IEEE Transactions on Cognitive and Developmental Systems最新文献_第2页

2024 Index IEEE Transactions on Cognitive and Developmental Systems Vol. 16 IEEE认知与发展系统汇刊第16卷

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-12-30 DOI: 10.1109/TCDS.2024.3521617

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Sensorimotor Integration: A Review of Neural and Computational Models and the Impact of Parkinson’s Disease 感觉运动整合：神经和计算模型的综述以及帕金森病的影响

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-12-23 DOI: 10.1109/TCDS.2024.3520976

Yokhesh K. Tamilselvam;Jacky Ganguly;Mandar S. Jog;Rajni V. Patel

{"title":"Sensorimotor Integration: A Review of Neural and Computational Models and the Impact of Parkinson’s Disease","authors":"Yokhesh K. Tamilselvam;Jacky Ganguly;Mandar S. Jog;Rajni V. Patel","doi":"10.1109/TCDS.2024.3520976","DOIUrl":"https://doi.org/10.1109/TCDS.2024.3520976","url":null,"abstract":"Sensorimotor integration (SMI) is a complex process that allows humans to perceive and interact with their environment. Any impairment in SMI may impact the day-to-day functioning of humans, particularly evident in Parkinson’s Disease (PD). SMI is critical to accurate perception and modulation of motor outputs. Therefore, understanding the associated neural pathways and mathematical underpinnings is crucial. In this article, a systematic review of the proposed neural and computational models associated with SMI is performed. While the neural models discuss the neural architecture and regions, the computational models explore the mathematical or computational mechanisms involved in SMI. The article then explores how PD may impair SMI, reviewing studies that discuss deficits in the perception of various modalities, pointing to an SMI impairment. This helps in understanding the nature of SMI deficits in PD. Overall, the review offers comprehensive insights into the basis of SMI and the effect of PD on SMI, enabling clinicians to better understand the SMI mechanisms and facilitate the development of targeted therapies to mitigate SMI deficits in PD.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 1","pages":"3-21"},"PeriodicalIF":5.0,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143361082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Transactions on Cognitive and Developmental Systems Information for Authors IEEE作者认知与发展系统信息汇刊

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-12-03 DOI: 10.1109/TCDS.2024.3482595

引用次数: 0

IEEE Computational Intelligence Society Information IEEE计算智能学会信息

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-12-03 DOI: 10.1109/TCDS.2024.3482593

引用次数: 0

Brain Network Reorganization in Response to Multilevel Mental Workload in Simulated Flight Tasks 模拟飞行任务中多层次心理负荷对脑网络重组的响应

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-12-03 DOI: 10.1109/TCDS.2024.3511394

Kuijun Wu;Jingjia Yuan;Xianliang Ge;Ioannis Kakkos;Linze Qian;Sujie Wang;Yamei Yu;Chuantao Li;Yu Sun

{"title":"Brain Network Reorganization in Response to Multilevel Mental Workload in Simulated Flight Tasks","authors":"Kuijun Wu;Jingjia Yuan;Xianliang Ge;Ioannis Kakkos;Linze Qian;Sujie Wang;Yamei Yu;Chuantao Li;Yu Sun","doi":"10.1109/TCDS.2024.3511394","DOIUrl":"https://doi.org/10.1109/TCDS.2024.3511394","url":null,"abstract":"In various real-world situations, inappropriate mental workload (MWL) can impair task performance and may cause operational safety risks. Growing efforts have been made to reveal the underlying neural mechanisms of MWL. However, most studies have been limited to well-controlled cognitive tasks, overlooking the exploration of the underlying neural mechanisms in close-to-real human–machine interaction tasks. Here, we investigated the brain network reorganization in response to MWL in a close-to-real simulated flight task. Specifically, a dual-task (primary flight simulation + secondary auditory choice reaction time task) design flight simulation paradigm to mimic real-flight cognitive challenges was introduced to induce varying levels of MWL. The perceived subjective task difficulty and secondary task performance validated the effectiveness of our experimental design. Moreover, multilevel MWL classification was performed to delve into the changes of functional connectivity (FC) in response to different MWL and achieved satisfactory performance (three levels, accuracy <inline-formula><tex-math>$=$</tex-math></inline-formula> 71.85%). Further inspection of the discriminative FCs highlighted the importance of frontal and parietal-occipital brain regions in MWL modulation. Additional graph theoretical analysis revealed increased information transfer efficiency across distributed brain regions with the increase of MWL. Overall, our research offers valuable insights into the neural mechanisms underlying MWL, with potential implications for improving safety in aviation contexts.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 3","pages":"698-709"},"PeriodicalIF":5.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Transactions on Cognitive and Developmental Systems Publication Information IEEE认知与发展系统汇刊

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-12-03 DOI: 10.1109/TCDS.2024.3482591

引用次数: 0

SMART: Sequential Multiagent Reinforcement Learning With Role Assignment Using Transformer SMART：使用变压器进行角色分配的顺序多智能体强化学习

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-11-29 DOI: 10.1109/TCDS.2024.3504256

