Suprathreshold stochastic resonance induced by ion channel fluctuation

In this study, we examine the signal detection ability of an array of neurons with intrinsic channel fluctuation. Numerical simulations show that estimation of the input signal from the output spiking activity of the neuronal array is most accurate if a proper amount of channel noise exists. Theoretical calculation of the mutual and Fisher information confirms the effect of the noise-aided information transfer in the array, or the presence of suprathreshold stochastic resonance. These results indicate that the channel noise, which induces response variability, may play an essential role in population coding.     

An objective quality assessment method for bit-reduction coding of wideband speech.

This paper proposes a new objective quality assessment method for bit-reduction coding of wideband speech taking into account the masking effect of quantizing noise. First, this paper analyzes the reliability and sensitivity of the speech quality assessment method, based on a paired-comparison test with a modulated noise reference signal, for the bit-reduction coding of high-quality wideband speech. Then, the perception of quantizing noise is studied using speech with noise synthesized similar to the quantizing noise. The detection of quantizing noise is found to be influenced by masking by the source signal. This leads to a new method of objectively estimating the quality of coding speech by multiple regression analysis. The factors for the estimation are segmental signal-to-noise ratio, spectrum envelope distance between source signal and quantizing noise, and the similarity of the noise power envelope to the source signal in the time domain. This estimation method is applied to the parameter optimization of wideband coding systems.     

非线性物理破解神经编码机制

信息在神经系统中以脉冲点序列的形式传输和处理，神经系统如何通过脉冲点序列对所表达的信息进行编码，一直是一个谜．人们曾普遍认为，神经可能通过发放率（单位时间发放脉冲出现的次数）对信息编码，也有人猜测，神经可通过脉冲点序列的时序编码．由于神经发放的随机性，这就使得任何编码机制都面临着被表达信息的确定性与表达该信息的信号的随机性的矛盾．通过神经非线性随机动力学模型，文章作者发现，神经点序列的发放率对点序列的时序信息传输的影响，揭示了神经点序列时序信息在神经非线性传输中的随机共振特征．由此预期，并进一步通过听觉心理物理实验观察到，在一定条件下噪声对听觉的增强作用．从而通过非线性物理揭示了听觉时序编码机制的存在以及在时序编码中随机性噪声的积极作用．     

Enhanced information transmission with signal dependent noise in an array of LIF neurons

Sensory cells usually transmit information to afferent neurons via chemical synapses, in which the level of noise is dependent on an applied stimulus. Taking into account such dependence, we model a sensory system as an array of LIF neurons with a common signal. We show that information transmission is enhanced by a nonzero level of noise. Moreover, we demonstrate a phenomenon similar to suprathreshold stochastic resonance with additive noise. We remark that many properties of information transmission found for the LIF neurons was predicted by us before with simple binary units [Phys. Rev. E 75, 021121 (2007)]. This confirmation of our predictions allows us to point out identical roots of the phenomena found in the simple threshold systems and more complex LIF neurons.     

一种快速的分形图像压缩编码方法

针对分形压缩编码存在耗时过长的问题 ,提出一种快速分形编码算法 :即利用快速卷积来计算图像块之间的互相关 ,从而对编码过程进行无损加速。经仿真实验表明 :与经典的分割迭代函数系统 (PIFS)方法相比 ,在信噪比可接受的前题下 ,该算法的压缩比和编码速度均有显著提高。     

Preference of sensory neural coding for 1/f signals

We investigated the influences of different types of temporal correlations in the input signal on the functions and coding properties of neurons in the primary visual cortex (V1). We found that the temporal transfer functions of V1 neurons exhibit higher gain, and the spike responses exhibit higher coding efficiency and information transmission rates, for the 1/f (natural long-term correlation) signals than for 1/f(0) (no correlation) and 1/f(2) (stronger long-term correlation) signals. These results suggest that the intermediate long-term correlation ubiquitous to natural signals may play an important role in shaping and optimizing the machinery of neurons in their adaptation to the natural environment.     

Neural coding: computational and biophysical perspectives

While recognizing a face or kicking a ball may seem to be easy tasks for us, they still constitute challenging problems for even the most sophisticated computer algorithms available nowadays. The brain has evolved complex mechanisms to encode behaviorally relevant information. Here we review the types of codes used by the brain, what their constraints are and how they map the sensory environment or the motor output. We start by defining neural codes and briefly describing some of the current tools available to record activity from the brain. We give several examples of coding strategies used by different systems and multiple organisms and discuss how spiking patterns can be read out. Going beyond correlations between physiology and stimuli, we show what is currently known about the direct causal link between neuronal responses and behavioral output or sensory input. Finally, we identify what we consider to be some of the pressing questions in the field.     

