大鼠慢波睡眠和睡眠过渡期脑电信号的小波变换分析

EEG信号经常包含许多快速的时变信息 ,将较长时间段的EEG信号近似看作平稳信号 ,进行FFT谱估计 ,存在其局限性。应用多分辨率小波变换方法 ,在频域和时域上可以同时定位分析大鼠慢波睡眠和睡眠过渡期脑电的动态变化特性。采用慢性埋植电极记录自由活动大鼠的皮层脑电 ,将信号用小波变换分解成δ、θ、α和 β四个分量 ,求各分量的功率和功率百分比的时间变化曲线 ,并与FFT功率谱分析结果进行比较。结果表明 :慢波睡眠期EEG中有 2 6 .2 %± 7.7%的时间段上δ分量功率小于总功率的 5 0 % ,且δ分量较大时 ,其他分量较小 ;δ分量较小时 ,其他分量较大 ,差别显著。此结果揭示了δ节律与θ和α节律之间的一种互补关系。而传统的FFT功率谱分析方法只能显示δ分量为主 (占总功率 70 .6 %± 6 .4 % )的功率谱 ,不能提供时变信息。对于睡眠过渡期的非稳态EEG信号 ,利用小波变换分解得到的θ和α分量可以鉴别出睡眠纺锤波 ,计算睡眠纺锤波的平均持续时间 ,并比较纺锤波和非纺锤波时期各个频谱分量的变化情况。由此可见 ,小波变换可用于计算新的EEG时频定量分析指标用于分析生理、病理和药理作用引起的睡眠EEG的变化过程 ,以弥补传统FFT功率谱分析的不足之处     

小波能量评价EEG的不同成分对癫痫发作预报的价值

癫痫是一种严重危害人类健康的常见疾病,对癫痫发作进行预报具有重要的重要意义。通过对3例部分性继发全身性发作的癫痫病人在发作最长约30min的8导EEG进行小波分解,将EEG中的棘波、尖波成分与慢波成分分别突出到不同的尺度上,并计算相应尺度上这些成分的能量,考察这些不同成分在发作前的变化趋势。发现在发作前的若干分钟,8导EEG的慢波能量都有显著增大,而与棘波／尖波有关的快波能量基本上没有什么变化趋势,说明EEG慢波成分的增大对部分性继发全身性发作的预报具有重要价值,EEG的“慢波过大”可能是癫痫从发作间状态转变为发作的重要因素。     

家鸽不同状态下脑电节律特异性分析

人类大脑神经电活动的不同节律与不同的状态有关,而其他物种如鸟类不同状态下脑信号的节律特异性尚不明确。本文通过分析家鸽(Columbaliviadomestica)在麻醉昏迷、清醒安静、自由探索三种典型状态下的局部场电位(LFP)信号,研究家鸽不同意识状态下神经电活动的节律特异性。首先采集不同状态下的LFP信号,提取δ(1～4 Hz)、θ(4～8 Hz)、α(8～12 Hz)、β(15～30 Hz)、γ(30～60 Hz)五个节律;然后使用小波变换进行时频分析,通过统计时频图的定性观察和小波能量的统计分析,使用Friedman检验进行统计假设检验,研究各状态不同节律的特异性,并基于样本熵分析信号复杂度,探索产生这种节律特异性的可能原因。结果表明,随着意识越来越清晰,较低频的δ、θ、α节律受到明显抑制(P 0.001),而较高频的γ节律活动明显增强(P 0.001);样本熵的分析表明,这可能是由于节律频带越高,信号样本熵越大,对应了从麻醉、清醒到自由探索意识清晰程度的提高。家鸽不同状态下神经电活动节律特异性的研究,有助于增进对不同物种脑信号节律编码机制的理解。     

基于替代数据思想的复杂度归一化方法及其在心电信号分析中的应用

基于替代数据(Surrogate)思想的复杂度归一化方法,克服了一般复杂度对信号采样长度与采样频率的敏感性。文章对在生物医学信号复杂度分析中最有潜在应用价值的近似熵和C0复杂度进行了归一化。应用该方法可以有效地反映人体心脏某些病理状态之间的差别。同时,通过比较各种复杂度指标发现,C0复杂度和近似熵对采样长度的敏感性最弱,适用于短数据量的信号分析。     

