BACKGROUND Adolescent major depressive disorder(MDD)is a significant mental health concern that often leads to recurrent depression in adulthood.Resting-state functional magnetic resonance imaging(rs-fMRI)offers uniqu...BACKGROUND Adolescent major depressive disorder(MDD)is a significant mental health concern that often leads to recurrent depression in adulthood.Resting-state functional magnetic resonance imaging(rs-fMRI)offers unique insights into the neural mechanisms underlying this condition.However,despite previous research,the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated.AIM To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation(ALE)meta-analysis.METHODS We performed a comprehensive literature search through July 12,2023,for studies investigating brain functional changes in adolescent MDD patients.We utilized regional homogeneity(ReHo),amplitude of low-frequency fluctuations(ALFF)and fractional ALFF(fALFF)analyses.We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls(HCs)using ALE.RESULTS Ten studies(369 adolescent MDD patients and 313 HCs)were included.Combining the ReHo and ALFF/fALFF data,the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs(voxel size:648 mm3,P<0.05),and no brain region exhibited increased activity.Based on the ALFF data,we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients(voxel size:736 mm3,P<0.05),with no regions exhibiting increased activity.CONCLUSION Through ALE meta-analysis,we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients,increasing our understanding of the neuropathology of affected adolescents.展开更多
BACKGROUND Attention deficit hyperactivity disorder(ADHD)is a prevalent neurodevelopmental disorder in adolescents characterized by inattention,hyperactivity,and impulsivity,which impact cognitive,behavioral,and emoti...BACKGROUND Attention deficit hyperactivity disorder(ADHD)is a prevalent neurodevelopmental disorder in adolescents characterized by inattention,hyperactivity,and impulsivity,which impact cognitive,behavioral,and emotional functioning.Resting-state functional magnetic resonance imaging(rs-fMRI)provides critical insights into the functional architecture of the brain in ADHD.Despite extensive research,specific brain regions consistently affected in ADHD patients during these formative years have not been comprehensively delineated.AIM To identify consistent vulnerable brain regions in adolescent ADHD patients using rs-fMRI and activation likelihood estimation(ALE)meta-analysis.METHODS We conducted a comprehensive literature search up to August 31,2024,to identify studies investigating functional brain alterations in adolescents with ADHD.We utilized regional homogeneity(ReHo),amplitude of low-frequency fluctuations(ALFF),dynamic ALFF(dALFF)and fractional ALFF(fALFF)analyses.We compared the regions of aberrant spontaneous neural activity in adolescents with ADHD with those in healthy controls(HCs)using ALE.RESULTS Fifteen studies(468 adolescent ADHD patients and 466 HCs)were included.Combining the ReHo and ALFF/fALFF/dALFF data,the results revealed increased activity in the right lingual gyrus[LING,Brodmann Area(BA)18],left LING(BA 18),and right cuneus(CUN,BA 23)in adolescent ADHD patients compared with HCs(voxel size:592-32 mm³,P<0.05).Decreased activity was observed in the left medial frontal gyrus(MFG,BA 9)and left precuneus(PCUN,BA 31)in adolescent ADHD patients compared with HCs(voxel size:960-456 mm³,P<0.05).Jackknife sensitivity analyses demonstrated robust reproducibility in 11 of the 13 tests for the right LING,left LING,and right CUN and in 11 of the 14 tests for the left MFG and left PCUN.CONCLUSION We identified specific brain regions with both increased and decreased activity in adolescent ADHD patients,enhancing our understanding of the neural alterations that occur during this pivotal stage of development.展开更多
This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent ...This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent to maximizing its logarithm, so the objective function ＇obj.fun＇ is maximizing log-likelihood function. Monte Carlo method adapted for implementing and designing the experiments of this simulation. This study including a comparison among three versions of PSO algorithm “Constriction coefficient CCPSO, Inertia weight IWPSO, and Fully Informed FIPSO”, the experiments designed by setting different values of model parameters al, bs sample size n, moreover the parameters of PSO algorithms. MSE used as test statistic to measure the efficiency PSO to estimate model. The results show the ability of PSO to estimate ARMA＇ s parameters, and the minimum values of MSE getting for COPSO.展开更多
