Due to their biological interpretability,memristors are widely used to simulate synapses between artificial neural networks.As a type of neural network whose dynamic behavior can be explained,the coupling of resonant ...Due to their biological interpretability,memristors are widely used to simulate synapses between artificial neural networks.As a type of neural network whose dynamic behavior can be explained,the coupling of resonant tunneling diode-based cellular neural networks(RTD-CNNs)with memristors has rarely been reported in the literature.Therefore,this paper designs a coupled RTD-CNN model with memristors(RTD-MCNN),investigating and analyzing the dynamic behavior of the RTD-MCNN.Based on this model,a simple encryption scheme for the protection of digital images in police forensic applications is proposed.The results show that the RTD-MCNN can have two positive Lyapunov exponents,and its output is influenced by the initial values,exhibiting multistability.Furthermore,a set of amplitudes in its output sequence is affected by the internal parameters of the memristor,leading to nonlinear variations.Undoubtedly,the rich dynamic behaviors described above make the RTD-MCNN highly suitable for the design of chaos-based encryption schemes in the field of privacy protection.Encryption tests and security analyses validate the effectiveness of this scheme.展开更多
Functional networks(FNs)hold significant promise in understanding brain function.Independent component analysis(ICA)has been applied in estimating FNs from functional magnetic resonance imaging(fMRI).However,determini...Functional networks(FNs)hold significant promise in understanding brain function.Independent component analysis(ICA)has been applied in estimating FNs from functional magnetic resonance imaging(fMRI).However,determining an optimal model order for ICA remains challenging,leading to criticism about the reliability of FN estimation.Here,we propose a SMART(splitting-merging assisted reliable)ICA method that automatically extracts reliable FNs by clustering independent components(ICs)obtained from multi-model-order ICA using a simplified graph while providing linkages among FNs deduced from different-model orders.We extend SMART ICA to multi-subject fMRI analysis,validating its effectiveness using simulated and real fMRI data.Based on simulated data,the method accurately estimates both group-common and group-unique components and demonstrates robustness to parameters.Using two age-matched cohorts of resting fMRI data comprising 1,950 healthy subjects,the resulting reliable group-level FNs are greatly similar between the two cohorts,and interestingly the subject-specific FNs show progressive changes while age increases.Furthermore,both small-scale and large-scale brain FN templates are provided as benchmarks for future studies.Taken together,SMART ICA can automatically obtain reliable FNs in analyzing multi-subject fMRI data,while also providing linkages between different FNs.展开更多
To investigate changes of functional activation areas of the cerebral cortex and the connectivity of motor cortex networks （MCNs） in stroke patients during the recovery, five patients with the infarct in their left ...To investigate changes of functional activation areas of the cerebral cortex and the connectivity of motor cortex networks （MCNs） in stroke patients during the recovery, five patients with the infarct in their left hemispheres are recruited. Functional magnetic resonance imaging （fMRI） is performed in the second, fourth, eighth, and sixteenth weeks after the stroke. Images are analyzed using the professional software SPM5 to obtain the bilateral activation of the motor cortex in left and right handgrip tests. MCN data are extracted from the active areas, and the structural and functional characteristic parameters are computed to indicate the connectivity of the network. Results show that the ipsilesional hemisphere recruits more areas with less active extent during the handgrip test, compared with the contralesional hemisphere. MCN shows a higher overall degree of statistical independence and more statistical dependence among motor areas with the gradual recovery. It can help physicians understand the recovery mechanism.展开更多
Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in bra...Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in brain activation induced by acupuncture. Thus, the time course of the therapeutic effects of acupuncture remains unclear. In this study, 32 patients with amnestic mild cognitive impairment were randomly divided into two groups, where they received either Tiaoshen Yizhi acupuncture or sham acupoint acupuncture. The needles were either twirled at Tiaoshen Yizhi acupoints, including Sishencong（EX-HN1）, Yintang（EX-HN3）, Neiguan（PC6）, Taixi（KI3）, Fenglong（ST40）, and Taichong（LR3）, or at related sham acupoints at a depth of approximately 15 mm, an angle of ± 60°, and a rate of approximately 120 times per minute. Acupuncture was conducted for 4 consecutive weeks, five times per week, on weekdays. Resting-state functional magnetic resonance imaging indicated that connections between cognition-related regions such as the insula, dorsolateral prefrontal cortex, hippocampus, thalamus, inferior parietal lobule, and anterior cingulate cortex increased after acupuncture at Tiaoshen Yizhi acupoints. The insula, dorsolateral prefrontal cortex, and hippocampus acted as central brain hubs. Patients in the Tiaoshen Yizhi group exhibited improved cognitive performance after acupuncture. In the sham acupoint acupuncture group, connections between brain regions were dispersed, and we found no differences in cognitive function following the treatment. These results indicate that acupuncture at Tiaoshen Yizhi acupoints can regulate brain networks by increasing connectivity between cognition-related regions, thereby improving cognitive function in patients with mild cognitive impairment.展开更多
Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain f...Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. Objective： To offer an overview of the different influences of acupuncture on the brain functional connec- tivity network from studies using resting-state fMRI. Search strategy： The authors performed a systematic search according to PRISMA guidelines, The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Inclusion criteria： Electronic searches were conducted in PubMed using the keywords ＂acupuncture＂ and ＂neuroimaging＂ or ＂resting-state fMRI＂ or ＂functional connectivity＂, Data extraction and analysis： Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Results： Forty-four resting-state fMRI studies were included in this systematic review according to inclu- sion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro- acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connec- tivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupunc- ture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. Conclusion： It can be presumed that the functional connectivity network is closely related to the mech- anism of acupuncture, and central integration plays a critical role in the acupuncture mechanism.展开更多
The regional specifi city of hippocampal abnormalities in late-life depression（LLD） has been demonstrated in previous studies. In this study,we sought to examine the functional connectivity（FC） patterns of hippoca...The regional specifi city of hippocampal abnormalities in late-life depression（LLD） has been demonstrated in previous studies. In this study,we sought to examine the functional connectivity（FC） patterns of hippocampal subregions in remitted late-onset depression（r LOD）,a special subtype of LLD. Fourteen r LOD patients and 18 healthy controls underwent clinical and cognitive evaluations as well as resting-state functional magnetic resonance imaging scans at baseline and at ~21 months of follow-up. Each hippocampus was divided into three parts,the cornu ammonis（CA）,the dentate gyrus,and the subicular complex,and then six seed-based hippocampal subregional networks were established.Longitudinal changes of the six networks over time were directly compared between the rL OD and control groups. From baseline to follow-up,the r LOD group showed a greater decline in connectivity of the left CA to the bilateral posterior cingulate cortex/precuneus（PCC/PCUN）,but showed increased connectivity of the right hippocampal subregional networks with the frontal cortex（bilateral medial prefrontal cortex/anterior cingulate cortex and supplementary motor area）. Further correlative analyses revealed thatthe longitudinal changes in FC between the left CA and PCC/PCUN were positively correlated with longitudinal changes in the Symbol Digit Modalities Test（r = 0.624,P = 0.017） and the Digit Span Test（r = 0.545,P = 0.044） scores in the r LOD group. These results may provide insights into the neurobiological mechanism underlying the cognitive dysfunction in r LOD patients.展开更多
Attention deficit hyperactivity disorder（ADHD） is a pervasive psychiatric disorder that affects both children and adults. Adult male and female patients with ADHD are differentially affected, but few studies have ex...Attention deficit hyperactivity disorder（ADHD） is a pervasive psychiatric disorder that affects both children and adults. Adult male and female patients with ADHD are differentially affected, but few studies have explored the differences. The purpose of this study was to quantify differences between adult male and female patients with ADHD based on neuroimaging and connectivity analysis. Resting-state functional magnetic resonance imaging scans were obtained and preprocessed in 82 patients. Group-wise differences between male and female patients were quantified using degree centrality for different brain regions. The medial-, middle-, and inferior-frontal gyrus, superior parietal lobule, precuneus, supramarginal gyrus, superior- and middle-temporal gyrus, middle occipital gyrus, and cuneus were identified as regions with significant group-wise differences. The identified regions were correlated with clinical scores reflecting depression and anxiety and significant correlations were found. Adult ADHD patients exhibit different levels of depression and anxiety depending on sex, and our study provides insight into how changes in brain circuitry might differentially impact male and female ADHD patients.展开更多
