Department of Biomedical Engineering, University of California, Irvine, CA, USA.
Division of Neurology, Children's Hospital Orange County, Orange, CA, USA; Department of Pediatrics, University of California, Irvine, CA, USA.
Clin Neurophysiol. 2020 May;131(5):1087-1098. doi: 10.1016/j.clinph.2020.02.014. Epub 2020 Mar 4.
Functional connectivity networks (FCNs) based on interictal electroencephalography (EEG) can identify pathological brain networks associated with epilepsy. FCNs are altered by interictal epileptiform discharges (IEDs), but it is unknown whether this is due to the morphology of the IED or the underlying pathological activity. Therefore, we characterized the impact of IEDs on the FCN through simulations and EEG analysis.
We introduced simulated IEDs to sleep EEG recordings of eight healthy controls and analyzed the effect of IED amplitude and rate on the FCN. We then generated FCNs based on epochs with and without IEDs and compared them to the analogous FCNs from eight subjects with infantile spasms (IS), based on 1340 visually marked IEDs. Differences in network structure and strength were assessed.
IEDs in IS subjects caused increased connectivity strength but no change in network structure. In controls, simulated IEDs with physiological amplitudes and rates did not alter network strength or structure.
Increases in connectivity strength in IS subjects are not artifacts caused by the interictal spike waveform and may be related to the underlying pathophysiology of IS.
Dynamic changes in EEG-based FCNs during IEDs may be valuable for identification of pathological networks associated with epilepsy.
基于发作间期脑电图(EEG)的功能连接网络(FCN)可以识别与癫痫相关的病理性大脑网络。FCN 受发作间期癫痫样放电(IED)的改变,但尚不清楚这是由于 IED 的形态还是潜在的病理活动所致。因此,我们通过模拟和 EEG 分析来描述 IED 对 FCN 的影响。
我们将模拟 IED 引入到 8 名健康对照者的睡眠 EEG 记录中,并分析了 IED 幅度和速率对 FCN 的影响。然后,我们基于有无 IED 的脑电段生成了 FCN,并将其与 8 名患有婴儿痉挛症(IS)的患者的类似 FCN 进行了比较,这些患者基于 1340 个视觉标记的 IED。评估了网络结构和强度的差异。
IS 患者的 IED 导致连接强度增加,但网络结构不变。在对照者中,具有生理幅度和速率的模拟 IED 不会改变网络强度或结构。
IS 患者连接强度的增加不是由发作间棘波波形引起的假象,可能与 IS 的潜在病理生理学有关。
IED 期间基于 EEG 的 FCN 的动态变化可能有助于识别与癫痫相关的病理性网络。