The calibration of transfer functions is essential for accurate pavement performance predictions in the PavementME design. Several studies have used the least square approach to calibrate these transfer functions. Lea...The calibration of transfer functions is essential for accurate pavement performance predictions in the PavementME design. Several studies have used the least square approach to calibrate these transfer functions. Least square is a widely used simplistic approach based on certain assumptions. Literature shows that these least square approach assumptions may not apply to the non-normal distributions. This study introduces a new methodology for calibrating the transverse cracking and international roughness index(IRI) models in rigid pavements using maximum likelihood estimation(MLE). Synthetic data for transverse cracking, with and without variability, are generated to illustrate the applicability of MLE using different known probability distributions(exponential,gamma, log-normal, and negative binomial). The approach uses measured data from the Michigan Department of Transportation's(MDOT) pavement management system(PMS) database for 70 jointed plain concrete pavement(JPCP) sections to calibrate and validate transfer functions. The MLE approach is combined with resampling techniques to improve the robustness of calibration coefficients. The results show that the MLE transverse cracking model using the gamma distribution consistently outperforms the least square for synthetic and observed data. For observed data, MLE estimates of parameters produced lower SSE and bias than least squares(e.g., for the transverse cracking model, the SSE values are 3.98 vs. 4.02, and the bias values are 0.00 and-0.41). Although negative binomial distribution is the most suitable fit for the IRI model for MLE, the least square results are slightly better than MLE. The bias values are-0.312 and 0.000 for the MLE and least square methods. Overall, the findings indicate that MLE is a robust method for calibration, especially for non-normally distributed data such as transverse cracking.展开更多
目的通过激活似然估计(ALE)的荟萃分析方法探讨感觉神经性耳聋(SNHL)病人的脑自发活动改变特点,进一步了解SNHL可能存在的脑功能损伤及重塑的神经机制。方法检索2023年8月21日之前Web of Science、PubMed、CNKI、万方医学网、中华医学...目的通过激活似然估计(ALE)的荟萃分析方法探讨感觉神经性耳聋(SNHL)病人的脑自发活动改变特点,进一步了解SNHL可能存在的脑功能损伤及重塑的神经机制。方法检索2023年8月21日之前Web of Science、PubMed、CNKI、万方医学网、中华医学期刊全文数据库中采用局部一致性(ReHo)及低频振幅/分数低频振幅(ALFF/fALFF)分析SNHL病人脑功能改变的文献,按照纳排标准对文献筛选后,采用激活似然估计法(ALE)纳入研究中SNHL病人自发脑神经活动异常的脑区进行Meta分析。结果共纳入22篇29项研究(SNHL 736例,对照487例),其中ReHo研究11项,ALFF/fALFF研究18项。联合ReHo/ALFF/fALFF分析方法且不区分耳聋侧别结果显示SNHL病人左侧丘脑背内侧核自发脑活动增加,左侧颞上回、左侧额下回岛盖部及左侧背外侧前额叶自发脑活动减低。分别依次对左/右耳SNHL病人、ReHo和ALFF/fALFF方法进行ALE分析,结果均未见任何异常活动脑区。结论运用ALE荟萃分析方法证实SNHL病人多个脑区存在自发活动异常,有助于进一步了解SNHL脑功能损伤及重塑的规律及特征,为其后续诊疗评估提供重要依据。展开更多
In this paper,we present a novel particle filter(PF)-based direct position tracking method utilizing multiple distributed observation stations.Traditional passive tracking methods are anchored on repetitive position e...In this paper,we present a novel particle filter(PF)-based direct position tracking method utilizing multiple distributed observation stations.Traditional passive tracking methods are anchored on repetitive position estimation,where the set of consecutive estimates provides the tracking trajectory,such as Two-step and direct position determination methods.However,duplicate estimates can be computationally expensive.In addition,these techniques suffer from data association problems.The PF algorithm is a tracking method that avoids these drawbacks,but the conventional PF algorithm is unable to construct a likelihood function from the received signals of multiple observatories to determine the weights of particles.Therefore,we developed an improved PF algorithm with the likelihood function modified by the projection approximation subspace tracking with deflation(PASTd)algorithm.The proposed algorithm uses the projection subspace and spectral function to replace the likelihood function of PF.Then,the weights of particles are calculated jointly by multiple likelihood functions.Finally,the tracking problem of multiple targets is solved by multiple sets of particles.Simulations demonstrate the effectiveness of the proposed method in terms of computational complexity and tracking accuracy.展开更多
