大脑中的抉择神经元

近年来神经科学领域的进展表明,大脑中不仅存在如位置神经元之类的特异性编码感觉信息的神经元,也存在能够特异性地反映动物思考过程的神经元。在一系列以侧内顶叶(LIP)为目标的猕猴电生理实验中,人们发现LIP神经元的动作电位发放率可以反映抉择思考的过程。抉择的研究为我们打开了一个研究大脑高级认知功能的窗口。抉择神经元的发现表明了大脑的高级认知功能是基于与感觉信息处理类似的神经计算原理。     

海马锥体神经元树突中电压依赖性钾通道研究进展

海马锥体神经元树突上分布着多种电压依赖性钾离子通道,但这些通道在胞体和树突不同部位的分布密度以及在突触电活动中的功能意义各不相同。倒传递动作电位（b-AP）和兴奋性突触后电位（EPSP）是树突中常见的功能电信号。本文简要介绍了近年来海马锥体神经元树突上这些钾离子通道及其电活动的生理和病理学研究成果。     

胞内钙信号作用的神经模型

细胞溶质内的游离钙离子在许多细胞活动中发挥着重要的作用.对于神经元,细胞膜上的神经电信号和胞内钙离子化学信号之间有着复杂的相互作用,每个神经元都可看作为一个含有细胞膜和内质网膜的双膜系统,而神经细胞的内质网则可视为神经元内的神经元.本综述探讨了神经元膜上神经电信号与内质网钙通道释放的胞内钙信号相耦合的动力学模型.我们认...     

视觉编码的快速学习

活动依赖的神经可塑性在视觉皮层信息处理过程中起着很重要的作用。该文将讲述几个关于视觉刺激引起皮层反应发生快速变化的研究工作。在体膜片钳的实验结果表明,将视觉刺激与能够诱发孽个视皮层神经元发放动作电位的电刺激相偶联可以改变神经元的感受野特性。单电极和多电极胞外记录的实验结果显示,反复地给予自然图形电影刺激,不仅能增加视皮层神经元反应的可靠性,而且能造成之后的自发活动中存在“记忆的痕迹”。最后,用电压敏感染料成像的方法对群体细胞活动进行考察,结果提示视觉活动之后的皮层回放可能是由皮层波介导的。     

神经解剖学和神经生理学中的基本概念简述(二)

神经冲动动作电位和分级电位用最一般的话来说,神经元的机能是迅速传播和处理信息。神经元传播信息的方法有两种:神经冲动和分级电位。动作电位是神经冲动的电信号,是神经细胞膜电位的一种迅速变化,这种变化能有100毫伏的升降。一次动作电位包括高而短的锋电位和锋电位后面低而长的后电位。一般所说的动作电位实     

大鼠运动皮层神经元集群锋电位时空模式解析

在大鼠前肢压杆任务中,同步记录初级运动皮层神经元集群活动信号与压杆的压力信号,分析神经元锋电位发放的时空模式,并用于大鼠前肢运动的解析和预测.数据分析显示在压杆阶段与非压杆阶段大鼠运动皮层神经元锋电位发放模式存在着显著差别,且神经元活动变化先于前肢运动的发生约300~400ms,并可通过与行为的相关性将神经元的发放模式分为4类.研究结果同时显示,两层Elman神经网络可用于神经元集群活动的解码,解码所得到的压力值与系统所采集的压杆压力信号有较好的拟合度,二者间的相关系数可达0.8766.研究表明了运动相关的神经信息处理和表征依赖于初级运动皮层神经元的相互作用和整合,揭示了神经元集群活动在运动信息编码中的重要作用.实验结果也揭示神经元集群活动信号解析后有望用于对外部器械进行直接控制,推动植入式脑-机接口及运动重建等康复技术的发展.     

脑电事件相关去同步化和同步化的神经元群模型

利用基于丘脑-皮层网络的神经元群模型,研究被试者在某种认知状态下脑功能区的连接状态。模型包括三个模块,分别对应脑电头皮电极C3、Cz、C4记录的三个皮质区。模型外部输入包括用高斯白噪声表示的上行传入感受器信号、用直流偏移表示的皮质对丘脑的兴奋性输入、用指数衰减表示的来自脑千和前脑基底神经元的调制信号。模型输出的兴奋性神经元群的平均膜电位反映脑电记录的局部电位。改变模型输入,进行多次仿真试验并进行线性和非线性分析。研究结果显示：仿真输出信号的alpha频带功率谱有与实际脑机接口实验一致的事件相关去同步化和同步化现象;模型中功能相近的区域间有更强的耦合,随着耦合强度的增加,输出信号间的相关性和同步性均增加。     