Temporal lobe resection is an important treatment option for epilepsy that involves removal of potentially essential brain regions. Selective amygdalohippocampectomy is a widely performed temporal lobe surgery. We sug...Temporal lobe resection is an important treatment option for epilepsy that involves removal of potentially essential brain regions. Selective amygdalohippocampectomy is a widely performed temporal lobe surgery. We suggest starting the incision for selective amygdalohippocampectomy at the inferior temporal gyrus based on diffusion magnetic resonance imaging（MRI） tractography. Diffusion MRI data from 20 normal participants were obtained from Parkinson＇s Progression Markers Initiative（PPMI） database（www.ppmi-info.org）. A tractography algorithm was applied to extract neuronal fiber information for the temporal lobe, hippocampus, and amygdala. Fiber information was analyzed in terms of the number of fibers and betweenness centrality. Distances between starting incisions and surgical target regions were also considered to explore the length of the surgical path. Middle temporal and superior temporal gyrus regions have higher connectivity values than the inferior temporal gyrus and thus are not good candidates for starting the incision. The distances between inferior temporal gyrus and surgical target regions were shorter than those between middle temporal gyrus and target regions. Thus, the inferior temporal gyrus is a good candidate for starting the incision. Starting the incision from the inferior temporal gyrus would spare the important（in terms of betweenness centrality values） middle region and shorten the distance to the target regions of the hippocampus and amygdala.展开更多
Based on the spatial modulation of active Raman gain,a two-dimensional gain cross-grating is theoretically proposed.As the probe field propagates along the z direction and passes through the intersectant region of the...Based on the spatial modulation of active Raman gain,a two-dimensional gain cross-grating is theoretically proposed.As the probe field propagates along the z direction and passes through the intersectant region of the two orthogonal standingwave fields in the x-y plane,it can be effectively diffracted into the high-order directions,and the zero-order diffraction intensity is amplified at the same time.In comparison with the two-dimensional electromagnetically induced cross-grating based on electromagnetically induced transparency,the two-dimensional gain cross-grating has much higher diffraction intensities in the first-order and the high-order directions.Hence,it is more suitable to be utilized as all-optical switching and routing in optical networking and communication.展开更多
Non-Hermitian topology provides an emergent research frontier for studying unconventional topological phenomena and developing new materials and applications.Here,we study the non-Hermitian Chern bands and the associa...Non-Hermitian topology provides an emergent research frontier for studying unconventional topological phenomena and developing new materials and applications.Here,we study the non-Hermitian Chern bands and the associated non-Hermitian skin effects in Floquet checkerboard lattices with synthetic gauge fluxes.Such lattices can be realized in a network of coupled resonator optical waveguides in two dimensions or in an array of evanescently coupled helical optical waveguides in three dimensions.Without invoking nonreciprocal couplings,the system exhibits versatile non-Hermitian topological phases that support various skin-topological effects.Remarkably,the non-Hermitian skin effect can be engineered by changing the symmetry,revealing rich non-Hermitian topological bulk-boundary correspondences.Our system offers excellent controllability and experimental feasibility,making it appealing for exploring diverse non-Hermitian topological phenomena in photonics.展开更多
Background Noninvasive functional magnetic resonance imaging （fMRI） techniques have opened a ＂window＂ into the brain, allowing us to investigate the anatomical and physiological function involving acupuncture need...Background Noninvasive functional magnetic resonance imaging （fMRI） techniques have opened a ＂window＂ into the brain, allowing us to investigate the anatomical and physiological function involving acupuncture needling. Imaging its sustained effect rather than acute effect on the brain networks may further help elucidate the mechanisms by which acupuncture achieves its therapeutic effects. In this study, we aimed to investigate the functional brain networks during the post-resting state following acupuncture at KI3 in comparison with acupuncture at GB40. Methods Needling at acupoints GB40 and KI3 was performed in twelve subjects. Six minutes of scanning at rest were adopted before and after acupuncture at different acupoints. Then we divided the whole brain into 39 regions and constructed functional brain networks during the post-acupuncture resting states （PARS）. Results For direct comparisons, increased correlations during post-resting state following acupuncture at KI3 compared to resting state （RS） were primarily located between the dorsolateral prefrontal cortex （DLPFC） and post temporal cortex, ventromedial prefrontal cortex （vmPFC） and post temporal cortex. These brain regions were all cognitive-related functions. In contrast, the increased connections between the anterior insula and temporal cortex mainly emerged following acupuncture at GB40 compared with the RS. Conclusions The present study demonstrates that acupuncture at different acupoints belonging to the same anatomic segment can exert different modulatory effects on the reorganizations of post-acupuncture RS networks. The heterogeneous modulation patterns between twoconditions may relate to the functional specific modulatory effects of acupuncture.展开更多
