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年徐京华等人应用的算法,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、２）的变化规律进行了比较分析,ＫＣ与Ｃ１的变化相一致。从安静睁眼到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。     

澳大利亚三种Callitris植物的核型及其系统学意义

对澳大利亚特产的Ｃａｌｌｉｔｒｉｓ属植物Ｃ．ｐｒｅｉｓｓｉｉ,Ｃ．ｖｅｒｒｕｃｏｓａ,Ｃ．ｅｎｄｌｉｃｈｅｒｉ（柏科）的核型进行了分析,后２种的为首次报道。它们的核型公式分别为Ｋ（２ｎ）＝２２＝２２ｍ（２ＳＡＴ）,２２ｍ（２ＳＡＴ）和２２ｍ（６ＳＡＴ）,均属１Ａ核型类型。染色体相对长度组成同是２ｎ＝２２＝１０Ｍ＿２＋１２Ｍ＿１该３种及其他８种Ｃａｌｌｔｒｉｓ属植物一致的核型Ｋ（２ｎ）＝２２ｍ和１Ａ类型的通常被认为是最对称和原始的。因此该属在柏科的系统发育上也许处于相当原始的地位。     

脉冲电场对鸡胚脑细胞Ca~(2 )和cAMP含量的影响

利用ｆｕｒａ－２／ＡＭ荧光方法和放射免疫方法分别研究了脉冲电场对１１天和１４天胚龄的悬浮鸡胚脑细胞内Ｃａ２＋和环腺苷酸（ｃＡＭＰ）含量的影响,并探讨了在脉冲电场作用下这两种信号物质变化的相关性。实验结果表明：当电激液中［Ｃａ２＋］为１ｍｍｏｌ／Ｌ时,在宽度为１００微秒．强度为０．５,１．０,２．０ｋＶ／ｃｍ的脉冲电场作用下,１１天胚龄的鸡胚脑细胞内钙离子浓度（以［Ｃａ２＋］ｉ表示）与对照相比显著上升,其升高值随着脉冲强度的增加而增加,而细胞内ｃＡＭＰ含量与对照相比显著降低;用ＥＧＴＡ络合电激液中游离Ｃａ２＋以后,虽然细胞内［Ｃａ２＋］ｉ显著上升,细胞内ｃＡＭＰ含量没有显著变化。１４天胚龄的鸡胚脑细胞内［Ｃａ２＋］ｉ在脉冲电场作用下显著上升,而细胞内ｃＡＭＰ含量没有显著变化。脉冲电场对１１天和１４天胚龄的鸡胚脑细胞膜和细胞内Ｃａ２＋库Ｃａ２＋转移系统的开放均有显著作用,此作用具有对脉冲强度的依赖性。为了解物理信号跨细胞膜传导的方式提供了初步的实验根据     

中国红豆杉属和白豆杉属的核形态学研究

报道了红豆杉属Ｔａｘｕｓ３种１变种及白豆杉属Ｐｓｅｕｄｏｔａｘｕｘ １种的核形态结构２,啼杉属３种１变种和白豆杉的间期核要形都为复杂染色中心型,前期染色体属于中间型,体细胞中期染色体分别为：（１）红豆杉Ｔａｘｕｘ ｃｈｉｎｅｎｓｉｓ Ｒｅｈｄ ．Ｋ＝２４＝２０ｍ＋２ｓｍ＋２Ｔ,着丝点端化值为５８．２２％;（２）南方啼杉Ｔ．ｃｈｉｎｅｎｓｉｓ Ｒｅｈｄ ｖａｒ．ｍａｉｒｅｉ Ｃｈｅｎｇ ｅｔ Ｌ．Ｋ     

脉冲电场对鸡胚脑细胞Ca~(2+)和cAMP含量的影响

利用ｆｕｒａ－２／ＡＭ荧光方法和放射免疫方法分别研究了脉冲电场对１１天和１４天胚龄的悬浮鸡胚脑细胞内Ｃａ２＋和环腺苷酸（ｃＡＭＰ）含量的影响,并探讨了在脉冲电场作用下这两种信号物质变化的相关性。实验结果表明：当电激液中［Ｃａ２＋］为１ｍｍｏｌ／Ｌ时,在宽度为１００微秒．强度为０．５,１．０,２．０ｋＶ／ｃｍ的脉冲电场作用下,１１天胚龄的鸡胚脑细胞内钙离子浓度（以［Ｃａ２＋］ｉ表示）与对照相比显著上升,其升高值随着脉冲强度的增加而增加,而细胞内ｃＡＭＰ含量与对照相比显著降低;用ＥＧＴＡ络合电激液中游离Ｃａ２＋以后,虽然细胞内［Ｃａ２＋］ｉ显著上升,细胞内ｃＡＭＰ含量没有显著变化。１４天胚龄的鸡胚脑细胞内［Ｃａ２＋］ｉ在脉冲电场作用下显著上升,而细胞内ｃＡＭＰ含量没有显著变化。脉冲电场对１１天和１４天胚龄的鸡胚脑细胞膜和细胞内Ｃａ２＋库Ｃａ２＋转移系统的开放均有显著作用,此作用具有对脉冲强度的依赖性。为了解物理信号跨细胞膜传导的方式提供了初步的实验根据     

青藏高原毛茛科3种特有植物核型和进化研究

对青藏高原高山冰缘地区毛茛科３种特有植物的核型进行了分析。它们的核型公式（Ｋ）、染色体相对长度组成（Ｃ．Ｒ．Ｌ．）和核型不对称系数（Ａｓ．Ｋ％）分别为：青藏金莲花Ｔｒｏｌｉｕｓｐｕｍｉｌｕｓｖａｒ．ｔａｎｇｕｔｉｃｕｓ：Ｋ（２ｎ）＝６ｍ＋８ｓｍ（２ＳＡＴ）＋２ｓｔ,Ｃ．Ｒ．Ｌ．＝４Ｌ＋４Ｍ２＋４Ｍ１＋４Ｓ,Ａｓ．Ｋ％＝６３．５７,核型属２Ｂ型;甘青乌头Ａｃｏｎｉｔｕｍｔａｎｇｕｔｉｃｕｍ为Ｋ（２ｎ）＝６ｍ＋１０ｓｍ,Ｃ．Ｒ．Ｌ．＝４Ｌ＋８Ｍ１＋４Ｓ,Ａｓ．Ｋ％＝６２．５４,２Ｂ型;单花翠雀花Ｄｅｌｐｈｉｎｉｕｍｃａｎｄｅｌａｂｒｕｍｖａｒ．ｍｏｎａｎｔｈｕｍ为Ｋ（２ｎ）＝６ｍ＋８ｓｍ＋２ｓｔ,Ｃ．Ｒ．Ｌ．＝４Ｌ＋４Ｍ２＋４Ｍ１＋６Ｓ,Ａｓ．Ｋ％＝６４．３４,属３Ｂ型。经同相关近缘种核型资料比较,青藏金莲花核型不对称性和进化程度比金莲花Ｔ．ｃｈｉｎｅｎｓｉｓ低;甘青乌头的核型不对称性和进化程度在其近缘类群（乌头组Ｓｅｃｔ．Ａｃｏｎｉｔｕｍ）已报道的种之内最低;单花翠雀花核型不对称性和进化水平比翠雀组（Ｓｅｃｔ．Ｄｅｌｐｈｉｎａｓｔｒｕｍ）已报道的展毛翠雀花Ｄ．ｋａｍａｏｅｎｓｅｖａｒ．ｇｌａｂｒｅｓｃｅｎｓ、     

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.