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Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring.

ABSTRACT: Error-related activity in the medial prefrontal cortex (mPFC) is thought to work in conjunction with lateral prefrontal cortex (lPFC) as a part of an action-monitoring network, where errors signal the need for increased cognitive control. The neural mechanism by which this mPFC-lPFC interaction occurs remains unknown. We hypothesized that transient synchronous oscillations in the theta range reflect a mechanism by which these structures interact. To test this hypothesis, we extracted oscillatory phase and power from current-source-density-transformed electroencephalographic data recorded during a Flanker task. Theta power in the mPFC was diminished on the trial preceding an error and increased immediately after an error, consistent with predictions of an action-monitoring system. These power dynamics appeared to take place over a response-related background of oscillatory theta phase coherence. Theta phase synchronization between FCz (mPFC) and F5/6 (lPFC) sites was robustly increased during error trials. The degree of mPFC-lPFC oscillatory synchronization predicted the degree of mPFC power on error trials, and both of these dynamics predicted the degree of posterror reaction time slowing. Oscillatory dynamics in the theta band may in part underlie a mechanism of communication between networks involved in action monitoring and cognitive control.

SUBMITTER: Cavanagh JF

PROVIDER: S-EPMC2742325 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

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Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring.

Cavanagh James F JF Cohen Michael X MX Allen John J B JJ

The Journal of neuroscience : the official journal of the Society for Neuroscience 20090101 1

Error-related activity in the medial prefrontal cortex (mPFC) is thought to work in conjunction with lateral prefrontal cortex (lPFC) as a part of an action-monitoring network, where errors signal the need for increased cognitive control. The neural mechanism by which this mPFC-lPFC interaction occurs remains unknown. We hypothesized that transient synchronous oscillations in the theta range reflect a mechanism by which these structures interact. To test this hypothesis, we extracted oscillatory ...[more]

PMID: 19129388

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Project description:A key feature of normal neonatal EEG at term age is interhemispheric synchrony (IHS), which refers to the temporal co-incidence of bursting across hemispheres during trace alternant EEG activity. The assessment of IHS in both clinical and scientific work relies on visual, qualitative EEG assessment without clearly quantifiable definitions. A quantitative measure, activation synchrony index (ASI), was recently shown to perform well as compared to visual assessments. The present study was set out to test whether IHS is stable enough for clinical use, and whether it could be an objective feature of EEG normality. We analyzed 31 neonatal EEG recordings that had been clinically classified as normal (n = 14) or abnormal (n = 17) using holistic, conventional visual criteria including amplitude, focal differences, qualitative synchrony, and focal abnormalities. We selected 20-min epochs of discontinuous background pattern. ASI values were computed separately for different channel pair combinations and window lengths to define them for the optimal ASI intraindividual stability. Finally, ROC curves were computed to find trade-offs related to compromised data lengths, a common challenge in neonatal EEG studies. Using the average of four consecutive 2.5-min epochs in the centro-occipital bipolar derivations gave ASI estimates that very accurately distinguished babies clinically classified as normal vs. abnormal. It was even possible to draw a cut-off limit (ASI~3.6) which correctly classified the EEGs in 97% of all cases. Finally, we showed that compromising the length of EEG segments from 20 to 5 min leads to increased variability in ASI-based classification. Our findings support the prior literature that IHS is an important feature of normal neonatal brain function. We show that ASI may provide diagnostic value even at individual level, which strongly supports its use in prospective clinical studies on neonatal EEG as well as in the feature set of upcoming EEG classifiers.

Dataset Information

Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring.

Publications

Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring.

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