In virtue of the notion of likelihood ratio and moment generating function, the limit properties of the sequences of absolutely continuous random variables are studied, and a class of strong limit theorems represented...In virtue of the notion of likelihood ratio and moment generating function, the limit properties of the sequences of absolutely continuous random variables are studied, and a class of strong limit theorems represented by inequalities with random bounds are obtained.展开更多
OBJECTIVE: The objective of this study is to summarize and analyze the brain signal patterns of empathy for pain caused by facial expressions of pain utilizing activation likelihood estimation, a meta-analysis method....OBJECTIVE: The objective of this study is to summarize and analyze the brain signal patterns of empathy for pain caused by facial expressions of pain utilizing activation likelihood estimation, a meta-analysis method. DATA SOURCES: Studies concerning the brain mechanism were searched from the Science Citation Index, Science Direct, PubMed, DeepDyve, Cochrane Library, SinoMed, Wanfang, VIP, China National Knowledge Infrastructure, and other databases, such as SpringerLink, AMA, Science Online, Wiley Online, were collected. A time limitation of up to 13 December 2016 was applied to this study. DATA SELECTION: Studies presenting with all of the following criteria were considered for study inclusion: Use of functional magnetic resonance imaging, neutral and pained facial expression stimuli, involvement of adult healthy human participants over 18 years of age, whose empathy ability showed no difference from the healthy adult, a painless basic state, results presented in Talairach or Montreal Neurological Institute coordinates, multiple studies by the same team as long as they used different raw data. OUTCOME MEASURES: Activation likelihood estimation was used to calculate the combined main activated brain regions under the stimulation of pained facial expression. RESULTS: Eight studies were included, containing 178 subjects. Meta-analysis results suggested that the anterior cingulate cortex(BA32), anterior central gyrus(BA44), fusiform gyrus, and insula(BA13) were activated positively as major brain areas under the stimulation of pained facial expression. CONCLUSION: Our study shows that pained facial expression alone, without viewing of painful stimuli, activated brain regions related to pain empathy, further contributing to revealing the brain's mechanisms of pain empathy.展开更多
基金Supported by The 2024 Guizhou Provincial Health Commission Science and Technology Fund Project,No.gzwkj2024-47502022 Provincial Clinical Key Specialty Construction Project。
文摘BACKGROUND Adolescent major depressive disorder(MDD)is a significant mental health concern that often leads to recurrent depression in adulthood.Resting-state functional magnetic resonance imaging(rs-fMRI)offers unique insights into the neural mechanisms underlying this condition.However,despite previous research,the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated.AIM To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation(ALE)meta-analysis.METHODS We performed a comprehensive literature search through July 12,2023,for studies investigating brain functional changes in adolescent MDD patients.We utilized regional homogeneity(ReHo),amplitude of low-frequency fluctuations(ALFF)and fractional ALFF(fALFF)analyses.We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls(HCs)using ALE.RESULTS Ten studies(369 adolescent MDD patients and 313 HCs)were included.Combining the ReHo and ALFF/fALFF data,the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs(voxel size:648 mm3,P<0.05),and no brain region exhibited increased activity.Based on the ALFF data,we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients(voxel size:736 mm3,P<0.05),with no regions exhibiting increased activity.CONCLUSION Through ALE meta-analysis,we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients,increasing our understanding of the neuropathology of affected adolescents.
基金Supported by National Natural Science Foundation of China,No.82460282Guizhou Province Science and Technology Plan Project,No.ZK-2023-195+1 种基金Guizhou High-Level Innovative Talent Project,No.gzwjrs2022-013Health Commission of Guizhou Province Project,No.gzwkj2024-475 and No.gzwkj2021-150.
