Trial-by-trial coupling of concurrent electroencephalogram and functional magnetic resonance imaging identifies the dynamics of performance monitoring
ABSTRACT Goal-directed behavior requires the continuous monitoring and dynamic adjustment of ongoing actions. Here, we report a direct coupling between the event-related electroencephalogram (EEG), functional magnetic resonance imaging (fMRI), and behavioral measures of performance monitoring in humans. By applying independent component analysis to EEG signals recorded simultaneously with fMRI, we found the single-trial error-related negativity of the EEG to be systematically related to behavior in the subsequent trial, thereby reflecting immediate behavioral adjustments of a cognitive performance monitoring system. Moreover, this trial-by-trial EEG measure of performance monitoring predicted the fMRI activity in the rostral cingulate zone, a brain region thought to play a key role in processing of response errors. We conclude that investigations of the dynamic coupling between EEG and fMRI provide a powerful approach for the study of higher order brain functions.
SourceAvailable from: Rinaldo Livio Perri[Show abstract] [Hide abstract]
ABSTRACT: The event-related potential (ERP) literature described two error-related brain activities: the error-related negativity (Ne/ERN) and the error positivity (Pe), peaking immediately after the erroneous response. ERP studies on error processing adopted a response-locked approach, thus, the question about the activities preceding the error is still open. In the present study, we tested the hypothesis that the activities preceding the false alarms (FA) are different from those occurring in the correct (responded or inhibited) trials. To this aim, we studied a sample of 36 Go/No-go performers, adopting a stimulus-locked segmentation also including the pre-motor brain activities. Present results showed that neither pre-stimulus nor perceptual activities explain why we commit FA. In contrast, we observed condition-related differences in two pre-response components: the fronto-central N2 and the prefrontal positivity (pP), respectively peaking at 250ms and 310ms after the stimulus onset. The N2 amplitude of FA was identical to that recorded in No-go trials, and larger than Hits. Because the new findings challenge the previous interpretations on the N2, a new perspective is discussed. On the other hand, the pP in the FA trials was larger than No-go and smaller than Go, suggesting an erroneous processing at the stimulus-response mapping level: because this stage triggers the response execution, we concluded that the neural processes underlying the pP were mainly responsible for the subsequent error commission. Finally, sLORETA source analyses of the post-error potentials extended previous findings indicating, for the first time in the ERP literature, the right anterior insula as Pe generator. Copyright © 2015. Published by Elsevier Inc.NeuroImage 03/2015; 113. DOI:10.1016/j.neuroimage.2015.03.040 · 6.13 Impact Factor
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ABSTRACT: The answer to the question of how the brain incorporates sensory feedback and links it with motor function to achieve goal-directed movement during vocalization remains unclear. We investigated the mechanisms of voice pitch motor control by examining the spectro-temporal dynamics of EEG signals when non-musicians (NM), relative pitch (RP), and absolute pitch (AP) musicians maintained vocalizations of a vowel sound and received randomized ± 100 cents pitch-shift stimuli in their auditory feedback. We identified a phase-synchronized (evoked) fronto-central activation within the theta band (5-8 Hz) that temporally overlapped with compensatory vocal responses to pitch-shifted auditory feedback and was significantly stronger in RP and AP musicians compared with non-musicians. A second component involved a non-phase-synchronized (induced) frontal activation within the delta band (1-4 Hz) that emerged at approximately 1 s after the stimulus onset. The delta activation was significantly stronger in the NM compared with RP and AP groups and correlated with the pitch rebound error (PRE), indicating the degree to which subjects failed to re-adjust their voice pitch to baseline after the stimulus offset. We propose that the evoked theta is a neurophysiological marker of enhanced pitch processing in musicians and reflects mechanisms by which humans incorporate auditory feedback to control their voice pitch. We also suggest that the delta activation reflects adaptive neural processes by which vocal production errors are monitored and used to update the state of sensory-motor networks for driving subsequent vocal behaviors. This notion is corroborated by our findings showing that larger PREs were associated with greater delta band activity in the NM compared with RP and AP groups. These findings provide new insights into the neural mechanisms of auditory feedback processing for vocal pitch motor control.Frontiers in Neuroscience 01/2015; 9:109. DOI:10.3389/fnins.2015.00109
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ABSTRACT: Response inhibition is a pivotal component of executive control, which is especially difficult to assess. Indeed, it is a substantial challenge to gauge brain-behavior relationships because this function is precisely intended to suppress overt measurable behaviors. A further complication is that no single neuroimaging method has been found that can disentangle the accurate time-course of concurrent excitatory and inhibitory mechanisms. Here, we argue that this objective can be achieved with electroencephalography (EEG) on some conditions. Based on a systematic review, we emphasize that the standard event-related potential N2 (N200) is not an appropriate marker of prepotent response inhibition. We provide guidelines for assessing the cortical brain dynamics of response inhibition with EEG. This includes the combined use of inseparable data processing steps (source separation, source localization, and single-trial and time-frequency analyses) as well as the amendment of the classical experimental designs to enable the recording of different kinds of electrophysiological activity predicted by different models of response inhibition. We conclude with an illustration based on recent findings of how fruitful this approach can be.Reviews in the neurosciences 04/2015; DOI:10.1515/revneuro-2014-0078 · 3.31 Impact Factor