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.     

Odour-plume dynamics influence the brain's olfactory code

The neural computations used to represent olfactory information in the brain have long been investigated. Recent studies in the insect antennal lobe suggest that precise temporal and/or spatial patterns of activity underlie the recognition and discrimination of different odours, and that these patterns may be strengthened by associative learning. It remains unknown, however, whether these activity patterns persist when odour intensity varies rapidly and unpredictably, as often occurs in nature. Here we show that with naturally intermittent odour stimulation, spike patterns recorded from moth antennal-lobe output neurons varied predictably with the fine-scale temporal dynamics and intensity of the odour. These data support the hypothesis that olfactory circuits compensate for contextual variations in the stimulus pattern with high temporal precision. The timing of output neuron activity is constantly modulated to reflect ongoing changes in stimulus intensity and dynamics that occur on a millisecond timescale.     

Correlation between neural spike trains increases with firing rate

Populations of neurons in the retina, olfactory system, visual and somatosensory thalamus, and several cortical regions show temporal correlation between the discharge times of their action potentials (spike trains). Correlated firing has been linked to stimulus encoding, attention, stimulus discrimination, and motor behaviour. Nevertheless, the mechanisms underlying correlated spiking are poorly understood, and its coding implications are still debated. It is not clear, for instance, whether correlations between the discharges of two neurons are determined solely by the correlation between their afferent currents, or whether they also depend on the mean and variance of the input. We addressed this question by computing the spike train correlation coefficient of unconnected pairs of in vitro cortical neurons receiving correlated inputs. Notably, even when the input correlation remained fixed, the spike train output correlation increased with the firing rate, but was largely independent of spike train variability. With a combination of analytical techniques and numerical simulations using 'integrate-and-fire' neuron models we show that this relationship between output correlation and firing rate is robust to input heterogeneities. Finally, this overlooked relationship is replicated by a standard threshold-linear model, demonstrating the universality of the result. This connection between the rate and correlation of spiking activity links two fundamental features of the neural code.     

Spatio-temporal correlations and visual signalling in a complete neuronal population

Statistical dependencies in the responses of sensory neurons govern both the amount of stimulus information conveyed and the means by which downstream neurons can extract it. Although a variety of measurements indicate the existence of such dependencies, their origin and importance for neural coding are poorly understood. Here we analyse the functional significance of correlated firing in a complete population of macaque parasol retinal ganglion cells using a model of multi-neuron spike responses. The model, with parameters fit directly to physiological data, simultaneously captures both the stimulus dependence and detailed spatio-temporal correlations in population responses, and provides two insights into the structure of the neural code. First, neural encoding at the population level is less noisy than one would expect from the variability of individual neurons: spike times are more precise, and can be predicted more accurately when the spiking of neighbouring neurons is taken into account. Second, correlations provide additional sensory information: optimal, model-based decoding that exploits the response correlation structure extracts 20% more information about the visual scene than decoding under the assumption of independence, and preserves 40% more visual information than optimal linear decoding. This model-based approach reveals the role of correlated activity in the retinal coding of visual stimuli, and provides a general framework for understanding the importance of correlated activity in populations of neurons.     

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.     

Noradrenaline and serotonin selectively modulate thalamic burst firing by enhancing a hyperpolarization-activated cation current

Neurons in many regions of the mammalian nervous system generate action potentials in two distinct modes: rhythmic oscillations in which spikes cluster together in a cyclical manner, and single spike firing in which action potentials occur relatively independently of one another. Which mode of action potential generation a neuron displays often varies with the behavioural state of the animal. For example, the shift from slow-wave sleep to waking and attentiveness is associated with a change in thalamic neurons from rhythmic burst firing to repetitive single spike activity, and a greatly increased responsiveness to excitatory synaptic inputs. This marked change in firing pattern and excitability is controlled in part by ascending noradrenergic and serotonergic inputs from the brainstem, although the cellular mechanisms of this effect have remained largely unknown. Here we report that noradrenaline and serotonin enhance a mixed Na+/K+ current which is activated by hyperpolarization (Ih) and that this enhancement may be mediated by increases in intracellular concentration of cyclic AMP. This novel action of noradrenaline and serotonin reduces the ability of thalamic neurons to generate rhythmic burst firing and promotes a state of excitability that is conducive to the thalamocortical synaptic processing associated with cognition.     

