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Association of the retrospective self-report ratings with the dynamics of EEG.

Galina V Portnova | Yulia V Ukraintseva | Krystsina M Liaukovich | Olga V Martynova
Heliyon | 2019

The neural underpinnings of subjective experience during resting state remain elusive. Dynamic features of EEG oscillations may provide more understanding of the relationship between the content of inner conscious experience and electrical brain activity. We tested a correlation of rating on the Amsterdam Resting-State Questionnaire (ARSQ) with dynamic parameters of EEG recorded in 49 healthy volunteers during the 10-min resting session. The participants filled ARSQ immediately after the rest. We investigated both linear (1 Hz-band power spectral density - PSD) and dynamic features (standard deviation and frequency of Hilbert envelope) of EEG averaged for the whole resting-state segment. Besides, we conducted a procedure of k-mean clustering based on PSD, localization of components retrieved by independent component analysis for 10-sec EEG epochs to assess spectral and temporal variability of EEG. The correlation analysis showed that the increase of PSD and cluster duration of the high-frequency alpha rhythm (12-13 Hz) in central and frontal areas was positively associated with the rating of experienced thoughts related to Planning (r = 0.44). The time of the presence of low amplitude delta oscillations correlated negatively with Planning (r = -0.52). The participants with higher ARSQ scores of Visual Thoughts had a higher standard deviation of the wideband (1-30 Hz) Hilbert envelope. Our data suggest that the dynamic properties of EEG reflect cognitive states assessed by ARSQ.

Pubmed ID: 31667386

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MATLAB (tool)

RRID:SCR_001622

Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.

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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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