Lateral predictive coding revisited: internal model,symmetry breaking,and response time

Predictive coding is a promising theoretical framework in neuroscience for understanding information transmission and perception. It posits that the brain perceives the external world through internal models and updates these models under the guidance of prediction errors. Previous studies on predictive coding emphasized top-down feedback interactions in hierarchical multilayered networks but largely ignored lateral recurrent interactions. We perform analytical and numerical investigations in this work on the effects of single-layer lateral interactions. We consider a simple predictive response dynamics and run it on the MNIST dataset of hand-written digits. We find that learning will generally break the interaction symmetry between peer neurons, and that high input correlation between two neurons does not necessarily bring strong direct interactions between them. The optimized network responds to familiar input signals much faster than to novel or random inputs, and it significantly reduces the correlations between the output states of pairs of neurons.     

Quantum dense coding with atomic qubits

We report the implementation of quantum dense coding on individual atomic qubits with the use of two trapped 9Be+ ions. The protocol is implemented with a complete Bell measurement that distinguishes the four operations used to encode two bits of classical information. We measure an average transmission fidelity of 0.85(1) and determine a channel capacity of 1.16(1).     

Optimal information transmission in nonlinear arrays through suprathreshold stochastic resonance

We examine the optimal threshold distribution in populations of noisy threshold devices. When the noise on each threshold is independent, and sufficiently large, the optimal thresholds are realized by the suprathreshold stochastic resonance effect, in which case all threshold devices are identical. This result has relevance for neural population coding, as such noisy threshold devices model the key dynamics of nerve fibres. It is also relevant to quantization and lossy source coding theory, since the model provides a form of stochastic signal quantization. Furthermore, it is shown that a bifurcation pattern appears in the optimal threshold distribution as the noise intensity increases. Fisher information is used to demonstrate that the optimal threshold distribution remains in the suprathreshold stochastic resonance configuration as the population size approaches infinity.     

Stochastic resonance in Hopfield neural networks for transmitting binary signals

We investigate the stochastic resonance phenomenon in a discrete Hopfield neural network for transmitting binary amplitude modulated signals, wherein the binary information is represented by two stored patterns. Based on the potential energy function and the input binary signal amplitude, the observed stochastic resonance phenomena involve two general noise-improvement mechanisms. A suitable amount of added noise assists or accelerates the switch of the network state vectors to follow input binary signals more correctly, yielding a lower probability of error. Moreover, at a given added noise level, the probability of error can be further reduced by the increase of the number of neurons. When the binary signals are corrupted by external heavy-tailed noise, it is found that the Hopfield neural network with a large number of neurons can outperform the matched filter in the region of low input signal-to-noise ratios per bit.     

基于随机共振进行弱信号探测的实验研究

非线性随机共振系统可利用噪声增强微弱信号检测的能力,为强噪声背景下微弱信号的检测开创了新方法.基于随机共振的基本原理设计了硬件电路系统,并将其应用于检测单频和多频微弱信号;通过输入模拟工程实际的带噪信号,采样所得的输出信号的频谱分析结果表明,利用随机共振技术可从强噪声背景下有效地提取出单频和多频弱信号.多频弱信号的有效提取拓展了基于随机共振原理的弱信号检测技术的应用领域,结合数字滤波处理技术有效地消除了低频噪声对信号识别的影响.基于随机共振的弱信号检测技术在信息识别与信息处理方面具有巨大的潜在的应用价值.     

High-capacity three-party quantum secret sharing with superdense coding

This paper presents a scheme for high-capacity three-party quantum secret sharing with quantum superdense coding, following some ideas in the work by Liu et al (2002 Phys. Rev. A 65 022304) and the quantum secret sharing scheme by Deng et al (2008 Phys. Lett. A 372 1957). Instead of using two sets of nonorthogonal states, the boss Alice needs only to prepare a sequence of Einstein--Podolsky--Rosen pairs in d-dimension. The two agents Bob and Charlie encode their information with dense coding unitary operations, and security is checked by inserting decoy photons. The scheme has a high capacity and intrinsic efficiency as each pair can carry 2lbd bits of information, and almost all the pairs can be used for carrying useful information.     

Stochastic resonance of a periodically driven neuron under non-Gaussian noise

We investigate the first-passage-time statistics of the integrate-fire neuron model driven by a sub-threshold harmonic signal superposed with a non-Gaussian noise. Here, we considered the noise as the result of a random multiplicative process displaced from the origin by an additive term. Such a mechanism generates a power-law distributed noise whose characteristic decay exponent can be finely tuned. We performed numerical simulations to analyze the influence of the noise non-Gaussian character on the stochastic resonance condition. We found that when the noise deviates from Gaussian statistics, the resonance condition occurs at weaker noise intensities, achieving a minimum at a finite value of the distribution function decay exponent. We discuss the possible relevance of this feature to the efficiency of the firing dynamics of biological neurons, as the present result indicates that neurons would require a lower noise level to detect a sub-threshold signal when its statistics departs from Gaussian.     

