2020
DOI: 10.1007/s00415-020-09957-3
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Modulatory effects of magnetic vestibular stimulation on resting-state networks can be explained by subject-specific orientation of inner-ear anatomy in the MR static magnetic field

Abstract: Strong static magnetic fields, as used in magnetic resonance imaging (MRI), stimulate the vestibular inner ear leading to a state of imbalance within the vestibular system that causes nystagmus. This magnetic vestibular stimulation (MVS) also modulates fluctuations of resting-state functional MRI (RS-fMRI) networks. MVS can be explained by a Lorentz force model, indicating that MVS is the result of the interaction of the static magnetic field strength and direction (called “B0 magnetic field” in MRI) with the … Show more

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Cited by 9 publications
(14 citation statements)
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“…We have now demonstrated how these MVS-induced RSN modulations can be addressed in fMRI analysis on the group-level [12]. We propose a parameter, derived from high-resolution anatomical imaging of the inner ear, that can be used for regressing out significant parts of the variance in RS-fMRI fluctuations [12]. We acquired RS-fMRI, and high-resolution CISS anatomical images of the inner ear in a sample of N=60 healthy volunteers balanced for age, gender, and handedness.…”
mentioning
confidence: 99%
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“…We have now demonstrated how these MVS-induced RSN modulations can be addressed in fMRI analysis on the group-level [12]. We propose a parameter, derived from high-resolution anatomical imaging of the inner ear, that can be used for regressing out significant parts of the variance in RS-fMRI fluctuations [12]. We acquired RS-fMRI, and high-resolution CISS anatomical images of the inner ear in a sample of N=60 healthy volunteers balanced for age, gender, and handedness.…”
mentioning
confidence: 99%
“…We have now demonstrated how these MVS-induced RSN modulations can be addressed in fMRI analysis on the group-level [12]. We propose a parameter, derived from high-resolution anatomical imaging of the inner ear, that can be used for regressing out significant parts of the variance in RS-fMRI fluctuations [12].…”
mentioning
confidence: 99%
See 3 more Smart Citations