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Evidence suggests that scalp-recorded occipital alpha-band (8-13 Hz) oscillations reflect phasic information transfer in thalamocortical neurons projecting from lateral geniculate nucleus to visual cortex. In animals, the phase of ongoing alpha oscillations has been shown to modulate stimulus discrimination and neuronal spiking. Human research has shown that alpha phase predicts visual perception of near-threshold stimuli and subsequent neural activity and that the frequency of these oscillations predicts reaction times, as well as the maximum temporal interval necessary for perceived simultaneity. These phasic effects have led to the hypothesis that conscious perception occurs in discrete temporal windows, clocked by the frequency of alpha oscillations. Under this hypothesis, variation in the frequency of occipital alpha oscillations should predict variation in the temporal resolution of visual perception. Specifically, when two stimuli fall within the same alpha cycle, they may be perceived as a single stimulus, resulting in perception with lower temporal resolution when alpha frequency is lower. We tested this by assessing the relationship between two-flash fusion thresholds (a measure of the temporal resolution of visual perception) and the frequency of eyes-closed and task-related alpha rhythms. We found, both between and within subjects, that faster alpha frequencies predicted more accurate flash discrimination, providing novel evidence linking alpha frequency to the temporal resolution of perception.
Pubmed ID: 26526370 RIS Download
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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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