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1.
<正>"这不公平,为什么那个转学生眼镜猴上课老睡觉,考试还是第一名?"拿到考卷后,海豚忿忿不平地向蝙蝠抱怨道。作为海豚的好密友,呆萌的蝙蝠说:"可是,海豚,你上课的时候也每天都在补觉啊!""这能一样吗?我有两个脑子,一个用来睡觉,一个用来学习。睡觉只是假象!还有,眼镜猴有我的智商吗?"如果单纯按照智商来说,海豚绝对是全班最聪明的,所以它确实有资格傲视群雄。再说了,海豚和蝙蝠的好成绩背后还有个秘密武器,那就是——作弊。海豚和蝙蝠在学习上各有所长,又都擅长使用超声波,每次考试都会使点儿"非常手段",偷偷用其他人听不到的频率交流考试答案。在眼镜猴转学来之前,它们长期盘踞班里第一二名的"宝座"。可是自从眼镜猴从菲律宾转学来之后,班里的格局便发生了变化,海豚和蝙蝠只能被逼到第二三名。  相似文献   

2.
付玲 《生物物理学报》2007,23(4):314-322
大脑功能的成像检测在认知神经科学领域具有极其重要的意义。现代光子学技术的发展为认知脑成像提供了新的研究手段,在神经系统信息处理机制研究中发挥重要作用。文章介绍了在神经元、神经元网络、特定脑皮层功能构筑以及系统与行为等不同层次开展神经系统信息处理机制研究的各种光学成像技术,包括多光子激发荧光显微成像、内源信号光学成像、激光散斑成像和近红外光学成像等,并评述了这些有特色的光学成像技术在多层次获取和分析神经信息中的研究进展。  相似文献   

3.
神经递质是神经系统中至关重要的组成部分,神经递质释放的时间和空间变化是神经网络中信息处理的核心,可视化监测神经递质的生物传感器是探究各类生理和病理活动的重要工具。文中综述了近年来具有较高时间和空间分辨率的监测神经递质时空分布变化技术的研究进展,介绍了对谷氨酸、多巴胺、γ-氨基丁酸和乙酰胆碱这4类重要的神经递质的检测方法,并归纳总结了各类检测方法的基本原理和优缺点,为设计具有高时空分辨率的神经递质传感器提供一个较为系统的参考。  相似文献   

4.
本文提出了一种新的模拟生物视觉神经系统并行信息处理功能的光学方法,它采用了昆虫复眼透镜阵列处理器和非相干光源实现图像矩阵正交变换,它为光神经计算提供了一种可能实现的新途径.  相似文献   

5.
神经控制论是用控制论的数学和物理(技术)方法,研究神经系统功能的一门学科。这种研究有两方面的意义。一方面是利用控制论中比较成熟的方法对研究神经系统提供新的手段,这方面的研究对基础医学、生物学和临床医学等具有重要意义。另一方面是以生物或人的神经系统的控制及信息处理的原理作为借鉴,  相似文献   

6.
王烁  赵思宁 《化石》2006,(2):6-9
在现生生物中,具有飞行能力的动物无疑只有鸟类、昆虫和蝙蝠。翅膀是鸟类由陆地飞向天空的工具,鸟类特有的飞行运动方式足在神经系统的控制下由骨骼、肌肉和羽片共同完成的。它的结构和运动方式区别于其他两种动物的飞行器。  相似文献   

7.
漫话三叶虫     
“三叶虫”名字是怎么来的? 三百多年前的明朝崇祯年间,有一个名叫张华东的人,在山东泰安大汶口发现了一种生在石头中的怪物。他当时还不清楚这究竟是什么东西,单凭外形容貌看,颇似蝙蝠展翅,于是命名为“蝙蝠石”。直到本世纪的20年代,我国的古生物工作者才给以科学的解释和描述,指出这是三叶虫的尾部,它是生活在晚寒武世海洋中的一种节肢动物,距今已有5亿年了。为了纪念这位世界上第一个给三叶虫取的名字,因此我们也就将拉丁学名翻译为“蝙蝠石”或“蝙蝠虫”(图1)。  相似文献   

