Combined acupuncture and HuangDiSan treatment affects behavior and synaptophysin levels in the hippocampus of senescence-accelerated mouse prone 8 after neural stem cell transplantation

Sanjiao acupuncture and HuangDiSan can promote the proliferation, migration and differentiation of exogenous neural stem cells in senescence-accelerated mouse prone 8 （SAMP8） mice and can improve learning and memory impairment and behavioral function in dementia-model mice. Thus, we sought to determine whether Sanjiao acupuncture and HuangDiSan can elevate the effect of neural stem cell transplantation in Alzheimer’s disease model mice. Sanjiao acupuncture was used to stimulate Danzhong （CV17）, Zhongwan （CV12）,Qihai （CV6）, bilateral Xuehai （SP10） and bilateral Zusanli （ST36） 15 days before and after implantation of neural stem cells （5 × 10^5） into the hippocampal dentate gyrus of SAMP8 mice. Simultaneously, 0.2 mL HuangDiSan, containing Rehmannia Root and Chinese Angelica,was intragastrically administered. Our results demonstrated that compared with mice undergoing neural stem cell transplantation alone,learning ability was significantly improved and synaptophysin mRNA and protein levels were greatly increased in the hippocampus of mice undergoing both Sanjiao acupuncture and intragastric administration of HuangDiSan. We conclude that the combination of Sanjiao acupuncture and HuangDiSan can effectively improve dementia symptoms in mice, and the mechanism of this action might be related to the regulation of synaptophysin expression.

Individual Differences in Aging: Behavioral and Neural Analyses

Aged populations have remarkable variability in recent memory and cognitive mapping. Although some individuals may have substantial age-related impairments, others perform almost as well as young individuals. This paper reviews the relevant data on aged rats and indicates two challenges for biomarkers of aging. The first is to provide an appropriate quantitative description of these individual differences. The second is to use them effectively as markers for age-related changes in psychological functions and their neural substrates.

Deep Neural Network Based Behavioral Model of Nonlinear Circuits

With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recognized as a powerful tool for nonlinear system modeling. To characterize the behavior of nonlinear circuits, a DNN based modeling approach is proposed in this paper. The procedure is illustrated by modeling a power amplifier (PA), which is a typical nonlinear circuit in electronic systems. The PA model is constructed based on a feedforward neural network with three hidden layers, and then Multisim circuit simulator is applied to generating the raw training data. Training and validation are carried out in Tensorflow deep learning framework. Compared with the commonly used polynomial model, the proposed DNN model exhibits a faster convergence rate and improves the mean squared error by 13 dB. The results demonstrate that the proposed DNN model can accurately depict the input-output characteristics of nonlinear circuits in both training and validation data sets.

Analog-Circuit Model of FGH96 Superalloy Hot Deformation Behaviors Based on Artificial Neural Network

At the present time, numerical models （such as, numerical simulation based on FEM） adopted broadly in technological design and process control in forging field can not implement the realtime control of material forming process. It is thus necessary to establish a dynamic model fitting for the real-time control of material deformation processing in order to increase production efficiency, improve forging qualities and increase yields. In this paper, hot deformation behaviors of FGH96 superalloy are characterized by using hot compressive simulation experiments. The artificial neural network （ANN） model of FGH96 superalloy during hot deformation is established by using back propagation （BP） network. Then according to electrical analogy theory, its analog-circuit （AC） model is obtained through mapping the ANN model into analog circuit. Testing results show that the ANN model and the AC model of FGH96 superalloy hot deformation behaviors possess high predictive precisions and can well describe the superalloy＇s dynamic flow behaviors. The ideas proposed in this paper can be applied in the real-time control of material deformation processing.

LONG-TIME BEHAVIOR OF TRANSIENT SOLUTIONS FOR CELLULAR NEURAL NETWORK SYSTEMS

By establishing concept an transient solutions of general nonlinear systems converging to its equilibrium set, long-time behavior of solutions for cellular neural network systems is studied. A stability condition in generalized sense is obtained. This result reported has an important guide to concrete neural network designs.

