Literature DB >> 22144291

Correlation between single-trial visual evoked potentials and the blood oxygenation level dependent response in simultaneously recorded electroencephalography-functional magnetic resonance imaging.

Dan Fuglø1, Henrik Pedersen, Egill Rostrup, Adam E Hansen, Henrik B W Larsson.   

Abstract

To compare different electroencephalography (EEG)-based regressors and their ability to predict the simultaneously recorded blood oxygenation level dependent response during blocked visual stimulation, simultaneous EEG-functional magnetic resonance imaging in 10 healthy volunteers was performed. The performance of different single-trial EEG regressors was compared in terms of predicting the measured blood oxygenation level dependent response. The EEG-based regressors were the amplitude and latency of the primary positive (P1) and negative (N2) peaks of the visual evoked potential, the combined P1-N2 amplitude, and the alpha power. Apart from peak latencies, all regressors showed significant positive or negative correlation with the blood oxygenation level dependent response in visual cortex. In addition, several EEG-based regressors were found to predict blood oxygenation level dependent variations in different occipital and extraoccipital cortical areas not explained by the boxcar regressor. The results suggest that the P1-N2 regressor is the best EEG-based regressor to model the visual paradigm, but when looking for additional effects like habituation or attention modulation that cannot be modeled by the boxcar regressor, it is better to include regressors based on individual peaks or alpha power.
Copyright © 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 22144291     DOI: 10.1002/mrm.23227

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  5 in total

1.  Hemispheric differences in electrical and hemodynamic responses during hemifield visual stimulation with graded contrasts.

Authors:  Juanning Si; Xin Zhang; Yujin Zhang; Tianzi Jiang
Journal:  Biomed Opt Express       Date:  2017-03-02       Impact factor: 3.732

2.  Modeling the Hemodynamic Response Function Using EEG-fMRI Data During Eyes-Open Resting-State Conditions and Motor Task Execution.

Authors:  Prokopis C Prokopiou; Alba Xifra-Porxas; Michalis Kassinopoulos; Marie-Hélène Boudrias; Georgios D Mitsis
Journal:  Brain Topogr       Date:  2022-04-30       Impact factor: 3.020

Review 3.  Electrophysiological correlates of the BOLD signal for EEG-informed fMRI.

Authors:  Teresa Murta; Marco Leite; David W Carmichael; Patrícia Figueiredo; Louis Lemieux
Journal:  Hum Brain Mapp       Date:  2014-10-03       Impact factor: 5.038

Review 4.  EEG-Informed fMRI: A Review of Data Analysis Methods.

Authors:  Rodolfo Abreu; Alberto Leal; Patrícia Figueiredo
Journal:  Front Hum Neurosci       Date:  2018-02-06       Impact factor: 3.169

5.  Data-driven analysis of simultaneous EEG/fMRI using an ICA approach.

Authors:  Lena Schmüser; Alexandra Sebastian; Arian Mobascher; Klaus Lieb; Oliver Tüscher; Bernd Feige
Journal:  Front Neurosci       Date:  2014-07-01       Impact factor: 4.677

  5 in total

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