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禁则的颅内 EEG 癫痫发作期模式表明人类癫痫发作中的确定性动力学。

Forbidden ordinal patterns of periictal intracranial EEG indicate deterministic dynamics in human epileptic seizures.

机构信息

Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.

出版信息

Epilepsia. 2011 Oct;52(10):1771-80. doi: 10.1111/j.1528-1167.2011.03202.x. Epub 2011 Aug 12.

Abstract

PURPOSE

Epileptic seizures typically reveal a high degree of stereotypy, that is, for an individual patient they are characterized by an ordered and predictable sequence of symptoms and signs with typically little variability. Stereotypy implies that ictal neuronal dynamics might have deterministic characteristics, presumably most pronounced in the ictogenic parts of the brain, which may provide diagnostically and therapeutically important information. Therefore the goal of our study was to search for indications of determinism in periictal intracranial electroencephalography (EEG) studies recorded from patients with pharmacoresistent epilepsy.

METHODS

We assessed the number of forbidden ordinal patterns of 110 periictal multichannel intracranial EEG studies of 16 patients. Ordinal patterns are derived from the rank order of short sequences of consecutive EEG values. Ordinal patterns are well suited for analyzing real-world time series, for they have low sensitivity for many forms of noise and are applicable to nonstationary data. Although Gaussian random dynamics generate all possible ordinal patterns for a given sequence length, deterministic dynamics typically manifest with less random and more regular signals that miss a certain number of all the possible ordinal patterns. These missing ordinal patterns are referred to as "forbidden ordinal patterns." In this study, the number of forbidden ordinal patterns n(fp) of an EEG signal was interpreted as an indication of determinism, when it was larger than the number of forbidden patterns occurring in amplitude adjusted Fourier transform surrogates. We computed n(fp) for each EEG signal in a time-resolved way by using a moving-window approach. Then we specifically investigated n(mean)(fp) denoting the average number of forbidden patterns across all EEG signals, and n(max)(fp), which represents the number of forbidden patterns occurring in the EEG signal with the largest n(fp) during the seizure-onset period.

KEY FINDINGS

The average number of forbidden patterns of all EEG signals, n(mean)(fp), typically first increased and then decreased during the seizures. However, these changes were not statistically significant relative to the preseizure time period. In contrast, n(max)(fp)typically increased significantly during the first third of the seizure period and then gradually decreased toward and beyond seizure termination. In those patients who became seizure free following surgery, a larger percentage of the EEG signals containing the maximal number of forbidden patterns during the seizure-onset period tended to be recorded from within the visually identified seizure-onset zones.

SIGNIFICANCE

Our findings demonstrate a spatiotemporally limited shift of neuronal dynamics toward a more deterministic dynamic regimen, specifically pronounced during the seizure-onset period. Assessing the number of forbidden ordinal patterns of intracranial EEG provides quantitative and observer-independent information. We propose that it is at least partially complementary to classical visual EEG reading and may be diagnostically helpful to better delineate ictogenic parts of the brain.

摘要

目的

癫痫发作通常表现出高度的刻板性,也就是说,对于个体患者,它们的特征是症状和体征呈有序且可预测的序列,通常变化很小。刻板性意味着发作期神经元动力学可能具有确定性特征,推测在致痫大脑区域最为明显,这可能为诊断和治疗提供重要信息。因此,我们研究的目的是寻找抗药性癫痫患者颅内脑电图(EEG)记录中发作期存在决定性的迹象。

方法

我们评估了 16 名患者的 110 例颅内多通道脑电图发作期研究的禁止有序模式数量。有序模式是从短序列 EEG 值的顺序中得出的。有序模式非常适合分析现实世界中的时间序列,因为它们对许多形式的噪声具有低敏感性,并且适用于非平稳数据。虽然高斯随机动力学为给定的序列长度生成所有可能的有序模式,但确定性动力学通常表现出较少的随机性和更规则的信号,从而错过某些可能的有序模式。这些缺失的有序模式被称为“禁止有序模式”。在这项研究中,当脑电图信号的禁止有序模式数量 n(fp)大于幅度调整傅里叶变换替代物中出现的禁止模式数量时,将其解释为确定性的迹象。我们通过使用移动窗口方法以时间分辨的方式计算每个 EEG 信号的 n(fp)。然后,我们专门研究了 n(mean)(fp),表示所有 EEG 信号中禁止模式的平均数量,以及 n(max)(fp),表示在发作起始期间具有最大 n(fp)的 EEG 信号中出现的禁止模式数量。

主要发现

所有 EEG 信号的平均禁止模式数量 n(mean)(fp)通常在发作期间先增加后减少。然而,与发作前时期相比,这些变化没有统计学意义。相比之下,n(max)(fp)在发作前 1/3 期间通常显著增加,然后逐渐减少到发作终止。在手术后癫痫发作停止的患者中,手术过程中记录到的最大禁止模式数量的 EEG 信号中,有更大比例的信号来自视觉识别的发作起始区。

意义

我们的研究结果表明,神经元动力学存在时空有限的向更确定性动态模式的转变,特别是在发作起始期间更为明显。评估颅内 EEG 的禁止有序模式数量提供了定量和观察者独立的信息。我们提出,它至少部分补充了经典的视觉 EEG 阅读,并可能有助于更好地描绘大脑的致痫部位。

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