不同生理状态时脑电时间序列的三神复杂度计算比较

为了研究不同生理状态下的脑电复杂度变化特点,本文依照１９９４年徐京等人应用的算法,对４种状态（安静睁眼,清醒闭目,浅度睡眠,深度睡眠）下的三种脑电复杂度（Ｋｃ,Ｃ１,Ｃ２）的变化规律进行了比较分析,Ｋｃ与Ｃ１的变化相一致,从安静睁眼剂的清醒闭目到浅睡到深度睡眠,Ｋｃ与Ｃ１值均依次下降,Ｃ２值的变化则与它们相反,尤其在深睡期显著升高,实验结果提示,复杂度可做为脑电时间序列的研究指标。     

局限性癫痫脑电时间序列的三种复杂度计算比较

为探索非线性动力学复杂性测度诊断癫痫病的新方法,对局限性癫痫病患者脑电时间序列进行了三种复杂度（Ｋｃ、Ｃ１、Ｃ２）的计算比较。观察到,痫性导联脑电的三种复杂度多低于对侧导联的值;复杂度Ｋｃ的相对变化量较Ｃ１和Ｃ２大;复杂度Ｋｃ和Ｃ１的变化趋势相似,而复杂度Ｃ２的变化趋势与复杂度Ｋｃ和Ｃ１的规律不尽相同;但正常人ＥＥＧ信号的复杂度没有这种显著变化。结果提示,脑电复杂性测度有可能成为诊断癫痫的特征参数,值得进一步深入研究。     

基于大脑皮层信息传输的脑电信息图示方法

提出一种基于大脑皮层信息传输的脑电地形图示方法—脑电信息图（Ｂｒａｉｎ ＩｎｆｏｒｍａｔｉｏｎＭａｐｐｉｎｇ － ＢＩＭ） 。其原理是从不同导联电极上采集脑电信号经相空间重建构成头皮电位信息传输矩阵, 将各导联信息传输时间序列的信息传输量和复杂度数据绘制成头皮拓扑分布图, 以直观地反映脑电信息传输分布模式在不同时相中的变化进程。该方法不仅是从新的角度观察大脑功能变化, 而且可克服传统的脑电频谱分段地形图不能表达长程脑电模式变化的不足。对局限性癫痫病患者的试用表明,脑电信息图能较好地反映癫痫发作前后的信息传输动向和复杂度（Ｋｃ 、Ｃ１ 、Ｃ２） 的变化趋势。结果提示,脑电信息图（ＢＩＭ） 有可能成为一种新的观察大脑功能活动的图示诊断方法,值得进一步深入研究。     

应用小波熵分析大鼠脑电信号的动态变化特性

应用小波熵（一种新的信号复杂度测量方法）分析大鼠在不同生理状态下脑电复杂度的动态时变特性。采用慢性埋植电极记录自由活动大鼠的皮层EEG,使用多分辨率小波变换将EEG信号分解为δ、θ、α和β四个分量,求得随时间变化的小波熵。结果表明：在清醒、慢波睡眠和快动眼睡眠三种生理状态下,EEG的小波熵之间存在显著差别,并且在不同时期其值与各个分解分量之间具有不同的关系,其中,慢波睡眠期小波熵还具有较明显的变化节律,反映了EEG微状态中慢波和纺锤波的互补性。由此可见,小波熵既能区别长时间段EEG复杂度之间的差别,又能反映EEG微状态的快速变化特性。     

牛磺酸调节缺氧性肺、脑血管反应的机理研究

本实验从磷脂酶Ａ＿２（ＰＬＡ＿２）、前列腺素（ＰＧｓ）、白三烯（ＬＴｓ）和过氧化脂质（ＬＰＯ）方面探讨了牛磺酸调节肺、脑血管对急、慢性缺氧反应的机制。急性缺氧时狗出肺与出脑血中ＬＰＯ增加,ＰＬＡ,活性有升高趋势,但出脑与出肺（入脑）血相比无显著性差异。出肺与出脑血中ＬＴＣ＿４、ＴＸＢ＿２、６－Ｋｅｔｏ－ＰＧＦ＿（１ａ）及ＴＸＢ＿２／６－Ｋｅｔｏ－ＰＧＦ＿（１ａ）比值均升高。慢性缺氧大鼠肺、脑组织中ＰＬＡ＿２活性均升高。牛磺酸增加缺氧时６－Ｋｅｔｏ－ＰＧＦ＿（１ａ）,减弱其它变化。提示牛磺酸对缺氧性肺缩血管反应的调节作用可能与降低缺氧时ＰＬＡ＿２活性,抑制脂质过氧化和ＬＴＣ＿４、ＴＸＡ＿２生成,降低ＴＸＡ＿２／ＰＧＩ＿２比值有关;而牛磺酸减弱缺氧性脑舒血管反应不是直接通过上述变化起作用的。     