文摘BACKGROUND Attention deficit hyperactivity disorder(ADHD)is a prevalent neurodevelopmental disorder in adolescents characterized by inattention,hyperactivity,and impulsivity,which impact cognitive,behavioral,and emotional functioning.Resting-state functional magnetic resonance imaging(rs-fMRI)provides critical insights into the functional architecture of the brain in ADHD.Despite extensive research,specific brain regions consistently affected in ADHD patients during these formative years have not been comprehensively delineated.AIM To identify consistent vulnerable brain regions in adolescent ADHD patients using rs-fMRI and activation likelihood estimation(ALE)meta-analysis.METHODS We conducted a comprehensive literature search up to August 31,2024,to identify studies investigating functional brain alterations in adolescents with ADHD.We utilized regional homogeneity(ReHo),amplitude of low-frequency fluctuations(ALFF),dynamic ALFF(dALFF)and fractional ALFF(fALFF)analyses.We compared the regions of aberrant spontaneous neural activity in adolescents with ADHD with those in healthy controls(HCs)using ALE.RESULTS Fifteen studies(468 adolescent ADHD patients and 466 HCs)were included.Combining the ReHo and ALFF/fALFF/dALFF data,the results revealed increased activity in the right lingual gyrus[LING,Brodmann Area(BA)18],left LING(BA 18),and right cuneus(CUN,BA 23)in adolescent ADHD patients compared with HCs(voxel size:592-32 mm³,P<0.05).Decreased activity was observed in the left medial frontal gyrus(MFG,BA 9)and left precuneus(PCUN,BA 31)in adolescent ADHD patients compared with HCs(voxel size:960-456 mm³,P<0.05).Jackknife sensitivity analyses demonstrated robust reproducibility in 11 of the 13 tests for the right LING,left LING,and right CUN and in 11 of the 14 tests for the left MFG and left PCUN.CONCLUSION We identified specific brain regions with both increased and decreased activity in adolescent ADHD patients,enhancing our understanding of the neural alterations that occur during this pivotal stage of development.
文摘This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent to maximizing its logarithm, so the objective function ＇obj.fun＇ is maximizing log-likelihood function. Monte Carlo method adapted for implementing and designing the experiments of this simulation. This study including a comparison among three versions of PSO algorithm “Constriction coefficient CCPSO, Inertia weight IWPSO, and Fully Informed FIPSO”, the experiments designed by setting different values of model parameters al, bs sample size n, moreover the parameters of PSO algorithms. MSE used as test statistic to measure the efficiency PSO to estimate model. The results show the ability of PSO to estimate ARMA＇ s parameters, and the minimum values of MSE getting for COPSO.
基金the Michigan Department of Transportation (MDOT) for the financial support of this study (report no. SPR1723)。
文摘The calibration of transfer functions is essential for accurate pavement performance predictions in the PavementME design. Several studies have used the least square approach to calibrate these transfer functions. Least square is a widely used simplistic approach based on certain assumptions. Literature shows that these least square approach assumptions may not apply to the non-normal distributions. This study introduces a new methodology for calibrating the transverse cracking and international roughness index(IRI) models in rigid pavements using maximum likelihood estimation(MLE). Synthetic data for transverse cracking, with and without variability, are generated to illustrate the applicability of MLE using different known probability distributions(exponential,gamma, log-normal, and negative binomial). The approach uses measured data from the Michigan Department of Transportation's(MDOT) pavement management system(PMS) database for 70 jointed plain concrete pavement(JPCP) sections to calibrate and validate transfer functions. The MLE approach is combined with resampling techniques to improve the robustness of calibration coefficients. The results show that the MLE transverse cracking model using the gamma distribution consistently outperforms the least square for synthetic and observed data. For observed data, MLE estimates of parameters produced lower SSE and bias than least squares(e.g., for the transverse cracking model, the SSE values are 3.98 vs. 4.02, and the bias values are 0.00 and-0.41). Although negative binomial distribution is the most suitable fit for the IRI model for MLE, the least square results are slightly better than MLE. The bias values are-0.312 and 0.000 for the MLE and least square methods. Overall, the findings indicate that MLE is a robust method for calibration, especially for non-normally distributed data such as transverse cracking.