Purpose Chinese Spallation Neutron Source(CSNS)is one of the key projects of China,in which the main magnet power supplies adopt the structures of resonant networks(Wang et al.in Sci China Phys Mech Astron 54(Suppl 2)...Purpose Chinese Spallation Neutron Source(CSNS)is one of the key projects of China,in which the main magnet power supplies adopt the structures of resonant networks(Wang et al.in Sci China Phys Mech Astron 54(Suppl 2):239-244,2011).Since each network contains a lot of components,and the working state of all the components will affect the whole accelerator,it is necessary to monitor the operation of each part in the resonant network.Methods In this protections system,a supervision to 314 switch signals and 118 analog signals is realized using a chip of field programmable gate array(FPGA).The details about the hardware and software designs are introduced in this paper.Results This protection system has been used in CSNS project,and the result proves that the RCS has been well monitored by this system.Conclusions This system is a self-developed protection system according to the engineering needs of CSNS.It can realize the real-time monitoring and protection of the working state of resonance network by processing a large number of data using FPGA.展开更多
Identification of faulty feeders in resonant grounding distribution networks remains a significant challenge dueto the weak fault current and complicated working conditions.In this paper, we present a deep learning-ba...Identification of faulty feeders in resonant grounding distribution networks remains a significant challenge dueto the weak fault current and complicated working conditions.In this paper, we present a deep learning-based multi-labelclassification framework to reliably distinguish the faulty feeder.Three different neural networks (NNs) including the multilayerperceptron, one-dimensional convolutional neural network (1DCNN), and 2D CNN are built. However, the labeled data maybe difficult to obtain in the actual environment. We use thesimplified simulation model based on a full-scale test field (FSTF)to obtain sufficient labeled source data. Being different frommost learning-based methods, assuming that the distribution ofsource domain and target domain is identical, we propose asamples-based transfer learning method to improve the domainadaptation by using samples in the source domain with properweights. The TrAdaBoost algorithm is adopted to update theweights of each sample. The recorded data obtained in the FSTFare utilized to test the domain adaptability. According to ourvalidation and testing, the validation accuracies are high whenthere is sufficient labeled data for training the proposed NNs.The proposed 2D CNN has the best domain adaptability. TheTrAdaBoost algorithm can help the NNs to train an efficientclassifier that has better domain adaptation. It has been thereforeconcluded that the proposed method, especially the 2D CNN, issuitable for actual distribution networks.展开更多
In neuropathological diseases such as Alzheimer's Disease(AD),neuroimaging and Magnetic Resonance Imaging(MRI)play crucial roles in the realm of Artificial Intelligence of Medical Things(AIoMT)by leveraging edge i...In neuropathological diseases such as Alzheimer's Disease(AD),neuroimaging and Magnetic Resonance Imaging(MRI)play crucial roles in the realm of Artificial Intelligence of Medical Things(AIoMT)by leveraging edge intelligence resources.However,accurately classifying MRI scans based on neurodegenerative diseases faces challenges due to significant variability across classes and limited intra-class differences.To address this challenge,we propose a novel approach aimed at improving the early detection of AD through MRI imaging.This method integrates a Convolutional Neural Network(CNN)with a Cascade Attention Model(CAM-CNN).The CAM-CNN model outperforms traditional CNNs in AD classification accuracy and processing complexity.In this architecture,the attention mechanism is effectively implemented by utilizing two constraint cost functions and a cross-network with diverse pre-trained parameters for a two-stream architecture.Additionally,two new cost functions,Satisfied Rank Loss(SRL)and Cross-Network Similarity Loss(CNSL),are introduced to enhance collaboration and overall network performance.Finally,a unique entropy addition method is employed in the attention module for network integration,converting intermediate outcomes into the final prediction.These components are designed to work collaboratively and can be sequentially trained for optimal performance,thereby enhancing the effectiveness of AD stage classification and robustness to interference from MR images.Validation using the Kaggle dataset demonstrates the model's accuracy of 99.07%in multiclass classification,ensuring precise classification and early detection of all AD subtypes.Further validation across three feature categories with varying numbers confirms the robustness of the proposed approach,with deviations from the standard criteria of less than 1%.Applied in Alzheimer's patient care,this capability holds promise for enhancing value-based therapy and clinical decision-making.It aids in differentiating Alzheimer's patients from healthy individuals,thereby improving patient care and enabling more targeted therapies.展开更多
基金supported by the Scientific Research Fund of Hunan Provincial Education Department(Grant No.24A0248)the National Key Research and Development Program“National Quality Infrastructure System”Special Project(Grant No.2024YFF0617900)the Hefei Minglong Electronic Technology Co.,Ltd.(Grant Nos.2024ZKHX293,2024ZKHX294,and 2024ZKHX295).
