IF 9 1区环境科学与生态学

Bioresource Technology Pub Date : 2025-12-01 Epub Date: 2025-08-05 DOI: 10.1016/j.biortech.2025.133063

João Fernando Ferri da Silva, Deisi Cristina Tápparo, Ana Claudia Lazaroto, Dagmara Beltrame de Asis, Igor Vinicius Machado Sophiatti, Flaviane Eva Magrini, Ricardo Luís Radis Steinmetz, Fabiane Goldschmidt Antes, Matias Vanotti, Suelen Paesi, Airton Kunz

{"title":"Enhancing anaerobic digestion of nitrogen-rich substrates through in situ ammonia recovery using tubular gas-permeable membranes.","authors":"João Fernando Ferri da Silva, Deisi Cristina Tápparo, Ana Claudia Lazaroto, Dagmara Beltrame de Asis, Igor Vinicius Machado Sophiatti, Flaviane Eva Magrini, Ricardo Luís Radis Steinmetz, Fabiane Goldschmidt Antes, Matias Vanotti, Suelen Paesi, Airton Kunz","doi":"10.1016/j.biortech.2025.133063","DOIUrl":"10.1016/j.biortech.2025.133063","url":null,"abstract":"This study evaluated ePTFE gas-permeable membranes (GPM) to mitigate ammonia inhibition during anaerobic digestion (AD). Two semi-continuous laboratory-scale reactors were operated with swine manure and urea as nitrogen sources. One reactor was equipped with GPM for in situ ammonia recovery, while the other served as a control. Initially, methane yield (MY) remained stable at ∼ 200 LCH4 kgVS-1. When free ammonia (FA) exceeded 500 mgN L-1, MY declined by 50 %, and microbial inhibition intensified. At 700 mgN L-1, inhibition reached 70 %, with increases in Clostridium_sensu_stricto_1, HN-HF0106, and Fastidiosipila. Methanosarcina remained dominant among archaea, showing greater tolerance to ammonium. After GPM activation, FA levels decreased and methane production recovered. The GPM system proved effective as both a preventive and corrective strategy, improving process stability and enabling ammonia recovery. These findings highlight the potential of GPM technology as a promising solution to enhance the robustness of AD treating nitrogen-rich substrates.","PeriodicalId":258,"journal":{"name":"Bioresource Technology","volume":" ","pages":"133063"},"PeriodicalIF":9.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144774422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Current status and challenges in electroencephalography (EEG)-based driver fatigue detection: a comprehensive survey. 基于脑电图（EEG）的驾驶员疲劳检测的现状与挑战综述。

IF 3.9 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-09-01 DOI: 10.1007/s11571-025-10320-3

Jahid Hassan, Shekh Naziullah, Mamunur Rashid, Thamina Islam, Md Nahidul Islam, Md Shofiqul Islam, Shoyeb Mahmud

{"title":"Current status and challenges in electroencephalography (EEG)-based driver fatigue detection: a comprehensive survey.","authors":"Jahid Hassan, Shekh Naziullah, Mamunur Rashid, Thamina Islam, Md Nahidul Islam, Md Shofiqul Islam, Shoyeb Mahmud","doi":"10.1007/s11571-025-10320-3","DOIUrl":"https://doi.org/10.1007/s11571-025-10320-3","url":null,"abstract":"Driver fatigue is a major contributor to traffic accidents, leading to increased fatality rates and severe damage compared to incidents involving alert drivers. Electroencephalography (EEG) has emerged as a widely used method for detecting driver fatigue due to its ability to capture brain activity patterns. This survey provides a thorough analysis of devices that detect driver fatigue using EEG, analyzing existing methodologies, challenges, and future research directions. This study was carried out according to PRISMA criteria. Relevant studies were retrieved from SpringerLink, Web of Science, IEEE Xplore, Scopus, and ScienceDirect, covering research published until February 16, 2025. After 267 publications were identified, 87 scientific papers were fully analyzed based on their relevance and contribution to the identification of driver fatigue using EEG. The review explores the article selection process, followed by an in-depth discussion of driver fatigue detection systems across various domains. Applications of Machine Learning (ML) in EEG-based fatigue evaluation are carefully reviewed, covering data collection, preliminary processing, feature extraction, categorization techniques, and performance assessment. Additionally, a comparative evaluation of cutting-edge research provides a comprehensive visualization of current research trends. This survey highlights the advantages, limitations, and future prospects of EEG-based driver fatigue detection, offering valuable insights for improving road safety. The findings contribute to the development of more reliable and real-time fatigue detection systems by addressing existing challenges and recommending potential solutions.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"142"},"PeriodicalIF":3.9,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12401835/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144991610","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