不同状态下脑电信号的双谱分析

根据脑电的非高斯随机特性,应用双谱技术分析脑电信号,引出脑电的参数化双谱估计,旨在克服脑电功率谱分析的缺陷。对四种不同脑功能状态（清醒闭眼、安神睁眼、快速心算、急促呼吸）的脑电进行双谱分析,并对对称脑电信号的互双谱作了初步的讨论。实验结果显示：所有脑电均出现明显的双谱结构,但不同生理状态下的脑电双谱结构存在明显的差异,结果表明双谱可能为研究脑电提供新的辅助信息。     

不同脑功能状态下脑电三维动态频谱的变化

应用三维动枋频谱分析方法,对不同脑功能状态下的脑电活动作定理分析结果表明:在睁眼时α波(8—13Hz)的总面积仅为闭目安静时的无56.1°.其中以X_1成份(8—10Hz)下降显著.降至41.1°.X_2成份(11—13Hz)下降至71.0°心算时x节律抑制不明显β波段(17— 45Hz)在睁眼和心算时总面积无显著变化,但心算时β_1(17—31Hz)略占优势,而睁眼时β_2(31—45Hz)略呈优势。     

盐度和CO2倍增环境下碱蓬幼苗呼吸酶活性的变化

研究了生长在正常大气ＣＯ２和ＣＯ２倍增环境中的盐生植物碱蓬（Ｓｕａｅｄａｓａｌｓａ）幼苗呼吸酶活性对ＫＣｌ和ＮａＣｌ的反应．结果表明,在ＣＯ２倍增（７００μｌ·Ｌ－１）和正常大气ＣＯ２（３５０μｌ·Ｌ－１）下,３００ｍｍｏｌ·Ｌ－１ＫＣｌ和ＮａＣｌ均能抑制琥珀酸脱氢酶（ＳＤＨ）和苹果酸脱氢酶（ＭＤＨ）活性,而异柠檬酸脱氢酶（ＩＤＨ）活性为ＮａＣｌ抑制、ＫＣｌ促进;ＮａＣｌ和ＫＣｌ明显抑制细胞色素氧化酶（ＣＯ）和光呼吸中乙醇酸氧化酶（ＧＯ）、羟基丙酮酸还原酶（ＨＰＲ）活性;并指出在ＫＣｌ胁迫下,ＣＯ２使三羧酸循环（ＴＣＡＣ）的运行变慢,ＮａＣｌ胁迫下使其加快,ＴＣＡＣ运行限速步骤与ＭＤＨ无关,ＣＯ为盐对呼吸代谢影响的重要位点．另外,Ｋ＋、Ｎａ＋对蛋白表达的影响有差异,ＣＯ２可使盐胁迫下的碱蓬幼苗蛋白表达降低．     

长期大强度运动对大鼠脑组织神经肽Y、亮氨酸脑啡肽、强啡肽A_(1-13)动态变化的影响

目的和方法：采用ＡＢＣ免疫组织化学法结合图象分析,观察大鼠脑组织神经肽Ｙ、亮氨酸脑啡肽、强啡肽Ａ１１３ 在长期（ 共７ 周）大强度（速度由１５ ｍ／ｍｉｎ 递增至３５ ｍ／ｍｉｎ、运动时间为２０ ～２５ ｍｉｎ／ｄ） 的运动下的变化。结果：安静状态下在丘脑室旁核（ＰＶ） 、下丘脑背内侧核（ＤＭ） 、下丘脑腹内侧核（ＶＭＨ）等核团ＮＰＹ 无显著性变化;在此基础上的末次急性运动结束后３ ｈ ＮＰＹ 变化尤为明显。安静状态下大鼠尾壳核ＬＥＮＫ 下降;而末次急性运动后大鼠下丘脑ＬＥＮＫ 被迅速激活而升高。该强度运动能激活下丘脑ＤＹＮＡ１１３ ,尤以运动结束后３０ ｍｉｎ 最为明显。结论： ＮＰＹ、ＬＥＮＫ、ＤＹＮＡ１１３ 在该强度运动下大鼠不同脑区呈现不同变化趋势     

