Epileptogenic modulation index and synchronization in hypsarrhythmia of West syndrome secondary to perinatal arterial ischemic stroke

Suzuki, Hiroharu; Otsubo, Hiroshi; Yokota, Nanako; Nishijima, S.; Go, Cristina; Snead, O. Carter; Ochi, Ayako; Rutka, James T.; Moharir, Mahendranath

doi:10.1016/j.clinph.2020.12.028

Cited by 9 publications

(6 citation statements)

References 38 publications

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“…In that study, classification of cases and controls based on modulation index had an area under the curve (AUC) of 0.98 when using sleep EEG and an AUC of 0.85 during wakefulness. A separate study found that delta-gamma modulation index was significantly higher in the affected hemisphere for children with West Syndrome secondary to perinatal arterial ischemic stroke ( 48 ).…”

Section: Computational Analysismentioning

confidence: 98%

“…This method relies on “embedding” each EEG time series in a higher dimensional state prior to comparing the activity in two independent channels, which means that high synchronization likelihood can occur even if the two EEG time series do not have a similar visual appearance ( 67 ). In children with IS and hypsarrhythmia secondary to perinatal arterial ischemic stroke, synchronization likelihood suggested stronger interhemispheric connectivity, as well as stronger intra-hemispheric connectivity in the affected hemisphere ( 48 ). This high connectivity was found in almost all frequency bands (ranging from 0.5 Hz to 70 Hz), and the authors speculated that this was related to the generation and modulation of hypsarrhythmia ( 48 ).…”

Section: Computational Analysismentioning

confidence: 99%

“…In children with IS and hypsarrhythmia secondary to perinatal arterial ischemic stroke, synchronization likelihood suggested stronger interhemispheric connectivity, as well as stronger intra-hemispheric connectivity in the affected hemisphere ( 48 ). This high connectivity was found in almost all frequency bands (ranging from 0.5 Hz to 70 Hz), and the authors speculated that this was related to the generation and modulation of hypsarrhythmia ( 48 ).…”

Section: Computational Analysismentioning

confidence: 99%

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EEG biomarkers for the diagnosis and treatment of infantile spasms

et al. 2022

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Early diagnosis and treatment are critical for young children with infantile spasms (IS), as this maximizes the possibility of the best possible child-specific outcome. However, there are major barriers to achieving this, including high rates of misdiagnosis or failure to recognize the seizures, medication failure, and relapse. There are currently no validated tools to aid clinicians in assessing objective diagnostic criteria, predicting or measuring medication response, or predicting the likelihood of relapse. However, the pivotal role of EEG in the clinical management of IS has prompted many recent studies of potential EEG biomarkers of the disease. These include both visual EEG biomarkers based on human visual interpretation of the EEG and computational EEG biomarkers in which computers calculate quantitative features of the EEG. Here, we review the literature on both types of biomarkers, organized based on the application (diagnosis, treatment response, prediction, etc.). Visual biomarkers include the assessment of hypsarrhythmia, epileptiform discharges, fast oscillations, and the Burden of AmplitudeS and Epileptiform Discharges (BASED) score. Computational markers include EEG amplitude and power spectrum, entropy, functional connectivity, high frequency oscillations (HFOs), long-range temporal correlations, and phase-amplitude coupling. We also introduce each of the computational measures and provide representative examples. Finally, we highlight remaining gaps in the literature, describe practical guidelines for future biomarker discovery and validation studies, and discuss remaining roadblocks to clinical implementation, with the goal of facilitating future work in this critical area.

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Section: Computational Analysismentioning

confidence: 98%

Section: Computational Analysismentioning

confidence: 99%

Section: Computational Analysismentioning

confidence: 99%

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EEG biomarkers for the diagnosis and treatment of infantile spasms

et al. 2022

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“…As the channels record the electrical activity in different brain regions, the MI values are analyzed after normalization using z-scores. Z-scores are often used to filter the data for abnormal values, which are considered abnormal when they are >3 typically ( 27 , 28 ).…”

Section: Methodsmentioning

confidence: 99%

Epileptogenic Zone Location of Temporal Lobe Epilepsy by Cross-Frequency Coupling Analysis

Liu

Han

et al. 2021

Front. Neurol.