Elucidating the integrative role and possible molecular mechanisms of Salvia miltiorrhiza ingredients and gut microbiota-derived metabolites in alleviating pyroptosis-mediated hepatic ischemia-reperfusion injury through network pharmacology. 通过网络药理学研究丹参成分和肠道微生物代谢物在减轻焦热介导的肝缺血再灌注损伤中的综合作用及其可能的分子机制。

IF 4.5 3区生物学

Artificial Cells, Nanomedicine, and Biotechnology Pub Date : 2025-12-01 Epub Date: 2025-08-21 DOI: 10.1080/21691401.2025.2547646

Rujia Wang, Danhong Yang, Yi Chen, Jiabing Wang

{"title":"Elucidating the integrative role and possible molecular mechanisms of Salvia miltiorrhiza ingredients and gut microbiota-derived metabolites in alleviating pyroptosis-mediated hepatic ischemia-reperfusion injury through network pharmacology.","authors":"Rujia Wang, Danhong Yang, Yi Chen, Jiabing Wang","doi":"10.1080/21691401.2025.2547646","DOIUrl":"https://doi.org/10.1080/21691401.2025.2547646","url":null,"abstract":"Currently, therapeutic options for hepatic ischemia-reperfusion injury (HIRI) remain limited and challenging. An emerging alternative involves the combination of ingredients from traditional Chinese medicine (TCM) and beneficial gut microbiota (GM) metabolites. This study integrates ingredients of Salvia miltiorrhiza (SM) and metabolites of GM to assess their combined therapeutic efficacy against HIRI through pyroptosis using network pharmacology. Twenty-nine final targets were recognized as key proteins responsible for the alleviation of HIRI by SM ingredients and GM metabolites through pyroptosis, with GAPDH, AKT1, ILB1 emerging as central targets in the protein-protein interaction (PPI) network. The Toll-like receptor (TLR), NOD-like receptor (NLR), IL-17, TNF and MAPK signalling pathways were identified as key pathways in the therapeutic effects of SM ingredients and GM metabolites. Eight microRNAs (miRNAs) were predicted to be potential miRNAs exerting the most influence. Four SM ingredients and 11 GM metabolites were identified as non-toxic, promising candidates against HIRI. Moreover, the results of molecular docking showed all compounds were well combined with the corresponding proteins. This study highlights the therapeutic potential of TCM and beneficial GM in HIRI treatment and provides a foundational dataset for future research on their combined application. Further in vitro and in vivo studies are needed to validate these findings.","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"420-435"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144940560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multimodal attention fusion deep self-reconstruction presentation model for Alzheimer's disease diagnosis and biomarker identification. 多模态注意力融合深度自我重建呈现模型用于阿尔茨海默病诊断和生物标志物识别。

IF 4.5 3区生物学

Artificial Cells, Nanomedicine, and Biotechnology Pub Date : 2025-12-01 Epub Date: 2025-05-23 DOI: 10.1080/21691401.2025.2506591

