Combined EEG/fMRI recording in musicogenic epilepsy

Marrosu, Francesco; Barberini, Luigi; Puligheddu, Monica; Bortolato, Marco; Mascia, Marcello Mario; Tuveri, A; Muroni, Antonella; Mallarini, G.; Avanzini, G.

doi:10.1016/j.eplepsyres.2008.11.019

Cited by 32 publications

(22 citation statements)

References 16 publications

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“…4). Therefore, we were not able to confirm previously published hypotheses about an initial frontal cortical involvement triggering the epileptic discharges (Marrosu et al, 2009;Morocz et al, 2003;Pittau et al, 2008). The alternative hypothesis suggested by previous papers that activity changes in the orbitofrontal lobes, which are believed to be key structures in processing emotional aspects of music (Morocz et al, 2003), reflect emotional arousal related to the music rather than seizure activity per se does not apply to our data either.…”

Section: Dynamic Causal Modelingcontrasting

confidence: 55%

“…the seizure-related BOLD map, and previous literature (Marrosu et al, 2009;Morocz et al, 2003;Pittau et al, 2008;Tayah et al, 2006;Trevathan et al, 1999) two regions of interest (ROI) were selected as possible seizure origins in this case: the frontal (MNI: 2 60 -14 mm) and the right mesiotemporal (MNI: 38 6 -12 mm) cluster of the fMRI activation map. To perform the effective connectivity analysis based on fMRI we computed the first principal eigenvariate of the voxel time series for each ROI and mean-corrected it using the "effects of interest" F-contrast.…”

Section: Effective Connectivity Analysesmentioning

confidence: 99%

“…Seizure origin has been shown to involve foci within the temporal lobes with a rightsided preponderance in most cases, but extra-temporal foci have also been described (for review see Pittau et al, 2008). Several (EEG-) fMRI-studies have even postulated that stimulus-induced activity in frontal cortical areas, which are believed to be key structures in processing emotional aspects of music, may initiate the seizure cascade in temporal regions finally visible as epileptic discharges in scalp EEG (Marrosu et al, 2009;Morocz et al, 2003;Pittau et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Multimodal effective connectivity analysis reveals seizure focus and propagation in musicogenic epilepsy

et al. 2015

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Dynamic causal modeling (DCM) is a method to non-invasively assess effective connectivity between brain regions. 'Musicogenic epilepsy' is a rare reflex epilepsy syndrome in which seizures can be elicited by musical stimuli and thus represents a unique possibility to investigate complex human brain networks and test connectivity analysis tools. We investigated effective connectivity in a case of musicogenic epilepsy using DCM for fMRI, high-density (hd-) EEG and MEG and validated results with intracranial EEG recordings. A patient with musicogenic seizures was examined using hd-EEG/fMRI and simultaneous '256-channel hd-EEG'/ 'whole head MEG' to characterize the epileptogenic focus and propagation effects using source analysis techniques and DCM. Results were validated with invasive EEG recordings. We recorded one seizure with hd-EEG/fMRI and four auras with hd-EEG/MEG. During the seizures, increases of activity could be observed in the right mesial temporal region as well as bilateral mesial frontal regions. Effective connectivity analysis of fMRI and hd-EEG/MEG indicated that right mesial temporal neuronal activity drives changes in the frontal areas consistently in all three modalities, which was confirmed by the results of invasive EEG recordings. Seizures thus seem to originate in the right mesial temporal lobe and propagate to mesial frontal regions. Using DCM for fMRI, hd-EEG and MEG we were able to correctly localize focus and propagation of epileptic activity and thereby characterize the underlying epileptic network in a patient with musicogenic epilepsy. The concordance between all three functional modalities validated by invasive monitoring is noteworthy, both for epileptic activity spread as well as for effective connectivity analysis in general.© 2015 Elsevier Inc. All rights reserved. IntroductionMany physiological and pathological processes of the human brain are driven by networks and connectivity between brain regions. Thus, analysis of these connections is of particular importance in neurosciences and several methods have been proposed to study connectivity in-vivo by means of functional imaging. One of these is dynamic causal modeling (DCM), a method to assess the effective connectivity between brain regions, i.e. the causal influence that one neuronal system exerts over others. It was first developed for fMRI with the aim to estimate the parameters of a neuronal system model from which a blood oxygenation level dependent (BOLD) signal can be predicted that corresponds as closely as possible to the measured BOLD time series (Friston et al., 2003). Later, DCM was extended to the analysis of effective connectivity in EEG and MEG data taking into account the very high temporal resolution of these techniques and thereby combining a spatial forward model with a biologically informed temporal forward model (Kiebel et al., 2008). DCM can be used to test which brain region drives which by constructing different models of interacting regions or nodes and identifying the best one by model comparison. Thi...

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Section: Dynamic Causal Modelingcontrasting

confidence: 55%

Section: Effective Connectivity Analysesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multimodal effective connectivity analysis reveals seizure focus and propagation in musicogenic epilepsy

et al. 2015

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“…Finally, analysis methods found entry into EEG-fMRI which had already been established in 'classical' neuroimaging studies including data driven methods such as independent component analysis Moeller et al, 2011;Rodionov et al, 2007;Siniatchkin et al, 2007b) and others with and without using EEG information for the detection of epileptiform activity with fMRI (Donaire et al, 2009;Hamandi et al, 2005;Morgan et al, 2007;Morgan et al, 2004). Using this variety of analysis methods, mainly more recently, ictal activity itself was investigated with EEG-fMRI (Auer et al, 2008;Bai et al, 2010;Berman et al, 2010;Bonaventura et al, 2006;Detre et al, 1996;Di Bonaventura et al, 2006;Donaire et al, 2009;Federico et al, 2005a;Kobayashi et al, 2006c;LeVan et al, 2010;Liu et al, 2008;Marrosu et al, 2009;Moeller et al, 2010;Salek-Haddadi et al, 2009;SalekHaddadi et al, 2002;Tyvaert et al, 2008a).…”

Section: Eeg-fmri Applications In Epilepsymentioning

confidence: 98%

A personalized history of EEG–fMRI integration

Laufs

2012

NeuroImage

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“…FMRI colocalisation of functional and epileptic networks was also recently reported in musicogenic9 and reading epilepsy 10. Other studies focused on the correspondence between BOLD and γ responses during sensory stimulation or cognitive tasks 2 11 12.…”

Section: Discussionmentioning

confidence: 76%

Multimodal imaging reveals the role of activity in eating-reflex seizures

Blauwblomme

Kahane

Minotti

et al. 2010

Journal of Neurology, Neurosurgery & Psychiatry

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In reflex epilepsies, alteration of γ oscillations may mediate transition between interictal and ictal states. Here, we explored a patient having seizures triggered by syrup intake. From intracranial electroencephalography combined with functional MRI, the overlap of the gustatory cortex and of the preictal and ictal onset zones, as defined by early gamma changes, motivated the successful resective surgery of the middle short gyrus of the right insula. This case provides a rare demonstration from human gamma activity that the route to seizure may be supported by the interplay between physiological and epileptogenic networks.

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Combined EEG/fMRI recording in musicogenic epilepsy

Cited by 32 publications

References 16 publications

Multimodal effective connectivity analysis reveals seizure focus and propagation in musicogenic epilepsy

Multimodal effective connectivity analysis reveals seizure focus and propagation in musicogenic epilepsy

A personalized history of EEG–fMRI integration

Multimodal imaging reveals the role of activity in eating-reflex seizures

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