Sparse optical microstimulation in barrel cortex drives learned behaviour in freely moving mice

Electrical microstimulation can establish causal links between the activity of groups of neurons and perceptual and cognitive functions. However, the number and identities of neurons microstimulated, as well as the number of action potentials evoked, are difficult to ascertain. To address these issues we introduced the light-gated algal channel channelrhodopsin-2 (ChR2) specifically into a small fraction of layer 2/3 neurons of the mouse primary somatosensory cortex. ChR2 photostimulation in vivo reliably generated stimulus-locked action potentials at frequencies up to 50 Hz. Here we show that naive mice readily learned to detect brief trains of action potentials (five light pulses, 1 ms, 20 Hz). After training, mice could detect a photostimulus firing a single action potential in approximately 300 neurons. Even fewer neurons (approximately 60) were required for longer stimuli (five action potentials, 250 ms). Our results show that perceptual decisions and learning can be driven by extremely brief epochs of cortical activity in a sparse subset of supragranular cortical pyramidal neurons.     

Temporal integration by a slowly inactivating K+ current in hippocampal neurons

A central aspect of neuronal function is how each nerve cell translated synaptic input into a sequence of action potentials that carry information along the axon, coded as spike frequency. When transduction from a graded depolarizing input to spikes is studied by injecting a depolarizing current, there is often a remarkably long delay to the first action potential, both in mammalian and molluscan neurons. Here, I report that the delayed excitation in rat hippocampal neurons is due to a slowly inactivating potassium current, ID. ID co-exists with other voltage-gated K+ currents, including a fast A current and a slow delayed rectifier current. As ID activates in the subthreshold range, and takes tens of seconds to recover from inactivation, it enables the cell to integrate separate depolarizing inputs over long times. ID also makes the encoding properties of the cell exceedingly sensitive to the prevailing membrane potential.     

Behavioural report of single neuron stimulation in somatosensory cortex

Understanding how neural activity in sensory cortices relates to perception is a central theme of neuroscience. Action potentials of sensory cortical neurons can be strongly correlated to properties of sensory stimuli and reflect the subjective judgements of an individual about stimuli. Microstimulation experiments have established a direct link from sensory activity to behaviour, suggesting that small neuronal populations can influence sensory decisions. However, microstimulation does not allow identification and quantification of the stimulated cellular elements. The sensory impact of individual cortical neurons therefore remains unknown. Here we show that stimulation of single neurons in somatosensory cortex affects behavioural responses in a detection task. We trained rats to respond to microstimulation of barrel cortex at low current intensities. We then initiated short trains of action potentials in single neurons by juxtacellular stimulation. Animals responded significantly more often in single-cell stimulation trials than in catch trials without stimulation. Stimulation effects varied greatly between cells, and on average in 5% of trials a response was induced. Whereas stimulation of putative excitatory neurons led to weak biases towards responding, stimulation of putative inhibitory neurons led to more variable and stronger sensory effects. Reaction times for single-cell stimulation were long and variable. Our results demonstrate that single neuron activity can cause a change in the animal's detection behaviour, suggesting a much sparser cortical code for sensations than previously anticipated.     

神经系统识别爆发性锋电位序列的机制讨论

讨论神经系统识别爆发型锋电位序列信息的机制,认为序列的信息存储在爆发锋电位组内间隔和组间间隔2个时间变量中,建立了一个神经回路,通过突触传递过程中的易化、反馈调节机制以及时间依赖的学习机制等突触可塑性机制,给出了神经系统识别爆发性锋电位序列信息的一种可能机制,其中包括分解机制和整合机制两部分.首先通过神经元选择性响应的动力学性质,将锋电位序列的信息分解,并将每组锋电位内部间隔的信息通过不同神经元学习存储.通过突触延迟时间的动力学调整,将2组锋电位之间的时间间隔学习、存储在回路中.经过多次学习训练,神经回路对输入信号形成特定的突触连接结构以及时空响应输出模式,实现对爆发性锋电位序列信息的识别.     