Shan Huang, Yixin Liu, Jingyu Zhang, Yiming Wang

{"title":"Multimodal attention fusion deep self-reconstruction presentation model for Alzheimer's disease diagnosis and biomarker identification.","authors":"Shan Huang, Yixin Liu, Jingyu Zhang, Yiming Wang","doi":"10.1080/21691401.2025.2506591","DOIUrl":"https://doi.org/10.1080/21691401.2025.2506591","url":null,"abstract":"The unknown pathogenic mechanisms of Alzheimer's disease (AD) make treatment challenging. Neuroimaging genetics offers a method for identifying disease biomarkers for early diagnosis, but traditional approaches struggle with complex non-linear, multimodal and multi-expression data. However, traditional association analysis methods face challenges in handling nonlinear, multimodal and multi-expression data. Therefore, a multimodal attention fusion deep self-restructuring presentation (MAFDSRP) model is proposed to solve the above problem. First, multimodal brain imaging data are processed through a novel histogram-matching multiple attention mechanisms to dynamically adjust the weight of each input brain image data. Simultaneous, the genetic data are preprocessed to remove low-quality samples. Subsequently, the genetic data and fused neuroimaging data are separately input into the self-reconstruction network to learn the nonlinear relationships and perform subspace clustering at the top layer of the network. Finally, the learned genetic data and fused neuroimaging data are analysed through expression association analysis to identify AD-related biomarkers. The identified biomarkers underwent systematic multi-level analysis, revealing biomarker roles at molecular, tissue and functional levels, highlighting processes like inflammation, lipid metabolism, memory and emotional processing linked to AD. The experimental results show that MAFDSRP achieved 0.58 in association analysis, demonstrating its great potential in accurately identifying AD-related biomarkers.","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"231-243"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new quantum-inspired pattern based on Goldner-Harary graph for automated alzheimer's disease detection. 一种新的基于Goldner-Harary图的量子启发模式，用于阿尔茨海默病的自动检测。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-05-10 DOI: 10.1007/s11571-025-10249-7

Ilknur Sercek, Niranjana Sampathila, Irem Tasci, Tuba Ekmekyapar, Burak Tasci, Prabal Datta Barua, Mehmet Baygin, Sengul Dogan, Turker Tuncer, Ru-San Tan, U R Acharya

{"title":"A new quantum-inspired pattern based on Goldner-Harary graph for automated alzheimer's disease detection.","authors":"Ilknur Sercek, Niranjana Sampathila, Irem Tasci, Tuba Ekmekyapar, Burak Tasci, Prabal Datta Barua, Mehmet Baygin, Sengul Dogan, Turker Tuncer, Ru-San Tan, U R Acharya","doi":"10.1007/s11571-025-10249-7","DOIUrl":"https://doi.org/10.1007/s11571-025-10249-7","url":null,"abstract":"Alzheimer's disease (AD) is a common cause of dementia. We aimed to develop a computationally efficient yet accurate feature engineering model for AD detection based on electroencephalography (EEG) signal inputs. New method: We retrospectively analyzed the EEG records of 134 AD and 113 non-AD patients. To generate multilevel features, a multilevel discrete wavelet transform was used to decompose the input EEG-signals. We devised a novel quantum-inspired EEG-signal feature extraction function based on 7-distinct different subgraphs of the Goldner-Harary pattern (GHPat), and selectively assigned a specific subgraph, using a forward-forward distance-based fitness function, to each input EEG signal block for textural feature extraction. We extracted statistical features using standard statistical moments, which we then merged with the extracted textural features. Other model components were iterative neighborhood component analysis feature selection, standard shallow k-nearest neighbors, as well as iterative majority voting and greedy algorithm to generate additional voted prediction vectors and select the best overall model results. With leave-one-subject-out cross-validation (LOSO CV), our model attained 88.17% accuracy. Accuracy results stratified by channel lead placement and brain regions suggested P4 and the parietal region to be the most impactful. Comparison with existing methods: The proposed model outperforms existing methods by achieving higher accuracy with a computationally efficient quantum-inspired approach, ensuring robustness and generalizability. Cortex maps were generated that allowed visual correlation of channel-wise results with various brain regions, enhancing model explainability.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"71"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12065701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143981499","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

MicroRNA-214-3p Delivered by Bone Marrow Mesenchymal Stem Cells-Secreted Exosomes Affects Oxidative Stress in Alzheimer's Disease Rats by Targeting CD151. 骨髓间充质干细胞分泌外泌体递送的MicroRNA-214-3p通过靶向CD151影响阿尔茨海默病大鼠的氧化应激

IF 1.6 4区生物学

Organogenesis Pub Date : 2025-12-01 Epub Date: 2025-04-27 DOI: 10.1080/15476278.2025.2489673

