TY  - JOUR
A1  - Kluger, Daniel
A1  - Quante, Laura
A1  - Kohler, Axel
A1  - Schubotz, Ricarda Ines
T1  - Being right matters : model-compliant events in predictive processing
T2  - PLoS one
N2  - While prediction errors (PE) have been established to drive learning through adaptation of internal models, the role of model-compliant events in predictive processing is less clear. Checkpoints (CP) were recently introduced as points in time where expected sensory input resolved ambiguity regarding the validity of the internal model. Conceivably, these events serve as on-line reference points for model evaluation, particularly in uncertain contexts. Evidence from fMRI has shown functional similarities of CP and PE to be independent of event-related surprise, raising the important question of how these event classes relate to one another. Consequently, the aim of the present study was to characterise the functional relationship of checkpoints and prediction errors in a serial pattern detection task using electroencephalography (EEG). Specifically, we first hypothesised a joint P3b component of both event classes to index recourse to the internal model (compared to non-informative standards, STD). Second, we assumed the mismatch signal of PE to be reflected in an N400 component when compared to CP. Event-related findings supported these hypotheses. We suggest that while model adaptation is instigated by prediction errors, checkpoints are similarly used for model evaluation. Intriguingly, behavioural subgroup analyses showed that the exploitation of potentially informative reference points may depend on initial cue learning: Strict reliance on cue-based predictions may result in less attentive processing of these reference points, thus impeding upregulation of response gain that would prompt flexible model adaptation. Overall, present results highlight the role of checkpoints as model-compliant, informative reference points and stimulate important research questions about their processing as function of learning und uncertainty.
KW  - Event-related potentials
KW  - Electroencephalography
KW  - Reaction time
KW  - Functional magnetic resonance imaging
KW  - Learning
KW  - Electrode potentials
KW  - Scalp
KW  - Permutation
Y1  - 2019
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/50370
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-503706
SN  - 1932-6203
N1  - Copyright: © 2019 Kluger et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
VL  - 14
IS  - (6): e0218311
SP  - 1
EP  - 22
PB  - PLoS
CY  - Lawrence, Kan.
ER  -