Modulation of intracortical synaptic potentials by presynaptic somatic membrane potential

Traditionally, neuronal operations in the cerebral cortex have been viewed as occurring through the interaction of synaptic potentials in the dendrite and soma, followed by the initiation of an action potential, typically in the axon. Propagation of this action potential to the synaptic terminals is widely believed to be the only form of rapid communication of information between the soma and axonal synapses, and hence to postsynaptic neurons. Here we show that the voltage fluctuations associated with dendrosomatic synaptic activity propagate significant distances along the axon, and that modest changes in the somatic membrane potential of the presynaptic neuron modulate the amplitude and duration of axonal action potentials and, through a Ca2+-dependent mechanism, the average amplitude of the postsynaptic potential evoked by these spikes. These results indicate that synaptic activity in the dendrite and soma controls not only the pattern of action potentials generated, but also the amplitude of the synaptic potentials that these action potentials initiate in local cortical circuits, resulting in synaptic transmission that is a mixture of triggered and graded (analogue) signals.     

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.     

Axonal site of spike initiation enhances auditory coincidence detection

Neurons initiate spikes in the axon initial segment or at the first node in the axon. However, it is not yet understood how the site of spike initiation affects neuronal activity and function. In nucleus laminaris of birds, neurons behave as coincidence detectors for sound source localization and encode interaural time differences (ITDs) separately at each characteristic frequency (CF). Here we show, in nucleus laminaris of the chick, that the site of spike initiation in the axon is arranged at a distance from the soma, so as to achieve the highest ITD sensitivity at each CF. Na+ channels were not found in the soma of high-CF (2.5-3.3 kHz) and middle-CF (1.0-2.5 kHz) neurons but were clustered within a short segment of the axon separated by 20-50 microm from the soma; in low-CF (0.4-1.0 kHz) neurons they were clustered in a longer stretch of the axon closer to the soma. Thus, neurons initiate spikes at a more remote site as the CF of neurons increases. Consequently, the somatic amplitudes of both orthodromic and antidromic spikes were small in high-CF and middle-CF neurons and were large in low-CF neurons. Computer simulation showed that the geometry of the initiation site was optimized to reduce the threshold of spike generation and to increase the ITD sensitivity at each CF. Especially in high-CF neurons, a distant localization of the spike initiation site improved the ITD sensitivity because of electrical isolation of the initiation site from the soma and dendrites, and because of reduction of Na+-channel inactivation by attenuating the temporal summation of synaptic potentials through the low-pass filtering along the axon.     

基于多元线性逆滤波器的视顶盖神经元集群亮度信息解码研究

通过解码鸽子视顶盖(the optic tectum,OT)神经元集群亮度信息的方法,研究了OT区神经元集群编码亮度信息的神经机制。首先设计了具有瞬态闪变特性的亮度视觉刺激模式,采用微电极阵列记录了多通道的锋电位(spike)发放序列;然后提取了神经元集群的spike发放率特征,构造多元线性逆滤波器解码视觉刺激亮度;最后采用互相关和信息论的方法对解码结果进行了分析。结果表明:采用的多元线性逆滤波器有效解码了OT区神经元集群编码的亮度信息。通过对解码参数变化与解码精度的分析可知神经元集群数目13个、bin的宽度5 ms、刺激后15 ms、刺激后持续时间35 ms具有最高的解码精度。通过神经元集群中逆滤波器形态的分析发现,单神经元在亮度信息的编码过程中受周围神经元的动态调制。通过对解码精度与刺激闪变频率关系的分析,发现在刺激闪变频率19 Hz到53 Hz的范围内,重建质量较好,在刺激闪变频率为33.5 Hz时,重建质量达到最优。     

基于概率神经网络的锋电位实时分类算法

为了实现便携式实时处理的实用型脑-机接口(BMI),提出了一种基于概率神经网络(PNN)的锋电位信号实时分类算法,并完成了该算法基于现场可编程门阵列(FPGA)的实现.该算法通过训练数据的快速导入完成PNN的训练,再由PNN实现锋电位的分类工作.文中通过调用FPGA片上DSP48Es资源实现单精度浮点的乘加运算,采用并行流水结构加速向量间距离的计算,通过查找表和坐标旋转数字计算方法完成PNN激活函数的准确逼近.实验结果表明,在完成高达93.82%准确率的情况下,基于FPGA的PNN实现方法比基于Matlab的方法快47.43倍,达到了便携式实时处理的设计要求.     