Luzy Zhang

{"title":"MicroRNA-214-3p Delivered by Bone Marrow Mesenchymal Stem Cells-Secreted Exosomes Affects Oxidative Stress in Alzheimer's Disease Rats by Targeting CD151.","authors":"Luzy Zhang","doi":"10.1080/15476278.2025.2489673","DOIUrl":"https://doi.org/10.1080/15476278.2025.2489673","url":null,"abstract":"Objective: This study probed the effect of targeted regulation of CD151 by microRNA-214-3p (miR-214-3p) delivered by bone marrow mesenchymal stem cells-secreted exosomes (BMSCs-exo) on oxidative stress and apoptosis of neurons in Alzheimer's disease (AD).Methods: Rat BMSCs were isolated, from which MSCs-exo were extracted and identified. The AD rat model was established and injected with MSC-exo suspension. Meanwhile, miR-214-3p and CD151 interfering lentivirus were transfected in MSCs. After injection, learning and cognitive ability of the rats were assessed, as well as neuronal apoptosis and oxidative stress injury. miR-214-3p and CD151 levels were determined, and their relationship was explored.Results: AD rats had prolonged escape latency, weakened learning and cognitive ability, increased neuronal apoptosis in the hippocampal CA3 region, and aggravated oxidative stress. After MSC-exo injection, these changes in AD rats were partially rescued. CD151 was targeted by miR-214-3p, and MSC-exo improved AD in rats through the miR-214-3p/CD151 axis.Conclusion: MSC-exo down-regulates CD151 by targeting miR-214-3p to enhance antioxidant capacity, thereby improving the pathological injury of AD rats.","PeriodicalId":19596,"journal":{"name":"Organogenesis","volume":"21 1","pages":"2489673"},"PeriodicalIF":1.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12036478/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143991800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized Individualized Nursing Improves Recovery and Reduces Complications in ICU Patients with Severe Pneumonia. 优化个体化护理提高重症监护病房重症肺炎患者的康复和减少并发症。

IF 1.6 4区生物学

Organogenesis Pub Date : 2025-12-01 Epub Date: 2025-04-07 DOI: 10.1080/15476278.2025.2489670

Linjuan Wu, Jingchuan Lin

{"title":"Optimized Individualized Nursing Improves Recovery and Reduces Complications in ICU Patients with Severe Pneumonia.","authors":"Linjuan Wu, Jingchuan Lin","doi":"10.1080/15476278.2025.2489670","DOIUrl":"10.1080/15476278.2025.2489670","url":null,"abstract":"Objective: This study evaluates the effectiveness of optimized individualized nursing interventions on clinical outcomes in intensive care unit (ICU) patients with severe pneumonia.Methods: In this randomized controlled trial, 76 patients with severe pneumonia were randomized into a control group and an experimental group. Both groups received routine nursing care. On this basis, the experimental group received optimized individualized nursing. After the nursing intervention, clinical outcomes, respiratory function, coagulation function, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and St. George's Respiratory Problems Questionnaire (SGRQ) score were assessed, and the complication and mortality rates were counted.Results: After the intervention, compared with the control group, the experimental group exhibited shorter times of fever reduction, white blood cell count recovery, and off-boarding and ICU stay, higher oxygenation index, lower rapid shallow breathing index, respiratory rate, activated partial thromboplastin time, prothrombin time, fibrinogen, and D-Dimer levels, lower APACHE II scores and SGRQ scores (p < 0.05). Additionally, the experimental group possessed a lower complication rate and mortality rate than the control group (p < 0.05).Conclusion: Implementing optimized individualized nursing can significantly enhance recovery and reduce complications in ICU patients with severe pneumonia.","PeriodicalId":19596,"journal":{"name":"Organogenesis","volume":"21 1","pages":"2489670"},"PeriodicalIF":1.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11980446/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143796129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cross-patient seizure prediction via continuous domain adaptation and similar sample replay. 通过连续域适应和相似样本回放来预测跨患者癫痫发作。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-15 DOI: 10.1007/s11571-024-10216-8