8.
《生命世界》2006,(8):9-9
马在陆地驰骋,蝙蝠在空中飞翔,一般认为这两种动物不具有相似性。但科学家日前证实,在马、牛、猪这些有蹄类动物中,马拥有独立的起源,它和蝙蝠的亲缘关系反而比同牛、猪等动物的关系更近。  相似文献   

9.
中国蝙蝠核型研究20年存在的问题与展望   总被引:2,自引:2,他引:2  
对20年来中国蝙蝠核型研究的现状进行了概述,在已有的研究中,报道了39种蝙蝠的核型,中国尚有2/3的蝙蝠种类未进行核型分析。针对以往研究论文中存在部分种类鉴定有误、图表欠准确合理和研究方法上的问题,提出了将蝙蝠核型研究与细胞分类和核型进化相结合的建议,以提高我国蝙蝠研究水平和论文质量。  相似文献   

10.
神经系统作为一个复杂的体系,在其发育过程中轴突需要延伸较长的距离才能与下一级神经元或靶细胞形成突触。在这个复杂的移动过程中,神经元轴突在空间分布上形成了精确有序的结构。过去认为这种有序结构的形成主要由形态发生素的化学浓度梯度来指导,而最近的研究发现力学因素对调控轴突的延伸速度与方向发挥着重要的作用。因此,轴突的延伸本质上是一个力化学耦合过程。本文将结合自己过去的工作论述力学因素对轴突延伸的调控机制及相关的信号转导。这一领域的研究将为认识对神经系统疾病的发生以及神经再生提供重要的参考。  相似文献   

11.
基于时间机理与部位机理整合的鲁棒性语音信号表达   总被引:1,自引:0,他引:1  
传统语音信号谱特征的提取是基于FFT 的能谱分析方法,在噪音环境情况下,对噪音的频谱成分与语音信号的频谱成分的处理采用“平均主义”的原则。也就是说噪音的频谱成分与语音信号的频谱成分占同等重要的地位。显然在噪音环境中这种处理方法会使噪音掩蔽掉语音信号的成分。在听觉系统中这种处理编码方式如同耳蜗滤波器的频率分析功能那样,也就是部位机理。实际上听觉系统对噪音和周期信号的处理不是“平均主义”原则,而是对周期信号敏感, 对噪音不敏感,听觉神经纤维通过神经脉冲发放的周期间隔来编码刺激信号, 这对应听觉处理机制中的时间编码方式。基于这两种处理机制,文中提出整合部位机理和时间机理的方法,这正是听觉的处理刺激的方式。这样处理的方法很好地结合了两种处理机制的优点,能有效地探测噪音环境中的语音信号  相似文献   

12.
Biological systems are characterized by a high number of interacting components. Determining the role of each component is difficult, addressed here in the context of biological oscillations. Rhythmic behavior can result from the interplay of positive feedback that promotes bistability between high and low activity, and slow negative feedback that switches the system between the high and low activity states. Many biological oscillators include two types of negative feedback processes: divisive (decreases the gain of the positive feedback loop) and subtractive (increases the input threshold) that both contribute to slowly move the system between the high- and low-activity states. Can we determine the relative contribution of each type of negative feedback process to the rhythmic activity? Does one dominate? Do they control the active and silent phase equally? To answer these questions we use a neural network model with excitatory coupling, regulated by synaptic depression (divisive) and cellular adaptation (subtractive feedback). We first attempt to apply standard experimental methodologies: either passive observation to correlate the variations of a variable of interest to system behavior, or deletion of a component to establish whether a component is critical for the system. We find that these two strategies can lead to contradictory conclusions, and at best their interpretive power is limited. We instead develop a computational measure of the contribution of a process, by evaluating the sensitivity of the active (high activity) and silent (low activity) phase durations to the time constant of the process. The measure shows that both processes control the active phase, in proportion to their speed and relative weight. However, only the subtractive process plays a major role in setting the duration of the silent phase. This computational method can be used to analyze the role of negative feedback processes in a wide range of biological rhythms.  相似文献   

