Activity in Pilots with Transient Ischemic Attacks

ZHOU Chuan-dai,HAN Dong-xu,LIU Yue-hong,ZHAI Yi-juan,LI Yan-song

(Institute of Space Medico-Engineering,Beijing 100094,China)

Abstract：Objective To study the characteristics of EEG after tramsient ischemic attack and to offer reference for screening procedure of aircrew and astronaut selection.Method The dominant frequency uncertainty of alpha band EEG in 12 pilots(males; age 30±5) with transient ischemic episodes in middle cerebral artery(MCA) territories and in 20 normal healthy pilots was analyzed with frequency-fluctuation analysis.Result The dominant probability of the main frequency coinciding with sites affected by transient ischaemic attack(TIA) in patient pilots was higher than that in healthy pilots (P＜0.01),and the dominant probability ratio logarithmic index I≥0 in all patient pilots with normal EEG, but I＜0 in all healthy pilots. It was also found that not only I≥0, but the second component shifted to lower frequency(8 Hz) in patients with slight focal EEG alterations,i.e. slowing of frequency. The relative entropy values (percentage) were decreased significantly in pilots with TIA as compared with healthy pilots (P＜0.05).Conclusion The dominant frequency uncertainty analysis of alpha band showed clear superiority of computerized evaluation over routine visual assessment for the diagnosis of minor cerebral ischemia. It offers not only a possibility of studying pathophysiological functional parameter, but also the reference for screening procedure in aircrew and astronaut selection.

Key wordsEEG；uncertainty；entropy；alpha rhythm；TIA

摘要：目的 探讨脑短暂性缺血发作(TIA)引起的脑功能紊乱的生物电特征，为飞行员、航天员选拔提供可参考的评价方法。方法 用CFM-8D EEG 监护仪记录了12名飞行员(男性，30±5)发生TIA后的EEG，应用脑波频率涨落分析系统分析了脑α波优势频率的不确定性，并与20名健康飞行员进行了比较。结果 发生TIA但EEG正常的飞行员，其主频出现优势涨落几率与健康飞行员比有明显的差异(P＜0.01)，且主频几率优势比指数I≥0，而健康飞行员主频几率优势比I＜0；与20名健康飞行员比较，相对熵值减少明显(P＜0.05)。发生TIA且局部出现EEG改变的飞行员不但I≥0且脑波出现优势频率慢化。结论 应用脑α波优势频率不确定性分析评价脑的缺血反应比EEG判读更优越。该研究结果不仅为TIA脑功能病理生理研究提供了评价参数，而且也为飞行员和航天员选拔提供了评价方法。

中图分类号：R338.1文献标识码：A文章编号：1002-0837(1999)02-0084-04

Quantitative EEG in cerebral ischemia was studied by Jonkman et al^［1］ using the multichannel spectral analysis technique and additional topographic displays of the data provided an overview of distribution of the different EEG parameters within a given frequency range. The event-related desynchronization (ERD) of EEG mapping in patients with TIA was investigated in a follow-up study^［2］.The dominant frequency analysis of EEG revealed brain response during injury and recovery^［3］.The bispectrum of EEG signals record from ischemic region in a model of focal cerebral ischemia in rat was analyzed using the third-order recursion method^［4］. However, it was found that one of the important features of alpha activity the uncertainty of dominant frequency fluctuation of alpha in EEG could be changed under hypoxic condition^［5］.The uncertainty of dominant frequency was investigated using relative entropy as parameter in 261 healthy pilots^［6］,it provided an analytical method for detecting functional changes of the brain.

The aim of this investigation was to study functional disorders of cortex following transient cerebral ischemic attacks(TIAs),using computerized analysis of changes in uncertainty of alpha dominant frequency,and to compare these data with investigations performed in normal healthy pilots in order to offer reference for the screening procedure in aircrew and astronaut selection.

Methods

SubjectsTwelve male pilots(aged 30±5) with transient episodes of ischemia in middle cerebral artery(MCA) territories. The transient focal neurological deficit involved the left MCA territory in eight and the right MCA territory in four patients. The standard EEG evaluated with descriptive visual analysis was normal in seven patients. Five patients showed slight focal alterations, coinciding in four of them with the hemisphere affected by the cerebrovascular episode. Control measurements were carried out in 20 normal healthy male pilots (aged 30±4).

EEG recordingsAccording to the 10～20 system, twelve electrodes were placed on F₃,F₄,C₃,C₄,P₃,P₄,O₁,O₂,F₇,F₈,T₅,T₆, using linked ear lobes reference. EEG recordings in patients with their eyes closed were made by means of a CFM-8D EEG monitor within 24 h following the acute event in a quiet, naturally illuminated room, with the subject in a sitting position, and bandpass filtered between 2 Hz and 24 Hz. The EEG data were digitized at a rate of 100 Hz for 240 s and stored on a disk. It was also displayed continuously on a high-resolution color monitor, with a reading sensitivity of 50 μV=10 mm. Registrations with fluctuations of alterness showing a decrease of the EEG power density, appearance of sleep rhythms and EEG registrations not distinctly free of artifacts were excluded from the data for analysis.

EEG analysisBy means of EEG-ET system, a newer system of frequency-fluctuation analysis was used , the uncertainty of the dominant frequency of alpha band(8～13 Hz) was analyzed according to the following method. Suppose there are six frequency components of alpha, i.e., 8,9, 10,11,12,13(Hz). Let a complete event be made up of the frequency components: A₈,A₉,A₁₀,A₁₁,A₁₂,A₁₃, and let cumulated probability of maximum power fluctuation in 240 s for each alpha frequency component is P₈,P₉,P₁₀,P₁₁,P₁₂,P₁₃ respectively, then the six cumulative dominant probability-time curves constructed the competitive synergetic structure of alpha frequency components. Let ΣPi =1 and it's entropy H=-Σp_ilnp_i,(i=8,9,10,11,12,13). If the p_is are equal,then H has a maximal value denoted by H_max.Thus the relative entropy value is Q=(H/H_max).

Results

Dominant probability ratio logarithmic index of α in patient pilots with TIAThe cumulated dominant fluctuation probability-time curves for individual frequency of alpha band in both patients and healthy pilots were showed in Fig.1. The uppermost curve in Fig.1 was of the main frequency, i.e., dominant frequency component, and it's probability was the highest in the six frequency components. The second was of the potential dominant frequency component, i.e., second frequency. It was obvious that the main frequency component was 9 Hz, and the second was 10 Hz for both patient pilots with TIA and healthy pilots. But the probability of the main frequency in TIA patient pilots coinciding with sites affected by cerebrovascular episode was more than in healthy pilots. The statistical significance estimated with the unpaired student's t-tests was observed in probability difference of main frequency in patients as compared with healthy (P＜0.01). Let the dominant probability ratio logarith