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How coherent neural oscillations are involved in task execution is a fundamental question in neuroscience. Although several electrophysiological studies have tackled this issue, the brain-wide task modulation of neural coherence remains uncharacterized. Here, with a fast fMRI technique, we studied shifts of brain-wide neural coherence across different task states in the ultraslow frequency range (0.01-0.7 Hz). First, we examined whether the shifts of the brain-wide neural coherence occur in a frequency-dependent manner. We quantified the shift of a region's average neural coherence by the inter-state variance of the mean coherence between the region and the rest of the brain. A clustering analysis based on the variance's spatial correlation between frequency components revealed four frequency bands (0.01-0.15 Hz, 0.15-0.37 Hz, 0.37-0.53 Hz, and 0.53-0.7 Hz) showing band-specific shifts of the brain-wide neural coherence. Next, we investigated the similarity of the inter-state variance's spectra between all pairs of regions. We found that regions showing similar spectra correspond to those forming functional modules of the brain network. Then, we investigated the relationship between identified frequency bands and modules' inter-state variances. We found that modules showing the highest variance are those made up of parieto-occipital regions at 0.01-0.15 Hz, while it is replaced with another consisting of frontal regions above 0.15 Hz. Furthermore, these modules showed specific shifting patterns of the mean coherence across states at 0.01-0.15 Hz and above 0.15 Hz, suggesting that identified frequency bands differentially contribute to neural interactions during task execution. Our results highlight that usage of the fast fMRI enables brain-wide investigation of neural coherence up to 0.7 Hz, which opens a promising track for assessment of the large-scale neural interactions in the ultraslow frequency range.
Pubmed ID: 32950690
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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
View all literature mentionsAn EEG toolbox developed to help users with 3 specific types of data and problems: simulatenous EEG-fMRI recording, continuous EEG scoring (e.g. sleep) and handling (visualisation, cutting, power spectrum, etc.) multi-channel recording of spontaneous EEG. The toolbox is written in Matlab and is specifically compatible with the BrainAmp family of EEG recorders (from BrainProducts GmbH) Three other data formats are now also supported: the edf "European Data Format", exported raw-EGI data (from Electrical Geodesics, Inc.) and the BCI2000 format.The results are directly compatible with SPM8 and are saved with SPM8 EEG data format.
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