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在数分钟到数天的个体特定时间尺度上,脑电图频段功率的波动解释了癫痫发作演变的变化。

Fluctuations in EEG band power at subject-specific timescales over minutes to days explain changes in seizure evolutions.

作者信息

Panagiotopoulou Mariella, Papasavvas Christoforos A, Schroeder Gabrielle M, Thomas Rhys H, Taylor Peter N, Wang Yujiang

机构信息

CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne.

Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne.

出版信息

Hum Brain Mapp. 2022 Jun 1;43(8):2460-2477. doi: 10.1002/hbm.25796. Epub 2022 Feb 4.

DOI:10.1002/hbm.25796
PMID:35119173
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9057101/
Abstract

Epilepsy is recognised as a dynamic disease, where both seizure susceptibility and seizure characteristics themselves change over time. Specifically, we recently quantified the variable electrographic spatio-temporal seizure evolutions that exist within individual patients. This variability appears to follow subject-specific circadian, or longer, timescale modulations. It is therefore important to know whether continuously recorded interictaliEEG features can capture signatures of these modulations over different timescales. In this study, we analyse continuous intracranial electroencephalographic (iEEG) recordings from video-telemetry units and find fluctuations in iEEG band power over timescales ranging from minutes up to 12 days. As expected and in agreement with previous studies, we find that all subjects show a circadian fluctuation in their iEEG band power. We additionally detect other fluctuations of similar magnitude on subject-specific timescales. Importantly, we find that a combination of these fluctuations on different timescales can explain changes in seizure evolutions in most subjects above chance level. These results suggest that subject-specific fluctuations in iEEG band power over timescales of minutes to days may serve as markers of seizure modulating processes. We hope that future study can link these detected fluctuations to their biological driver(s). There is a critical need to better understand seizure modulating processes, as this will enable the development of novel treatment strategies that could minimise the seizure spread, duration or severity and therefore the clinical impact of seizures.

摘要

癫痫被认为是一种动态疾病,其癫痫易感性和癫痫发作特征本身都会随时间变化。具体而言,我们最近对个体患者中存在的可变脑电图时空癫痫发作演变进行了量化。这种变异性似乎遵循特定个体的昼夜节律或更长时间尺度的调制。因此,了解连续记录的发作间期脑电图特征是否能在不同时间尺度上捕捉到这些调制的特征非常重要。在本研究中,我们分析了来自视频遥测单元的连续颅内脑电图(iEEG)记录,发现iEEG频段功率在从几分钟到12天的时间尺度上存在波动。正如预期并与先前研究一致,我们发现所有受试者的iEEG频段功率都呈现昼夜节律波动。我们还在特定个体的时间尺度上检测到了类似幅度的其他波动。重要的是,我们发现这些不同时间尺度上的波动组合可以在大多数受试者中高于机遇水平地解释癫痫发作演变的变化。这些结果表明,iEEG频段功率在数分钟到数天时间尺度上的特定个体波动可能作为癫痫发作调节过程的标志物。我们希望未来的研究能够将这些检测到的波动与其生物学驱动因素联系起来。迫切需要更好地理解癫痫发作调节过程,因为这将有助于开发新的治疗策略,从而最大限度地减少癫痫发作的传播、持续时间或严重程度,进而降低癫痫发作的临床影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/14d0f918b93c/HBM-43-2460-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/30e11801434d/HBM-43-2460-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/5af45997a440/HBM-43-2460-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/657c99820555/HBM-43-2460-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/0b53daccf914/HBM-43-2460-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/0416538b327a/HBM-43-2460-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/14d0f918b93c/HBM-43-2460-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/30e11801434d/HBM-43-2460-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/5af45997a440/HBM-43-2460-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/657c99820555/HBM-43-2460-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/0b53daccf914/HBM-43-2460-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/0416538b327a/HBM-43-2460-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2740/9057101/14d0f918b93c/HBM-43-2460-g003.jpg

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Cycles in epilepsy.癫痫发作的周期。
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Viability of Preictal High-Frequency Oscillation Rates as a Biomarker for Seizure Prediction.发作前高频振荡率作为癫痫发作预测生物标志物的可行性。
体内病理组织中人类大脑活动的昼夜节律和超日节律减弱。
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