健康人不同生理状态下的脑电近似熵的观测

目的：应用近似熵（ＡｐＥｎ）研究不同生理状态下脑电图非线性动力学特性。方法：在一组健康人４０例中,进行五种生理状态的脑电图记录：闭眼安静;睁眼安静;看图;听短纯音;闭眼数数目１００￣７,并计算各种状态的近似熵。结果：闭眼安静状态额区（Ｆ３,Ｆ４）的ＡｐＥｎ最高,枕区（Ｏ１,Ｏ２）最低,睁眼状态所有脑区的ＡｐＥｎ均增高,不同的生理刺激任务对ＥＥＧ ＡｐＥｎ产生不同的影响,其中额区的影响最大。结论：Ａ     

EEG changes with unblocking of acoustic and visual sensory canals

Modally specific and supramodal components of EEG dynamics, related to involuntary reorientation of anticipatory attention from internal into external, were studied using unblocking of either visual or acoustic apparatus. EEG registration took place while the examinees were in the resting states: with opened eyes; with closed eyes; with closed eyes and inserted noise-protective earplugs. Averaged values of EEG power in each of the derivations and of EEG coherence in each of the derivation pairs were calculated for an every examinee and for each of the states. The estimations were done in delta, theta, alphal, alpha2, beta1, beta2, gamma frequency bands. The received results support an idea about manifestation of both supramodal and modally specific components in brain mechanisms of involuntary anticipatory attention. These results seem to be of certain interest for existing discussion on divergence and convergence between systemic mechanisms of visual and auditory attention.     

Quantification of sleepiness through principal component analysis of the electroencephalographic spectrum

Although circadian and sleep research has made extraordinary progress in the recent years, one remaining challenge is the objective quantification of sleepiness in individuals suffering from sleep deprivation, sleep restriction, and excessive somnolence. The major goal of the present study was to apply principal component analysis to the wake electroencephalographic (EEG) spectrum in order to establish an objective measure of sleepiness. The present analysis was led by the hypothesis that in sleep-deprived individuals, the time course of self-rated sleepiness correlates with the time course score on the 2nd principal component of the EEG spectrum. The resting EEG of 15 young subjects was recorded at 2-h intervals for 32-50 h. Principal component analysis was performed on the sets of 16 single-Hz log-transformed EEG powers (1-16 Hz frequency range). The time course of self-perceived sleepiness correlated strongly with the time course of the 2nd principal component score, irrespective of derivation (frontal or occipital) and of analyzed section of the 7-min EEG record (2-min section with eyes open or any of the five 1-min sections with eyes closed). This result indicates the possibility of deriving an objective index of physiological sleepiness by applying principal component analysis to the wake EEG spectrum.     

Effects of unstructured video exposure on EEG power in situations of forced attention and rest

Group 1 (N = 30) and Group 2 (N = 22) of healthy volunteers participated in the experiment. In both groups, the EEG was recorded in the state of rest with the eyes closed (REC); at rest with eyes open (REO); and during passively watching TV channel noises (white noise). EEG was also recorded in the state of forced visual attention: when counting colored symbols appearing on the screen (group 1) and when searching for an image of a real object in the noise (group 2). The averaged values of EEG power in each derivation were calculated for every subject and for each state in the Δ, θ, α₁, α₂, β₁, β₂, and γ frequency bands. The results demonstrate that the exposure to unstructured noninformative video noise may lead to significant changes in the EEG power in various frequency bands, with the most prominent changes taking place in the α₂ band. These changes are topically wide, reflecting systemic changes in the corresponding brain mechanisms, but are much less intense compared to the difference between the states of rest with the eyes open and closed.     

Quantification of Sleepiness Through Principal Component Analysis of the Electroencephalographic Spectrum

Although circadian and sleep research has made extraordinary progress in the recent years, one remaining challenge is the objective quantification of sleepiness in individuals suffering from sleep deprivation, sleep restriction, and excessive somnolence. The major goal of the present study was to apply principal component analysis to the wake electroencephalographic (EEG) spectrum in order to establish an objective measure of sleepiness. The present analysis was led by the hypothesis that in sleep-deprived individuals, the time course of self-rated sleepiness correlates with the time course score on the 2nd principal component of the EEG spectrum. The resting EEG of 15 young subjects was recorded at 2-h intervals for 32–50?h. Principal component analysis was performed on the sets of 16 single-Hz log-transformed EEG powers (1–16?Hz frequency range). The time course of self-perceived sleepiness correlated strongly with the time course of the 2nd principal component score, irrespective of derivation (frontal or occipital) and of analyzed section of the 7-min EEG record (2-min section with eyes open or any of the five 1-min sections with eyes closed). This result indicates the possibility of deriving an objective index of physiological sleepiness by applying principal component analysis to the wake EEG spectrum. (Author correspondence: putilov@ngs.ru)     

