神经放电序列模式的一种识别方法及应用

提出了神经放电序列模式识别的一种新方法。首先,把放电序列用阶梯状的响应函数来表示,然后定义了其一阶、二阶形式导数以及形式积分。这三个特征量均有着不同的几何和物理意义,因此采用这三个特征量来刻画神经放电序列的模式,就可以较全面地表示其特征。对神经放电序列的重构也表明通过这几个特征量可以很好地反映序列中所包含的信息。作为应用例子,这种量化方法用来研究冷热感受器模型所产生的放电模式,结果表明它能够识别在不同温度条件下的放电模式。     

Key role of calcium signaling in synaptic transmission

The review analyzes current concepts on the role of calcium signals in the process of synaptic neuron-to-neuron and neuron-effector transmission and on the respective intracellular mechanisms (participation of different types of ion channels, mitochondria, and endoplasmic reticulum). The involvement of calcium both in the transmission per se, in particular in the process of exocytotic neurotransmitter release, and in long-lasting modulations of the efficacy of synaptic transmission (potentiation or depression) is considered. Neirofiziologiya/Neurophysiology, Vol. 39, Nos. 4/5, pp. 290–293, July–October, 2007.     

Regulation of synaptic nanodomain by liquid–liquid phase separation: A novel mechanism of synaptic plasticity

Advances in microscopy techniques have revealed the details of synaptic nanodomains as defined by the segregation of specific molecules on or beneath both presynaptic and postsynaptic membranes. However, it is yet to be clarified how such segregation is accomplished without demarcating membrane and how nanodomains respond to the neuronal activity. It was recently discovered that proteins at the synapse undergo liquid–liquid phase separation (LLPS), which not only contributes to the accumulation of synaptic proteins but also to further segregating the proteins into subdomains by forming phase-in-phase structures. More specifically, CaMKII, a postsynaptic multifunctional kinase that serves as a signaling molecule, acts as a synaptic cross-linker which segregates certain molecules through LLPS in a manner triggered by Ca²⁺. Nanodomain formation contributes to the establishment of trans-synaptic nanocolumns, which may be involved in the optimization of spatial arrangement of the transmitter release site and receptor, thereby serving as a new mechanism of synaptic plasticity.     

A single dose of cocaine potentiates glutamatergic synaptic transmission onto locus coeruleus neurons

The brainstem locus coeruleus (LC), the primary norepinephrinergic (NE) nucleus in the brain, has been implicated in the abuse of drugs such as opioids. However, whether and how the LC-NE system is involved in cocaine addiction remains elusive. Here, we demonstrated cocaine-evoked synaptic plasticity of glutamatergic transmission onto LC neurons as one of the earliest traces occurring after a single injection of cocaine. Twenty-four hours after mice were injected intraperitoneally with cocaine, the evoked α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) mediated synaptic transmission onto LC neurons were strongly potentiated without major effect on N-methyl-d-aspartate receptor (NMDAR) mediated synaptic transmission. Compared with saline-pretreated mice, AMPAR-mediated excitatory postsynaptic currents (EPSCs) of cocaine-pretreated mice showed a marked inward rectification, demonstrating the insertion of GluR2-lacking AMPARs to plasma membrane. In addition, the single injection of cocaine did not affect presynaptic glutamate release probability measured by paired pulse ratio. Furthermore, we found that the cocaine-induced potentiation of AMPAR EPSCs could be blocked by prazosin, an inhibitor of α1-adrenoreceptor (AR), indicating that cocaine increases AMPAR transmission via α1-ARs. These results reveal that LC-NE serves as an initial target of drug intake.     