基于物联网和卷积神经网络的智能农机安全驾驶系统

基于物联网和卷积神经网络的智能农机安全驾驶系统是一种创新的农业技术应用,通过将农机设备的摄像装置连接到互联网上,实现对农机设备和驾驶员的实时监测和数据采集;再利用卷积神经网络技术对采集到的驾驶数据进行特征提取和驾驶行为分类与识别,实现对驾驶行为的自动监测和预警。实验结果表明:系统对驾驶行为的类别检测准确率较高,可以提高农机驾驶安全性和驾驶效率,为农业生产提供更加智能化和高效的服务。

Acute histopathological responses and long-term behavioral outcomes in mice with graded controlled cortical impact injury

While animal models of controlled cortical impact often display short-term motor dysfunction after injury, histological examinations do not show severe cortical damage. Thus, this model requires further improvement. Mice were subjected to injury at three severities using a Pin-Point^(TM)-controlled cortical impact device to establish secondary brain injury mouse models. Twenty-four hours after injury, hematoxylin-eosin staining, Fluoro-Jade B histofluorescence, and immunohistochemistry were performed for brain slices. Compared to the uninjured side, we observed differences of histopathological findings, neuronal degeneration, and glial cell number in the CA2 and CA3 regions of the hippocampus on the injured side. The Morris water maze task and beam-walking test verified long-term(14–28 days) spatial learning/memory and motor balance. To conclude, the histopathological responses were positively correlated with the degree of damage,as were the long-term behavioral manifestations after controlled cortical impact. All animal procedures were approved by the Institutional Animal Care and Use Committee at Shanghai Jiao Tong University School of Medicine.

Neural mechanism of proposer's decision-making in the ultimatum and dictator games

Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer＇s decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. ＂The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.

Human neural stem cells promote proliferation of endogenous neural stem cells and enhance angiogenesis in ischemic rat brain

Transplantation of human neural stem cells into the dentate gyrus or ventricle of rodents has been reportedly to enhance neurogenesis. In this study, we examined endogenous stem cell proliferation and angiogenesis in the ischemic rat brain after the transplantation of human neural stem cells. Focal cerebral ischemia in the rat brain was induced by middle cerebral artery occlusion. Human neural stem cells were transplanted into the subventricular zone. The behavioral performance of human neural stem cells-treated ischemic rats was significantly improved and cerebral infarct volumes were reduced compared to those in untreated animals. Numerous transplanted human neural stem cells were alive and preferentially localized to the ipsilateral ischemic hemisphere. Furthermore, 5-bromo-2′-deoxyuridine-labeled endogenous neural stem cells were observed in the subventricular zone and hippocampus, where they differentiated into cells immunoreactive for the neural markers doublecortin, neuronal nuclear antigen Neu N, and astrocyte marker glial fibrillary acidic protein in human neural stem cells-treated rats, but not in the untreated ischemic animals. The number of 5-bromo-2′-deoxyuridine-positive ？ anti-von Willebrand factor-positive proliferating endothelial cells was higher in the ischemic boundary zone of human neural stem cells-treated rats than in controls. Finally, transplantation of human neural stem cells in the brains of rats with focal cerebral ischemia promoted the proliferation of endogenous neural stem cells and their differentiation into mature neural-like cells, and enhanced angiogenesis. This study provides valuable insights into the effect of human neural stem cell transplantation on focal cerebral ischemia, which can be applied to the development of an effective therapy for stroke.

A Short Glance at the Neural Circuitry Mechanism Underlying Depression

Depression leads to a large social burden because of its substantial impairment and disability in everyday activities. The prevalence and considerable impact of this disorder call for a better understanding of its pathophysiology to improve the diagnosis, treatment and prevention. Though productive animal models and pathophysiological theories have been documented, it is still very far to uncover the complex array of symptoms caused by depression. Moreover, the neural circuitry mechanism underlying behavioral changes in some depression-like behavior animals is still limited. Changes in the neural circuitry of amygdala, dorsal raphe nucleus, ventral tegmental area, hippocampus, locus coeruleus and nucleus accumbens are related to depression. However, the interactions between individual neural circuitry of different brain areas, have not yet been fully elucidated. The purpose of the present review is to examine and summarize the current evidence for the pathophysiological mechanism of depression, with a focus on the neural circuitry, and emphasize the necessity and importance of integrating individual neural circuitry in different brain regions to understand depression.

916 MHz electromagnetic field exposure affects rat behavior and hippocampal neuronal discharge

Wistar rats were exposed to a 916 MHz, 10 W/m2 mobile phone electromagnetic field for 6 hours a day 5 days a week. Average completion times in an eight-arm radial maze were longer in the exposed rats than control rats after 4-5 weeks of exposure. Error rates in the exposed rats were greater than the control rats at 6 weeks. Hippocampal neurons from the exposed rats showed irregular firing patterns during the experiment, and they exhibited decreased spiking activity 6-9 weeks compared with that after 2 5 weeks of exposure. These results indicate that 916 MHz electromagnetic fields influence leaming and memory in rats during exposure, but long-term effects are not obvious.

Brain Signaling in Psychiatric Disorders: What Can They Tell Us in the Absence of Behavioral Differences?