13.
Since the discovery of steady-state visually evoked potential (SSVEP), it has been used in many fields. Numerous studies suggest that there exist three SSVEP neural networks in different frequency bands. An obvious phenomenon has been observed, that the amplitude and phase of SSVEP can be modulated by a cognitive task. Previous works have studied this modulation on separately activated SSVEP neural networks by a cognitive task. If two or more SSVEP neural networks are activated simultaneously in the process of a cognitive task, is the modulation on different SSVEP neural networks the same? In this study, two different SSVEP neural networks were activated simultaneously by two different frequency flickers, with a working memory task irrelevant to the flickers being conducted at the same time. The modulated SSVEP waves were compared with each other and to those only under one flicker in previous studies. The comparison results show that the cognitive task can modulate different SSVEP neural networks with a similar style.  相似文献   

14.
The human horizontal eye movement system produces quick, precise, conjugate eye movements called saccades. These are important in normal vision. For example, reading tasks exclusively utilize saccadic eye movements. The majority of saccades have dynamic overshoot. The amplitude of this overshoot is independent of saccadic amplitude, and is such that it places the image of the stimulus within the retinal region of maximum acuity within a minimum of time. A computer based model of the saccadic mechanisms was used to study the origin of this overshoot. It was discussed that dynamic overshoot cannot be attributed to biomechanism properites of the eye movement mechanism, but must instead be explained by variations in the controlling nervous activity. The form of this neural controller signal is very similar to that required for a time optimal response of an inertial system.  相似文献   

15.
Recently, it was found that rhythmic movements (e.g. locomotion, swimmeret beating) are controlled by mutually coupled endogeneous neural oscillators (Kennedy and Davis, 1977; Pearson and Iles, 1973; Stein, 1974; Shik and Orlovsky, 1976; Grillner and Zangger, 1979). Meanwhile, it has been found out that the phase resetting experiment is useful to investigate the interaction of neural oscillators (Perkel et al., 1963; Stein, 1974). In the preceding paper (Yamanishi et al., 1979), we studied the functional interaction between the neural oscillator which is assumed to control finger tapping and the neural networks which control some tasks. The tasks were imposed on the subject as the perturbation of the phase resetting experiment. In this paper, we investigate the control mechanism of the coordinated finger tapping by both hands. First, the subjects were instructed to coordinate the finger tapping by both hands so as to keep the phase difference between two hands constant. The performance was evaluated by a systematic error and a standard deviation of phase differences. Second, we propose two coupled neural oscillators as a model for the coordinated finger tapping. Dynamical behavior of the model system is analyzed by using phase transition curves which were measured on one hand finger tapping in the previous experiment (Yamanishi et al., 1979). Prediction by the model is in good agreement with the results of the experiments. Therefore, it is suggested that the neural mechanism which controls the coordinated finger tapping may be composed of a coupled system of two neural oscillators each of which controls the right and the left finger tapping respectively.  相似文献   

16.
Comparison of different methods of time shift measurement in EEG   总被引:3,自引:0,他引:3  
Digital signal processing techniques are often used for measurement of small time shifts between EEG signals. In our work we tested properties of linear cross-correlation and phase/coherence method. The last mentioned method was used in two versions. The first version used fast Fourier transform (FFT) algorithm and the second was based on autoregressive modeling with fixed or adaptive model order. Methods were compared on several testing signals mimicking real EEG signals. The accuracy index for each method was computed. Results showed that for long signal segments all methods bring comparably good results. Accuracy of FFT phase/coherence method significantly decreased when very short segments were used and also decreased with an increasing level of the additive noise. The best results were obtained with autoregressive version of phase/coherence. This method is more reliable and may be used with high accuracy even in very short signals segments and it is also resistant to additive noise.  相似文献   

