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。     

多通道神经元锋电位检测和分类的新方法

大脑神经元胞外单细胞动作电位(即锋电位)的检测和分类是提取神经元脉冲序列、研究神经系统信息处理机制的关键．为了提高锋电位的检出率和分类的正确性,设计了一种处理多通道锋电位记录信号的算法,用于分析微电极阵列记录的大鼠海马神经元锋电位信号,电极阵列上的测量点排列紧密,4个通道可以同时记录到来自相同神经元的信号．该算法首先利用一种多通道阈值检测法检出四通道记录信号中的锋电位,然后利用一种基于复合锋电位的主成分特征参数分类法将锋电位分类．仿真数据和实验记录信号的检验结果表明：与相应的单通道算法相比,该算法的锋电位检出率和分类的正确性显著提高,并且可以增加单次实验测得的神经元数目．因此,该算法为实现神经元锋电位的自动检测提供了一种简单有效的新 方法．     

Adaptive Social Learning Strategies in Temporally and Spatially Varying Environments

Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial??but not temporal??variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.     

Advantages and Limitations of the Use of Optogenetic Approach in Studying Fast-Scale Spike Encoding

Understanding single-neuron computations and encoding performed by spike-generation mechanisms of cortical neurons is one of the central challenges for cell electrophysiology and computational neuroscience. An established paradigm to study spike encoding in controlled conditions in vitro uses intracellular injection of a mixture of signals with fluctuating currents that mimic in vivo-like background activity. However this technique has two serious limitations: it uses current injection, while synaptic activation leads to changes of conductance, and current injection is technically most feasible in the soma, while the vast majority of synaptic inputs are located on the dendrites. Recent progress in optogenetics provides an opportunity to circumvent these limitations. Transgenic expression of light-activated ionic channels, such as Channelrhodopsin2 (ChR2), allows induction of controlled conductance changes even in thin distant dendrites. Here we show that photostimulation provides a useful extension of the tools to study neuronal encoding, but it has its own limitations. Optically induced fluctuating currents have a low cutoff (~70Hz), thus limiting the dynamic range of frequency response of cortical neurons. This leads to severe underestimation of the ability of neurons to phase-lock their firing to high frequency components of the input. This limitation could be worked around by using short (2 ms) light stimuli which produce membrane potential responses resembling EPSPs by their fast onset and prolonged decay kinetics. We show that combining application of short light stimuli to different parts of dendritic tree for mimicking distant EPSCs with somatic injection of fluctuating current that mimics fluctuations of membrane potential in vivo, allowed us to study fast encoding of artificial EPSPs photoinduced at different distances from the soma. We conclude that dendritic photostimulation of ChR2 with short light pulses provides a powerful tool to investigate population encoding of simulated synaptic potentials generated in dendrites at different distances from the soma.     

Encoding Stimulus Information by Spike Numbers and Mean Response Time in Primary Auditory Cortex

Neurons can transmit information about sensory stimuli via their firing rate, spike latency, or by the occurrence of complex spike patterns. Identifying which aspects of the neural responses actually encode sensory information remains a fundamental question in neuroscience. Here we compared various approaches for estimating the information transmitted by neurons in auditory cortex in two very different experimental paradigms, one measuring spatial tuning and the other responses to complex natural stimuli. We demonstrate that, in both cases, spike counts and mean response times jointly carry essentially all the available information about the stimuli. Thus, in auditory cortex, whereas spike counts carry only partial information about stimulus identity or location, the additional availability of relatively coarse temporal information is sufficient in order to extract essentially all the sensory information available in the spike discharge pattern, at least for the relatively short stimuli (< ∼ 100 ms) commonly used in auditory research.     

Mutual Temporal Relationships among Neuronal Spike Trains: Statistical Techniques for Display and Analysis

We describe a statistical technique, the joint peristimulus time (PST) scatter diagram, for the analysis of data from simultaneously recorded neurons subjected to repeated stimulation. Distinguishable features in the scatter diagram are related to effects of the stimulus on the observed neurons and to functional relations among the neurons. Properties of this measure and its variants are described and practical aspects of its application to experimental data are discussed.     