Ziye Zhang, Aiping Liu, Yikai Gao, Ruobing Qian, Xun Chen

{"title":"Cross-patient seizure prediction via continuous domain adaptation and similar sample replay.","authors":"Ziye Zhang, Aiping Liu, Yikai Gao, Ruobing Qian, Xun Chen","doi":"10.1007/s11571-024-10216-8","DOIUrl":"10.1007/s11571-024-10216-8","url":null,"abstract":"Seizure prediction based on electroencephalogram (EEG) for people with epilepsy, a common brain disorder worldwide, has great potential for life quality improvement. To alleviate the high degree of heterogeneity among patients, several works have attempted to learn common seizure feature distributions based on the idea of domain adaptation to enhance the generalization ability of the model. However, existing methods ignore the inherent inter-patient discrepancy within the source patients, resulting in disjointed distributions that impede effective domain alignment. To eliminate this effect, we introduce the concept of multi-source domain adaptation (MSDA), considering each source patient as a separate domain. To avoid additional model complexity from MSDA, we propose a continuous domain adaptation approach for seizure prediction based on the convolutional neural network (CNN), which performs sequential training on multiple source domains. To relieve the model catastrophic forgetting during sequential training, we replay similar samples from each source domain, while learning common feature representations based on subdomain alignment. Evaluated on a publicly available epilepsy dataset, our proposed method attains a sensitivity of 85.0% and a false alarm rate (FPR) of 0.224/h. Compared to the prevailing domain adaptation paradigm and existing domain adaptation works in the field, the proposed method can efficiently capture the knowledge of different patients, extract better common seizure representations, and achieve state-of-the-art performance.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"26"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735696/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001017","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 stacking classifier for distinguishing stages of Alzheimer's disease from a subnetwork perspective. 从子网角度区分阿尔茨海默病阶段的堆叠分类器。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-02-05 DOI: 10.1007/s11571-025-10221-5

Gaoxuan Li, Bo Chen, Weigang Sun, Zhenbing Liu

引用次数: 0

Neural dynamics of deception: insights from fMRI studies of brain states. 欺骗的神经动力学：来自大脑状态的功能磁共振成像研究的见解。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-02-20 DOI: 10.1007/s11571-025-10222-4

Weixiong Jiang, Lin Li, Yulong Xia, Sajid Farooq, Gang Li, Shuaiqi Li, Jinhua Xu, Sailing He, Xiangyu Wu, Shoujun Huang, Jing Yuan, Dexing Kong

{"title":"Neural dynamics of deception: insights from fMRI studies of brain states.","authors":"Weixiong Jiang, Lin Li, Yulong Xia, Sajid Farooq, Gang Li, Shuaiqi Li, Jinhua Xu, Sailing He, Xiangyu Wu, Shoujun Huang, Jing Yuan, Dexing Kong","doi":"10.1007/s11571-025-10222-4","DOIUrl":"10.1007/s11571-025-10222-4","url":null,"abstract":"Deception is a complex behavior that requires greater cognitive effort than truth-telling, with brain states dynamically adapting to external stimuli and cognitive demands. Investigating these brain states provides valuable insights into the brain's temporal and spatial dynamics. In this study, we designed an experiment paradigm to efficiently simulate lying and constructed a temporal network of brain states. We applied the Louvain community clustering algorithm to identify characteristic brain states associated with lie-telling, inverse-telling, and truth-telling. Our analysis revealed six representative brain states with unique spatial characteristics. Notably, two distinct states-termed truth-preferred and lie-preferred-exhibited significant differences in fractional occupancy and average dwelling time. The truth-preferred state showed higher occupancy and dwelling time during truth-telling, while the lie-preferred state demonstrated these characteristics during lie-telling. Using the average z-score BOLD signals of these two states, we applied generalized linear models with elastic net regularization, achieving a classification accuracy of 88.46%, with a sensitivity of 92.31% and a specificity of 84.62% in distinguishing deception from truth-telling. These findings revealed representative brain states for lie-telling, inverse-telling, and truth-telling, highlighting two states specifically associated with truthful and deceptive behaviors. The spatial characteristics and dynamic attributes of these brain states indicate their potential as biomarkers of cognitive engagement in deception.Supplementary information: The online version contains supplementary material available at 10.1007/s11571-025-10222-4.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"42"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11842687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143482401","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

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