基于受限玻尔兹曼机的神经元群体响应的贝叶斯解码

神经元通过尖峰模式传递有关刺激的信息,多个神经元通过突触相互联系,构成了复杂的神经回路。在过去的一个世纪中,多电极记录技术的进步使科学家们能够获取一个完整神经回路的细胞响应。这些记录表明,神经元的活动之间存在显著相关性。因此,本文提出利用受限玻尔兹曼机模型描述神经元响应活动之间的相关性,建立神经元群体响应的编码模型,并利用贝叶斯定理构建了基于受限玻尔兹曼机模型的解码器,将它应用于模拟的小鼠视觉皮层神经元的响应序列中。实验结果表明,此解码器在准确率方面优于不考虑神经元之间相关性的独立模型解码器。     

多种突触耦合的集群动力学研究

大量的生理实验证实神经系统主要存在3种不同的突触耦合方式:电突触、化学突触、电突触与化学突触共存的混合突触.但是这些突触耦合方式对神经系统的涌现动力学及其复杂性的产生机制还没有完全研究清楚.基于Wang-Buzsaki神经元所构成的兴奋性与抑制性平衡神经网络,兴奋性神经元网络满足小世界特性.当兴奋性神经元之间采用电突触耦合时,随着耦合参数的改变,兴奋性神经元群不仅能产生同步状态,也能产生不同相位共存的亚稳态;当兴奋性神经元之间采用化学突触连接时,该集团能够产生簇同步现象;当兴奋性集团存在混合突触连接时,兴奋性神经元集团不仅能产生全同步和阈下振荡同步,还产生不同频率的行波共存,呈现出激发模式的多样性.抑制性神经元群在3种突触耦合情况下,只能产生周期性的簇同步.这些结果为理解突触耦合方式对神经元激发模式和储存的多样性提供了一个可能的机制.     

神经系统信号传导的研究进展

人脑由上千亿的神经细胞组成,他们通过突触相互连接并传递信息。突触为相邻神经元之间的点状连结区域,包括有突触前膜、突触间隙和突触后膜。突触前膜可以分泌一些化学物质－神经递质（如多巴胺、去甲肾上腺素和5－羟色胺等）,这些递质通过突触间隙与突触后膜上的受体结合,将信号－神经冲动－从一个神经细胞传至另一个神经细胞,以实现神经的信号传导功能。神经系统的信号传导是学习记忆、感觉、睡眠、运动等各种脑正常的物质基础。神经系统信号的传导障碍可以引起许多神经和精神疾病,因此,神经的信号传导理论也是神经精神病理学的基础。促进或抑制神经递质的合成、分泌、调节的作用,不仅可以影响神经系统的功能,而且还可防治神经和精神性疾病。这对神经、精神系统新药的研究和开发也有着十分重要的意义。     

经颅磁声电刺激下皮层钙信号及突触传递特性的仿真与实验分析

为了探究经颅磁声电刺激(transcranial magneto-acoustic-electrical stimulation, TMAES)不同磁场强度和超声功率强度对工作记忆信息编码相关的皮层神经元钙信号及突触传递特性的影响,首先通过搭建基于磁声电效应改进的皮层锥体神经元模型,引入钙依赖神经递质释放的计算方法以计算TMAES引起的兴奋性突触后电位(excitatory postsynaptic potential, EPSP),以EPSP作为评价指标来评估不同TMAES磁场强度和超声功率强度下突触传递的短时程可塑性.随后使用光纤光度检测技术实时记录TMAES下小鼠前额叶皮层神经集群的钙信号,以揭示TMAES下钙依赖神经信息传递机制.仿真结果表明：TMAES不同磁场强度和超声功率强度对突触后响应的大小具有双向调节作用,其中,突触传递产生的短时程增强和抑制是由于TMAES下胞内钙浓度的变化引起的囊泡释放和囊泡耗竭.实验结论表明：TMAES对前额叶皮层神经元集群钙信号幅度和频率均有明显的调节作用,TMAES可以通过调节神经钙浓度进而影响突触间的信息传递.     

