Relevant bibliographies by topics / EEG-fMRI,BCG artefact,imaging artefact

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  1. Journal articles
  2. Dissertations / Theses

Academic literature on the topic 'EEG-fMRI,BCG artefact,imaging artefact'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "EEG-fMRI,BCG artefact,imaging artefact"

1

Leclercq, Yves, Jessica Schrouff, Quentin Noirhomme, Pierre Maquet, and Christophe Phillips. "fMRI Artefact Rejection and Sleep Scoring Toolbox." Computational Intelligence and Neuroscience 2011 (2011): 1–11. http://dx.doi.org/10.1155/2011/598206.

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We started writing the “fMRI artefact rejection and sleep scoring toolbox”, or “FAST”, to process our sleep EEG-fMRI data, that is, the simultaneous recording of electroencephalographic and functional magnetic resonance imaging data acquired while a subject is asleep. FAST tackles three crucial issues typical of this kind of data: (1) data manipulation (viewing, comparing, chunking, etc.) of long continuous M/EEG recordings, (2) rejection of the fMRI-induced artefact in the EEG signal, and (3) manual sleep-scoring of the M/EEG recording. Currently, the toolbox can efficiently deal with these issues via a GUI, SPM8 batching system or hand-written script. The tools developed are, of course, also useful for other EEG applications, for example, involving simultaneous EEG-fMRI acquisition, continuous EEG eye-balling, and manipulation. Even though the toolbox was originally devised for EEG data, it will also gracefully handle MEG data without any problem. “FAST” is developed in Matlab as an add-on toolbox for SPM8 and, therefore, internally uses its SPM8-meeg data format. “FAST” is available for free, under the GNU-GPL.
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Javed, Ehtasham, Ibrahima Faye, Aamir Saeed Malik, and Jafri Malin Abdullah. "Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA." Journal of Neuroscience Methods 291 (November 2017): 150–65. http://dx.doi.org/10.1016/j.jneumeth.2017.08.020.

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Chowdhury, Muhammad, Amith Khandakar, Belayat Hossain, and Khawla Alzoubi. "Effects of the Phantom Shape on the Gradient Artefact of Electroencephalography (EEG) Data in Simultaneous EEG–fMRI." Applied Sciences 8, no. 10 (October 18, 2018): 1969. http://dx.doi.org/10.3390/app8101969.

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Electroencephalography (EEG) signals greatly suffer from gradient artefacts (GAs) due to the time-varying field gradients in the magnetic resonance (MR) scanner during the simultaneous acquisition of EEG and functional magnetic resonance imaging (fMRI) data. The GAs are the principal contributors of artefacts while recording EEG inside an MR scanner, and most of them come from the interaction of the EEG cap and the subject’s head. Many researchers have been using a spherical phantom to characterize the GA in EEG data in combined EEG–fMRI studies. In this study, we investigated how the phantom shape could affect the characterization of the GA. EEG data were recorded with a spherical phantom, a head-shaped phantom, and six human subjects, individually, during the execution of customized and standard echo-planar imaging (EPI) sequences. The spatial potential maps of the root-mean-square (RMS) voltage of the GA over EEG channels for the trials with a head-shaped phantom closely mimicked those related to the human head rather than those obtained for the spherical phantom. This was confirmed by measuring the average similarity index (0.85/0.68). Moreover, a paired t-test showed that the head-shaped phantom’s and the spherical phantom’s data were significantly different (p < 0.005) from the subjects’ data, whereas the difference between the head-shaped phantom’s and the spherical phantom’s data was not significant (p = 0.07). The results of this study strongly suggest that a head-shaped phantom should be used for GA characterization studies in concurrent EEG–fMRI.
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Chowdhury, M. E. H., Karen J. Mullinger, and Richard Bowtell. "Simultaneous EEG–fMRI: evaluating the effect of the cabling configuration on the gradient artefact." Physics in Medicine and Biology 60, no. 12 (June 4, 2015): N241—N250. http://dx.doi.org/10.1088/0031-9155/60/12/n241.

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Daniel, Alexander J., James A. Smith, Glyn S. Spencer, João Jorge, Richard Bowtell, and Karen J. Mullinger. "Exploring the relative efficacy of motion artefact correction techniques for EEG data acquired during simultaneous fMRI." Human Brain Mapping 40, no. 2 (October 19, 2018): 578–96. http://dx.doi.org/10.1002/hbm.24396.

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Leclercq, Yves, Evelyne Balteau, Thanh Dang-Vu, Manuel Schabus, André Luxen, Pierre Maquet, and Christophe Phillips. "Rejection of pulse related artefact (PRA) from continuous electroencephalographic (EEG) time series recorded during functional magnetic resonance imaging (fMRI) using constraint independent component analysis (cICA)." NeuroImage 44, no. 3 (February 2009): 679–91. http://dx.doi.org/10.1016/j.neuroimage.2008.10.017.

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Yan, Winston X., Karen J. Mullinger, Gerda B. Geirsdottir, and Richard Bowtell. "Physical modeling of pulse artefact sources in simultaneous EEG/fMRI." Human Brain Mapping, 2009, NA. http://dx.doi.org/10.1002/hbm.20891.

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Maziero, Danilo, Victor A. Stenger, and David W. Carmichael. "Unified Retrospective EEG Motion Educated Artefact Suppression for EEG-fMRI to Suppress Magnetic Field Gradient Artefacts During Motion." Brain Topography, September 23, 2021. http://dx.doi.org/10.1007/s10548-021-00870-0.

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Dissertations / Theses on the topic "EEG-fMRI,BCG artefact,imaging artefact"

1

Del, Castello Mariangela. "Analysis of electroencephalography signals collected in a magnetic resonance environment: characterisation of the ballistocardiographic artefact." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13214/.

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L’acquisizione simultanea di segnali elettroencefalografici (EEG) e immagini di risonanza magnetica funzionale (fMRI) permette di investigare attivazioni cerebrali in modo non invasivo. La presenza del campo magnetico altera però in modo non trascurabile la qualità dei segnali EEG acquisiti. In particolare due artefatti sono stati individuati: l’artefatto da gradiente e l’artefatto da ballistocardiogramma (BCG). L’artefatto da BCG è legato all’attività cardiaca del soggetto, ed è caratterizzato da elevata variabilità tra un’occorrenza e l’altra in termini di ampiezza, forma d’onda e durata dell’artefatto. Differenti algoritmi sono stati implementati al fine di rimuoverlo, ma la rimozione completa rimane ancora un difficile obiettivo da raggiungere a causa della sua complessa natura. L’argomento della tesi riguarda l’analisi di segnali EEG acquisiti in ambiente di risonanza magnetica e la caratterizzazione dell’artefatto BCG. L’obiettivo è individuare ulteriori caratteristiche dell’artefatto che possano condurre al miglioramento dei precedenti metodi, o all’implementazione di nuovi. Con questa tesi abbiamo mostrato quali sono i motivi che causano la presenza di residui artefattuali nei segnali EEG processati con i metodi presenti in letteratura. Attraverso analisi statistica abbiamo riscontrato che occorrenze dell’artefatto BCG sono caratterizzate da un ritardo variabile rispetto al picco R sull’ECG, che nella nostra analisi rappresenta l’evento di riferimento nell’attività cardiaca. Abbiamo inoltre trovato che il ritardo R-BCG varia con la frequenza cardiaca. Le successive valutazioni riguardano i maggiori contributi all’artefatto BCG. Attraverso l’analisi alle componenti principali, sono stati individuati due contributi legati al fluire del sangue dal cuore verso il cervello e alla sua pulsatilità nei vasi principali dello scalpo.
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