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Probing the cortical network underlying the psychological refractory period: a combined EEG-fMRI study.

NeuroImage | 2011

Human performance exhibits strong multi-tasking limitations in simple response time tasks. In the psychological refractory period (PRP) paradigm, where two tasks have to be performed in brief succession, central processing of the second task is delayed when the two tasks are performed at short time intervals. Here, we aimed to probe the cortical network underlying this postponement of central processing by simultaneously recording electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data while 12 subjects performed two simple number-comparison tasks. Behavioral data showed a significant slowing of response times to the second target stimulus at short stimulus-onset asynchronies, together with significant correlations between response times to the first and second target stimulus, i.e., the hallmarks of the PRP effect. The analysis of EEG data showed a significant delay of the post-perceptual P3 component evoked by the second target, which was of similar magnitude as the effect on response times. fMRI data revealed an involvement of parietal and prefrontal regions in dual-task processing. The combined analysis of fMRI and EEG data-based on the trial-by-trial variability of the P3-revealed that BOLD signals in two bilateral regions in the inferior parietal lobe and precentral gyrus significantly covaried with P3 related activity. Our results show that combining neuroimaging methods of high spatial and temporal resolutions can help to identify cortical regions underlying the central bottleneck of information processing, and strengthen the conclusion that fronto-parietal cortical regions participate in a distributed "global neuronal workspace" system that underlies the generation of the P3 component and may be one of the key cerebral underpinnings of the PRP bottleneck.

Pubmed ID: 21397701 RIS Download

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BrainVision Analyzer (tool)

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Software to manage the daily work of analyzing various neurophysiological data. Features include a history tree, automated analysis, various data format readers, and more.

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EEGLAB (tool)

RRID:SCR_007292

Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling

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