fMRI functional connectivity as an indicator of interictal epileptic discharges

Su, Jianpo; Khoo, Hui Ming; Ellenrieder, Nicolás von; Zeng, Ling‐Li; Hu, Dewen; Dubeau, François; Gotman, Jean

doi:10.1016/j.nicl.2019.102038

Cited by 10 publications

(9 citation statements)

References 37 publications

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“…Su et al ( 130 ) identified the different types of IEDs according to the spatial distributions from 38 patients with focal epilepsy and were used separately in the analysis of IED-related BOLD responses. The concordance between the maximal BOLD responses and the SOZ was found using iEEG, and then the functionally connected zone was determined for each one using the maximal BOLD as a seed ( Figure 10 ).…”

Section: Localization Approachesmentioning

confidence: 99%

Section: Localization Approachesmentioning

confidence: 99%

“…The results of this technique were like those of the conventional analysis in all five patients who had significant BOLD changes associated with IEDs. More importantly, the (130). (A) Functional MRI data were preprocessed through realignment, slice timing, outlier detection, coregistration, segmentation, spatial smoothing, and noise regression.…”

Section: Long-term Eeg Recordingmentioning

confidence: 99%

“…(D) The number of IEDs in each channel was normalized by the median number of IEDs in each subject. Statistical analysis was performed to determine group difference of IED rates between channels inside and outside the FCZ (130). method correlated BOLD responses with the scalp maps of epileptic activity in 14 out of the remaining 18 patients who had inconclusive simultaneous EEG-fMRI study using conventional analysis due to the absence of IEDs in the inside scanner EEG recording.…”

Section: Long-term Eeg Recordingmentioning

confidence: 99%

“…FIGURE 10 |The general pipeline of the research(130). (A) Functional MRI data were preprocessed through realignment, slice timing, outlier detection, coregistration, segmentation, spatial smoothing, and noise regression.…”

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confidence: 99%

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Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

et al. 2021

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Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG–fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG–fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG–fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.

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Section: Localization Approachesmentioning

confidence: 99%

Section: Localization Approachesmentioning

confidence: 99%

Section: Long-term Eeg Recordingmentioning

confidence: 99%

Section: Long-term Eeg Recordingmentioning

confidence: 99%

mentioning

confidence: 99%

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Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

et al. 2021

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Estimation of fMRI responses related to epileptic discharges using Bayesian hierarchical modeling

Cai,

von Ellenrieder,

Koupparis

et al. 2023

Human Brain Mapping

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Simultaneous electroencephalography–functional MRI (EEG‐fMRI) is a unique and noninvasive method for epilepsy presurgical evaluation. When selecting voxels by null‐hypothesis tests, the conventional analysis may overestimate fMRI response amplitudes related to interictal epileptic discharges (IEDs), especially when IEDs are rare. We aimed to estimate fMRI response amplitudes represented by blood oxygen level dependent (BOLD) percentage changes related to IEDs using a hierarchical model. It involves the local and distributed hemodynamic response homogeneity to regularize estimations. Bayesian inference was applied to fit the model. Eighty‐two epilepsy patients who underwent EEG‐fMRI and subsequent surgery were included in this study. A conventional voxel‐wise general linear model was compared to the hierarchical model on estimated fMRI response amplitudes and on the concordance between the highest response cluster and the surgical cavity. The voxel‐wise model overestimated fMRI responses compared to the hierarchical model, evidenced by a practically and statistically significant difference between the estimated BOLD percentage changes. Only the hierarchical model differentiated brief and long‐lasting IEDs with significantly different BOLD percentage changes. Overall, the hierarchical model outperformed the voxel‐wise model on presurgical evaluation, measured by higher prediction performance. When compared with a previous study, the hierarchical model showed higher performance metric values, but the same or lower sensitivity. Our results demonstrated the capability of the hierarchical model of providing more physiologically reasonable and more accurate estimations of fMRI response amplitudes induced by IEDs. To enhance the sensitivity of EEG‐fMRI for presurgical evaluation, it may be necessary to incorporate more appropriate spatial priors and bespoke decision strategies.

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Enhanced Regional Functional Connectivity Indicates Seizure Onset Zone

Ellenrieder

et al. 2020

Brain Topogr

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fMRI functional connectivity as an indicator of interictal epileptic discharges

Cited by 10 publications

References 37 publications

Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

Estimation of fMRI responses related to epileptic discharges using Bayesian hierarchical modeling

Enhanced Regional Functional Connectivity Indicates Seizure Onset Zone

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