2018
DOI: 10.1007/s10548-018-0671-6
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Electrophysiological Signatures of Intrinsic Functional Connectivity Related to rTMS Treatment for Mal de Debarquement Syndrome

Abstract: To determine intrinsic functional connectivity (IFC) related to symptom changes induced by rTMS in mal de debarquement syndrome (MdDS), a motion perceptual disorder induced by entrainment to oscillating motion. Twenty right-handed women (mean age: 52.9 ± 12.6 years; mean duration illness: 35.2 ± 24.2 months) with MdDS received five sessions of rTMS (1 Hz right DLPFC, 10 Hz left DLPFC) over consecutive days. High-density (128-channel) resting-state EEG were recorded prior to and following treatment sessions and… Show more

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Cited by 16 publications
(20 citation statements)
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“…Simultaneously acquired fMRI-EEG data on individuals with MdDS have provided cross-modal validation of biomarkers found separately, showing that brain network-level changes associated with clinical effects are consistent across modalities of different temporal resolutions (49,69,70,(72)(73)(74). Our data showed that after rTMS at DLPFC, EEG synchronization changes in medial frontal gyrus were associated with fMRI-measured connectivity changes involving deeper cortical structures, particularly in a network that includes the entorhinal cortex and right IPL, indicating that the modulatory effect of rTMS is at least partially related to reducing the connectivity within the DMN (49,73).…”
Section: Simultaneous Functional Magnetic Resonance Imaging-electroenmentioning
confidence: 99%
See 1 more Smart Citation
“…Simultaneously acquired fMRI-EEG data on individuals with MdDS have provided cross-modal validation of biomarkers found separately, showing that brain network-level changes associated with clinical effects are consistent across modalities of different temporal resolutions (49,69,70,(72)(73)(74). Our data showed that after rTMS at DLPFC, EEG synchronization changes in medial frontal gyrus were associated with fMRI-measured connectivity changes involving deeper cortical structures, particularly in a network that includes the entorhinal cortex and right IPL, indicating that the modulatory effect of rTMS is at least partially related to reducing the connectivity within the DMN (49,73).…”
Section: Simultaneous Functional Magnetic Resonance Imaging-electroenmentioning
confidence: 99%
“…Measurement of this connectivity was reflected through independent component phase coherence (ICPC), a calculation of synchronicity at individual frequency bands (delta, theta, low alpha, high alpha, beta, and gamma) on an independent component level rather than an individual channel level ( 69 ). ICPC calculations on 128-channel EEG data collected pre and post rTMS have shown distinct differences in synchronizations across independent component regions and frequencies ( 69 , 70 ). In general, reduction in ICPC in the delta, high alpha, beta, and gamma bands were noted with symptom improvement, whereas increase in ICPC was noted in the low alpha band ( Figure 6A ).…”
Section: Electroencephalographymentioning
confidence: 99%
“…36 Markers of symptom improvement after DLPFC stimulation include a reduction in connectivity within the posterior default mode network, specifically a reduction in connectivity with the entorhinal cortex. [37][38][39] Moreover, symptom improvement was characterized by reduced longrange connectivity (frontoparietal) in the high α À band (11)(12)(13) and β-bands (14-30 Hz), and an increase in connectivity in the low α-band (8-10 Hz). 39…”
Section: Theory 2: Entrainment and Activation Of Central Oscillatorsmentioning
confidence: 99%
“…[37][38][39] Moreover, symptom improvement was characterized by reduced longrange connectivity (frontoparietal) in the high α À band (11)(12)(13) and β-bands (14-30 Hz), and an increase in connectivity in the low α-band (8-10 Hz). 39…”
Section: Theory 2: Entrainment and Activation Of Central Oscillatorsmentioning
confidence: 99%
“…Weak rTMS-induced electric fields produce neural entrainment in humans Ando et al (2018) RMT 90 n/r 3 Bai et al (2016) RMT 90 n/r 4 Bharath et al 2017RMT 90 n/r 5 Cao et al (2018) RMT 100 44.5 6 Capotosto et al (2017) RMT 100 n/r 7 Cha et al (2018) RMT 110 n/r 8 Chen et al (2017) RMT 110 n/r 9 D'Agata et al 2016RMT 80 n/r 10 Daltrozzo et al (2016) RMT 90 n/r 11 DelFelice et al 2016RMT 100 58.6/61.9 12 DiGiacomo et al 2018RMT 80 47.4 13 Emrich et al 2017RMT 110 72 14 Fisher et al (2018) RMT 90 n/r 15 Gongora et al 2016RMT 80 47.4 16 He et al 2018RMT 100 n/r 17 Hunter et al 2018RMT 80-120 n/r 18 Jin et al 2017RMT 90 n/r 19 Kamp et al (2016) RMT 110 n/r 20 Karton et al (2017) vMT 80 n/r 21 Kazemi et al (2016) RMT 100/120 n/r 22 Kazemi et al (2018) RMT 100/120 n/r 23 Keuper et al (2018) FXD i/r 50 24 Kim et al (2016) vMT 110 n/r 25 Kito et al (2017) MT 120 n/r 26 Koch et al (2018) RMT 110 60. 8 27 Li et al (2016) MT 100 n/r 28 RMT 110 n/r 29 RMT 110 n/r 30 Lowe et al (2018) RMT 80 52/53 31 Lozeron et al (2017) RMT 80 n/r 32 Moebius et al (2017) RMT 110 n/r 33 Nathou et al (2018) RMT 80 n/r 34 Nicolo et al (2016) vMT 90 n/r 35 Noda et al (2017) RMT 95 82.…”
Section: Supplemental Informationmentioning
confidence: 99%