神经元放电阈值的可变性及其意义

神经元能够将不同时空模式的突触输入转化为时序精确的动作电位输出，这种灵活、可靠的信息编码方式是神经集群在动态环境或特定任务下产生所需活动模式的重要基础。动作电位的产生遵循全或无规律，只有当细胞膜电压达到放电阈值时，神经元才产生动作电位。放电阈值在细胞内和细胞间具有高度可变性，具体动态依赖于刺激输入和放电历史。特别是，放电阈值对动作电位起始前的膜电压变化十分敏感，这种状态依赖性产生的生物物理根源包括Na⁺失活和K⁺激活。在绝大多数神经元中，动作电位的触发位置是轴突起始端，这个位置处的阈值可变性是决定神经元对时空输入转化规律的关键因素。但是，电生理实验中动作电位的记录位置却通常是胞体或近端树突，此处的阈值可变性高于轴突起始端，而其产生的重要根源是轴突动作电位的反向传播。基于胞体测量的相关研究显示，放电阈值动态能够增强神经元的时间编码、特征选择、增益调控和同时侦测能力。本文首先介绍放电阈值的概念及量化方法，然后详细梳理近年来国内外关于放电阈值可变性及产生根源的研究进展，在此基础上归纳总结放电阈值可变性对神经元编码的重要性，最后对未来放电阈值的研究方向进行展望。     

基于混沌降噪的神经元放电峰峰间期序列分析

围绕如何来消除神经元峰峰间期序列中随机噪声影响从而提取出决定不规则性的确定性动力学关系这个问题,本文首先简要介绍峰峰间期序列样本的制备,然后着重讨论一个简单可行的混沌时间序列降噪方法的原理和算法实现,最终将该方法运用到神经元放电活动数值模拟和实验记录到的峰峰间期时间序列样本分析中。本文分析结果再次证明神经放电活动中确实存在着不规则混沌运动,而且降噪结果进一步揭示了神经电生理实验中决定混沌放电的不连续但分段光滑的单峰函数关系     

大鼠大脑皮层神经元上的延迟整流型钾离子单通道

延迟整流型钾通道在动作电位的复极化和时程控制以及绝对不应期的形成中充当重要角色.本文用细胞贴附式和内面向外式膜片箝技术研究了急性分离的SD大鼠大脑皮层神经元上延迟整流型钾通道的特性和阻断剂对其的作用,对推动钾通道的研究,了解皮层神经元电活动的规律有重要意义.     

Energy coding in biological neural networks

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, we present a brand new scientific theory that offers an unique mechanism for brain information processing. We demonstrate that the neural coding produced by the activity of the brain is well described by our theory of energy coding. Due to the energy coding model’s ability to reveal mechanisms of brain information processing based upon known biophysical properties, we can not only reproduce various experimental results of neuro-electrophysiology, but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, we estimate that the theory has very important consequences for quantitative research of cognitive function.     

Mitochondrial regulation of local supply of energy in neurons

Brain computation is metabolically expensive and requires the supply of significant amounts of energy. Mitochondria are highly specialized organelles whose main function is to generate cellular energy. Due to their complex morphologies, neurons are especially dependent on a set of tools necessary to regulate mitochondrial function locally in order to match energy provision with local demands. By regulating mitochondrial transport, neurons control the local availability of mitochondrial mass in response to changes in synaptic activity. Neurons also modulate mitochondrial dynamics locally to adjust metabolic efficiency with energetic demand. Additionally, neurons remove inefficient mitochondria through mitophagy. Neurons coordinate these processes through signalling pathways that couple energetic expenditure with energy availability. When these mechanisms fail, neurons can no longer support brain function giving rise to neuropathological states like metabolic syndromes or neurodegeneration.     

Speed encoding in correlation motion detectors as a consequence of spatial structure

For animals to carry out a wide range of detection, recognition and navigation tasks, visual motion signals are crucial. The encoding of motion information has therefore, attracted much attention in the experimental and computational study of brain function. Two main alternative mechanisms have been proposed on the basis of behavioural and physiological experiments. On one hand, correlation-type and motion energy detectors are simple and efficient in the design of their basic mechanism but are tuned to temporal frequency rather than to speed. On other hand, gradient-type motion detectors directly represent an estimate of speed, but may require more demanding processing mechanisms. We demonstrate here how the temporal frequency dependence observed for sine-wave gratings can disappear for less constrained stimuli, to be replaced by responses reflecting speed for stimuli like square waves when a phase-sensitive detection mechanism is employed. We conclude from these observations that temporal frequency tuning is not necessarily a limitation for motion vision based on correlation detectors, and more generally demonstrate in view of the typical Fourier composition of natural scenes, that correlation detectors operating in such environments can encode image speed. In the context of our results, we discuss the implications of the loss of phase sensitivity inherent in using a linear system approach to describe neural processing.     

An information theoretic characterisation of auditory encoding

The entropy metric derived from information theory provides a means to quantify the amount of information transmitted in acoustic streams like speech or music. By systematically varying the entropy of pitch sequences, we sought brain areas where neural activity and energetic demands increase as a function of entropy. Such a relationship is predicted to occur in an efficient encoding mechanism that uses less computational resource when less information is present in the signal: we specifically tested the hypothesis that such a relationship is present in the planum temporale (PT). In two convergent functional MRI studies, we demonstrated this relationship in PT for encoding, while furthermore showing that a distributed fronto-parietal network for retrieval of acoustic information is independent of entropy. The results establish PT as an efficient neural engine that demands less computational resource to encode redundant signals than those with high information content.     

