脑电非线性分析在认知功能研究中的应用

目的　探讨在不同认知作业状态下脑电非线性动力学特性的变化规律、脑电非线性动态分析在认知过程研究中的作用。方法　我们用关联维数 (D2 )、点关联维数 (PD2 )对 30名健康成年人四种状态下的脑电数据进行了分析 :安静闭眼、安静睁眼、闭眼心算作业和睁眼图形推理作业。结果　认知作业过程相对于安静状态 ,D2 和PD2 有明显的升高。闭眼和心算 ,睁眼和图形推理状态之间差异有显著意义 (D2 分别为 3 93和 4 33,P <0 0 1;4 4 7和 4 98,P <0 0 1)。D2 和PD2 随时间存在时高时低的现象。结论　动态的、短时程的非线性动力学分析方法 ,更适合研究认知过程中大脑功能活动的变化规律。以D2 和PD2 地形图为基础的动态分析 ,可以清晰地展示认知过程中D2 和PD2的分布情况及与认知作业相关的大脑部位活跃顺序和活跃程度的变化 ,有助于我们了解认知过程中大脑的工作机制。     

脑电近似熵分析对帕金森病患者认知功能障碍的评估作用

目的:观察帕金森病(PD)患者与对照者的脑电近似嫡的差异,并探讨其对PD认知功能障碍的评估作用.方法:对31例PD患者和31例对照组进行简易精神状态检查量表(MMSE)测试、蒙特利尔认知评估量表(MoCA)测试、事件相关电位(ERP)检测P300波潜伏期(P3PL),采集安静闭眼、闭眼心算、安静睁眼三种状态下的脑电信号...     

失眠症患者的脑电非线性动力学初步研究

目的探讨失眠症患者在不同认知作业状态下脑电非线性动力学的初步特点。方法应用日本光电1518K脑电图和地形图系统,以及关联维数（D2）、点关联维数（PD2）方法对75例失眠症和64名正常成人在安静闭眼、安静睁眼、闭眼心算作业、睁眼记忆和数字划消五种状态下的脑电数据进行了分析。结果 （1）在D2和PD2上,正常和失眠症睁闭眼实验中差异均未达到显著性。（2）在D2上,与正常对照组比较,失眠症在心算和数字划消两个认知心理测试中均见降低。（3）在PD2上,与正常对照组比较,失眠症在心算、汉字记忆和数字划消三个认知心理测试中也见降低（P〈0.05或P〈0.01）。结论非线性动力学分析为临床提供了一种处理分析脑电信号的新思路,有助于进一步了解失眠症认知过程中大脑的工作机制。     

发作间期癫(癎)患者脑电非线性分析

目的:通过比较癫(癎)发作间期不同发作类型患者与正常对照组之间脑电非线性特点,探讨非线性脑电图在发作间期癫(癎)患者脑功能评价中的意义及应用价值.方法:对发作间期36例癫(癎)发作患者(其中21例强直阵挛发作患者和15例复杂部分性发作)和32例健康对照组分别行安静闭眼、闭眼心算、安静睁眼3种脑功能活动状态下的脑电图检查...     

基于小波变换与近似熵的睡眠分期研究*

目的：考察睡眠各期与近似熵的相互关系及相关参数选取对其的影响，以获取一种能较好反映睡眠分期的特征量。 方法：数据处理于2007-05/09在江苏大学电气信息工程学院生物医学工程系实验室完成。睡眠脑电数据取自波士顿Beth Israel医疗睡眠数据库，16个测试对象均为男性，年龄32~56岁。对睡眠脑电数据首先应用小波变换，将脑电信号中的噪声进行消噪处理，然后再利用近似熵将消噪后的睡眠脑电信号进行特征提取。 结果：睡眠各期脑电的近似熵是不一样的，清醒状态时，其值最大，随着睡眠的深入，大脑思维活动减少，近似熵的值逐渐降低；进入III期、IV期深度睡眠状态时，近似熵的值减到最低；在快速眼动睡眠期，脑电信号又与非快速眼动睡眠期I期类似，近似熵的值开始回升。近似熵在睡眠各个阶段具有显著差异性和规律性，表明近似熵能很好的用于表征睡眠分期。 结论：①睡眠脑电信号经过小波变换能有效的消除噪声并保持原信号的突变性质，从而表明了小波变换对非平稳信号的消噪具有很好的有效性和实用性。②对消除噪声后的睡眠脑电信号利用近似熵能很好的实现睡眠分期，从而实现了提取睡眠脑电有用信息的目的。     

磁刺激神门穴脑电信号的非线性动力学分析

背景：中医临床已经证明针刺或电刺神门穴可以改变神经活动或者治疗神经系统疾病。磁刺激技术是一种新型生物刺激技术,鉴于其刺激强度高且无痛无创,所以可以采用经颅磁刺激技术刺激穴位替代针刺或电刺穴位。 目的：应用磁刺激刺激人肢体神门穴,分析大脑不同的功能状态与脑电信号混沌程度的关系,初步验证应用磁刺激疗法治疗疾病的可行性。 设计、时间及地点：对照观察,于2007-01/2008-05在河北工业大学河北省电磁场与电器可靠性重点实验室完成。 对象：被试选择健康右利手男性4名,无实验经历,无既往神经、精神系统病史,实验期间被试保持闭眼静息。 方法：共进行2个实验。静息实验即测量被试安静状态下的脑电信号样本,磁刺激实验即采用经颅磁刺激刺激被试肢体神门穴,并测量脑电信号样本。用非线性动力学的方法对被试在2种状态下的脑电信号样本进行分析。 主要观察指标：安静与磁刺激状态下脑电信号非线性动力学参数。 结果：磁刺激状态下被试的非线性特征指标如关联维数、Lyapunov指数和样本熵均较安静状态低(P < 0.05)。以上3个指标越低,大脑的状态越趋于平静、有序。 结论：磁刺激肢体神门穴降低了脑电信号的混沌程度,使大脑更加镇静。提示磁刺激肢体神门穴具有改善脑功能的作用,在一定程度上证明了磁刺激疗法的可行性。     

阿尔茨海默病定量脑电图临床应用新进展

阿尔茨海默病(AD)早期诊断常是困难的,基因、影像等手段可发现一些生物学标记物,但临床上仍缺乏客观、简便易于普及的检测手段。近年来定量脑电图在认知功能障碍方面研究日益受到关注。通过定量分析可以获得脑电的频率、相位、网络相关性及复杂度、子波熵等定量信息,揭示大脑电活动的动力学机制,从而帮助我们发现可能的AD脑电相关的生物标记物。定量脑电不仅可以显示安静状态下的脑电信息,也可以检测不同认知任务下脑电的定量演变,观察药物使用后脑电的定量变化。定量脑电图作为认知功能障碍研究的新方法,显示了良好的研究前景。     

睁闭眼在临床脑电图检查中的意义

众所周知,临床脑电图描记,一般都是在清醒、安静、闭眼状态下进行,此时在两半球后部的基本电活动为8～13次/秒的α节律。而在描记过程进行时,还要睁眼10秒钟左右,然后再闭眼,观察在睁眼状态下脑电图的变化。一般的注意力都集中在α节律的变化,因为睁眼时,α节律消失,而为低幅β波所替     

心算实验中事件相关去同步化脑电变化初探

探讨事件刺激处理时心理活动的脑电生理改变。方法应用脑电地形图的检测技术对３０例正常人安静状态及在两种作业难度下脑电功率值的变化进行观察。结果（１）事件刺激后α２频带功率值降低,β、α１频带功率值增高,变化以枕区,顶区,后颞区的功率值最为显著;（２）随作业难度的的增加α２频带功率呈梯度降低,β频带功率则呈梯度增高;（３）在心算过程中,安静状态下呈现的两侧半球电位值差异消失。结论：心算期间大脑皮层出现     

69例正常人事件相关电位P300的研究

事件相关电位（Event—related potentials，ERPs）也称为内源性事件相关电位，是人对外界或环境刺激的心理反应。它是当人对某客体进行认知加工（如注意、记忆、思维）时，通过平均叠加技术从头颅表面记录到的大脑电位。反应大脑皮层认知功能状况，亦即探讨大脑思维的轨迹。狭义的事件相关电位P300检测是了解大脑认知功能的一种较理想的客观方法。由于刺激方式及各实验室仪器的不同，     