A two-age-classes dengue transmission model

In this paper, we discuss a two-age-classes dengue transmission model with vaccination. The reason to divide the human population into two age classes is for practical purpose, as vaccination is usually concentrated in one age class. We assume that a constant rate of individuals in the child-class is vaccinated. We analyze a threshold number which is equivalent to the basic reproduction number. If there is an undeliberate vaccination to infectious children, which worsens their condition as the time span of being infectious increases, then paradoxically, vaccination can be counter productive. The paradox, stating that vaccination makes the basic reproduction number even bigger, can occur if the worsening effect is greater than a certain threshold, a function of the human demographic and epidemiological parameters, which is independent of the level of vaccination. However, if the worsening effect is to increase virulence so that one will develop symptoms, then the vaccination is always productive. In both situations, screening should take place before vaccination. In general, the presence of class division has obscured the known rule of thumb for vaccination.     

A neural network model of attention-modulated neurodynamics

Visual attention appears to modulate cortical neurodynamics and synchronization through various cholinergic mechanisms. In order to study these mechanisms, we have developed a neural network model of visual cortex area V4, based on psychophysical, anatomical and physiological data. With this model, we want to link selective visual information processing to neural circuits within V4, bottom-up sensory input pathways, top-down attention input pathways, and to cholinergic modulation from the prefrontal lobe. We investigate cellular and network mechanisms underlying some recent analytical results from visual attention experimental data. Our model can reproduce the experimental findings that attention to a stimulus causes increased gamma-frequency synchronization in the superficial layers. Computer simulations and STA power analysis also demonstrate different effects of the different cholinergic attention modulation action mechanisms.     

A simple model of retina-LGN transmission

To gain a deeper understanding of the transmission of visual signals from retina through the lateral geniculate nucleus (LGN), we have used a simple leaky integrate and-fire model to simulate a relay cell in the LGN. The simplicity of the model was motivated by two questions: (1) Can an LGN model that is driven by a retinal spike train recorded as synaptic (‘S’) potentials, but does not include a diverse array of ion channels, nor feedback inputs from the cortex, brainstem, and thalamic reticular nucleus, accurately simulate the LGN discharge on a spike-for-spike basis? (2) Are any special synaptic mechanisms, beyond simple summation of currents, necessary to model experimental recordings? We recorded cat relay cell responses to spatially homogeneous small or large spots, with luminance that was rapidly modulated in a pseudo-random fashion. Model parameters for each cell were optimized with a Simplex algorithm using a short segment of the recording. The model was then tested on a much longer, distinct data set consisting of responses to numerous repetitions of the noisy stimulus. For LGN cells that spiked in response to a sufficiently large fraction of retinal inputs, we found that this simplified model accurately predicted the firing times of LGN discharges. This suggests that modulations of the efficacy of the retino-geniculate synapse by pre-synaptic facilitation or depression are not necessary in order to account for the LGN responses generated by our stimuli, and that post-synaptic summation is sufficient.     

An individual-based model of hepatitis A transmission

Viral hepatitis A, as other endemic diseases, represents a public health priority worldwide. To study long-time scale human pathogens through individual-based simulations, the development of a dynamic network of contacts is required. In this work, we introduce an individual-based model accounting for the birth and death of the individuals, the generation of new households, and the educational career of the individuals, in order to investigate viral hepatitis A dynamics in the most affected Italian areas. Intervention options such as targeted vaccination, social distancing measures (e.g., closure of day care centers and kindergartens) and improvements in standards of living and hygiene are evaluated. Results show that a very low vaccination coverage is sufficient to control hepatitis A in Italy, while its elimination is not possible since new cases are continuously imported from high endemicity areas outside the country. Finally, the considered social distancing measures can be counterproductive since the fraction of recovered individuals does not decline while the age at infection increases, thus augmenting the probability of developing acute symptoms.     

A model of neural network extracting binocular parallax

A model of neural network extracting binocular parallax is proposed. It is a multilayered network composed of analog threshold elements. Three types of binocular neurons are included in this model. They are binocular simple neurons, binocular gate neurons and binocular depth neurons. The final layers of this model consist of elements which correspond to the binocular depth neurons. The performance of the model has been simulated on a digital computer. The results of the computer simulation show that every element of this model acts like neurons found in cat's and monkey's visual system and this model extracts binocular parallax caused by simple line components satisfactorily.     