Spatial information transmission using orthogonal mutual coherence coding

We use the coherence of a light beam to encode spatial information. We apply this principle to obtain spatial superresolution in a limited aperture system. The method is based on shaping the mutual intensity function of the illumination beam in a set of orthogonal distributions, each one carrying the information for a different frequency bandpass or spatial region of the input object. The coherence coding is analogous to time multiplexing but with multiplexing time slots that are given by the coherence time of the illumination beam. Most images are static during times much longer than this coherence time, and thus the increase of resolution in our system is obtained without any noticeable cost.     

Neural signal transduction aided by noise in multisynaptic excitatory and inhibitory pathways with saturation

We study the stochastic resonance phenomenon in saturating dynamical models of neural signal transduction, at the synaptic stage, wherein the noise in multipathways enhances the processing of neuronal information integrated by excitatory and inhibitory synaptic currents. For an excitatory synaptic pathway, the additive intervention of an inhibitory pathway reduces the stochastic resonance effect. However, as the number of synaptic pathways increases, the signal transduction is greatly improved for parallel multipathways that feature both excitation and inhibition. The obtained results lead us to the realization that the collective property of inhibitory synapses assists neural signal transmission, and a parallel array of neurons can enhance their responses to multiple synaptic currents by adjusting the contributions of excitatory and inhibitory currents.     

Stochastic resonance on Newman-Watts networks of Hodgkin-Huxley neurons with local periodic driving

We study the phenomenon of stochastic resonance on Newman-Watts small-world networks consisting of biophysically realistic Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise via voltage-gated ion channels embedded in neuronal membranes. Importantly thereby, the subthreshold periodic driving is introduced to a single neuron of the network, thus acting as a pacemaker trying to impose its rhythm on the whole ensemble. We show that there exists an optimal intensity of intrinsic ion channel noise by which the outreach of the pacemaker extends optimally across the whole network. This stochastic resonance phenomenon can be further amplified via fine-tuning of the small-world network structure, and depends significantly also on the coupling strength among neurons and the driving frequency of the pacemaker. In particular, we demonstrate that the noise-induced transmission of weak localized rhythmic activity peaks when the pacemaker frequency matches the intrinsic frequency of subthreshold oscillations. The implications of our findings for weak signal detection and information propagation across neural networks are discussed.     

利用反向投影的flash场景自适应视频编码算法

针对闪光造成的光照变化会导致视频帧之间巨大的强度差异问题,提出利用反向投影的flash场景自适应视频编码算法。根据直方图差异提取闪光和非闪光帧,相应地为每个帧分配适当的编码类型,并在加权预测(WP)参数集确定中采用运动向量导数,通过反向投影保证flash场景的全局一致性。实验结果表明,相比其他几种加权预测算法,本文算法在峰值信噪比(PSNR)及计算复杂度方面获得了更加优越的编码性能。     

Implementation of physical-layer network coding

This paper presents the first implementation of a two-way relay network based on the principle of physical-layer network coding (PNC). To date, only a simplified version of PNC, called analog network coding (ANC), has been successfully implemented. The advantage of ANC is that it is simple to implement; the disadvantage, on the other hand, is that the relay amplifies the noise along with the signal before forwarding the signal. PNC systems in which the relay performs XOR or other denoising PNC mappings of the received signal have the potential for significantly better performance. However, the implementation of such PNC systems poses many challenges. For example, the relay in a PNC system must be able to deal with symbol and carrier-phase asynchronies of the simultaneous signals received from multiple nodes, and the relay must perform channel estimation before detecting the signals. We investigate a PNC implementation in the frequency domain, referred to as FPNC, to tackle these challenges. FPNC is based on OFDM. In FPNC, XOR mapping is performed on the OFDM samples in each subcarrier rather than on the samples in the time domain. We implement FPNC on the universal soft radio peripheral (USRP) platform. Our implementation requires only moderate modifications of the packet preamble design of 802.11a/g OFDM PHY. With the help of the cyclic prefix (CP) in OFDM, symbol asynchrony and the multi-path fading effects can be dealt with simultaneously in a similar fashion. Our experimental results show that symbol-synchronous and symbol-asynchronous FPNC have essentially the same BER performance, for both channel-coded and non-channel-coded FPNC systems.     

Two-step quantum secure direct communication scheme with frequency coding

Quantum secure direct communication(QSDC) is an important branch of quantum cryptography. It can transmit secret information directly without establishing a key first, unlike quantum key distribution which requires this precursory event. Here we propose a QSDC scheme by applying the frequency coding technique to the two-step QSDC protocol, which enables the two-step QSDC protocol to work in a noisy environment. We have numerically simulated the performance of the protocol in a noisy channel, and the results show that the scheme is indeed robust against channel noise and loss. We also give an estimate of the channel noise upper bound.