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Extraversion and fronto-posterior EEG spectral power gradient: an independent component analysis.

Gennady G Knyazev | Andrey V Bocharov | Liudmila V Pylkova
Biological psychology | 2012

Several studies show that the fronto-posterior EEG spectral power gradient is a stable individual characteristic related to personality. Whether this characteristic is specifically related to agentic extraversion and theta band of frequencies or is associated with a broader set of personality traits and frequency bands is a matter of debate, as well as the specific cortical regions contributing to this effect. To clarify these questions, we used group independent component analysis (ICA) and source localization techniques. Agentic extraversion was associated with higher theta activity in the default mode network's (DMN) posterior hub and lower theta activity in the orbitofrontal cortex (OFC). Regression analyses showed that theta activity predicted agentic extraversion better than other frequency bands and agentic extraversion predicted posterior versus frontal activity better than other personality dimensions. These results are taken to indicate higher tonic activity in OFC and lower activity in DMN in extraverts as compared to introverts.

Pubmed ID: 22234364

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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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