文摘Due to their biological interpretability,memristors are widely used to simulate synapses between artificial neural networks.As a type of neural network whose dynamic behavior can be explained,the coupling of resonant tunneling diode-based cellular neural networks(RTD-CNNs)with memristors has rarely been reported in the literature.Therefore,this paper designs a coupled RTD-CNN model with memristors(RTD-MCNN),investigating and analyzing the dynamic behavior of the RTD-MCNN.Based on this model,a simple encryption scheme for the protection of digital images in police forensic applications is proposed.The results show that the RTD-MCNN can have two positive Lyapunov exponents,and its output is influenced by the initial values,exhibiting multistability.Furthermore,a set of amplitudes in its output sequence is affected by the internal parameters of the memristor,leading to nonlinear variations.Undoubtedly,the rich dynamic behaviors described above make the RTD-MCNN highly suitable for the design of chaos-based encryption schemes in the field of privacy protection.Encryption tests and security analyses validate the effectiveness of this scheme.
基金supported by the National Natural Science Foundation of China(62076157 and 61703253)the Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province(20210033)the National Institutes of Health(R01MH123610 and R01EB006841).
文摘Functional networks(FNs)hold significant promise in understanding brain function.Independent component analysis(ICA)has been applied in estimating FNs from functional magnetic resonance imaging(fMRI).However,determining an optimal model order for ICA remains challenging,leading to criticism about the reliability of FN estimation.Here,we propose a SMART(splitting-merging assisted reliable)ICA method that automatically extracts reliable FNs by clustering independent components(ICs)obtained from multi-model-order ICA using a simplified graph while providing linkages among FNs deduced from different-model orders.We extend SMART ICA to multi-subject fMRI analysis,validating its effectiveness using simulated and real fMRI data.Based on simulated data,the method accurately estimates both group-common and group-unique components and demonstrates robustness to parameters.Using two age-matched cohorts of resting fMRI data comprising 1,950 healthy subjects,the resulting reliable group-level FNs are greatly similar between the two cohorts,and interestingly the subject-specific FNs show progressive changes while age increases.Furthermore,both small-scale and large-scale brain FN templates are provided as benchmarks for future studies.Taken together,SMART ICA can automatically obtain reliable FNs in analyzing multi-subject fMRI data,while also providing linkages between different FNs.
基金Supported by the National Natural Science Foundation of China (30670543)~~
文摘To investigate changes of functional activation areas of the cerebral cortex and the connectivity of motor cortex networks （MCNs） in stroke patients during the recovery, five patients with the infarct in their left hemispheres are recruited. Functional magnetic resonance imaging （fMRI） is performed in the second, fourth, eighth, and sixteenth weeks after the stroke. Images are analyzed using the professional software SPM5 to obtain the bilateral activation of the motor cortex in left and right handgrip tests. MCN data are extracted from the active areas, and the structural and functional characteristic parameters are computed to indicate the connectivity of the network. Results show that the ipsilesional hemisphere recruits more areas with less active extent during the handgrip test, compared with the contralesional hemisphere. MCN shows a higher overall degree of statistical independence and more statistical dependence among motor areas with the gradual recovery. It can help physicians understand the recovery mechanism.
基金supported by the National Natural Science Foundation of China,No.81173354a grant from the Science and Technology Plan Project of Guangdong Province of China,No.2013B021800099a grant from the Science and Technology Plan Project of Shenzhen City of China,No.JCYJ20150402152005642
文摘Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in brain activation induced by acupuncture. Thus, the time course of the therapeutic effects of acupuncture remains unclear. In this study, 32 patients with amnestic mild cognitive impairment were randomly divided into two groups, where they received either Tiaoshen Yizhi acupuncture or sham acupoint acupuncture. The needles were either twirled at Tiaoshen Yizhi acupoints, including Sishencong（EX-HN1）, Yintang（EX-HN3）, Neiguan（PC6）, Taixi（KI3）, Fenglong（ST40）, and Taichong（LR3）, or at related sham acupoints at a depth of approximately 15 mm, an angle of ± 60°, and a rate of approximately 120 times per minute. Acupuncture was conducted for 4 consecutive weeks, five times per week, on weekdays. Resting-state functional magnetic resonance imaging indicated that connections between cognition-related regions such as the insula, dorsolateral prefrontal cortex, hippocampus, thalamus, inferior parietal lobule, and anterior cingulate cortex increased after acupuncture at Tiaoshen Yizhi acupoints. The insula, dorsolateral prefrontal cortex, and hippocampus acted as central brain hubs. Patients in the Tiaoshen Yizhi group exhibited improved cognitive performance after acupuncture. In the sham acupoint acupuncture group, connections between brain regions were dispersed, and we found no differences in cognitive function following the treatment. These results indicate that acupuncture at Tiaoshen Yizhi acupoints can regulate brain networks by increasing connectivity between cognition-related regions, thereby improving cognitive function in patients with mild cognitive impairment.