局灶性脑缺血损伤无创检测中EEG近似熵研究

局灶性脑缺血的早期无创诊断在临床实际中有着非常重要的意义。采用SD（Sparague-Dawley)大鼠建立了局灶性脑缺血的动物实验模型,记录了缺血前后缺血区域和正常区域的脑电信号EEG。由于近似熵复杂度算法所需时间序列长度较短,大大减少了脑电信号非平稳所带来的困难,且无需粗粒化,采用近似熵对局灶性缺血动物实验模型的脑电信号的复杂度进行了分析。结果发现缺血前后缺血与非缺血区域的近似熵均有着易于区分的特征,因此EEG信号的近似熵分析可以用于对局灶性缺血的脑损伤程度进行诊断,并区分损伤区域和非损伤区域,有望在临床中加以应用。     

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     

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。     

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。     

用近似熵测量神经放电峰峰间期的复杂性

近似熵是用来测量信号复杂程度的非线性方法。为了研究神经放电序列的复杂性,用该方法及其改进方法对大鼠损伤坐崩神经模型、大鼠脑薄片视上核神经元自发放电模型、背根节自发放电模型峰峰间期以及Rose-Hindmarsh理论神经元模型分叉数据进行了动态测量。结果表明,近似熵可以定量反映多种神经放电序列复杂性的变化,是一种较为有效的复杂性序量方法。     

一种改进的近似熵——样品熵及其在颞叶癫痫患者脑电信号分析中的应用

采用了近似熵(approximately entropy,ApEn)和它的改进算法,即样品熵(sample entropy,SampEn)分析了8位颞叶癫痫患者和10位健康人员的短程脑电信号。在计算过程中使用了两种滑动窗口和5个不同的过滤标准r。结果显示颞叶癫痫患者组脑电信号的熵值显著低于健康组,而且患者癫痫病灶所在的脑半球的复杂度远远小于非癫痫病灶的脑半球。小的滑动窗口能更多地反映与癫痫发作相关的细节。对于1秒的滑动窗口,过滤标准r不能小于时间序列标准差的0．15％;而对于4秒的滑动窗口,则过滤标准r不能小于时间序列标准差的10％。研究结果表明,在短程脑电信号的非线性分析中,样品熵是一种比近似熵更为可靠的非线性分析方法。颞叶癫痫患者脑电信号的熵值低于健康人员,这可能表明脑电活动的非线性程度的降低是由于神经信号在大脑内的传递受到了阻碍或者损坏,使得神经信号成了相对孤立的信息源。     

Calculation of entropy change accompanying growth of Escherichia coli K-12 on succinic acid

The ΔS of one unit carbon formula weight of Escherichia coli K-12 cells, when grown on succinic acid, was calculated to be ?80.13 J/deg. This value could then be used to calculate the entropy change accompanying the anabolism and metabolism of succinic acid to be 30.82 J/deg and 32.40 J/mol deg, respectively. The entropy of one unit carbon formula weight of dried E. Coli K-12 cells is calculated to be 94.40 J/deg, which when divided by the mass of these cells becomes 3.90 J/g deg. The corresponding entropy of succinic acid is 2.77 J/g deg, making it apparent that the entropy per unit mass of the cells is greater than that of the substrate. It might be thought that because the cells appear to be so much more complex than the substrate, the cells should have a lesser entropy per unit mass than the substrate. That this does not appear to be true leads to the conclusion that the macromolecular organization (informational content?) of the cells contributes only in a very minor way to the total physical entropy of cells. © 1993 John Wiley & Sons, Inc.     

亚热带森林转换对土壤微生物呼吸及其熵值的影响

土壤微生物呼吸及其熵值是表征土壤质量变化的敏感性指标,不仅能衡量土壤微生物碳利用效率,还能揭示土壤有机碳的变化。通过比较亚热带米槠天然林转换为马尾松人工林和杉木人工林后土壤微生物呼吸速率、土壤微生物生物量碳以及微生物熵、代谢熵的差异,研究亚热带森林转换对土壤微生物碳利用效率的影响。研究结果显示:(1)与天然林相比,马尾松人工林0—10 cm土壤微生物呼吸速率上升32%(P0.05),马尾松人工林和杉木人工林10—20 cm土壤微生物呼吸速率分别下降26%和24%(P0.05);但在20—40 cm土层和40—60 cm土层,天然林土壤微生物呼吸速率比马尾松人工林分别高50%和43%;(2)马尾松人工林和杉木人工林0—10 cm土层土壤微生物生物量碳(MBC)比天然林分别下降19%和40%(P0.05),但马尾松人工林10—20 cm土壤MBC上升29%(P0.05);(3)人工林表层土壤微生物熵与天然林没有显著差异,但与天然林相比,杉木人工林和马尾松人工林20—40 cm土层土壤微生物熵分别下降51%和71%(P0.05),40—60 cm分别下降52%、66%(P0.05)。土壤微生物代谢熵的变化主要发生在0—10 cm土层,马尾松人工林和杉木人工林分别比天然林增加38%和29%(P0.05),在深层土壤,3种林分微生物代谢熵没有显著差异。亚热带森林转换导致表层土壤微生物碳利用效率下降,深层土壤易分解碳在总有机碳库中占比下降,有机碳可利用程度降低。     