EEG differences between resting states with eyes open and closed in darkness

Transition from a resting state with eyes closed (REC) to a resting state with eyes open (REO) is associated with visible changes in EEG, which are traditionally considered to be a sign of reorganization of the brain’s activity in response to visual stimuli. The EEGs recorded in the REC and REO states in complete darkness, when the stimulatory effect of light to the eye’s retina was absent, were compared. Thirty healthy subjects participated in the study. EEG in the range of 1.5–50 Hz was recorded from nineteen zones of the head monopolarly. It was found that, under conditions of complete darkness, the REC and REO states significantly differed in their EEG spectral power and coherence in the Δ, θ, α₁, α₂, β₁, β₂ and γ frequency bands. Under experimental conditions, these changes in the EEG could not be induced by external influence to the visual system. Therefore, we suppose that they are correlates of the switching of involuntary preliminary attention from internally directed attention specific for the REC state to externally directed attention specific for the REO state.     

Measures of entropy and complexity in altered states of consciousness

Quantification of complexity in neurophysiological signals has been studied using different methods, especially those from information or dynamical system theory. These studies have revealed a dependence on different states of consciousness, and in particular that wakefulness is characterized by a greater complexity of brain signals, perhaps due to the necessity for the brain to handle varied sensorimotor information. Thus, these frameworks are very useful in attempts to quantify cognitive states. We set out to analyze different types of signals obtained from scalp electroencephalography (EEG), intracranial EEG and magnetoencephalography recording in subjects during different states of consciousness: resting wakefulness, different sleep stages and epileptic seizures. The signals were analyzed using a statistical (permutation entropy) and a deterministic (permutation Lempel–Ziv complexity) analytical method. The results are presented in complexity versus entropy graphs, showing that the values of entropy and complexity of the signals tend to be greatest when the subjects are in fully alert states, falling in states with loss of awareness or consciousness. These findings were robust for all three types of recordings. We propose that the investigation of the structure of cognition using the frameworks of complexity will reveal mechanistic aspects of brain dynamics associated not only with altered states of consciousness but also with normal and pathological conditions.     

Generalized dimension of the intersection between EEGs

 The generalized dimension defined by [Mandelbrot (1995) J Fourier Anal Appl special J.P. Kahane issue: 409–432] was applied to studying the interrelationship between various parts of human cerebral cortex in different functional conditions. Taking EEG signals from different brain areas as different sets, the generalized dimensions of their intersections were calculated to describe the interrelationship between them. The results showed that the generalized dimensions of intersections in different brain states decreased according to the following order: rest with eyes open, closed, light sleep, and deep sleep. The generalized dimensions of intersections related to the left or right temporal lobe were higher than the others when the subjects was doing mental arithmetic, and there was a decrease when the subjects listened to soft classical music. In addition, it was found that there was a noticeable difference in singular spectra between epileptic patients and normal subjects, irrespective of whether the epileptic patient was experiencing a seizure or not. Received: 3 July 2000 / Accepted in revised form: 30 October 2000     

Evidence for age-associated disinhibition of the wake drive provided by scoring principal components of the resting EEG spectrum in sleep-provoking conditions

Age-associated changes in different bandwidths of the human electroencephalographic (EEG) spectrum are well documented, but their functional significance is poorly understood. This spectrum seems to represent summation of simultaneous influences of several sleep–wake regulatory processes. Scoring of its orthogonal (uncorrelated) principal components can help in separation of the brain signatures of these processes. In particular, the opposite age-associated changes were documented for scores on the two largest (1st and 2nd) principal components of the sleep EEG spectrum. A decrease of the first score and an increase of the second score can reflect, respectively, the weakening of the sleep drive and disinhibition of the opposing wake drive with age. In order to support the suggestion of age-associated disinhibition of the wake drive from the antagonistic influence of the sleep drive, we analyzed principal component scores of the resting EEG spectra obtained in sleep deprivation experiments with 81 healthy young adults aged between 19 and 26 and 40 healthy older adults aged between 45 and 66 years. At the second day of the sleep deprivation experiments, frontal scores on the 1st principal component of the EEG spectrum demonstrated an age-associated reduction of response to eyes closed relaxation. Scores on the 2nd principal component were either initially increased during wakefulness or less responsive to such sleep-provoking conditions (frontal and occipital scores, respectively). These results are in line with the suggestion of disinhibition of the wake drive with age. They provide an explanation of why older adults are less vulnerable to sleep deprivation than young adults.