A neural network model of the McCollough effect

A self-organizing, feature-extracting network (von der Malsburg, 1973) is extended to two feature dimensions to encompass line orientation and color. It is applied to McCollough effects, particularly longlasting, contingent-aftereffects. McCollough effects are thought to involve low-level associative memory in the form of synaptic modification. The McCollough-Malsburg Model (MMM) embodies positive synaptic modification with correlated firing of units in an input layer and an excitatory cortical layer. Computer simulation of MMM reproduces orientation-contingent color aftereffects. The model embodies many of the mechanisms thought to be operating in developmental plasticity, suggesting that equivalent mechanisms may be involved in adult long-term adaptation as well.This work was supported in part by NIH Grant No. 5 R01 NS09755-4 COM of the National Institute of Neurological Diseases and Stroke (M.A. Arbib, Principal Investigator)     

Adenosine A(2A) receptors are required for normal BDNF levels and BDNF-induced potentiation of synaptic transmission in the mouse hippocampus

Brain-derived neurotrophic factor (BDNF), a member of neurotrophin family, enhances synaptic transmission and regulates neuronal proliferation and survival. Both BDNF and its tyrosine kinase receptors (TrkB) are highly expressed in the hippocampus, where an interaction with adenosine A_2A receptors (A_2ARs) has been recently reported. In the present paper, we evaluated the role of A_2ARs in mediating functional effects of BDNF in hippocampus using A_2AR knock-out (KO) mice. In hippocampal slices from WT mice, application of BDNF (10 ng/mL) increased the slope of excitatory post-synaptic field potentials (fEPSPs), an index of synaptic facilitation. This increase of fEPSP slope was abolished by the selective A_2A antagonist ZM 241385. Similarly, genetic deletion of the A_2ARs abolished BDNF-induced increase of the fEPSP slope in slices from A_2AR KO mice The reduced functional ability of BDNF in A_2AR KO mice was correlated with the reduction in hippocampal BDNF levels. In agreement, the pharmacological blockade of A₂Rs by systemic ZM 241385 significantly reduced BDNF levels in the hippocampus of normal mice. These results indicate that the tonic activation of A_2ARs is required for BDNF-induced potentiation of synaptic transmission and for sustaining a normal BDNF tone in the hippocampus.     

A neural network model of ventriloquism effect and aftereffect

Presenting simultaneous but spatially discrepant visual and auditory stimuli induces a perceptual translocation of the sound towards the visual input, the ventriloquism effect. General explanation is that vision tends to dominate over audition because of its higher spatial reliability. The underlying neural mechanisms remain unclear. We address this question via a biologically inspired neural network. The model contains two layers of unimodal visual and auditory neurons, with visual neurons having higher spatial resolution than auditory ones. Neurons within each layer communicate via lateral intra-layer synapses; neurons across layers are connected via inter-layer connections. The network accounts for the ventriloquism effect, ascribing it to a positive feedback between the visual and auditory neurons, triggered by residual auditory activity at the position of the visual stimulus. Main results are: i) the less localized stimulus is strongly biased toward the most localized stimulus and not vice versa; ii) amount of the ventriloquism effect changes with visual-auditory spatial disparity; iii) ventriloquism is a robust behavior of the network with respect to parameter value changes. Moreover, the model implements Hebbian rules for potentiation and depression of lateral synapses, to explain ventriloquism aftereffect (that is, the enduring sound shift after exposure to spatially disparate audio-visual stimuli). By adaptively changing the weights of lateral synapses during cross-modal stimulation, the model produces post-adaptive shifts of auditory localization that agree with in-vivo observations. The model demonstrates that two unimodal layers reciprocally interconnected may explain ventriloquism effect and aftereffect, even without the presence of any convergent multimodal area. The proposed study may provide advancement in understanding neural architecture and mechanisms at the basis of visual-auditory integration in the spatial realm.     

