Cognitive Neurodynamics最新文献_第9页

Classification for Alzheimer's disease and frontotemporal dementia via resting-state electroencephalography-based coherence and convolutional neural network. 基于静息状态脑电图的相干性和卷积神经网络对阿尔茨海默病和额颞叶痴呆的分类。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-03-04 DOI: 10.1007/s11571-025-10232-2

Rundong Jiang, Xiaowei Zheng, Jiamin Sun, Lei Chen, Guanghua Xu, Rui Zhang

{"title":"Classification for Alzheimer's disease and frontotemporal dementia via resting-state electroencephalography-based coherence and convolutional neural network.","authors":"Rundong Jiang, Xiaowei Zheng, Jiamin Sun, Lei Chen, Guanghua Xu, Rui Zhang","doi":"10.1007/s11571-025-10232-2","DOIUrl":"10.1007/s11571-025-10232-2","url":null,"abstract":"The study aimed to diagnose of Alzheimer's Disease (AD) and Frontotemporal Dementia (FTD) based on brain functional connectivity features extracted via resting-state Electroencephalographic (EEG) signals, and subsequently developed a convolutional neural network (CNN) model, Coherence-CNN, for classification. First, a publicly available dataset of EEG resting state-closed eye recordings containing 36 AD subjects, 23 FTD subjects, and 29 cognitively normal (CN) subjects was used. Then, coherence metrics were utilized to quantify brain functional connectivity, and the differences in coherence between groups across various frequency bands were investigated. Next, spectral clustering was used to analyze variations and differences in brain functional connectivity related to disease states, revealing distinct connectivity patterns in brain electrode position maps. The results demonstrated that brain functional connectivity between different regions was more robust in the CN group, while the AD and FTD groups exhibited various degrees of connectivity decline, reflecting the pronounced differences in connectivity patterns associated with each condition. Furthermore, Coherence-CNN was developed based on CNN and the feature of coherence for three-class classification, achieving a commendable accuracy of 94.32% through leave-one-out cross-validation. This study revealed that Coherence-CNN demonstrated significant performance for distinguishing AD, FTD, and CN groups, supporting the disorder of brain functional connectivity in AD and FTD.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"46"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11880455/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143572409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multidimensional adaptive transformer network for fatigue detection. 一种多维自适应变压器网络疲劳检测方法。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-02-20 DOI: 10.1007/s11571-025-10224-2

Dingming Wu, Liu Deng, Quanping Lu, Shihong Liu

{"title":"A multidimensional adaptive transformer network for fatigue detection.","authors":"Dingming Wu, Liu Deng, Quanping Lu, Shihong Liu","doi":"10.1007/s11571-025-10224-2","DOIUrl":"10.1007/s11571-025-10224-2","url":null,"abstract":"Variations in information processing patterns induced by operational directives under varying fatigue conditions within the cerebral cortex can be identified and analyzed through electroencephalogram (EEG) signals. The inherent complexity of EEG signals poses significant challenges in the effective detection of driver fatigue across diverse task scenarios. Recent advancements in deep learning, particularly the Transformer architecture, have shown substantial benefits in the retrieval and integration of multi-dimensional information. Nevertheless, the majority of current research primarily focuses on the application of Transformers for temporal information extraction, often overlooking other dimensions of EEG data. In response to this gap, the present study introduces a Multidimensional Adaptive Transformer Recognition Network specifically tailored for the identification of driving fatigue states. This network features a multidimensional Transformer architecture for feature extraction that adaptively assigns weights to various information dimensions, thereby facilitating feature compression and the effective extraction of structural information. This methodology ultimately enhances the model's accuracy and generalization capabilities. The experimental results indicate that the proposed methodology outperforms existing research methods when utilized with the SEED-VIG and SFDE datasets. Additionally, the analysis of multidimensional and frequency band features highlights the ability of the proposed network framework to elucidate differences in various multidimensional features during the identification of fatigue states.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"43"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11842677/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143482399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Grid cell modules coordination improves accuracy and reliability for spatial navigation. 网格单元模块的协调提高了空间导航的精度和可靠性。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-05-19 DOI: 10.1007/s11571-025-10263-9