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Epilepsy is a chronic brain disease with dysfunctional brain networks, and electroencephalography (EEG) is an important tool for epileptogenic zone (EZ) identification, with rich information about frequencies. Different frequency oscillations have different contributions to brain function, and cross-frequency coupling (CFC) has been found to exist within brain regions. Cross-channel and inter-channel analysis should be both focused because they help to analyze how epilepsy networks change and also localize the EZ. In this paper, we analyzed long-term stereo-electroencephalography (SEEG) data from 17 patients with temporal lobe epilepsy. Single-channel and cross-channel CFC features were combined to establish functional brain networks, and the network characteristics under different periods and the localization of EZ were analyzed. It was observed that theta–gamma phase amplitude coupling (PAC) within the electrodes in the seizure region increased during the ictal (p < 0.05). Theta–gamma and delta–gamma PAC of cross-channel were enhanced in the early and mid-late ictal, respectively. It was also found that there was a strong cross-frequency coupling state between channels of EZ in the functional network during the ictal, along with a more regular network than interictal. The accuracy rate of EZ localization was 82.4%. Overall, the combination of single-channel and multi-channel cross-band coupling analysis can help identify seizures and localize EZ for temporal lobe epilepsy. Rhythmic coupling reveals a relationship between the functional network and the seizure status of epilepsy.

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“…In epilepsy research, several studies used EEG-derived FC metrics with the aim of 1) improving diagnosis [ 17 , 18 ], 2) predicting the occurrence of seizures [ 19 ], and/or 3) assessing the effect of different therapies [ 5 , 20 , 21 ]. While various FC measures exist, the metrics focusing on the coupling of signal phases are known as phase synchronization measures [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Electroencephalogram synchronization measure as a predictive biomarker of Vagus nerve stimulation response in refractory epilepsy: A retrospective study

Danthine,

Cottin,

Berger

et al. 2024

PLoS ONE

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There are currently no established biomarkers for predicting the therapeutic effectiveness of Vagus Nerve Stimulation (VNS). Given that neural desynchronization is a pivotal mechanism underlying VNS action, EEG synchronization measures could potentially serve as predictive biomarkers of VNS response. Notably, an increased brain synchronization in delta band has been observed during sleep–potentially due to an activation of thalamocortical circuitry, and interictal epileptiform discharges are more frequently observed during sleep. Therefore, investigation of EEG synchronization metrics during sleep could provide a valuable insight into the excitatory-inhibitory balance in a pro-epileptogenic state, that could be pathological in patients exhibiting a poor response to VNS. A 19-channel-standard EEG system was used to collect data from 38 individuals with Drug-Resistant Epilepsy (DRE) who were candidates for VNS implantation. An EEG synchronization metric–the Weighted Phase Lag Index (wPLI)—was extracted before VNS implantation and compared between sleep and wakefulness, and between responders (R) and non-responders (NR). In the delta band, a higher wPLI was found during wakefulness compared to sleep in NR only. However, in this band, no synchronization difference in any state was found between R and NR. During sleep and within the alpha band, a negative correlation was found between wPLI and the percentage of seizure reduction after VNS implantation. Overall, our results suggest that patients exhibiting a poor VNS efficacy may present a more pathological thalamocortical circuitry before VNS implantation. EEG synchronization measures could provide interesting insights into the prerequisites for responding to VNS, in order to avoid unnecessary implantations in patients showing a poor therapeutic efficacy.

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Epileptogenic modulation index and synchronization in hypsarrhythmia of West syndrome secondary to perinatal arterial ischemic stroke

Cited by 9 publications

References 38 publications

EEG biomarkers for the diagnosis and treatment of infantile spasms

EEG biomarkers for the diagnosis and treatment of infantile spasms

Epileptogenic Zone Location of Temporal Lobe Epilepsy by Cross-Frequency Coupling Analysis

Electroencephalogram synchronization measure as a predictive biomarker of Vagus nerve stimulation response in refractory epilepsy: A retrospective study

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