This is a commentary on the often-observed phenomenon of observing task-based brain signaling differences between clinical populations and healthy control participants in the absence of any behavioral decrements in the clinical group. We offer several explanations for why brain-based differences amid normative performance may be of interest to researchers and clinicians. First, neural processing in the clinical group may not be as efficient as that in the control group. Second, differences in activation could reveal important differences in the cognition behind the (normative) behavior. Third, differences in activation may be prognostic biomarkers of injury or decline. In addition, we contend that similar behavior between groups is important in properly interpreting brain data. Finally, we offer caveats and future directions to further clarify brain mechanisms underlying behavior in clinical populations.

Covid-19 Diagnosis by Artificial Intelligence Based on Vibraimage Measurement of Behavioral Parameters

The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional reflex parameters on COVID-19, various diseases and pathologies are proposed. Micro-movements of a head for representatives of the control group (with a confirmed absence of COVID-19 disease) and a group of patients with a confirmed diagnosis of COVID-19 were studied using vibraimage technology. Parameters and criteria for the diagnosis of COVID-19 for training artificial intelligence (AI) on the control group and the patient group are proposed. 3-layer (one hidden layer) feedforward neural network (40 + 20 + 1 sigmoid neurons) was developed for AI training. AI was firstly trained on the primary sample of patients and a control group. Study of a random sample of people with trained AI was carried out and the possibility of detecting COVID-19 using the proposed method was proved a week before the onset of clinical symptoms of the disease. Number of COVID-19 diagnostic parameters was increased to 26 and AI was trained on a sample of 536 measurements, 268 patient measurement results and 268 measurement results in the control group. The achieved diagnostic accuracy was more than 99%, 4 errors per 536 measurements (2 false positive and 2 false negative), specificity 99.25% and sensitivity 99.25%. The issues of improving the accuracy and reliability of the proposed method for diagnosing COVID-19 are discussed. Further ways to improve the characteristics and applicability of the proposed method of diagnosis and self-diagnosis of COVID-19 are outlined.

Automated monitoring of early neurobehavioral changes in mice following traumatic brain injury

Traumatic brain injury often causes a variety of behavioral and emotional impairments that can develop into chronic disorders. Therefore, there is a need to shift towards identifying early symptoms that can aid in the prediction of traumatic brain injury outcomes and behavioral endpoints in patients with traumatic brain injury after early interventions. In this study, we used the Smart Cage system, an automated quantitative approach to assess behavior alterations in mice during an early phase of traumatic brain injury in their home cages. Female C57BL/6 adult mice were subjected to moderate controlled cortical impact（CCI） injury. The mice then received a battery of behavioral assessments including neurological score, locomotor activity, sleep/wake states, and anxiety-like behaviors on days 1, 2, and 7 after CCI. Histological analysis was performed on day 7 after the last assessment. Spontaneous activities on days 1 and 2 after injury were significantly decreased in the CCI group. The average percentage of sleep time spent in both dark and light cycles were significantly higher in the CCI group than in the sham group. For anxiety-like behaviors, the time spent in a light compartment and the number of transitions between the dark/light compartments were all significantly reduced in the CCI group than in the sham group. In addition, the mice suffering from CCI exhibited a preference of staying in the dark compartment of a dark/light cage. The CCI mice showed reduced neurological score and histological abnormalities, which are well correlated to the automated behavioral assessments. Our findings demonstrate that the automated Smart Cage system provides sensitive and objective measures for early behavior changes in mice following traumatic brain injury.

双酚G对斑马鱼神经行为的影响及机制研究

使用双酚G(BPG)慢性染毒成年斑马鱼,以评估其毒性效应和作用机制.结果表明,50μg/L BPG染毒组显著降低了斑马鱼的移动距离和上下水层切换频率,在底部累积时间增加了22.7%,表现出显著的行为异常;5和50μg/L染毒导致社交距离分别增加了126.8%和151.2%,社交累积时间分别减少了80.1%和73.7%,表现出显著的社交障碍.切片染色显示脑结构和肠道绒毛受损以及肠道杯状细胞数量和粘液分泌增加,表明潜在的肠道炎症以及神经疾病的发生.进一步的靶向代谢组学显示肠脑神经递质水平紊乱,色氨酸、GABA、谷氨酰胺、去甲肾上腺素、胆碱和组胺等水平显著改变;KEGG通路富集分析表明,苯丙氨酸、酪氨酸和色氨酸生物合成,缬氨酸、亮氨酸和异亮氨酸生物合成,精氨酸生物合成及苯丙氨酸代谢是主要受影响通路且存在性别差异,这些通路通过干扰神经递质转运和稳态,调控斑马鱼行为.BPG染毒,斑马鱼表现出显著的神经行为毒性效应和肠脑神经递质代谢紊乱,肠脑调节可能参与介导该效应.