Luca Sarramone, Jose A Fernandez-Leon

{"title":"Grid cell modules coordination improves accuracy and reliability for spatial navigation.","authors":"Luca Sarramone, Jose A Fernandez-Leon","doi":"10.1007/s11571-025-10263-9","DOIUrl":"10.1007/s11571-025-10263-9","url":null,"abstract":"Most mammals efficiently overcome self-localization deviations by coordinating grid and place cells in their brain's navigation system. However, the coordination of grid cell modules during spatial navigation and its impact on position estimation are poorly understood. This study addresses this issue by introducing a system that decodes grid-cell module activity and integrates networks of multiple grid-cell modules for self-position estimation in a mobile robot. Our results show that even when individual grid module estimates deviated substantially from the robot's actual location, the modules remained tightly coordinated. Corrections of these deviations were studied based on anchoring the activity of grid cells to spatial landmarks. Detailed numerical investigations indicate that path integration is critically dependent on the intrinsic coordination between grid cell modules which enhances the accuracy and reliability of spatial navigation. Furthermore, we show that this coordination enables effective vector navigation, even when the overall position estimation is inaccurate. These insights advance our understanding of grid-cell module coordination in location estimation during path integration and offer potential applications in robotics.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"76"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12089575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144119120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiple-timescale dynamics, mixed mode oscillations and mixed affective states in a model of bipolar disorder. 双相情感障碍模型中的多重时间尺度动力学、混合模式振荡和混合情感状态。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-12-01 Epub Date: 2022-10-26 DOI: 10.1007/s11571-022-09900-4

Efstathios Pavlidis, Fabien Campillo, Albert Goldbeter, Mathieu Desroches

{"title":"Multiple-timescale dynamics, mixed mode oscillations and mixed affective states in a model of bipolar disorder.","authors":"Efstathios Pavlidis, Fabien Campillo, Albert Goldbeter, Mathieu Desroches","doi":"10.1007/s11571-022-09900-4","DOIUrl":"10.1007/s11571-022-09900-4","url":null,"abstract":"Mixed affective states in bipolar disorder (BD) is a common psychiatric condition that occurs when symptoms of the two opposite poles coexist during an episode of mania or depression. A four-dimensional model by Goldbeter (Progr Biophys Mol Biol 105:119-127, 2011; Pharmacopsychiatry 46:S44-S52, 2013) rests upon the notion that manic and depressive symptoms are produced by two competing and auto-inhibited neural networks. Some of the rich dynamics that this model can produce, include complex rhythms formed by both small-amplitude (subthreshold) and large-amplitude (suprathreshold) oscillations and could correspond to mixed bipolar states. These rhythms are commonly referred to as mixed mode oscillations (MMOs) and they have already been studied in many different contexts by Bertram (Mathematical analysis of complex cellular activity, Springer, Cham, 2015), (Petrov et al. in J Chem Phys 97:6191-6198, 1992). In order to accurately explain these dynamics one has to apply a mathematical apparatus that makes full use of the timescale separation between variables. Here we apply the framework of multiple-timescale dynamics to the model of BD in order to understand the mathematical mechanisms underpinning the observed dynamics of changing mood. We show that the observed complex oscillations can be understood as MMOs due to a so-called folded-node singularity. Moreover, we explore the bifurcation structure of the system and we provide possible biological interpretations of our findings. Finally, we show the robustness of the MMOs regime to stochastic noise and we propose a minimal three-dimensional model which, with the addition of noise, exhibits similar yet purely noise-driven dynamics. The broader significance of this work is to introduce mathematical tools that could be used to analyse and potentially control future, more biologically grounded models of BD.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"18 6","pages":"3239-3257"},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655942/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pupil dilation and behavior as complementary measures of fear response in Mice. 瞳孔扩张和行为作为小鼠恐惧反应的互补测量。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-12-01 Epub Date: 2024-10-21 DOI: 10.1007/s11571-024-10180-3

Jing Sun, Lin Zhu, Xiaojing Fang, Yong Tang, Yuci Xiao, Shaolei Jiang, Jianbang Lin, Yuantao Li