文摘目的通过激活似然估计(ALE)的荟萃分析方法探讨感觉神经性耳聋(SNHL)病人的脑自发活动改变特点,进一步了解SNHL可能存在的脑功能损伤及重塑的神经机制。方法检索2023年8月21日之前Web of Science、PubMed、CNKI、万方医学网、中华医学期刊全文数据库中采用局部一致性(ReHo)及低频振幅/分数低频振幅(ALFF/fALFF)分析SNHL病人脑功能改变的文献,按照纳排标准对文献筛选后,采用激活似然估计法(ALE)纳入研究中SNHL病人自发脑神经活动异常的脑区进行Meta分析。结果共纳入22篇29项研究(SNHL 736例,对照487例),其中ReHo研究11项,ALFF/fALFF研究18项。联合ReHo/ALFF/fALFF分析方法且不区分耳聋侧别结果显示SNHL病人左侧丘脑背内侧核自发脑活动增加,左侧颞上回、左侧额下回岛盖部及左侧背外侧前额叶自发脑活动减低。分别依次对左/右耳SNHL病人、ReHo和ALFF/fALFF方法进行ALE分析,结果均未见任何异常活动脑区。结论运用ALE荟萃分析方法证实SNHL病人多个脑区存在自发活动异常,有助于进一步了解SNHL脑功能损伤及重塑的规律及特征,为其后续诊疗评估提供重要依据。
基金supported by China NSF Grants(62371225,62371227)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX250590).
文摘In this paper,we present a novel particle filter(PF)-based direct position tracking method utilizing multiple distributed observation stations.Traditional passive tracking methods are anchored on repetitive position estimation,where the set of consecutive estimates provides the tracking trajectory,such as Two-step and direct position determination methods.However,duplicate estimates can be computationally expensive.In addition,these techniques suffer from data association problems.The PF algorithm is a tracking method that avoids these drawbacks,but the conventional PF algorithm is unable to construct a likelihood function from the received signals of multiple observatories to determine the weights of particles.Therefore,we developed an improved PF algorithm with the likelihood function modified by the projection approximation subspace tracking with deflation(PASTd)algorithm.The proposed algorithm uses the projection subspace and spectral function to replace the likelihood function of PF.Then,the weights of particles are calculated jointly by multiple likelihood functions.Finally,the tracking problem of multiple targets is solved by multiple sets of particles.Simulations demonstrate the effectiveness of the proposed method in terms of computational complexity and tracking accuracy.
基金Supported by the National Nature Science Foundation of China (Grant No. 11101014)the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20101103120016)+4 种基金the Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality (Grant No. PHR20110822)Training Programme Foundation for the Beijing Municipal Excellent Talents (Grant No. 2010D005015000002)the Fundamental Research Foundation of Beijing University of Technology (Grant No. X4006013201101)Education Department Science Project of Hebei Province (Grant No. Z2010297)Science Project of Shijiazhuang University of Economics (Grant No. XN0912)
文摘In virtue of the notion of likelihood ratio and moment generating function, the limit properties of the sequences of absolutely continuous random variables are studied, and a class of strong limit theorems represented by inequalities with random bounds are obtained.
基金supported by the National Natural Science Foundation of China,No.81473769(to WW),81772430(to WW)a grant from the Training Program of Innovation and Entrepreneurship for Undergraduates of Southern Medical University of Guangdong Province of China in 2016,No.201612121057(to WW)
文摘OBJECTIVE: The objective of this study is to summarize and analyze the brain signal patterns of empathy for pain caused by facial expressions of pain utilizing activation likelihood estimation, a meta-analysis method. DATA SOURCES: Studies concerning the brain mechanism were searched from the Science Citation Index, Science Direct, PubMed, DeepDyve, Cochrane Library, SinoMed, Wanfang, VIP, China National Knowledge Infrastructure, and other databases, such as SpringerLink, AMA, Science Online, Wiley Online, were collected. A time limitation of up to 13 December 2016 was applied to this study. DATA SELECTION: Studies presenting with all of the following criteria were considered for study inclusion: Use of functional magnetic resonance imaging, neutral and pained facial expression stimuli, involvement of adult healthy human participants over 18 years of age, whose empathy ability showed no difference from the healthy adult, a painless basic state, results presented in Talairach or Montreal Neurological Institute coordinates, multiple studies by the same team as long as they used different raw data. OUTCOME MEASURES: Activation likelihood estimation was used to calculate the combined main activated brain regions under the stimulation of pained facial expression. RESULTS: Eight studies were included, containing 178 subjects. Meta-analysis results suggested that the anterior cingulate cortex(BA32), anterior central gyrus(BA44), fusiform gyrus, and insula(BA13) were activated positively as major brain areas under the stimulation of pained facial expression. CONCLUSION: Our study shows that pained facial expression alone, without viewing of painful stimuli, activated brain regions related to pain empathy, further contributing to revealing the brain's mechanisms of pain empathy.
