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Recent neurophysiological studies have proposed distinct roles of β and γ oscillations in implementing top-down and bottom-up processes. The present study aims to test this hypothesis in the domain of speech perception. We examined β and γ oscillations elicited to a tone contrast in a passive oddball paradigm, and their relationships with discrimination sensitivity d' and RT from two groups of healthy adults who showed high and low discrimination sensitivity to the contrast. The low-sensitivity group showed a significant reduction in β, which was further related to d'. Individual differences in RT were related to different frequency bands in the two groups, with a RT-β correlation in the low-sensitivity group, and a RT-γ relation in the high-sensitivity group. Based on these findings, we suggest that β, implicated in top-down processing, reflects individual differences in phonological representations, and that γ, involved in bottom-up processing, reflects individual differences in acoustic encoding.
Pubmed ID: 31586791
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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
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