多电极阵列上神经元自发放电序列的时间编码

根据多电极阵列上培养的海马神经元不同自发放电模式,研究神经元发放序列的时间编码规律。采用锋电位间隔(ISI)时域图、锋电位间隔直方图(ISIH)、联合锋电位间隔分布图(JISI)对3种典型自发放电模式(爆发、持续单发、爆发与单发交替)进行时间编码分析.结果表明3种放电模式编码规律在ISI时域图中呈现分层结构,分别是两层,一层和近似三层;编码在ISIH中符合指数分布、正态分布、χ~2分布;在线性尺度JISI图中信号编码分别表现为"L"型、集聚型和伴随散点的"L"型,而对数尺度的JISI编码规律则按照三簇、一簇和四簇分布.可见ISI随时间变化能反映自发放电模式时间编码整体趋势;不同放电模式的ISIH编码规律可用数学分布函数描述;JISI可从时空角度体现放电模式的特定时间编码.     

基于提升小波的神经元锋电位并行检测方法

神经元动作电位(即锋电位)的实时检测是植入式脑—机接口系统的重要组成环节,为了能够从多通道神经微电极阵列记录的神经信号中实时地检测并提取出神经元的锋电位信息,文中提出了基于提升小波的神经元锋电位检测方法.该方法采用提升小波方法去除了神经信号中的漂移和噪声,然后通过阈值法检测出锋电位信号,最后利用现场可编程门阵列(FPG...     

忆阻器类脑神经突触的研究进展

大脑之所以能够控制人和动物的复杂生命活动,使生物体在多变的自然环境得以生存,得益于大规模神经网络中高效、快速、精准的信息传递。神经突触作为神经元之间信息传递的重要机构,保证了神经网络的高效运转,因此构建具有神经突触功能的电子突触是研究仿生系统和类脑神经网络的必经之路。研究人员尝试各种电子元件对神经突触进行模拟,其中忆阻器由于其独特的器件结构和具有“记忆特性”的电学性能,成为构建类脑神经突触的最佳选择。文章全面概述近年来忆阻器模拟神经突触的研究进展,包括忆阻器模拟神经突触的可塑性、再可塑性、非联想学习、联想学习等功能,总结了忆阻器神经突触在人工神经网络中的应用、存在的问题和挑战,并对忆阻器神经突触的研究进行展望。     

基于STDP的神经元连接电路的仿真和分析

人工神经网络是一种模仿人脑结构及其功能的信息处理系统,人工神经网络的硬件实现能充分发挥神经网络大规模并行处理的特点应用于各种工程中,并促进脑科学基础研究的进一步发展.本文实现了（integrate-and-fire,IF）神经元电路设计;完成了（spike-timing dependent plasticity,STDP）机制的电路设计;构建了基于STDP机制的神经元连接电路;分析了STDP机制对神经元连接电路放电特性的影响.研究结果表明：在基于STDP机制的神经元连接电路中,当突触前神经元和突触后神经元的脉冲尖峰具有时间上的差异时,突触权重会发生变化,且进一步影响突触后神经元的脉冲释放.     

基于一种自适应突触学习的动态相关系数与相位同步分析

本文提出了一种自适应的突触学习模型模拟了神经突触的可塑性,通过这种学习规则在定义的动态相关系数指标下发现,可以使得一般非全同随机神经网络达到同步,表明该方法具有较好的鲁棒性.为了刻画网络在整体上的相同步提出了基于Poincare截面的相位定义法,将动作电位峰值所在的位置定义为Poincare截面,进而定义同步差,网络相位同步.网络相位差计算结果显示,任意两个神经元之间的相位差随着时间变化趋于常数,即网络中任意两个神经元出现相同步,神经网络平均相位差趋于常数,神经网络出现全局的相位同步.     

两栖类交感神经节的突触传递

两栖类交感神经节广泛地用于神经生物学研究,包括突触和膜生物物理学研究．交感神经节细胞体积大,细胞的形状简单,无树突,突触位于细胞体上,神经节结构简单,但同时又具有中间神经元,在体外易于长时间存活．两栖动物交感神经节表现出多种突触后电位,包括快兴奋性突触后电位（ｆＥＰＳＰ）,慢抑制性突触后电位（ｓＩＰＳＰ）,慢兴奋性突触后电位（ｓＥＰＳＰ）,晚期慢兴奋性突触后电位（ｌｓＥＰＳＰ）,同时还表现多种突触塑性,说明该神经节具有信息存储功能,因此,两栖动物交感神经节可作为研究学习与记忆的模型系统．     