Robust modeling based on optimized EEG bands for functional brain state inference

The need to infer brain states in a data driven approach is crucial for BCI applications as well as for neuroscience research. In this work we present a novel classification framework based on Regularized Linear Regression classifier constructed from time-frequency decomposition of an EEG (electro-encephalography) signal. The regression is then used to derive a model of frequency distributions that identifies brain states. The process of classifier construction, preprocessing and selection of optimal regularization parameter by means of cross-validation is presented and discussed. The framework and the feature selection technique are demonstrated on EEG data recorded from 10 healthy subjects while requested to open and close their eyes every 30 s. This paradigm is well known in inducing Alpha power modulations that differ from low power (during eyes opened) to high (during eyes closed). The classifier was trained to infer eyes opened or eyes closed states and achieved higher than 90% classification accuracy. Furthermore, our findings reveal interesting patterns of relations between experimental conditions, EEG frequencies, regularization parameters and classifier choice. This viable tool enables identification of the most contributing frequency bands to any given brain state and their optimal combination in inferring this state. These features allow for much greater detail than the standard Fourier Transform power analysis, making it an essential method for both BCI proposes and neuroimaging research.     

Decrease of non-linear structure in the EEG of Alzheimer patients compared to healthy controls.

OBJECTIVE: Non-linear EEG analysis can provide information about the functioning of neural networks that cannot be obtained with linear analysis. The correlation dimension (D2) is considered to be a reflection of the complexity of the cortical dynamics underlying the EEG signal. The presence of non-linear dynamics can be determined by comparing the D2 calculated from original EEG data with the D2 from phase-randomized surrogate data. METHODS: In a prospective study, we used this method in order to investigate non-linear structure in the EEG of Alzheimer patients and controls. Twenty-four patients (mean age 75.6 years) with 'probable Alzheimer's disease' (NINCDS-ADRDA criteria) and 22 controls (mean age 70.3 years) were examined. D2 was calculated from original and surrogate data at 16 electrodes and in three conditions: with eyes open, eyes closed and during mental arithmetic. RESULTS: D2 was significantly lower in the Alzheimer patients compared to controls (P = 0.023). The difference between original and surrogate data was significant in both groups, implicating that non-linear dynamics play a role in the D2 value. Moreover, this difference between original and surrogate data was smaller in the patient group. D2 increased with activation, but not significantly more in controls than in patients. CONCLUSIONS: In conclusion, we found decreased dimensional complexity in the EEG of Alzheimer patients. This decrease seems to be attributable at least partially to different non-linear EEG dynamics. Because of this, non-linear EEG analysis could be a useful tool to increase our insight into brain dysfunction in Alzheimer's disease.     

Abnormal EEG synchronisation in heavily drinking students.

OBJECTIVE: In alcoholics, grey and white brain matter is damaged. In addition, functional brain connectivity as measured by EEG coherence is abnormal. We investigated whether heavily drinking students, although drinking for a shorter period than alcoholics, already show differences in functional connectivity compared to light-drinking controls. METHODS: EEG was recorded in 11 light and 11 heavy male student drinkers during eyes closed, and eyes closed plus mental rehearsal of pictures. Functional connectivity was assessed with the Synchronisation Likelihood method. RESULTS: Heavily drinking students had more synchronisation in the theta (4-8 Hz) and gamma (30-45 Hz) band than lightly drinking students during eyes closed, both with and without a mental-rehearsal task. CONCLUSIONS: Heavy student drinkers have increases in EEG synchronisation that are indicative of changes in hippocampal-neocortical connectivity. SIGNIFICANCE: Heavy student drinkers show differences in functional connectivity as compared to their lightly drinking counterparts, even though they have a relatively short drinking history.     

Approximate entropy of the electroencephalogram in healthy awake subjects and absence epilepsy patients.

