Low-frequency cortical oscillations are modulated by temporal prediction and temporal error coding
Monitoring and updating temporal predictions are critical abilities for adaptive behavior. Here, we investigated whether neural oscillations are related to violation and updating of temporal predictions. Human participants performed an experiment in which they had to generate a target at an expected...
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Published in: | NeuroImage (Orlando, Fla.) Vol. 146; pp. 40 - 46 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
United States
Elsevier Inc
01-02-2017
Elsevier Limited |
Subjects: | |
Online Access: | Get full text |
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Summary: | Monitoring and updating temporal predictions are critical abilities for adaptive behavior. Here, we investigated whether neural oscillations are related to violation and updating of temporal predictions. Human participants performed an experiment in which they had to generate a target at an expected time point, by pressing a button while taking into account a variable delay between the act and the stimulus occurrence. Our behavioral results showed that participants quickly adapted their temporal predictions in face of an error. Concurrent electrophysiological (EEG) data showed that temporal errors elicited markers that are classically related to error coding. Furthermore, intertrial phase coherence of frontal theta oscillations was modulated by error magnitude, possibly indexing the degree of surprise. Finally, we found that delta phase at stimulus onset was correlated with future behavioral adjustments. Together, our findings suggest that low frequency oscillations play a key role in monitoring and in updating temporal predictions.
•Temporal predictions are quickly adjusted in face of an error.•Temporal errors elicit an increase in frontal intertrial theta phase coherence.•Delta phase at stimulus onset is correlated with future behavioral adjustments. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2016.11.028 |