Entropy in biological binding processes: Estimation of translational entropy loss

The loss of translational degrees of freedom makes an important, unfavorable contribution to the free energy of binding. Examination of experimental values suggest that calculation of this entropy using the Sackur–Tetrode equation produces largely overestimated values. Better agreement is obtained using the cratic entropy. Theoretical considerations suggest that the volumes available for the movement of a ligand in solution and in a complex are rather similar, suggesting also that the cratic entropy provides the best estimate of the loss of translational entropy. © 1994 John Wiley & Sons, Inc.     

An automatic image registration scheme using Tsallis entropy

We have investigated the registration of mammograms based on the Tsallis entropy using mutual information measure. Tsallis entropy has one more parameter ‘q’ and the values of ‘q’ decide the quality of the registration. Existing Tsallis entropy based algorithms are not automatic as they claimed to be. In this article, an automatic affine image registration based on Tsallis entropy is proposed and its performance is analyzed for clinically acquired mammograms for globally registering them. The accuracy is compared with traditionally used mutual information and normalized mutual information based on Shannon entropy. Our algorithm shows promising results with increased accuracy with reduction in number of evaluations. Further, the need for pre-registration in mammogram is discussed in detail. Through this experiment, it is found that the proposed algorithm is effective enough to replace Shannon and existing Tsallis entropy based affine registration schemes.     

Changes of human movement complexity during maturation: quantitative assessment using multiscale entropy

Movement complexity can be defined as the capability of using different strategies to accomplish a specific task and is expected to increase with maturation, reaching its highest level in adulthood.Multiscale Entropy (MSE) has been proposed to estimate complexity on different kinematic signals, at different time scales. When applied on trunk acceleration data during natural walking (NW) at different ages, MSE decreased from childhood to adulthood, apparently contradicting the premises. On the contrary, authors hypothesised that this decrease was dependent on the specific task analysed and resulted from the concurrent increase in gait automaticity.This work aims to test this hypothesis, applying MSE on a non-paradigmatic task (tandem walking, TW), in order to exclude aspects related to automaticity.MSE was estimated on trunk acceleration data, collected on children, adolescents, and young adults during TW and NW. As hypothesized, MSE increased significantly with age in TW and decreased in NW on the sagittal plane. Assuming the development of complexity in TW as reference, MSE in NW showed a reduction to half of the complexity of TW with maturation on the sagittal plane. These results indicate MSE as sensitive to differences in performance due to maturation and to expected changes in complexity related to the specific performed task.     

最大信息熵原理与群体遗传平衡

建立了用最大信息熵原理推导群体遗传平衡定律的统一数学模型,并给出了模型的统一解,此解正是Hardy-Weinberg定律所给出的平衡群体的基因型频率,说明当群体信息熵达到最大时,群体基因型频率不再变化,即达到“平衡”。这证明了最大熵分布就是Hardy-Weinberg平衡分布。Hardy-Weinberg平衡定律与最大信息熵原理的内在一致性说明,杂交和随机交配是一个不可逆过程,使群体基因型信息熵增大,无序性增,是选择和近亲交配使群体的信息熵降低,有序性增加,育种过程实际就是调节群体信息熵的过程。过程信息熵的含义是表示一个概率分布的不确定性,最大熵原理意味着在一定的约束条件,选择具有最大不确定性的分布,从而其分布是最为随机的。最大熵原理在信息,工程,天文,地理,图像处理,模式识别等自然科学和社会科学领域都有广泛的成功应用,本文从群体遗传学角度证明了这一原理具有普遍适用性。熵是描述系统状态的函数,而最大熵原理则表明了系统发展变化的趋势,系统的最终状态必然是熵增加至最大值的状态,对于任何系统都是如此。因此,群体遗传系统的平衡定律可以统一用最大熵原理进行判定和描述;任意群体的基因型信息熵在随机交配世代传递时有不断增加的趋势;在一定约束条件下基因型信息熵达到最大值时,就称之为达到遗传平衡。本文将信息论原理应用于群体遗传学研究,揭示了基因信息熵的生物学意义,并表明可以用信息学和控制论的原理和方法来研究群体遗传学问题。     