Organization of cell assemblies in the hippocampus

Neurons can produce action potentials with high temporal precision. A fundamental issue is whether, and how, this capability is used in information processing. According to the 'cell assembly' hypothesis, transient synchrony of anatomically distributed groups of neurons underlies processing of both external sensory input and internal cognitive mechanisms. Accordingly, neuron populations should be arranged into groups whose synchrony exceeds that predicted by common modulation by sensory input. Here we find that the spike times of hippocampal pyramidal cells can be predicted more accurately by using the spike times of simultaneously recorded neurons in addition to the animals location in space. This improvement remained when the spatial prediction was refined with a spatially dependent theta phase modulation. The time window in which spike times are best predicted from simultaneous peer activity is 10-30 ms, suggesting that cell assemblies are synchronized at this timescale. Because this temporal window matches the membrane time constant of pyramidal neurons, the period of the hippocampal gamma oscillation and the time window for synaptic plasticity, we propose that cooperative activity at this timescale is optimal for information transmission and storage in cortical circuits.     

Support for a synaptic chain model of neuronal sequence generation

In songbirds, the remarkable temporal precision of song is generated by a sparse sequence of bursts in the premotor nucleus HVC. To distinguish between two possible classes of models of neural sequence generation, we carried out intracellular recordings of HVC neurons in singing zebra finches (Taeniopygia guttata). We found that the subthreshold membrane potential is characterized by a large, rapid depolarization 5-10 ms before burst onset, consistent with a synaptically connected chain of neurons in HVC. We found no evidence for the slow membrane potential modulation predicted by models in which burst timing is controlled by subthreshold dynamics. Furthermore, bursts ride on an underlying depolarization of ～10-ms duration, probably the result of a regenerative calcium spike within HVC neurons that could facilitate the propagation of activity through a chain network with high temporal precision. Our results provide insight into the fundamental mechanisms by which neural circuits can generate complex sequential behaviours.     

An ultra-sparse code underlies the generation of neural sequences in a songbird

Sequences of motor activity are encoded in many vertebrate brains by complex spatio-temporal patterns of neural activity; however, the neural circuit mechanisms underlying the generation of these pre-motor patterns are poorly understood. In songbirds, one prominent site of pre-motor activity is the forebrain robust nucleus of the archistriatum (RA), which generates stereotyped sequences of spike bursts during song and recapitulates these sequences during sleep. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA. Recordings of identified HVC neurons in sleeping and singing birds show that individual HVC neurons projecting onto RA neurons produce bursts sparsely, at a single, precise time during the RA sequence. These HVC neurons burst sequentially with respect to one another. We suggest that at each time in the RA sequence, the ensemble of active RA neurons is driven by a subpopulation of RA-projecting HVC neurons that is active only at that time. As a population, these HVC neurons may form an explicit representation of time in the sequence. Such a sparse representation, a temporal analogue of the 'grandmother cell' concept for object recognition, eliminates the problem of temporal interference during sequence generation and learning attributed to more distributed representations.     

Neurotrophic regulation of synapse development and plasticity

Neurotrophic factors are traditionally thought to be secretory proteins that regulate long-tern survival and differe, ntiation of neurons. Recent studies have revealed a previously unexpected role for these factors in synaptie de velopment ami plasticity in diverse neuronal populations. Here we review experimeuts carried oul in our own laboratory in the last few years.. We have made two important discoveries.First,we were among the first to report that brain-derived. neurotrophie faclor (BDNF) facilitates hippocampal hmg-term potentiation (LTP), a form of synaptic plaslicity believed to be involved in learning and memory. BDNF modulates LTP al CAI synapses by enhaneing synaptic responses to high frequency, tetanic slimulalion. This is achieved primafily by facilitating synaptie vesicle doeking, possibly due to an in crease in the levels of the vesicle prolein synaptobrevin and synaptoplysin in the nerve terminals. Gene knockout study demonstrates thai the effects of BDNF are primarily mediated through presynaptic mechanisms. Second, we demonstrated a form of long-term, neurotrophin-mediated synaptic regulation. We showed that long-term treatment of the neuromuscu lar synapses with neurotrophin-3 (NT3) resulted in an enhancement of both spontaneous and evoked synaptic currcuts, as well as profound changes in thc number of synaptic varicosities and syuaptic vesicle proteins in motoneurons, all of which are indicative of more mature synapses. Our current work addresses the following issues:(i) activity-dependent trafficking of neurotrophin receptors, and its role in synapse-specific modulation; (ii) signal transduction mechanisms medialing the acute enhancement of synaplic transmission by neurotrophins; (iii) acute and long-tenn synaptie actions of the GDNF family; (iv) role of BDNF in late-phase LTP and in the development of hippocampal circuit.     

