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Torben Ellegaard Lund

Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies

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Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies. / Liston, A D; Lund, Torben Ellegaard; Salek-Haddadi, A; Hamandi, K; Friston, K J; Lemieux, L.

In: NeuroImage, Vol. 30, No. 3, 2005, p. 827-34.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Liston, AD, Lund, TE, Salek-Haddadi, A, Hamandi, K, Friston, KJ & Lemieux, L 2005, 'Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies', NeuroImage, vol. 30, no. 3, pp. 827-34. https://doi.org/10.1016/j.neuroimage.2005.10.025

APA

Liston, A. D., Lund, T. E., Salek-Haddadi, A., Hamandi, K., Friston, K. J., & Lemieux, L. (2005). Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies. NeuroImage, 30(3), 827-34. https://doi.org/10.1016/j.neuroimage.2005.10.025

CBE

MLA

Vancouver

Author

Liston, A D ; Lund, Torben Ellegaard ; Salek-Haddadi, A ; Hamandi, K ; Friston, K J ; Lemieux, L. / Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies. In: NeuroImage. 2005 ; Vol. 30, No. 3. pp. 827-34.

Bibtex

@article{fc82fb60cc2d11dd9710000ea68e967b,
title = "Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies",
abstract = "Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these studies, ECG is routinely recorded, enabling cardiac effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 +/- 10.9% of grey matter voxels contained significant cardiac effects and 22.3 +/- 24.1% of those voxels exhibiting significantly IED-correlated BOLD signal also contained significant cardiac effects. We quantified the improvement of the TAP model over the original model, without cardiac effects, by evaluating changes in efficiency, with respect to estimating the contrast of the effects of interest. Over voxels containing significant, cardiac-related signal, efficiency was improved by 18.5 +/- 4.8%. Over the remaining voxels, no improvement was demonstrated. This suggests that, while improving sensitivity in particular regions of the brain, there is no risk that the TAP model will reduce sensitivity elsewhere.",
author = "Liston, {A D} and Lund, {Torben Ellegaard} and A Salek-Haddadi and K Hamandi and Friston, {K J} and L Lemieux",
year = "2005",
doi = "10.1016/j.neuroimage.2005.10.025",
language = "English",
volume = "30",
pages = "827--34",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Elsevier BV",
number = "3",

}

RIS

TY - JOUR

T1 - Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies

AU - Liston, A D

AU - Lund, Torben Ellegaard

AU - Salek-Haddadi, A

AU - Hamandi, K

AU - Friston, K J

AU - Lemieux, L

PY - 2005

Y1 - 2005

N2 - Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these studies, ECG is routinely recorded, enabling cardiac effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 +/- 10.9% of grey matter voxels contained significant cardiac effects and 22.3 +/- 24.1% of those voxels exhibiting significantly IED-correlated BOLD signal also contained significant cardiac effects. We quantified the improvement of the TAP model over the original model, without cardiac effects, by evaluating changes in efficiency, with respect to estimating the contrast of the effects of interest. Over voxels containing significant, cardiac-related signal, efficiency was improved by 18.5 +/- 4.8%. Over the remaining voxels, no improvement was demonstrated. This suggests that, while improving sensitivity in particular regions of the brain, there is no risk that the TAP model will reduce sensitivity elsewhere.

AB - Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these studies, ECG is routinely recorded, enabling cardiac effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 +/- 10.9% of grey matter voxels contained significant cardiac effects and 22.3 +/- 24.1% of those voxels exhibiting significantly IED-correlated BOLD signal also contained significant cardiac effects. We quantified the improvement of the TAP model over the original model, without cardiac effects, by evaluating changes in efficiency, with respect to estimating the contrast of the effects of interest. Over voxels containing significant, cardiac-related signal, efficiency was improved by 18.5 +/- 4.8%. Over the remaining voxels, no improvement was demonstrated. This suggests that, while improving sensitivity in particular regions of the brain, there is no risk that the TAP model will reduce sensitivity elsewhere.

U2 - 10.1016/j.neuroimage.2005.10.025

DO - 10.1016/j.neuroimage.2005.10.025

M3 - Journal article

C2 - 16343949

VL - 30

SP - 827

EP - 834

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

IS - 3

ER -