基金supported by the National Natural Science Foundation of China(No.81473784)University Science Research Project of Anhui Province of China(No.KJ2017A298)+1 种基金the Key Project of the Youth Elite Support Plan in Universities of Anhui Province of China(No.gxyq ZD2016134)Construction Project of Scientific Research Innovation Platform of Anhui Province of China(No.2015TD033)
文摘Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. Objective： To offer an overview of the different influences of acupuncture on the brain functional connec- tivity network from studies using resting-state fMRI. Search strategy： The authors performed a systematic search according to PRISMA guidelines, The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Inclusion criteria： Electronic searches were conducted in PubMed using the keywords ＂acupuncture＂ and ＂neuroimaging＂ or ＂resting-state fMRI＂ or ＂functional connectivity＂, Data extraction and analysis： Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Results： Forty-four resting-state fMRI studies were included in this systematic review according to inclu- sion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro- acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connec- tivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupunc- ture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. Conclusion： It can be presumed that the functional connectivity network is closely related to the mech- anism of acupuncture, and central integration plays a critical role in the acupuncture mechanism.
基金supported by the National Natural Science Foundation of China (30825014,81061120529,30970814,81371488,91132727 and 30830046)the Key Program for Clinical Medicine and Science and Technology,Jiangsu Provincial Clinical Medical Research Center,China (BL2013025)
文摘The regional specifi city of hippocampal abnormalities in late-life depression（LLD） has been demonstrated in previous studies. In this study,we sought to examine the functional connectivity（FC） patterns of hippocampal subregions in remitted late-onset depression（r LOD）,a special subtype of LLD. Fourteen r LOD patients and 18 healthy controls underwent clinical and cognitive evaluations as well as resting-state functional magnetic resonance imaging scans at baseline and at ~21 months of follow-up. Each hippocampus was divided into three parts,the cornu ammonis（CA）,the dentate gyrus,and the subicular complex,and then six seed-based hippocampal subregional networks were established.Longitudinal changes of the six networks over time were directly compared between the rL OD and control groups. From baseline to follow-up,the r LOD group showed a greater decline in connectivity of the left CA to the bilateral posterior cingulate cortex/precuneus（PCC/PCUN）,but showed increased connectivity of the right hippocampal subregional networks with the frontal cortex（bilateral medial prefrontal cortex/anterior cingulate cortex and supplementary motor area）. Further correlative analyses revealed thatthe longitudinal changes in FC between the left CA and PCC/PCUN were positively correlated with longitudinal changes in the Symbol Digit Modalities Test（r = 0.624,P = 0.017） and the Digit Span Test（r = 0.545,P = 0.044） scores in the r LOD group. These results may provide insights into the neurobiological mechanism underlying the cognitive dysfunction in r LOD patients.
基金supported in part by the Institute for Basic Science(to HP)No.IBS-R015-D1
文摘Attention deficit hyperactivity disorder（ADHD） is a pervasive psychiatric disorder that affects both children and adults. Adult male and female patients with ADHD are differentially affected, but few studies have explored the differences. The purpose of this study was to quantify differences between adult male and female patients with ADHD based on neuroimaging and connectivity analysis. Resting-state functional magnetic resonance imaging scans were obtained and preprocessed in 82 patients. Group-wise differences between male and female patients were quantified using degree centrality for different brain regions. The medial-, middle-, and inferior-frontal gyrus, superior parietal lobule, precuneus, supramarginal gyrus, superior- and middle-temporal gyrus, middle occipital gyrus, and cuneus were identified as regions with significant group-wise differences. The identified regions were correlated with clinical scores reflecting depression and anxiety and significant correlations were found. Adult ADHD patients exhibit different levels of depression and anxiety depending on sex, and our study provides insight into how changes in brain circuitry might differentially impact male and female ADHD patients.