Spike-timing-dependent synaptic modification induced by natural spike trains

The strength of the connection between two neurons can be modified by activity, in a way that depends on the timing of neuronal firing on either side of the synapse. This spike-timing-dependent plasticity (STDP) has been studied by systematically varying the intervals between pre- and postsynaptic spikes. Here we studied how STDP operates in the context of more natural spike trains. We found that in visual cortical slices the contribution of each pre-/postsynaptic spike pair to synaptic modification depends not only on the interval between the pair, but also on the timing of preceding spikes. The efficacy of each spike in synaptic modification was suppressed by the preceding spike in the same neuron, occurring within several tens of milliseconds. The direction and magnitude of synaptic modifications induced by spike patterns recorded in vivo in response to natural visual stimuli were well predicted by incorporating the suppressive inter-spike interaction within each neuron. Thus, activity-induced synaptic modification depends not only on the relative spike timing between the neurons, but also on the spiking pattern within each neuron. For natural spike trains, the timing of the first spike in each burst is dominant in synaptic modification.     

Detection of bursts in neuronal spike trains by the mean inter-spike interval method

Bursts are electrical spikes firing with a high frequency, which are the most important property in synaptic plasticity and information processing in the central nervous system. However, bursts are difficult to identify because bursting activities or patterns vary with physiological conditions or external stimuli. In this paper, a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains, without any arbitrary choices or any operator judgment. When the mean value of several successive inter-spike intervals is not larger than the parameter, a burst is identified. By this method, bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays, as accurately as by visual inspection. Furthermore, significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.     

氧化锌/氧化钽双介质层忆阻器的突触特性分析

人工突触的开发是模拟人脑功能的关键。忆阻器由于具备独特的电阻记忆行为,在人工突触研究领域得到广泛的关注。氧化钽和氧化锌均是优良的忆阻器材料,鉴于有关ZnO/TaOx双介质忆阻器突触特性的研究较少,本文将氧化锌介质层引入Ti/TaOx/ITO忆阻器中拟改善其突触性能。研究发现,器件Ti/ZnO/TaOx/ITO在功耗和电导调制线性度方面皆有改善,并有着电阻渐变的行为,利于器件突触功能的实现及应用。为此对Ti/ZnO/TaOx/ITO双介质层器件进行了电压脉冲训练,并成功模拟了学习饱和、经验学习以及短时程记忆向长时程记忆转变等生物突触行为。     

Motor learning in a recurrent network model based on the vestibulo-ocular reflex.

Most models of neural networks have assumed that neurons process information on a timescale of milliseconds and that the long-term modification of synaptic strengths underlies learning and memory. But neurons also have cellular mechanisms that operate on a timescale of tens or hundreds of milliseconds, such as a gradual rise in firing rate in response to injection of constant current or a rapid rise followed by a slower adaptation. These dynamic properties of neuronal responses are mediated by ion channels that are subject to modulation. We demonstrate here how a neural network with recurrent feedback connections can convert long-term modulation of neural responses that occur over these intermediate timescales into changes in the amplitude of the steady output from the system. This general principle may be relevant to many feedback systems in the brain. Here it is applied to the vestibulo-ocular reflex, whose amplitude is subject to long-term adaptive modification by visual inputs. The model reconciles apparently contradictory data on the neural locus of the cellular mechanisms that mediate this simple form of learning and memory.     

基于人工神经网络的低信噪比神经元锋电位分类

基于人工神经网络和模板匹配,提出了对低信噪比神经元信号分类的方法.首先对待分类信号进行阈值检测,获得尖峰信号,对这些尖峰信号进行主成分分析,再选取主成分进行聚类,根据聚类结果,取对应的尖峰信号作为人工神经网络的训练样本.网络测试和结合模板匹配识别叠加信号的仿真结果表明了该方法的优越性.