神经元信息编码的代谢消耗：动作电位与能量效率

人脑是一个高效、可靠的信息处理系统,它主导着个体的认知、情感、意识与行为,这些功能的实现需要不断地消耗代谢能量.大脑的能量需求主要被神经元信息编码所消耗,相应的亚细胞过程包括产生和传导动作电位、维持静息电位以及突触传递.神经元编码信息的主要载体是动作电位序列,它的产生与传导贡献了大脑的大部分代谢消耗.动作电位的能量消耗受离子通道的生物物理特性控制.生物物理特性的细胞特异性和空间异质性使得动作电位对代谢能量的利用效率呈现高度可变性,它为理解神经元代谢消耗的规律、起因与结果带来了挑战.本文首先介绍参与神经元编码的亚细胞过程及它们在大脑和小脑皮层中的代谢消耗,然后详细梳理近年来关于动作电位代谢消耗的研究成果,重点讨论影响其能量效率的生物物理因素和放电形状特性,并归纳总结放电消耗的特点,最后对未来神经元编码的代谢消耗研究进行展望.     

Imaging neural activity with temporal and cellular resolution using FISH

Immediate early genes have gained widespread use as neural activity markers in studies of brain function. The recent development of cellular compartment analysis of temporal activity, which combines sensitive fluorescence in situ hybridization and laser scanning confocal microscopy, overcomes the lack of temporal resolution of standard methodologies and allows the tracking of distinct steps in the synthesis and processing of immediate early gene RNAs. Thus, this technique provides information about when individual neurons are activated and allows the visualization, within a single brain, of different neuronal populations engaged by two distinct experiences.     

老化和精神疾病引起的皮层抑制功能变化

脑神经网络信息加工的实现方式主要依赖于兴奋性和抑制性突触连接.脑内抑制性神经元数量较少,但在信息加工和神经可塑性等方面作用极其重要,而且抑制系统失常与多种脑功能障碍有关联.脑内抑制性神经环路可粗略分为皮层内和皮层间(包括前馈和反馈)两种,分别介导同一脑区内和不同脑区间的抑制作用.本文先围绕中心-外周抑制和运动方向互斥介绍了皮层间、皮层内抑制的行为表现和作用机制,然后以老化和精神疾病为例综述了脑功能障碍与视觉系统皮层抑制功能变化间的联系,希望能对相关研究工作有所助益.     

Implications on visual apperception: Energy, duration, structure and synchronization

Although primary visual cortex (V1 or striate) activity per se is not sufficient for visual apperception (normal conscious visual experiences and conscious functions such as detection, discrimination, and recognition), the same is also true for extrastriate visual areas (such as V2, V3, V4/V8/VO, V5/M5/MST, IT, and GF). In the lack of V1 area, visual signals can still reach several extrastriate parts but appear incapable of generating normal conscious visual experiences. It is scarcely emphasized in the scientific literature that conscious perceptions and representations must have also essential energetic conditions. These energetic conditions are achieved by spatiotemporal networks of dynamic mitochondrial distributions inside neurons. However, the highest density of neurons in neocortex (number of neurons per degree of visual angle) devoted to representing the visual field is found in retinotopic V1. It means that the highest mitochondrial (energetic) activity can be achieved in mitochondrial cytochrome oxidase-rich V1 areas. Thus, V1 bear the highest energy allocation for visual representation.In addition, the conscious perceptions also demand structural conditions, presence of adequate duration of information representation, and synchronized neural processes and/or ‘interactive hierarchical structuralism.’ For visual apperception, various visual areas are involved depending on context such as stimulus characteristics such as color, form/shape, motion, and other features. Here, we focus primarily on V1 where specific mitochondrial-rich retinotopic structures are found; we will concisely discuss V2 where smaller riches of these structures are found. We also point out that residual brain states are not fully reflected in active neural patterns after visual perception. Namely, after visual perception, subliminal residual states are not being reflected in passive neural recording techniques, but require active stimulation to be revealed.     

A genetic approach to visualization of multisynaptic neural pathways using plant lectin transgene

The wiring patterns among various types of neurons via specific synaptic connections are the basis of functional logic employed by the brain for information processing. This study introduces a powerful method of analyzing the neuronal connectivity patterns by delivering a tracer selectively to specific types of neurons while simultaneously transsynaptically labeling their target neurons. We developed a novel genetic approach introducing cDNA for a plant lectin, wheat germ agglutinin (WGA), as a transgene under the control of specific promoter elements. Using this method, we demonstrate three examples of visualization of specific transsynaptic neural pathways: the mouse cerebellar efferent pathways, the mouse olfactory pathways, and the Drosophila visual pathways. This strategy should greatly facilitate studies on the anatomical and functional organization of the developing and mature nervous system.     

Power-law inter-spike interval distributions infer a conditional maximization of entropy in cortical neurons

The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI), which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously) and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE) solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates) at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains.