Literature DB >> 23274186

Visual gamma oscillations: the effects of stimulus type, visual field coverage and stimulus motion on MEG and EEG recordings.

S D Muthukumaraswamy1, K D Singh.   

Abstract

Increases in the power of neural oscillations in the gamma (>40 Hz) band are a key signature of information processing in cortical neuronal networks. However, non-invasive detection of these very small oscillations is difficult due to the presence of potential artefacts (both muscular and ocular) in the same frequency band and requires highly optimised paradigms. Numerous studies have shown that the properties of visual gamma-band responses to simple pattern stimuli are highly tuned to the stimuli parameters used. The aim of this work was to compare gamma oscillation response properties across some of the more commonly used stimulus configurations. To do this, MEG and EEG recordings were made during the presentation of eight different stimulus types in a 2 × 2 × 2 design. For the first stimulus factor, "Type", the stimulus pattern was either an annulus grating or a square wave grating. For the second stimulus factor, "Field", stimuli were presented in either four visual field quadrants simultaneously or only in the lower left quadrant. Finally, for the "Move" factor, stimuli either drifted at 1.33°s(-1) or were stationary. For MEG gamma band responses, the following main effects were observed, a) gamma-band power was increased for annular stimuli compared to square wave stimuli, b) gamma-band power was increased for full field stimuli compared to single quadrant stimuli and c) gamma-band power was larger for drifting compared to stationary stimuli and were of significantly higher frequency. For the detectors used, the signal to noise ratio was substantially higher for MEG than EEG. The advantages and disadvantages of the different types of stimulus types are discussed.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 23274186     DOI: 10.1016/j.neuroimage.2012.12.038

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  70 in total

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Authors:  Christina Andreou; Guido Nolte; Gregor Leicht; Nenad Polomac; Ileana L Hanganu-Opatz; Martin Lambert; Andreas K Engel; Christoph Mulert
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