The approximate entropy (ApEn) of signals in the electroencephalogram (EEG) was evaluated in 8 healthy volunteers and in 10 patients with absence epilepsy, both during seizure-free and seizure intervals. We estimated the nonlinearity of each 3-sec EEG segment using surrogate data methods. The mean (+/- SD) ApEn in EEG was 0.83 +/- 0.22 in healthy subjects awake with eyes closed. It was significantly lower during epileptic seizures (0.48 +/- 0.05) than during seizure-free intervals (0.80 +/- 0.13) (P < 0.001). Nonlinearity was clearly detected in EEG signals from epileptic patients during seizures but not during seizure-free intervals or in EEG signals from healthy subjects. The ApEn of EEG signals estimated over consecutive intervals could serve to determine pathological brain activity such as that occurring during absence epilepsy.     

On-going EEG in depression: a topographic spectral analytical pilot study

Spontaneous EEG activities recorded with 19 electrodes (10-20 system) on the scalp were quantified by spectral analytical methods (power and coherence spectra) to reveal changes of power and coherence during different conditions (eyes closed/relaxed, eyes opened/relaxed, flicker stimulation, reading, listening to a story). Control subjects and depressive patients were compared. Power as well as coherence changes were found in all frequency bands. Changes in the organization of the EEG were found in different areas of both hemispheres. The EEG organization was different in control subjects and depressive patients, indicating different levels of vigilance and/or different cognitive strategies in verbal tasks in the two groups.     

EEG correlates in the spectrum of cognitive decline.

OBJECTIVE: To investigate relations between EEG measures and performance on tests of global cognition, memory, language and executive functioning. METHODS: Twenty-two controls, 18 patients with mild cognitive impairment (MCI) and 16 with probable Alzheimer's disease (AD) underwent neuropsychological and EEG investigations. We used the following EEG measures: theta relative power during eyes closed, alpha reactivity during memory activation (i.e. the percentual decrease in alpha power as compared to eyes closed) and alpha coherence during eyes closed and memory activation. RESULTS: Theta relative power was increased in AD patients as compared with controls (p<0.001) and MCI patients (p<0.01) and related to decreased performance in all cognitive domains. Alpha reactivity was decreased in AD patients as compared with controls (p<0.005) and related to decreased performance on tests of global cognition, memory and executive functioning. Alpha coherence did not differ between groups and was unrelated to cognition. CONCLUSIONS: EEG power measures were associated with decreased performance on tests of global cognition, memory, language and executive functioning, while coherence measures were not. SIGNIFICANCE: The EEG yielded several power measures related to cognitive functions. These EEG power measures might prove useful in prospective studies aimed at predicting longitudinal cognitive decline and dementia.     

Abnormal EEG complexity in patients with schizophrenia and depression.

OBJECTIVE: Schizophrenics are usually unable to perform well on cognitive tasks due to disturbances in cortical information processing that are observable as abnormalities in electroencephalogram (EEG) signals. However, whether such cortical disturbances can be assessed by quantitative EEG analysis remains unclear. The purpose of this study was to characterize EEG disturbances, using the Lempel-Ziv complexity (LZC), in the subjects with schizophrenia at rest or while performing mental arithmetic tasks. The results were compared to those from the subjects with depression and with healthy controls. METHODS: The subjects included 62 schizophrenia patients, 48 depression patients and 26 age-matched healthy controls. EEG was recorded under two conditions: (i) resting with eyes closed, and (ii) a mentally active condition wherein the subjects were asked to subtract 7 from 100 iteratively with their eyes closed. EEG signals were analyzed by LZC and conventional spectral methods. RESULTS: In all the groups, LZC of EEG decreased during the mental arithmetic compared with those under the resting conditions. Both the schizophrenia and the depression groups had a higher LZC (p<0.05) than the controls. Also, the schizophrenia group had a lower LZC (p<0.05) than the depression group during the mental arithmetic task as well as during the resting state. Significant differences in LZC, at some symmetrically located loci (FP1/FP2, F7/F8), between the two hemispheres were found in all the patient groups only during the arithmetic task. CONCLUSIONS: Compared with conventional spectral analysis, LZC was more sensitive to both the power spectrum and the temporal amplitude distribution. LZC was associated with the ability to attend to the task and adapt the information processing system to the cognitive challenge. Thus, it would be useful in studying the disturbances in the cortical information processing patients with depression or schizophrenia. SIGNIFICANCE: LZC of EEG is associated with mental activity. Thus, LZC analysis can be an important tool in understanding the pathophysiology of schizophrenia and depression in future studies.