Dynamical Behavior of the Stochastic Delay Mutualism System

We discuss the dynamical behavior of the stochastic delay three-specie mutualism system. We develop the technique for stochastic differential equations to deal with the asymptotic property. Using it we obtain the existence of the unique positive solution, the asymptotic properties, and the nonpersistence. Finally, we give the numerical examinations to illustrate our results

Regulation of Irregular Neuronal Firing by Autaptic Transmission

The importance of self-feedback autaptic transmission in modulating spike-time irregularity is still poorly understood. By using a biophysical model that incorporates autaptic coupling, we here show that self-innervation of neurons participates in the modulation of irregular neuronal firing, primarily by regulating the occurrence frequency of burst firing. In particular, we find that both excitatory and electrical autapses increase the occurrence of burst firing, thus reducing neuronal firing regularity. In contrast, inhibitory autapses suppress burst firing and therefore tend to improve the regularity of neuronal firing. Importantly, we show that these findings are independent of the firing properties of individual neurons, and as such can be observed for neurons operating in different modes. Our results provide an insightful mechanistic understanding of how different types of autapses shape irregular firing at the single-neuron level, and they highlight the functional importance of autaptic self-innervation in taming and modulating neurodynamics.Comment: 27 pages, 8 figure

Persistence and Nonpersistence of a Nonautonomous Stochastic Mutualism System

In this paper, a two-species nonautonomous stochastic mutualism system is investigated. The intrinsic growth rates of the two species at time t are estimated by rit+σitB˙i(t),  i=1,2, respectively. Viewing the different intensities of the noises σi(t), i=1,2 as two parameters at time t, we conclude that there exists a global positive solution and the pth moment of the solution is bounded. We also show that the system is permanent, including stochastic permanence, persistence in mean, and asymptotic boundedness in time average. Besides, we show that the large white noise will make the system nonpersistent. Finally, we establish sufficient criteria for the global attractivity of the system

A Synapse-Threshold Synergistic Learning Approach for Spiking Neural Networks

Spiking neural networks (SNNs) have demonstrated excellent capabilities in various intelligent scenarios. Most existing methods for training SNNs are based on the concept of synaptic plasticity; however, learning in the realistic brain also utilizes intrinsic non-synaptic mechanisms of neurons. The spike threshold of biological neurons is a critical intrinsic neuronal feature that exhibits rich dynamics on a millisecond timescale and has been proposed as an underlying mechanism that facilitates neural information processing. In this study, we develop a novel synergistic learning approach that simultaneously trains synaptic weights and spike thresholds in SNNs. SNNs trained with synapse-threshold synergistic learning (STL-SNNs) achieve significantly higher accuracies on various static and neuromorphic datasets than SNNs trained with two single-learning models of the synaptic learning (SL) and the threshold learning (TL). During training, the synergistic learning approach optimizes neural thresholds, providing the network with stable signal transmission via appropriate firing rates. Further analysis indicates that STL-SNNs are robust to noisy data and exhibit low energy consumption for deep network structures. Additionally, the performance of STL-SNN can be further improved by introducing a generalized joint decision framework (JDF). Overall, our findings indicate that biologically plausible synergies between synaptic and intrinsic non-synaptic mechanisms may provide a promising approach for developing highly efficient SNN learning methods.Comment: 13 pages, 9 figures, submitted for publicatio

A Spatial-channel-temporal-fused Attention for Spiking Neural Networks

Spiking neural networks (SNNs) mimic brain computational strategies, and exhibit substantial capabilities in spatiotemporal information processing. As an essential factor for human perception, visual attention refers to the dynamic selection process of salient regions in biological vision systems. Although mechanisms of visual attention have achieved great success in computer vision, they are rarely introduced into SNNs. Inspired by experimental observations on predictive attentional remapping, we here propose a new spatial-channel-temporal-fused attention (SCTFA) module that can guide SNNs to efficiently capture underlying target regions by utilizing historically accumulated spatial-channel information. Through a systematic evaluation on three event stream datasets (DVS Gesture, SL-Animals-DVS and MNIST-DVS), we demonstrate that the SNN with the SCTFA module (SCTFA-SNN) not only significantly outperforms the baseline SNN (BL-SNN) and other two SNN models with degenerated attention modules, but also achieves competitive accuracy with existing state-of-the-art methods. Additionally, our detailed analysis shows that the proposed SCTFA-SNN model has strong robustness to noise and outstanding stability to incomplete data, while maintaining acceptable complexity and efficiency. Overall, these findings indicate that appropriately incorporating cognitive mechanisms of the brain may provide a promising approach to elevate the capability of SNNs.Comment: 12 pages, 8 figures, 5 tabes; This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Dexmedetomidine provides renoprotection against ischemia-reperfusion injury in mice