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.     

基于神经元连接的脑网络减边演化算法

神经元间的连接以先增大后减小的方式演化,这提示了大脑神经元网络在演化过程中存在“剪除”过程。以“剪除”为启发,本文首先使用数学方法对大脑网络进行建模,然后基于大脑网络中的神经元连接方式,设计了网络减边演化算法。最后,考虑布线消耗和信息传输之间的效率,建立了大神经元优先与距离优先的演化博弈模型,探索该模型对脑网络拓扑结构特性的影响。实验结果显示,在此演化过程中呈现了中心节点度≈200、小世界特性S>1和高效率代价比等性质, 表明该算法能够有效模拟仿神经元剪除机制。上述算法和模型为有效模拟高效低能耗的脑网络提供了一种新途径。     

Neuronal pacemaker for breathing visualized in vitro.

Breathing movements in mammals arise from a rhythmic pattern of neural activity, thought to originate in the pre-B?tzinger complex in the lower brainstem. The mechanisms generating the neural rhythm in this region are unknown. The central question is whether the rhythm is generated by a network of bursting pacemaker neurons coupled by excitatory synapses that synchronize pacemaker activity. Here we visualized the activity of inspiratory pacemaker neurons at single-cell and population levels with calcium-sensitive dye. We developed methods to label these neurons retrogradely with the dye in neonatal rodent brainstem slices that retain the rhythmically active respiratory network. We simultaneously used infrared structural imaging to allow patch-clamp recording from the identified neurons. After we pharmacologically blocked glutamatergic synaptic transmission, a subpopulation of inspiratory neurons continued to burst rhythmically but asynchronously. The intrinsic bursting frequency of these pacemaker neurons depended on the baseline membrane potential, providing a cellular mechanism for respiratory frequency control. These results provide evidence that the neuronal kernel for rhythm generation consists of a network of synaptically-coupled pacemaker neurons.     

Feedback inhibition controls spike transfer in hybrid thalamic circuits

Sensory information reaches the cerebral cortex through the thalamus, which differentially relays this input depending on the state of arousal. Such 'gating' involves inhibition of the thalamocortical relay neurons by the reticular nucleus of the thalamus, but the underlying mechanisms are poorly understood. We reconstructed the thalamocortical circuit as an artificial and biological hybrid network in vitro. With visual input simulated as retinal cell activity, we show here that when the gain in the thalamic inhibitory feedback loop is greater than a critical value, the circuit tends towards oscillations -- and thus imposes a temporal decorrelation of retinal cell input and thalamic relay output. This results in the functional disconnection of the cortex from the sensory drive, a feature typical of sleep states. Conversely, low gain in the feedback inhibition and the action of noradrenaline, a known modulator of arousal, converge to increase input output correlation in relay neurons. Combining gain control of feedback inhibition and modulation of membrane excitability thus enables thalamic circuits to finely tune the gating of spike transmission from sensory organs to the cortex.     

Intracellular calcium stores regulate activity-dependent neuropeptide release from dendrites

Information in neurons flows from synapses, through the dendrites and cell body (soma), and, finally, along the axon as spikes of electrical activity that will ultimately release neurotransmitters from the nerve terminals. However, the dendrites of many neurons also have a secretory role, transmitting information back to afferent nerve terminals. In some central nervous system neurons, spikes that originate at the soma can travel along dendrites as well as axons, and may thus elicit secretion from both compartments. Here, we show that in hypothalamic oxytocin neurons, agents that mobilize intracellular Ca(2+) induce oxytocin release from dendrites without increasing the electrical activity of the cell body, and without inducing secretion from the nerve terminals. Conversely, electrical activity in the cell bodies can cause the secretion of oxytocin from nerve terminals with little or no release from the dendrites. Finally, mobilization of intracellular Ca(2+) can also prime the releasable pool of oxytocin in the dendrites. This priming action makes dendritic oxytocin available for release in response to subsequent spike activity. Priming persists for a prolonged period, changing the nature of interactions between oxytocin neurons and their neighbours.