关于最大信息熵原理与群体遗传平衡一致性的探讨

汪小龙等建立了用最大信息熵原理推导一个基因座上群体遗传平衡的统一数学模型,并给出了模型的最大值解,此解正是Hardy-Weinberg平衡定律所给出的基因型频率。这说明当群体基因型信息熵最大时,群体基因型频率不再变化,达到平衡状态,从而证明了最大信息熵原理与Hardy-Weinberg平衡定律具有一致性,同时指出这一结论可以推广至有迁移、突变、选择、遗传漂变、近亲交配的群体以及多个基因座情形。概括地说就是：最大信息熵原理与群体遗传平衡具有一致性。但是,他们仅仅证明了最大信息熵原理与一个基因座上Hardy-Weinberg平衡定律具有一致性,本文在这个范围内将其推广至多个基因座,且每一个基因座均为复等位基因情形。至于最大信息熵原理是否与其它的群体遗传平衡具有一致性,他们的结论仅仅是猜想,并未严格推导。事实上,要想将这种一致性推广到迁移、突变、随机漂变和近亲交配等群体,则不见得正确。      

Deep Learning Using Havrda-Charvat Entropy for Classification of Pulmonary Optical Endomicroscopy

1) ObjectivePulmonary optical endomicroscopy (POE) is an imaging technology in real time. It allows to examine pulmonary alveoli at a microscopic level. Acquired in clinical settings, a POE image sequence can have as much as 25% of the sequence being uninformative frames (i.e. pure-noise and motion artifacts). For future data analysis, these uninformative frames must be first removed from the sequence. Therefore, the objective of our work is to develop an automatic detection method of uninformative images in endomicroscopy images.2) Material and methodsWe propose to take the detection problem as a classification one. Considering advantages of deep learning methods, a classifier based on CNN (Convolutional Neural Network) is designed with a new loss function based on Havrda-Charvat entropy which is a parametrical generalization of the Shannon entropy. We propose to use this formula to get a better hold on all sorts of data since it provides a model more stable than the Shannon entropy.3) ResultsOur method is tested on one POE dataset including 3895 distinct images and is showing better results than using Shannon entropy and behaves better with regard to the problem of overfitting. We obtain 70% of accuracy with Shannon entropy versus 77 to 79% with Havrda-Charvat.4) ConclusionWe can conclude that Havrda-Charvat entropy is better suited for restricted and or noisy datasets due to its generalized nature. It is also more suitable for classification in endomicroscopy datasets.     

Functional co-evolutionary study of glucosamine-6-phosphate synthase in mycoses causing fungi

Invasive fungal opportunistic infections or mycoses have been on the rise with increase in the number of immuno-compromised patients accounting for associated high morbidity and mortality rates. The antifungal drugs are not completely effective due to increased resistance and varied susceptibility of fungi. Hence, the functional diversification study of novel targets has to be carried out. The enzyme glucosamine-6-phosphate synthase [EC 2.6.1.16], a novel drug target, catalyzes the rate-limiting step of the fungal cell-wall biosynthetic pathway, comprising four conserved domains, two glutaminase and sugar-isomerising (SIS) domains with active site. The amino acids within these domains tend to mutate simultaneously and exert mutual selective forces which might result in untoward fungal adaptations that are fixed through random genetic drift over time. The current study is an attempt to investigate such 'non-independent' coevolving residues which play critical functional and structural role in the protein. Residues with Shannon entropy ≦1 (calculated by the Protein Variability Server) were considered and subsequently, positional correlations were estimated by InterMap3D 1.3 server. It was observed that majority of coevolving pairs of first SIS domain involved interactions with hydrophobic leucine and found to be spatially coupled in 3-dimensional structure of the enzyme. The coevolving groups of Aspergillus niger and Rhizopus oryzae species might play a role in drug resistance. Such coevolutionary analysis is important for understanding the receptor-ligand interactions and effective drug designing.