Yixing Lan;Hao Gao;Xin Xu;Qiang Fang;Yujun Zeng

{"title":"SMART: Sequential Multiagent Reinforcement Learning With Role Assignment Using Transformer","authors":"Yixing Lan;Hao Gao;Xin Xu;Qiang Fang;Yujun Zeng","doi":"10.1109/TCDS.2024.3504256","DOIUrl":"https://doi.org/10.1109/TCDS.2024.3504256","url":null,"abstract":"Multiagent reinforcement learning (MARL) has received increasing attention and been used to solve cooperative multiagent decision-making and learning control tasks. However, the high complexity of the joint action space and the nonstationary learning process are two major problems that negatively impact on the sample efficiency and solution quality of MARL. To this end, this article proposes a novel approach named sequential MARL with role assignment using transformer (SMART). By learning the effects of different actions on state transitions and rewards, SMART realizes the action abstraction of the original action space and the adaptive role cognitive modeling of multiagent, which reduces the complexity of the multiagent exploration and learning process. Meanwhile, SMART uses causal transformer networks to update role assignment policy and action selection policy sequentially, alleviating the influence of nonstationary multiagent policy learning. The convergence characteristic of SMART is theoretically analyzed. Extensive experiments on the challenging Google football and StarCraft multiagent challenge are conducted, demonstrating that compared with mainstream MARL algorithms such as MAT and HAPPO, SMART achieves a new state-of-the-art performance. Meanwhile, the learned policies through SMART have good generalization ability when the number of agents changes.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 3","pages":"615-630"},"PeriodicalIF":5.0,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Effect of Audio Trigger’s Frequency on Autonomous Sensory Meridian Response 音频触发频率对自主感觉经络反应的影响

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-11-27 DOI: 10.1109/TCDS.2024.3506039

Lili Li;Zhiqing Wu;Zhongliang Yu;Zhibin He;Zhizhong Wang;Liyu Lin;Shaolong Kuang

{"title":"The Effect of Audio Trigger’s Frequency on Autonomous Sensory Meridian Response","authors":"Lili Li;Zhiqing Wu;Zhongliang Yu;Zhibin He;Zhizhong Wang;Liyu Lin;Shaolong Kuang","doi":"10.1109/TCDS.2024.3506039","DOIUrl":"https://doi.org/10.1109/TCDS.2024.3506039","url":null,"abstract":"Autonomous sensory meridian response (ASMR) is an experience-dependent sensation in response to audio and audio–visual triggers. The acoustical characteristics of audio trigger have been speculated to be in connection with ASMR. To explore the effect of audio trigger’s frequency on ASMR and then to discover ASMR’s mechanism, the ASMR phenomenon under random-frequency audio, high-frequency audio, low-frequency audio, original audio, white-noise and rest were analyzed by EEG. The differential entropy and power spectral density were applied to quantitative analysis. The results suggest the audio’s frequency can modulate the brain activities on <italic>θ, <italic>α, <italic>β, <italic>γ, and high <italic>γ frequencies. Moreover, ASMR responder and nonresponder may be more sensitive to low-frequency audio and white-noise by suppressing brain activities of central areas in <italic>γ and high <italic>γ frequencies. Further, for ASMR responders, ASMR evoked by low-frequency audio trigger may involve more attentional selection or semantic processing and may not alter the brain functions in information processing and execution.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 3","pages":"672-681"},"PeriodicalIF":5.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Location-Guided Head Pose Estimation for Fisheye Image 鱼眼图像位置导向头部姿态估计

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-11-27 DOI: 10.1109/TCDS.2024.3506060

Bing Li;Dong Zhang;Cheng Huang;Yun Xian;Ming Li;Dah-Jye Lee

引用次数: 0

A Biomathematical Model for Classifying Sleep Stages Using Deep Learning Techniques 使用深度学习技术分类睡眠阶段的生物数学模型

IF 5 3区计算机科学

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-11-21 DOI: 10.1109/TCDS.2024.3503767

Ruijie He;Wei Tong;Miaomiao Zhang;Guangyu Zhu;Edmond Q. Wu

{"title":"A Biomathematical Model for Classifying Sleep Stages Using Deep Learning Techniques","authors":"Ruijie He;Wei Tong;Miaomiao Zhang;Guangyu Zhu;Edmond Q. Wu","doi":"10.1109/TCDS.2024.3503767","DOIUrl":"https://doi.org/10.1109/TCDS.2024.3503767","url":null,"abstract":"A biomathematical model is a framework that calculates corresponding indices based on biological and physiological parameters, and can be used to study the fatigue states of submarine crew members during long-duration operations. Submarine personnel are prone to fatigue and decreased vigilance, leading to unnecessary risks. Sleep quality plays a crucial role in assessing human vigilance; however, traditional biomathematical models generally categorize human sleep into two different pressure stages based on circadian rhythms. To accurately classify sleep stages based on physiological signals, this article proposes a novel deep learning architecture using single-channel EEG signals. This architecture comprises four modules: beginning with a feature preliminary extraction module employing a multiscale convolutional neural network (MSCNN), followed by a feature aggregation module combining reparameterizable large kernel network with temporal convolutions network (RepLKnet), then utilizing a multivariate weighted recurrent network as the tensor encoder (MWRN), and finally, decoding with a dynamic graph convolutional neural network (DGCNN). The output is provided by a final classifier. We assessed the effectiveness of the proposed model using two publicly available datasets. The results demonstrate that our model surpasses current leading benchmarks.","PeriodicalId":54300,"journal":{"name":"IEEE Transactions on Cognitive and Developmental Systems","volume":"17 3","pages":"659-671"},"PeriodicalIF":5.0,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0