprising events not eliciting updating. EEG data were analyzed through a regression-based massive approach in the electrode and source space. Distinct late positive, centro-parietally distributed, event-related potentials (ERPs) were associated with surprise and belief updating in the electrode space. While surprise modulated the commonly observed P3b, updating was associated with a later and more sustained P3b-like waveform deflection. Results from source analyses revealed that surprise encoding comprises neural activity in the cingulo-opercular network (CON). These data provide evidence that temporal predictions are computed in a Bayesian manner, and that this is reflected in P3 modulations, akin to other cognitive domains. Overall, our study revealed that analyzing P3 modulations provides an important window into the Bayesian brain. Data and scripts are shared on OSF: https://osf.io/ckqa5/?view_only=f711e6f878784d4ab94f4b14b31eef46

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P300 amplitude variations, prior probabilities, and likelihoods: A Bayesian ERP study

Cited by 52 publications

References 68 publications

Cognitive modelling reveals distinct electrophysiological markers of decision confidence and error monitoring

Cognitive modelling reveals distinct electrophysiological markers of decision confidence and error monitoring

Effects of relevance and response frequency on P3b amplitudes: Review of findings and comparison of hypotheses about the process reflected by P3b

Electroencephalographic Correlates of Temporal Bayesian Belief Updating and Surprise

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