Concurrent Codes: A Holographic-Type Encoding Robust against Noise and Loss

Concurrent coding is an encoding scheme with ‘holographic’ type properties that are shown here to be robust against a significant amount of noise and signal loss. This single encoding scheme is able to correct for random errors and burst errors simultaneously, but does not rely on cyclic codes. A simple and practical scheme has been tested that displays perfect decoding when the signal to noise ratio is of order -18dB. The same scheme also displays perfect reconstruction when a contiguous block of 40% of the transmission is missing. In addition this scheme is 50% more efficient in terms of transmitted power requirements than equivalent cyclic codes. A simple model is presented that describes the process of decoding and can determine the computational load that would be expected, as well as describing the critical levels of noise and missing data at which false messages begin to be generated.     

Hyperexcitable Neurons Enable Precise and Persistent Information Encoding in the Superficial Retrosplenial Cortex

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Cloning and Tissue Expressional Characterization of a Full-Length cDNA Encoding Human Neuronal Protein P17.3

A full-length cDNA of 595 bp was isolated froma human fetal brain cDNA library. It contains an openreading frame encoding 153 amino acids, with an 18-bp5UTR and a 118-bp 3UTR in which there isan atypicalpolyadenylation signal (ATTAAA). The calculatedmolecular weight of the deduced protein is 17.3 kU. Thepredicted isoelectric point is 4.89. On account of itshigh homology to mouse neuronal protein NP15.6(81.2% identity), the deduced protein was namedneuronal protein 17.3 (NP17.3). When its secondarystructure was examined by the GGBSM program of PCGENEsoftware, it was found that 32.6 and 15.0% of itsamino acids are involved in formingalpha-helices and beta-sheets, respectively. Examinedwith the PESTFIND program, a typical PEST region foundin rapidly degraded proteins was found between residue48and residue 68.     

综述: 脑功能原理：神经细胞编程和信息储存

大脑采集感觉信息、整合认知和控制行为过程,这些任务的实现依赖于神经细胞及其环路的信息储存与编程.澄清神经信息编程与储存的原理是研制拟脑计算机的基础.本文将基于神经细胞的模拟-数字信号转换、数字信号兼容式输出以及新信息储存与提取等方面的研究揭示脑认知原理.     

Optimal Information Representation and Criticality in an Adaptive Sensory Recurrent Neuronal Network

Recurrent connections play an important role in cortical function, yet their exact contribution to the network computation remains unknown. The principles guiding the long-term evolution of these connections are poorly understood as well. Therefore, gaining insight into their computational role and into the mechanism shaping their pattern would be of great importance. To that end, we studied the learning dynamics and emergent recurrent connectivity in a sensory network model based on a first-principle information theoretic approach. As a test case, we applied this framework to a model of a hypercolumn in the visual cortex and found that the evolved connections between orientation columns have a "Mexican hat" profile, consistent with empirical data and previous modeling work. Furthermore, we found that optimal information representation is achieved when the network operates near a critical point in its dynamics. Neuronal networks working near such a phase transition are most sensitive to their inputs and are thus optimal in terms of information representation. Nevertheless, a mild change in the pattern of interactions may cause such networks to undergo a transition into a different regime of behavior in which the network activity is dominated by its internal recurrent dynamics and does not reflect the objective input. We discuss several mechanisms by which the pattern of interactions can be driven into this supercritical regime and relate them to various neurological and neuropsychiatric phenomena.     

Injection of Fully-Defined Signal Mixtures: A Novel High-Throughput Tool to Study Neuronal Encoding and Computations

Understanding of how neurons transform fluctuations of membrane potential, reflecting input activity, into spike responses, which communicate the ultimate results of single-neuron computation, is one of the central challenges for cellular and computational neuroscience. To study this transformation under controlled conditions, previous work has used a signal immersed in noise paradigm where neurons are injected with a current consisting of fluctuating noise that mimics on-going synaptic activity and a systematic signal whose transmission is studied. One limitation of this established paradigm is that it is designed to examine the encoding of only one signal under a specific, repeated condition. As a result, characterizing how encoding depends on neuronal properties, signal parameters, and the interaction of multiple inputs is cumbersome. Here we introduce a novel fully-defined signal mixture paradigm, which allows us to overcome these problems. In this paradigm, current for injection is synthetized as a sum of artificial postsynaptic currents (PSCs) resulting from the activity of a large population of model presynaptic neurons. PSCs from any presynaptic neuron(s) can be now considered as “signal”, while the sum of all other inputs is considered as “noise”. This allows us to study the encoding of a large number of different signals in a single experiment, thus dramatically increasing the throughput of data acquisition. Using this novel paradigm, we characterize the detection of excitatory and inhibitory PSCs from neuronal spike responses over a wide range of amplitudes and firing-rates. We show, that for moderately-sized neuronal populations the detectability of individual inputs is higher for excitatory than for inhibitory inputs during the 2–5 ms following PSC onset, but becomes comparable after 7–8 ms. This transient imbalance of sensitivity in favor of excitation may enhance propagation of balanced signals through neuronal networks. Finally, we discuss several open questions that this novel high-throughput paradigm may address.     