Abstract Introduction Acute kidney injury following surgery incurs significant mortality with no proven preventative therapy. We investigated whether the α2 adrenoceptor agonist dexmedetomidine (Dex) provides protection against ischemia-reperfusion induced kidney injury in vitro and in vivo. Methods In vitro, a stabilised cell line of human kidney proximal tubular cells (HK2) was exposed to culture medium deprived of oxygen and glucose. Dex decreased HK2 cell death in a dose-dependent manner, an effect attenuated by the α2 adrenoceptor antagonist atipamezole, and likely transduced by phosphatidylinositol 3-kinase (PI3K-Akt) signaling. In vivo C57BL/6J mice received Dex (25 μg/kg, intraperitoneal (i.p.)) 30 minutes before or after either bilateral renal pedicle clamping for 25 minutes or right renal pedicle clamping for 40 minutes and left nephrectomy. Results Pre- or post-treatment with Dex provided cytoprotection, improved tubular architecture and function following renal ischemia. Consistent with this cytoprotection, dexmedetomidine reduced plasma high-mobility group protein B1 (HMGB-1) elevation when given prior to or after kidney ischemia-reperfusion; pretreatment also decreased toll-like receptor 4 (TLR4) expression in tubular cells. Dex treatment provided long-term functional renoprotection, and even increased survival following nephrectomy. Conclusions Our data suggest that Dex likely activates cell survival signal pAKT via α2 adrenoceptors to reduce cell death and HMGB1 release and subsequently inhibits TLR4 signaling to provide reno-protection

Portable near-infrared diffusive light imager for breast cancer detection

We present a frequency-domain near-infrared optical tomography system designed for breast cancer detection, in conjunction, with conventional ultrasound. It features fast optical switching, threewavelength excitations, and avalanche photodiode as detectors. Laser diodes at 660, 780, and 830 nm are used as light sources and their outputs are distributed sequentially to one of nine source fibers. An equivalent 130-dB isolation between electrical signals from different source channels is achieved with the optical switches of very low crosstalk. Ten detection channels, each of which includes a silicon avalanche photodiode, detect diffusive photon density waves simultaneously. The dynamic range of an avalanche photodiode is about 20 to 30 dB higher than that of a photomultiplier tube, thus eliminating the need for multistep system gain control. The entire system is compact in size (<0.051 m3) and fast in data acquisition (less than 2 sec for a complete scan). Calibration and the clinical experiment results are presented in the paper.Electrical and Computer Engineerin

Ambient Temperature and Stroke Occurrence: A Systematic Review and Meta-Analysis

Abstract: Biologically plausible associations exist between climatic conditions and stroke risk, but study results are inconsistent. We aimed to summarize current evidence on ambient temperature and overall stroke occurrence, and by age, sex, and variation of temperature. We performed a systematic literature search across MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, and GEOBASE, from inception to 16 October 2015 to identify all population-based observational studies. Where possible, data were pooled for meta-analysis with Odds ratios (OR) and corresponding 95% confidence intervals (CI) by means of the random effects meta-analysis. We included 21 studies with a total of 476,511 patients. The data were varied as indicated by significant heterogeneity across studies for both ischemic stroke (IS) and intracerebral hemorrhage (ICH). Pooled OR (95% CI) in every 1 degree Celsius increase in ambient temperature was significant for ICH 0.97 (0.94–1.00), but not for IS 1.00 (0.99–1.01) and subarachnoid hemorrhage (SAH) 1.00 (0.98–1.01). Meta-analysis was not possible for the pre-specified subgroup analyses by age, sex, and variation of temperature. Change in temperature over the previous 24 h appeared to be more important than absolute temperature in relation to the risk of stroke, especially in relation to the risk of ICH. Older age appeared to increase vulnerability to low temperature for both IS and ICH. To conclude, this review shows that lower mean ambient temperature is significantly associated with the risk of ICH, but not with IS and SAH. Larger temperature changes were associated with higher stroke rates in the elderly