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It is generally assumed that different electroencephalogram (EEG) frequency bands are somehow related to different computational modes in the brain. Integration of these computational modes is reflected in the phenomenon of cross-frequency coupling (CFC). On slow temporal scales, CFC may reflect trait-like properties, which posits a question of its developmental trends. This is the first study that explored source-level CFC measures in a developmental perspective using both cross-sectional and longitudinal designs. CFC measures demonstrated good test-retest stability and proved to be higher in adults in cortical areas participating in sensory-motor integration, response inhibition, and attentional control. In children, greater CFC was observed in parietal regions involved in self-centered cognition. Over the period from 7 to 10 years, CFC demonstrated nonlinear growth trajectories. Introversion was associated with higher CFC in cortical areas related to emotion, attention, and social cognition, implying that the association between introversion and CFC appears early in the development.
Pubmed ID: 31139068
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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 mentionsTHIS RESOURCE IS NO LONGER IN SERVICE, documented on February 1st, 2022. Software application for genetic analysis of classical biometric traits like blood pressure or height that are caused by a combination of polygenic inheritance and complex environmental forces. (entry from Genetic Analysis Software)
View all literature mentionsA software application which computes images of electric neuronal activity from EEG and MEG. Standard Low Resolution Brain Electromagnetic Tomography, or sLORETA, localizes “test point sources” exactly (under ideal conditions) when estimating electric neuronal generators. This property can be generalized to any source distribution, based on the principles of linearity and superposition. However, it would be noted that sLORETA has very low spatial resolution.
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