基于多模态神经网络流量特征的网络应用层DDoS攻击检测方法

农业设备、传感器和监控系统与网络的连接日益紧密,给农村配电网带来了新的网络安全挑战。其中,分布式拒绝服务(DDoS)攻击是一种常见的网络威胁,对农村配电网的安全性构成了严重威胁。针对农村配电网的特殊需求,提出一种基于多模态神经网络流量特征的网络应用层DDoS攻击检测方法。通过制定网络应用层流量数据包捕获流程并构建多模态神经网络模型,成功提取并分析了网络应用层DDoS攻击流量的特征。在加载DDoS攻击背景下的异常流量特征后,计算相关系数并设计相应的DDoS攻击检测规则,以实现对DDoS攻击的有效检测。经试验分析,所提出的方法在提取DDoS攻击相关特征上表现出色,最大提取完整度可达95%,效果明显优于对比试验中基于EEMD-LSTM的检测方法和基于条件熵与决策树的检测方法。

基于自注意力卷积神经网络的吸烟行为识别方法

卷积神经网络因其强大的特征提取能力,已成为当前视觉行为识别任务中的主流方法。为应对公共场所吸烟行为有效监测预警,文章提出了一种基于自注意力卷积神经网络的吸烟行为识别方法。通过分析吸烟行为在图像和视频中的关键特征,设计了一种高效的卷积神经网络模型。该模型通过引入自注意力机制,能准确高效提取图像的关键特征,以实现对吸烟行为的准确识别。实验结果表明,所提出的方法在不同场景下均表现出良好的识别效果和鲁棒性,具有较高的实用价值。

深度神经网络修复策略综述

随着智能信息时代的发展,深度神经网络在人类社会众多领域中的应用,尤其是在自动驾驶、军事国防等安全攸关系统中的部署,引起了学术界和工业界对神经网络模型可能表现出的错误行为的担忧.虽然神经网络验证和神经网络测试可以提供关于错误行为的定性或者定量结论,但这种事后分析并不能防止错误行为的发生,如何修复表现出错误行为的预训练神经网络模型依然是极具挑战性的问题.为此,深度神经网络修复这一领域应运而生,旨在消除有缺陷的神经网络产生的错误预测,使得神经网络满足特定的规约性质.目前为止,典型的神经网络修复范式有3种:重训练、无错误定位的微调和包含错误定位的微调.介绍深度神经网络的发展和神经网络修复的必要性;厘清相近概念;明确神经网络修复的挑战;详尽地调研目前已有的神经网络修复策略,并对内在联系与区别进行分析和比较;调研整理神经网络修复策略常用的评价指标和基准测试;展望未来神经网络修复领域研究中需要重点关注的可行方向.

糖类与甜味剂的肠-脑轴效应研究进展及评估方法分析

尽管甜味剂能够提供类似糖类的风味感受和远高于糖类的甜味强度,但仍旧不能完全替代糖类所带来的满足感,明确该现象的生物学机制对于完善甜味剂的功能评估体系和指导甜味剂的创新发展方向都具有十分重要的意义。本文系统综述了糖类与甜味剂引发的动物行为偏好差异、动物脑区活动差异和肠-脑轴神经激活模式差异3个方面的研究进展,揭示了大脑可以辨别糖和甜味剂,从而产生个体行为偏好差异的深层原因,提出动物行为学、脑区神经活动和关键受体激活能力可用于评估甜味剂肠-脑轴效应,可为甜味剂领域的创新发展提供参考。

Correlation between photoreceptor injury-regeneration and behavior in a zebrafish model

Direct exposure to intensive visible light can lead to solar retinopathy, including macular injury. The signs and symptoms include central scotoma, metamorphopsia, and decreased vision. However, there have been few studies examining retinal injury due to intensive light stimulation at the cellular level. Neural network arrangements and gene expression patterns in zebrafish photoreceptors are similar to those observed in humans, and photoreceptor injury in zebrafish can induce stem cell-based cellular regeneration. Therefore, the zebrafish retina is considered a useful model for studying photoreceptor injury in humans. In the current study, the central retinal photoreceptors of zebrafish were selectively ablated by stimulation with high-intensity light. Retinal injury, cell proliferation and regeneration of cones and rods were assessed at 1, 3 and 7 days post lesion with immunohistochemistry and in situ hybridization. Additionally, a light/dark box test was used to assess zebrafish behavior. The results revealed that photoreceptors were regenerated by 7 days after the light-induced injury. However, the regenerated cells showed a disrupted arrangement at the lesion site. During the injury-regeneration process, the zebrafish exhibited reduced locomotor capacity, weakened phototaxis and increased movement angular velocity. These behaviors matched the morphological changes of retinal injury and regeneration in a number of ways. This study demonstrates that the zebrafish retina has a robust capacity for regeneration. Visual impairment and stress responses following high-intensity light stimulation appear to contribute to the alteration of behaviors.