基金supported by the National Research Foundation of Korea,No.20100023233
文摘Temporal lobe resection is an important treatment option for epilepsy that involves removal of potentially essential brain regions. Selective amygdalohippocampectomy is a widely performed temporal lobe surgery. We suggest starting the incision for selective amygdalohippocampectomy at the inferior temporal gyrus based on diffusion magnetic resonance imaging（MRI） tractography. Diffusion MRI data from 20 normal participants were obtained from Parkinson＇s Progression Markers Initiative（PPMI） database（www.ppmi-info.org）. A tractography algorithm was applied to extract neuronal fiber information for the temporal lobe, hippocampus, and amygdala. Fiber information was analyzed in terms of the number of fibers and betweenness centrality. Distances between starting incisions and surgical target regions were also considered to explore the length of the surgical path. Middle temporal and superior temporal gyrus regions have higher connectivity values than the inferior temporal gyrus and thus are not good candidates for starting the incision. The distances between inferior temporal gyrus and surgical target regions were shorter than those between middle temporal gyrus and target regions. Thus, the inferior temporal gyrus is a good candidate for starting the incision. Starting the incision from the inferior temporal gyrus would spare the important（in terms of betweenness centrality values） middle region and shorten the distance to the target regions of the hippocampus and amygdala.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11274112 and 11347133)
文摘Based on the spatial modulation of active Raman gain,a two-dimensional gain cross-grating is theoretically proposed.As the probe field propagates along the z direction and passes through the intersectant region of the two orthogonal standingwave fields in the x-y plane,it can be effectively diffracted into the high-order directions,and the zero-order diffraction intensity is amplified at the same time.In comparison with the two-dimensional electromagnetically induced cross-grating based on electromagnetically induced transparency,the two-dimensional gain cross-grating has much higher diffraction intensities in the first-order and the high-order directions.Hence,it is more suitable to be utilized as all-optical switching and routing in optical networking and communication.
文摘Non-Hermitian topology provides an emergent research frontier for studying unconventional topological phenomena and developing new materials and applications.Here,we study the non-Hermitian Chern bands and the associated non-Hermitian skin effects in Floquet checkerboard lattices with synthetic gauge fluxes.Such lattices can be realized in a network of coupled resonator optical waveguides in two dimensions or in an array of evanescently coupled helical optical waveguides in three dimensions.Without invoking nonreciprocal couplings,the system exhibits versatile non-Hermitian topological phases that support various skin-topological effects.Remarkably,the non-Hermitian skin effect can be engineered by changing the symmetry,revealing rich non-Hermitian topological bulk-boundary correspondences.Our system offers excellent controllability and experimental feasibility,making it appealing for exploring diverse non-Hermitian topological phenomena in photonics.
基金This study was supported by the grams from the National Natural Science Foundation of China （No. 81071217 and 81173354）, the Project for the National Key Basic Research and Development Program （973） （No. 2010CB530506）, the Natural Science Foundation of Guangdong Province （No. 10451810 l 01005862 and 8451040701000553）, the Fundamental Research Funds for the Central University, the Beijing Nova Program （No. Zl11101054511116）, Beijing Natural Science Foundation （No. 4122082） and the Administration of Traditional Chinese Medicine of Guangdong Province （No. 20111032）.
文摘Background Noninvasive functional magnetic resonance imaging （fMRI） techniques have opened a ＂window＂ into the brain, allowing us to investigate the anatomical and physiological function involving acupuncture needling. Imaging its sustained effect rather than acute effect on the brain networks may further help elucidate the mechanisms by which acupuncture achieves its therapeutic effects. In this study, we aimed to investigate the functional brain networks during the post-resting state following acupuncture at KI3 in comparison with acupuncture at GB40. Methods Needling at acupoints GB40 and KI3 was performed in twelve subjects. Six minutes of scanning at rest were adopted before and after acupuncture at different acupoints. Then we divided the whole brain into 39 regions and constructed functional brain networks during the post-acupuncture resting states （PARS）. Results For direct comparisons, increased correlations during post-resting state following acupuncture at KI3 compared to resting state （RS） were primarily located between the dorsolateral prefrontal cortex （DLPFC） and post temporal cortex, ventromedial prefrontal cortex （vmPFC） and post temporal cortex. These brain regions were all cognitive-related functions. In contrast, the increased connections between the anterior insula and temporal cortex mainly emerged following acupuncture at GB40 compared with the RS. Conclusions The present study demonstrates that acupuncture at different acupoints belonging to the same anatomic segment can exert different modulatory effects on the reorganizations of post-acupuncture RS networks. The heterogeneous modulation patterns between twoconditions may relate to the functional specific modulatory effects of acupuncture.