A model of neural network for spatiotemporal pattern recognition

A model of neural network to recognize spatiotemporal patterns is presented. The network consists of two kinds of neural cells: P-cells and B-cells. A P-cell generates an impulse responding to more than one impulse and embodies two special functions: short term storage (STS) and heterosynaptic facilitation (HSF). A B-cell generates several impulses with high frequency as soon as it receives an impulse. In recognizing process, an impulse generated by a P-cell represents a recognition of stimulus pattern, and triggers the generation of impulses of a B-cell. Inhibitory impulses with high frequency generated by a B-cell reset the activities of all P-cells in the network.Two examples of spatiotemporal pattern recognition are presented. They are achieved by giving different values to the parameters of the network. In one example, the network recognizes both directional and non-directional patterns. The selectivities to directional and non-directional patterns are realized by only adjusting excitatory synaptic weights of P-cells. In the other example, the network recognizes time series of spatial patterns, where the lengths of the series are not necessarily the same and the transitional speeds of spatial patterns are not always the same. In both examples, the HSF signal controls the total activity of the network, which contributes to exact recognition and error recovery. In the latter example, it plays a role to trigger and execute the recognizing process. Finally, we discuss the correspondence between the model and physiological findings.     

A self-organising neural network model of image velocity encoding

A self-organising neural network has been developed which maps the image velocities of rigid objects, moving in the fronto-parallel plane, topologically over a neural layer. The input is information in the Fourier domain about the spatial components of the image. The computation performed by the network may be viewed as a neural instantiation of the Intersection of Constraints solution to the aperture problem. The model has biological plausibility in that the connectivity develops simply as a result of exposure to inputs derived from rigid translation of textures and its overall organisation is consistent with psychophysical evidence.     

A neural network model for the mechanism of feature-extraction

We propose a new multilayered neural network model which has the ability of rapid self-organization. This model is a modified version of the cognitron (Fukushima, 1975). It has modifiable inhibitory feedback connections, as well as conventional modifiable excitatory feedforward connections, between the cells of adjoining layers. If a feature-extracting cell in the network is excited by a stimulus which is already familiar to the network, the cell immediately feeds back inhibitory signals to its presynaptic cells in the preceding layer, which suppresses their response. On the other hand, the feature-extracting cell does not respond to an unfamiliar feature, and the responses from its presynaptic cells are therefore not suppressed because they do not receive any feedback inhibition. Modifiable synapses in the new network are reinforced in a way similar to those in the cognitron, and synaptic connections from cells yielding a large sustained output are reinforced. Since familiar stimulus features do not elicit a sustained response from the cells of the network, only circuits which detect novel stimulus features develop. The network therefore quickly acquires favorable pattern-selectivity by the mere repetitive presentation of set of learning patterns.     

Towards a unifying model of neural net activity in the visual cortex

A neural net model describing the non-linear interactions between axonal spikes is presented. It reconciles aspects of pattern recognition (as action of an associative memory) with those of spike synchronization and phase locking. The stability of the synchronized state is studied in detail.     

灭多威对美洲大蠊腹六神经节突触传递的阻断作用

用电生理学方法研究了灭多威对美洲大蠊Periplanetaamerwana腹六神经节(A6节)突触传递的影响。用灭多威溶液浸泡A6节,电刺激尾须神经粗支,用甘露醇间隙法记录兴奋性突触后电位(EPSP)和突触后动作电位。给予弱刺激只记录到EPSP时,灭多威作用初期EPSP幅度增加、时程延长,能诱发突触后动作电位,随后EPSP逐渐减小至消失,冲洗可恢复,突触前反应保持不变。增加电刺激强度记录到突触后动作电位时,灭多威可阻断A6节的突触传递,阻断时间是浓度依赖性的,阻断是可逆的,但冲洗30 min仍保留一定的后作用。对美洲大蠊雄性成虫腹腔注射灭多威测定致死中量(LD₅₀)为(3.56±0.01) μg/g体重。根据灭多威的作用机理对其阻断A6节突触传递的特点以及对虫体的毒杀机制进行了讨论。