Role of synaptic filtering on the firing response of simple model neurons

During active states of the brain neurons process their afferent currents with an effective membrane time constant much shorter than its value at rest. This fact, together with the existence of several synaptic time scales, determines to which aspects of the input the neuron responds best. Here we present a solution to the response of a leaky integrate-and-fire neuron with synaptic filters when long synaptic times are present, and predict the firing rate for all values of the synaptic time constant. We also discuss under which conditions this neuron becomes a coincidence detector.     

A multichannel shot noise approach to describe synaptic background activity in neurons

Systems driven by Poisson-distributed quantal inputs can be described as “shot noise” stochastic processes. This formalism can apply to neurons which receive a large number of Poisson-distributed synaptic inputs of similar quantal size. However, the presence of temporal correlations between these inputs destroys their quantal nature, and such systems can no longer be described by classical shot noise processes. Here, we show that explicit expressions for various statistical properties, such as the amplitude distribution and the power spectral density, can be deduced and investigated as functions of the correlation between input channels. The monotonic behavior of these expressions allows an one-to-one relation between temporal correlations and the statistics of fluctuations. Multi-channel shot noise processes, therefore, open a way to deduce correlations in input patterns by analyzing fluctuations in experimental systems. We discuss applications such as detecting correlations in networks of neurons from intracellular recordings of single neurons.     

Diverse population-bursting modes of adapting spiking neurons

We study the dynamics of a noisy network of spiking neurons with spike-frequency adaptation (SFA), using a mean-field approach, in terms of a two-dimensional Fokker-Planck equation for the membrane potential of the neurons and the calcium concentration gating SFA. The long time scales of SFA allow us to use an adiabatic approximation and to describe the network as an effective nonlinear two-dimensional system. The phase diagram is computed for varying levels of SFA and synaptic coupling. Two different population-bursting regimes emerge, depending on the level of SFA in networks with noisy emission rate, due to the finite number of neurons.     

Thermal impact on spiking properties in Hodgkin-Huxley neuron with synaptic stimulus

The effect of environmental temperature on neuronal spiking behaviors is investigated by numerically simulating the temperature dependence of spiking threshold of the Hodgkin-Huxley neuron subject to synaptic stimulus. We find that the spiking threshold exhibits a global minimum in a specific temperature range where spike initiation needs weakest synaptic strength, which form the engineering perspective indicates the occurrence of optimal use of synaptic transmission in the nervous system. We further explore the biophysical origin of this phenomenon associated with ion channel gating kinetics and also discuss its possible biological relevance in information processing in neuronal systems.      

Channel block-optimized spiking activity of Hodgkin-Huxley neurons on random networks

In this paper, we numerically study the effect of channel block on the spiking temporal coherence and spatial synchronization on Hodgkin-Huxley (HH) neuron networks. It is found that under sodium CB the spike coherence is badly reduced, and the synchronization can, depending on the network randomness (the fraction of random shortcuts), be either enhanced or reduced, while, under potassium CB, the spike coherence can be enhanced but the synchronization is reduced. Interestingly, for certain networks of relatively large randomness, the neuron firings can achieve the best temporal coherence at an optimal potassium CB. These results show that under certain conditions channel blocking can increase and optimize the spike coherence and the synchronization on the complex HH neuron networks, whereby the neurons would exhibit a better and the best sub-threshold signal encoding.     

Lattice form adaptive infinite impulse response filtering algorithm for active noise control

In some situations of active noise control, infinite impulse response (IIR) filters are more suitable than finite impulse response (FIR) filters owing to the poles in the transfer function. A number of algorithms have been derived for applying IIR filters in active noise control; however, most of them use the direct form IIR filter structure, which faces the difficulties of checking stability and relatively slow convergence speed for noise composed of narrow-band components with large power disparity. To overcome these difficulties along with using the direct form IIR filters, a new adaptive algorithm is proposed in this paper, which uses and updates the lattice form adaptive IIR filter in an active noise control system. Full mathematical derivations of the proposed algorithm are presented, and the comparison between the proposed algorithm and the commonly used filtered-u LMS and filtered-v LMS algorithms shows the superiority of the proposed algorithm.     