文摘Purpose Chinese Spallation Neutron Source(CSNS)is one of the key projects of China,in which the main magnet power supplies adopt the structures of resonant networks(Wang et al.in Sci China Phys Mech Astron 54(Suppl 2):239-244,2011).Since each network contains a lot of components,and the working state of all the components will affect the whole accelerator,it is necessary to monitor the operation of each part in the resonant network.Methods In this protections system,a supervision to 314 switch signals and 118 analog signals is realized using a chip of field programmable gate array(FPGA).The details about the hardware and software designs are introduced in this paper.Results This protection system has been used in CSNS project,and the result proves that the RCS has been well monitored by this system.Conclusions This system is a self-developed protection system according to the engineering needs of CSNS.It can realize the real-time monitoring and protection of the working state of resonance network by processing a large number of data using FPGA.
基金the Key Program of the Chinese Academy of Sciences under Grant QYZDJ-SSW-JSC025in part by the National Natural Science Foundation of China under Grant 51721005,and in part by the Chinese Scholarship Council(CSC).
文摘Identification of faulty feeders in resonant grounding distribution networks remains a significant challenge dueto the weak fault current and complicated working conditions.In this paper, we present a deep learning-based multi-labelclassification framework to reliably distinguish the faulty feeder.Three different neural networks (NNs) including the multilayerperceptron, one-dimensional convolutional neural network (1DCNN), and 2D CNN are built. However, the labeled data maybe difficult to obtain in the actual environment. We use thesimplified simulation model based on a full-scale test field (FSTF)to obtain sufficient labeled source data. Being different frommost learning-based methods, assuming that the distribution ofsource domain and target domain is identical, we propose asamples-based transfer learning method to improve the domainadaptation by using samples in the source domain with properweights. The TrAdaBoost algorithm is adopted to update theweights of each sample. The recorded data obtained in the FSTFare utilized to test the domain adaptability. According to ourvalidation and testing, the validation accuracies are high whenthere is sufficient labeled data for training the proposed NNs.The proposed 2D CNN has the best domain adaptability. TheTrAdaBoost algorithm can help the NNs to train an efficientclassifier that has better domain adaptation. It has been thereforeconcluded that the proposed method, especially the 2D CNN, issuitable for actual distribution networks.
基金funded by the National Elites Foundation(No.711.5095).
文摘In neuropathological diseases such as Alzheimer's Disease(AD),neuroimaging and Magnetic Resonance Imaging(MRI)play crucial roles in the realm of Artificial Intelligence of Medical Things(AIoMT)by leveraging edge intelligence resources.However,accurately classifying MRI scans based on neurodegenerative diseases faces challenges due to significant variability across classes and limited intra-class differences.To address this challenge,we propose a novel approach aimed at improving the early detection of AD through MRI imaging.This method integrates a Convolutional Neural Network(CNN)with a Cascade Attention Model(CAM-CNN).The CAM-CNN model outperforms traditional CNNs in AD classification accuracy and processing complexity.In this architecture,the attention mechanism is effectively implemented by utilizing two constraint cost functions and a cross-network with diverse pre-trained parameters for a two-stream architecture.Additionally,two new cost functions,Satisfied Rank Loss(SRL)and Cross-Network Similarity Loss(CNSL),are introduced to enhance collaboration and overall network performance.Finally,a unique entropy addition method is employed in the attention module for network integration,converting intermediate outcomes into the final prediction.These components are designed to work collaboratively and can be sequentially trained for optimal performance,thereby enhancing the effectiveness of AD stage classification and robustness to interference from MR images.Validation using the Kaggle dataset demonstrates the model's accuracy of 99.07%in multiclass classification,ensuring precise classification and early detection of all AD subtypes.Further validation across three feature categories with varying numbers confirms the robustness of the proposed approach,with deviations from the standard criteria of less than 1%.Applied in Alzheimer's patient care,this capability holds promise for enhancing value-based therapy and clinical decision-making.It aids in differentiating Alzheimer's patients from healthy individuals,thereby improving patient care and enabling more targeted therapies.
