Identifying the structures involved in seizure generation using sequential analysis of ictal-fMRI data

Donaire, Antonio; Bargalló, Núria; Falcón, Carlos; Maestro, Iratxe; Carreño, Mar; Setoaín, Javier; Rumià, Jordi; Fernández, Santiago; Pintor, Luís; Boget, Teresa

doi:10.1016/j.neuroimage.2009.03.059

Cited by 42 publications

(59 citation statements)

References 42 publications

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“…We did not observe this in other cases as we compared each seizure phase with the baseline, rather than comparing BOLD signal change across phases (Donaire et al, 2009;Tyvaert et al, 2009). …”

Section: Neurophysiological Significancementioning

confidence: 97%

“…Our three-phase model, based on the observation that in many cases ictal EEG starts from baseline, evolves in amplitude and frequency as the epileptic network is recruited and terminates with post-ictal slowing (Niedermeyer, 1999) allows for the evolution of haemodynamic changes between phases. Although this is not a perfect representation of the underlying neuronal activity (Binnie and Stefan, 1999), we suggest that this provides a more physiologically informed model than either representing seizures as one continuous block or a series of short epochs of uniform length (Donaire et al, 2009;Tyvaert et al, 2009). The degree of concordance observed using this strategy was greatest for the early ictal phase and for the combined phases, than for either the clinical or late ictal phases, which is unsurprising given that seizure activity begins in one region and propagates to local and remotely connected cerebral areas.…”

Section: Eeg-based Glmmentioning

confidence: 99%

“…In addition, neurovascular coupling may vary in ictal events (Zhao et al, 2009) (SalekHaddadi et al, 2006. Inferences on the nature of the discrepancies between EEG onset and fMRI change beyond those accounted for by variation in HRF (Donaire et al, 2009;Tyvaert et al, 2009) are limited in the absence of an accurate measure of the event (e.g. simultaneous icEEG).…”

Section: Icamentioning

confidence: 99%

“…fMRI studies of seizures are less common, but case reports and small series have shown ictal BOLD signal change both with (Donaire et al, 2009;Kobayashi et al, 2006;Salek-Haddadi et al, 2002;Tyvaert et al, 2008) and without (Detre et al, 1995;Federico et al, 2005) concurrent EEG.…”

mentioning

confidence: 99%

“…Flexible modelling methods have been used, such as those based on Fourier basis sets or series of short blocks (Donaire et al, 2009;Tyvaert et al, 2009) addressing the potential complexity of ictal BOLD signal changes but they do not address the issue of how best to model these changes based on the available scalp EEG.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Imaging haemodynamic changes related to seizures: Comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG

Thornton¹,

Rodionov²,

Laufs³

et al. 2010

NeuroImage

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Section: Neurophysiological Significancementioning

confidence: 97%

Section: Eeg-based Glmmentioning

confidence: 99%

Section: Icamentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Imaging haemodynamic changes related to seizures: Comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG

Thornton¹,

Rodionov²,

Laufs³

et al. 2010

NeuroImage

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Mapping hemodynamic correlates of seizures using fMRI: A review

Chaudhary

Duncan

Lemieux

2011

Human Brain Mapping

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Functional magnetic resonance imaging (fMRI) is able to detect changes in blood oxygenation level associated with neuronal activity throughout the brain. For more than a decade, fMRI alone or in combination with simultaneous EEG recording (EEG-fMRI) has been used to investigate the hemodynamic changes associated with interictal and ictal epileptic discharges. This is the first literature review to focus on the various fMRI acquisition and data analysis methods applied to map epileptic seizure-related hemodynamic changes from the first report of an fMRI scan of a seizure to the present day. Two types of data analysis approaches, based on temporal correlation and data driven, are explained and contrasted. The spatial and temporal relationship between the observed hemodynamic changes using fMRI and other non-invasive and invasive electrophysiological and imaging data is considered. We then describe the role of fMRI in localizing and exploring the networks involved in spontaneous and triggered seizure onset and propagation. We also discuss that fMRI alone and combined with EEG hold great promise in the investigation of seizure-related hemodynamic changes non-invasively in humans. We think that this will lead to significant improvements in our understanding of seizures with important consequences for the treatment of epilepsy.

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Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

Murta

Leite

Carmichael³

et al. 2014

Hum. Brain Mapp.

130

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Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations.

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Identifying the structures involved in seizure generation using sequential analysis of ictal-fMRI data

Cited by 42 publications

References 42 publications

Imaging haemodynamic changes related to seizures: Comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG

Imaging haemodynamic changes related to seizures: Comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG

Mapping hemodynamic correlates of seizures using fMRI: A review

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

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