{"title":"Pupil dilation and behavior as complementary measures of fear response in Mice.","authors":"Jing Sun, Lin Zhu, Xiaojing Fang, Yong Tang, Yuci Xiao, Shaolei Jiang, Jianbang Lin, Yuantao Li","doi":"10.1007/s11571-024-10180-3","DOIUrl":"10.1007/s11571-024-10180-3","url":null,"abstract":"The precise assessment of emotional states in animals under the combined influence of multiple stimuli remains a challenge in neuroscience research. In this study, multi-dimensional assessments, including high-precision pupil tracking and behavioral analysis, were conducted to investigate the combined effects of fear stimuli and drug manipulation on emotional responses in mice. Mice exposed to foot shocks showed typical freezing and flight behaviors, but neither of these measures could effectively distinguish between dexmedetomidine, isoflurane, and saline groups. In contrast, the change in pupil diameter clearly distinguished the groups. Our results showed that fear stimulation could induce significant pupil dilation, and dexmedetomidine-isoflurane combined stimulation could significantly inhibit this response, but isoflurane anesthesia alone could not achieve good inhibitory effect. This further demonstrates the superiority of pupil data in resolving the effects of combined stimuli on emotional states and the potential of multidimensional assessments to refine animal disease models and drug evaluations.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"18 6","pages":"4047-4054"},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resting state EEG delta-beta amplitude-amplitude coupling: a neural predictor of cortisol response under stress. 静息状态脑电图δ - β振幅-振幅耦合：应激下皮质醇反应的神经预测因子。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-12-01 Epub Date: 2024-10-03 DOI: 10.1007/s11571-024-10174-1

Xiaoyu Wang, Li Lin, Lei Zhan, Xianghong Sun, Zheng Huang, Liang Zhang

{"title":"Resting state EEG delta-beta amplitude-amplitude coupling: a neural predictor of cortisol response under stress.","authors":"Xiaoyu Wang, Li Lin, Lei Zhan, Xianghong Sun, Zheng Huang, Liang Zhang","doi":"10.1007/s11571-024-10174-1","DOIUrl":"10.1007/s11571-024-10174-1","url":null,"abstract":"Stress is ubiquitous in daily life. Subcortical and cortical regions closely interact to respond to stress. Delta-beta cross-frequency coupling (CFC), believed to signify communication between different brain areas, can serve as a neural signature underlying the heterogeneity in stress responses. Nevertheless, the role of cross-frequency coupling in stress prediction has not received sufficient attention. To examine the predictive role of resting state delta-beta CFC across the whole scalp, we obtained amplitude-amplitude coupling (AAC) and phase-amplitude coupling (PAC) from 4-minute resting state EEG of seventy-three healthy participants. The Trier Social Stress Test (TSST) was administered on a separate day to induce stress. Salivary cortisol and heart rate were recorded to measure stress responses. Utilizing cluster-based permutation analysis, the results showed that delta-beta AAC was positively correlated with cortisol increase magnitude (cluster t = 26.012, p = .020) and cortisol AUCi (cluster t = 23.039, p = .022) over parietal-occipital areas, which means that individuals with a stronger within-subject AAC demonstrated a greater cortisol response. These results suggest that AAC could be a valuable biomarker for predicting neuroendocrine activity under stress. However, no association between PAC and stress responses was found. Additionally, we did not detect the predictive effect of power in the delta or beta frequency bands on stress responses, suggesting that delta-beta AAC provides unique insights beyond single-band power. These findings enhance our understanding of the neurophysiological mechanism underpinning individual differences in stress responses and offer promising biomarkers for stress assessment and the detection of stress-related disorders.Supplementary information: The online version contains supplementary material available at 10.1007/s11571-024-10174-1.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"18 6","pages":"3995-4007"},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655767/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A review of ethical considerations for the medical applications of brain-computer interfaces. 脑机接口医学应用的伦理考虑综述。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-12-01 Epub Date: 2024-09-24 DOI: 10.1007/s11571-024-10144-7

Zhe Zhang, Yanxiao Chen, Xu Zhao, Wang Fan, Ding Peng, Tianwen Li, Lei Zhao, Yunfa Fu

{"title":"A review of ethical considerations for the medical applications of brain-computer interfaces.","authors":"Zhe Zhang, Yanxiao Chen, Xu Zhao, Wang Fan, Ding Peng, Tianwen Li, Lei Zhao, Yunfa Fu","doi":"10.1007/s11571-024-10144-7","DOIUrl":"10.1007/s11571-024-10144-7","url":null,"abstract":"The development and potential applications of brain-computer interfaces (BCIs) are directly related to the human brain and may have adverse effects on the users' physical and mental health. Ethical issues, particularly those associated with BCIs, including both non-medical and medical applications, have captured societal attention. This article initially reviews the application of three ethical frameworks in BCI technology: consequentialism, deontology, and virtue ethics. Subsequently, it introduces the ethical standards under consideration within the medical objective framework for BCI medical applications. Finally, the paper discusses and forecasts the ethical standards for BCI medical applications. The paper emphasizes the necessity to differentiate between the ethical issues of implantable and non-implantable BCIs, to approach the research on BCI-based \"controlling the brain\" with caution, and to establish standardized operational procedures and efficacy evaluation methods for BCI medical applications. This paper aims to provide ideas for the establishment of ethical standards in BCI medical applications.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"18 6","pages":"3603-3614"},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655950/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On hyper-parameter selection for guaranteed convergence of RMSProp. RMSProp保证收敛的超参数选择