17.
Interaction mechanisms between excitatory and inhibitory impulse sequences operating on neurons play an important role for the processing of information by the nervous system. For instance, the convergence of excitatory and inhibitory influences on retinal ganglion cells to form their receptive fields has been taken as an example for the process of neuronal sharpening by lateral inhibition. In order to analyze quantitatively the functional behavior of such a system, Shannon's entropy method for multiple access channels has been applied to biological two-inputs-one-output systems using the theoretical model developed by Tsukada et al. (1979). Here we give an extension of this procedure from the point of view to reduce redundancy of information in the input signal space of single neurons and attempt to obtain a new interpretation for the information processing of the system. The concept for the redundancy reducing mechanism in single neurons is examined and discussed for the following two processes. The first process is concerned with a signal space formed by superposing two random sequences on the input of a neuron. In this process, we introduce a coding technique to encode the inhibitory sequence by using the timing of the excitatory sequence, which is closely related to an encoding technique of multiple access channels with a correlated source (Marko, 1966, 1970, 1973; Slepian and Wolf, 1973) and which is an invariant transformation in the input signal space without changing the information contents of the input. The second process is concerned with a procedure of reducing redundant signals in the signal space mentioned before. In this connection, it is an important point to see how single neurons reduce the dimensionality of the signal space via transformation with a minimum loss of effective information. For this purpose we introduce the criterion that average transmission of information from signal space to the output does not change when redundant signals are added. This assumption is based on the fact that two signals are equivalent if and only if they have identical input-output behavior. The mechanism is examined and estimated by using a computer-simulated model. As the result of such a simulation we can estimate the minimal segmentation in the signal space which is necessary and sufficient for temporal pattern sensitivity in neurons.  相似文献   

18.
Ultrasound techniques are well suited to provide real‐time characterization of bioprocesses in non‐invasive, non‐contact, and non‐destructive low‐power consumption measurements. In this paper, a spectral analysis method was proposed to estimate time of flight (TOF) between the propagated echoes, and its corresponding speed of sound (USV). Instantaneous power spectrum distribution was used for accurate detection of echo start times, and phase shift distribution for correcting the involved phase shifts. The method was validated by reference USV for pure water at 9–30.8°C, presenting a maximum error of 0.22%, which is less than that produced by the crosscorrelation method. Sensitivity analyses indicated a precision of 6.4 × 10?3% over 50 repeated experiments, and 0.11% over two different configurations. The method was competently implemented online in a yeast fermentation process, and the calculated USV was combined with temperature and nine signal features in an artificial neural network. The network was designed by back propagation algorithm to estimate the instantaneous density of the fermentation mixture, producing a maximum error of 0.95%.  相似文献   

19.
In this contribution, the advantages of the artificial neural network approach to the identification and control of a laboratory-scale biochemical reactor are demonstrated. It is very important to be able to maintain the levels of two process variables, pH and dissolved oxygen (DO) concentration, over the course of fermentation in biosystems control. A PC-supported, fully automated, multi-task control system has been designed and built by the authors. Forward and inverse neural process models are used to identify and control both the pH and the DO concentration in a fermenter containing a Saccharomyces cerevisiae based-culture. The models are trained off-line, using a modified back-propagation algorithm based on conjugate gradients. The inverse neural controller is augmented by a new adaptive term that results in a system with robust performance. Experimental results have confirmed that the regulatory and tracking performances of the control system proposed are good.  相似文献   

20.
A neural mechanism for control of dynamics and function of associative processes in a hierarchical memory system is demonstrated. For the representation and processing of abstract knowledge, the semantic declarative memory system of the human brain is considered. The dynamics control mechanism is based on the influence of neuronal adaptation on the complexity of neural network dynamics. Different dynamical modes correspond to different levels of the ultrametric structure of the hierarchical memory being invoked during an associative process. The mechanism is deterministic but may also underlie free associative thought processes. The formulation of an abstract neural network model of hierarchical associative memory utilizes a recent approach to incorporate neuronal adaptation. It includes a generalized neuronal activation function recently derived by a Hodgkin-Huxley-type model. It is shown that the extent to which a hierarchically organized memory structure is searched is controlled by the neuronal adaptability, i.e. the strength of coupling between neuronal activity and excitability. In the brain, the concentration of various neuromodulators in turn can regulate the adaptability. An autonomously controlled sequence of bifurcations, from an initial exploratory to a final retrieval phase, of an associative process is shown to result from an activity-dependent release of neuromodulators. The dynamics control mechanism may be important in the context of various disorders of the brain and may also extend the range of applications of artificial neural networks.  相似文献   

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