Discovering Precise Temporal Patterns in Large-Scale Neural Recordings through Robust and Interpretable Time Warping

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哺乳动物抗凝血酶基因的分子特征、微共线性与适应性进化

抗凝血酶(AT)是哺乳动物体内重要的天然抗凝血因子之一,它隶属于丝氨酸蛋白酶抑制物家族,主要参与并调节复杂的血凝过程。基于比较基因组学手段,共挖掘出17个哺乳动物抗凝血酶基因(AT),并剖析了它们的基因结构、微共线性、保守基序、功能结构域、以及系统进化关系。基因结构与微共线分析表明,哺乳动物AT基因具有5-12个外显子,大多数是7个外显子;不同物种AT基因所处区段之间具有较好的共线性。哺乳动物AT蛋白特征分析显示,SERPIN功能结构域与保守基序1、2、3、4、5、8和9存在相互重叠的部分。AT基因进化树揭示基因进化和通常认为的物种进化几乎一致。同时,利用PAML中Codeml的位点特异模型在AT基因中发掘了1个正选择位点328D。     

Lys842 in Neuronal Nitric-oxide Synthase Enables the Autoinhibitory Insert to Antagonize Calmodulin Binding, Increase FMN Shielding, and Suppress Interflavin Electron Transfer

Neuronal nitric-oxide synthase (nNOS) contains a unique autoinhibitory insert (AI) in its FMN subdomain that represses nNOS reductase activities and controls the calcium sensitivity of calmodulin (CaM) binding to nNOS. How the AI does this is unclear. A conserved charged residue (Lys⁸⁴²) lies within a putative CaM binding helix in the middle of the AI. We investigated its role by substituting residues that neutralize (Ala) or reverse (Glu) the charge at Lys⁸⁴². Compared with wild type nNOS, the mutant enzymes had greater cytochrome c reductase and NADPH oxidase activities in the CaM-free state, were able to bind CaM at lower calcium concentration, and had lower rates of heme reduction and NO synthesis in one case (K842A). Moreover, stopped-flow spectrophotometric experiments with the nNOS reductase domain indicate that the CaM-free mutants had faster flavin reduction kinetics and had less shielding of their FMN subdomains compared with wild type and no longer increased their level of FMN shielding in response to NADPH binding. Thus, Lys⁸⁴² is critical for the known functions of the AI and also enables two additional functions of the AI as newly identified here: suppression of electron transfer to FMN and control of the conformational equilibrium of the nNOS reductase domain. Its effect on the conformational equilibrium probably explains suppression of catalysis by the AI.     

RNA Binding Protein Rbms1 Enables Neuronal Differentiation and Radial Migration during Neocortical Development by Binding and Stabilizing the RNA Message for Efr3a

Various RNA-binding proteins (RBPs) are key components in RNA metabolism and contribute to several neurodevelopmental disorders. To date, only a few of such RBPs have been characterized for their roles in neocortex development. Here, we show that the RBP, Rbms1, is required for radial migration, polarization and differentiation of neuronal progenitors to neurons in the neocortex development. Rbms1 expression is highest in the early development in the developing cortex, with its expression gradually diminishing from embryonic day 13.5 (E13.5) to postnatal day 0 (P0). From in utero electroporation (IUE) experiments when Rbms1 levels are knocked down in neuronal progenitors, their transition from multipolar to bipolar state is delayed and this is accompanied by a delay in radial migration of these cells. Reduced Rbms1 levels in vivo also reduces differentiation as evidenced by a decrease in levels of several differentiation markers, meanwhile having no significant effects on proliferation and cell cycle rates of these cells. As an RNA binding protein, we profiled the RNA binders of Rbms1 by a cross-linked-RIP sequencing assay, followed by quantitative real-time polymerase chain reaction verification and showed that Rbms1 binds and stabilizes the mRNA for Efr3a, a signaling adapter protein. We also demonstrate that ectopic Efr3a can recover the cells from the migration defects due to loss of Rbms1, both in vivo and in vitro migration assays with cultured cells. These imply that one of the functions of Rbms1 involves the stabilization of Efr3a RNA message, required for migration and maturation of neuronal progenitors in radial migration in the developing neocortex.