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-12-01 Epub Date: 2022-07-28 DOI: 10.1007/s11571-022-09845-8

Jinlan Liu, Dongpo Xu, Huisheng Zhang, Danilo Mandic

引用次数: 0

Enhanced brain network flexibility by physical exercise in female methamphetamine users. 通过体育锻炼增强女性冰毒使用者的大脑网络灵活性

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-12-01 Epub Date: 2022-07-26 DOI: 10.1007/s11571-022-09848-5

Xiaoying Qi, Yingying Wang, Yingzhi Lu, Qi Zhao, Yifan Chen, Chenglin Zhou, Yuguo Yu

{"title":"Enhanced brain network flexibility by physical exercise in female methamphetamine users.","authors":"Xiaoying Qi, Yingying Wang, Yingzhi Lu, Qi Zhao, Yifan Chen, Chenglin Zhou, Yuguo Yu","doi":"10.1007/s11571-022-09848-5","DOIUrl":"10.1007/s11571-022-09848-5","url":null,"abstract":"Methamphetamine (MA) abuse is increasing worldwide, and evidence indicates that MA causes degraded cognitive functions such as executive function, attention, and flexibility. Recent studies have shown that regular physical exercise can ameliorate the disturbed functions. However, the potential functional network alterations resulting from physical exercise have not been extensively studied in female MA users. We collaborated with a drug rehabilitation center for this study to investigate changes in brain activity and network dynamics after two types of acute and long-term exercise interventions based on 64-channel electroencephalogram recordings of seventy-nine female MA users, who were randomly divided into three groups: control group (CG), dancing group (DG) and bicycling group (BG). Over a 12-week period, we observed a clear drop in the rate of brain activity in the exercise groups, especially in the frontal and temporal regions in the DG and the frontal and occipital regions in the BG, indicating that exercise might suppress hyperactivity and that different exercise types have distinct impacts on brain networks. Importantly, both exercise groups demonstrated enhancements in brain flexibility and network connectivity entropy, particularly after the acute intervention. Besides, a significantly negative correlation was found between Δattentional bias and Δbrain flexibility after acute intervention in both DG and BG. Analysis strongly suggested that exercise programs can reshape patient brains into a highly energy-efficient state with a lower activity rate but higher information communication capacity and more plasticity for potential cognitive functions. These results may shed light on the potential therapeutic effects of exercise interventions for MA users.Supplementary information: The online version contains supplementary material available at 10.1007/s11571-022-09848-5.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":" ","pages":"3209-3225"},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655724/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43833994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the influence of latency variability on EEG classifiers - a case study of face repetition priming. 评估潜伏期变异对脑电分类器的影响——以人脸重复启动为例。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-12-01 Epub Date: 2024-10-21 DOI: 10.1007/s11571-024-10181-2

Yilin Li, Werner Sommer, Liang Tian, Changsong Zhou

{"title":"Assessing the influence of latency variability on EEG classifiers - a case study of face repetition priming.","authors":"Yilin Li, Werner Sommer, Liang Tian, Changsong Zhou","doi":"10.1007/s11571-024-10181-2","DOIUrl":"10.1007/s11571-024-10181-2","url":null,"abstract":"Data-driven strategies have been widely used to distinguish experimental effects on single-trial EEG signals. However, how latency variability, such as within-condition jitter or latency shifts between conditions, affects the performance of EEG classifiers has not been well investigated. Without explicitly considering and disentangling such attributes of single trials, neural network-based classifiers have limitations in measuring their contributions. Inspired by domain knowledge of subcomponent latency and amplitude from traditional cognitive neuroscience, this study applies a stepwise latency correction method on single trials to control for their contributions to classifier behavior. As a case study demonstrating the value of this method, we measure repetition priming effects of faces, which induce large reaction time differences, latency shifts, and amplitude effects in averaged event-related potentials. The results show that within-condition jitter negatively impacts classifier performance, but between-condition latency shifts improve accuracy, whereas genuine amplitude differences have no significant influence. While demonstrated in the case of priming effects, this methodology can be generalized to experiments involving many kinds of time-varying signals to account for the contributions of latency variability to classifier performance.Supplementary information: The online version contains supplementary material available at 10.1007/s11571-024-10181-2.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"18 6","pages":"4055-4069"},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655819/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0