Random noise filtering method based on the inter-frame registration

One of the problems to be solved in image processing is how to eliminate image noise effectively. In this work, we brought forward a random noise filtering method based on the inter-frame registration. Firstly, we calculated the relative displacement of the adjacent frames by a registration algorithm. Then we divided the image into the overlapping area and the non-overlapping area according to the relative displacement. Finally, we do noise reduction processing for these two areas respectively. The experiments results indicate that the proposed method can reduce noise in both spatial and time domain of video images. The main advantage is that it cannot only remove noise, but also effectively protect the image edge and detail information. Besides, it not only maintains the de-noising effect of traditional inter-frame algorithm, but also is suitable for moving targets. It has better real-time performance and wider application range.     

Impact of network activity on noise delayed spiking for a Hodgkin-Huxley model

In a Hodgkin-Huxley neuron model driven just above threshold, external noise can increase both jitter and latency of the first spike, an effect called “noise delayed decay” (NDD). This phenomenon is important when considering how neuronal information is represented, thus by the precise timing of spikes or by their rate. We examine how NDD can be affected by network activity by varying the model's membrane time constant, τ_m. We show that NDD is significant for small τ_m or high network activity, and decreases for large τ_m, or low network activity. Our results suggest that for inputs just above threshold, the activity of the network constrains the neuronal coding strategy due to, at least in part, the NDD effect.     

Spontaneous dynamics and response properties of a Hodgkin-Huxley-type neuron model driven by harmonic synaptic noise

We study statistical properties, response dynamics, and information transmission in a Hodgkin-Huxley–type neuron system, modeling peripheral electroreceptors in paddlefish. In addition to sodium and potassium currents, the neuron model includes fast calcium and slow afterhyperpolarization (AHP) potassium currents. The synaptic transmission from sensory epithelium is modeled by a Poission process with a rate modulated by narrow-band noise, mimicking stochastic epithelial oscillations observed experimentally. We study how the interplay of parameters of AHP current and synaptic noise affects the statistics of spontaneous dynamics and response properties of the system. In particular, we confirm predictions made earlier with perfect integrate and fire and phase neuron models that epithelial oscillations enhance stimulus–response coherence and thus information transmission in electroreceptor system. In addition, we consider a strong stimulus regime and show that coherent epithelial oscillations may reduce variability of electroreceptor responses to time-varying stimuli.     

Parameter-dependent synchronization transition of coupled neurons with co-existing spiking and bursting

A firing pattern transition is simulated in the Leech neuron model, firstly from bursting to co-existence of spiking and bursting and then to spiking. The attraction domain of spiking and bursting for three different parameter values are calculated. Synchronization transition processes of two coupled Leech neurons, one is bursting and the other the co-existing spiking, are simulated for the three parameters. The three synchronization processes appear similar as the coupling strength increases, beginning from non-synchronization to complete synchronization through a complex dynamical procedure, but their detailed processes are different depending on the parameter values. The transition procedure is complex and the complete synchronization is in bursting for larger parameter values, while the process is simple with complete synchronization of spiking for smaller values. The potential relationship between complete synchronization and the attraction domain is also discussed. The results are instructive to understanding the synchronization behaviors of the coupled neuronal system with co-existing attractors.     

L波段低温低噪声滤波放大组件设计研究

仿真和设计了一种以超导滤波器和低温低噪声放大器为核心的滤波放大组件,在77K温度下,该组件带外抑制大于100d B,在工作频段内,噪声系数优于0.44d B,增益为29.9±0.4d B,输入回波损耗优于-13.8d B,满足设计指标要求。     

Variability of spatio-temporal patterns in non-homogeneous rings of spiking neurons

We show that a ring of unidirectionally delay-coupled spiking neurons may possess a multitude of stable spiking patterns and provide a constructive algorithm for generating a desired spiking pattern. More specifically, for a given time-periodic pattern, in which each neuron fires once within the pattern period at a predefined time moment, we provide the coupling delays and/or coupling strengths leading to this particular pattern. The considered homogeneous networks demonstrate a great multistability of various travelling time- and space-periodic waves which can propagate either along the direction of coupling or in opposite direction. Such a multistability significantly enhances the variability of possible spatio-temporal patterns and potentially increases the coding capability of oscillatory neuronal loops. We illustrate our results using FitzHugh-Nagumo neurons interacting via excitatory chemical synapses as well as limit-cycle oscillators.     

基于空时级联滤波的拖船自噪声抵消方法

拖船自噪声属于近场多途强干扰信号,具有显著角度扩展现象,是影响拖曳阵探测性能的重要因素之一。在逆波束形成自噪声抵消方法基础上,结合空域和时域滤波,提出了空时级联滤波的拖船自噪声抵消方法。首先,由方位估计器估计拖船自噪声方位,经过波束形成空域滤波估计得到自噪声信号;然后,利用自噪声空域滤波输出设计最优维纳滤波器,将自噪声抵消在阵元级。基于简正波声场模型的仿真和实际海试数据的处理表明,该方法能够有效抵消拖船自噪声,性能优于逆波束形成方法。     

GABAergic synaptic response and its opioidergic modulation in periaqueductal gray neurons of rats with neuropathic pain

Background  

Neuropathic pain is a chronic and intractable symptom associated with nerve injury. The periaqueductal gray (PAG) is important in the endogenous pain control system and is the main site of the opioidergic analgesia. To investigate whether neuropathic pain affects the endogenous pain control system, we examined the effect of neuropathic pain induced by sacral nerve transection on presynaptic GABA release, the kinetics of postsynaptic GABA-activated Cl^- currents, and the modulatory effect of μ-opioid receptor (MOR) activation in mechanically isolated PAG neurons with functioning synaptic boutons.     

Random networks of spiking neurons: instability in the Xenopus tadpole moto-neural pattern

A large network of integrate-and-fire neurons is studied analytically when the synaptic weights are independently randomly distributed according to a Gaussian distribution with arbitrary mean and variance. The relevant order parameters are identified, and it is shown that such network is statistically equivalent to an ensemble of independent integrate-and-fire neurons with each input signal given by the sum of a self-interaction deterministic term and a Gaussian colored noise. The model is able to reproduce the quasisynchronous oscillations, and the dropout of their frequency, of the central nervous system neurons of the swimming Xenopus tadpole. Predictions from the model are proposed for future experiments.     

小角度衍射噪声光栅滤波方法研究

针对因衍射等原因引起的小角度差光噪声信号,探讨了利用闪耀光栅的2级闪耀,实现角度差放大,提高空间低通滤波器适应性的滤波新方法。理论分析和模拟仿真表明,对于小于5°的角度差,可实现3倍以上放大。放大所需闪耀光栅的频率与入射单色波长成反比,波长越长,所需光栅频率越低。与正的斜入射角相比,负斜入射角度差的放大倍数更大。当负斜入射角超过一定值时,会因为全反射角的限制而导致斜入射2级闪耀不存在,只保留了有效信号的2级闪耀,滤波效果更好。     

异质神经元的排列对环形耦合神经元网络频率同步的影响

以一维环形耦合的非全同FitzHugh-Nagumo神经元网络为研究对象,讨论这种异质神经元在环上的不同排列对其频率同步的影响.研究结果显示,异质神经元的排列不同,对应的神经元网络达到频率同步所需的临界耦合强度也不完全相同.在平均意义下,异质性较小的神经元在环上的距离越近,神经元网络达到频率同步所需的临界耦合强度越大;相反,异质性较大的神经元在环上的距离越近,神经元网络达到同步所需的临界耦合强度越小.通过对频率同步过程的分析,进一步给出了产生这一现象的动力学机理.     

Linear filtering of nonstationary stochastic Gaussian noise power

Optimum linear filtering of the variance of stationary Gaussian noise is extended to the case where the noise variance is a function of an unobservable Markov control process. Discrete observations are examined. Tomsk State University. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 4, pp. 3–7, April, 1999.