工程技术最新文献

{"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":"<p><p>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.</p>","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}

{"title":"A stacking classifier for distinguishing stages of Alzheimer's disease from a subnetwork perspective.","authors":"Gaoxuan Li, Bo Chen, Weigang Sun, Zhenbing Liu","doi":"10.1007/s11571-025-10221-5","DOIUrl":"10.1007/s11571-025-10221-5","url":null,"abstract":"<p><p>Accurately distinguishing stages of Alzheimer's disease (AD) is crucial for diagnosis and treatment. In this paper, we introduce a stacking classifier method that combines six single classifiers into a stacking classifier. Using brain network models and network metrics, we employ <i>t</i>-tests to identify abnormal brain regions, from which we construct a subnetwork and extract its features to form the training dataset. Our method is then applied to the ADNI (Alzheimer's Disease Neuroimaging Initiative) datasets, categorizing the stages into four categories: Alzheimer's disease, mild cognitive impairment (MCI), mixed Alzheimer's mild cognitive impairment (ADMCI), and healthy controls (HCs). We investigate four classification groups: AD-HCs, AD-MCI, HCs-ADMCI, and HCs-MCI. Finally, we compare the classification accuracy between a single classifier and our stacking classifier, demonstrating superior accuracy with our stacking classifier from a subnetwork-based viewpoint.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"38"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11799466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143381814","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}

{"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":"<p><p>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 <i>truth-preferred</i> and <i>lie-preferred</i>-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.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-025-10222-4.</p>","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}

{"title":"The role of beta band phase resetting in audio-visual temporal order judgment.","authors":"Yueying Li, Yasuki Noguchi","doi":"10.1007/s11571-024-10183-0","DOIUrl":"10.1007/s11571-024-10183-0","url":null,"abstract":"<p><p>The integration of auditory and visual stimuli is essential for effective language processing and social perception. The present study aimed to elucidate the mechanisms underlying audio-visual (A-V) integration by investigating the temporal dynamics of multisensory regions in the human brain. Specifically, we evaluated inter-trial coherence (ITC), a neural index indicative of phase resetting, through scalp electroencephalography (EEG) while participants performed a temporal-order judgment task that involved auditory (beep, A) and visual (flash, V) stimuli. The results indicated that ITC phase resetting was greater for bimodal (A + V) stimuli compared to unimodal (A or V) stimuli in the posterior temporal region, which resembled the responses of A-V multisensory neurons reported in animal studies. Furthermore, the ITC got lager as the stimulus-onset asynchrony (SOA) between beep and flash approached 0 ms. This enhancement in ITC was most clearly seen in the beta band (13-30 Hz). Overall, these findings highlight the importance of beta rhythm activity in the posterior temporal cortex for the detection of synchronous audiovisual stimuli, as assessed through temporal order judgment tasks.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-024-10183-0.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"28"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001022","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}

{"title":"<i>ZmNF-YB10</i>, a maize NF-Y transcription factor, positively regulates drought and salt stress response in <i>Arabidopsis thaliana</i>.","authors":"Yimeng Wang, Peng Jiao, Chenyang Wu, Chunlai Wang, Ke Shi, Xiaoqi Gao, Shuyan Guan, Yiyong Ma","doi":"10.1080/21645698.2024.2438421","DOIUrl":"https://doi.org/10.1080/21645698.2024.2438421","url":null,"abstract":"<p><p>Maize (<i>Zea mays</i> L.) is a major food and feed crop and an important raw material for energy, chemicals, and livestock. The NF-Y family of transcription factors in maize plays a crucial role in the regulation of plant development and response to environmental stress. In this study, we successfully cloned and characterized the maize NF-Y transcription factor gene <i>ZmNF-YB10</i>. We used bioinformatics, quantitative fluorescence PCR, and other techniques to analyze the basic properties of the gene, its tissue expression specificity, and its role in response to drought, salt, and other stresses. The results indicated that the gene was 1209 base pairs (bp) in length, with a coding sequence (CDS) region of 618 bp, encoding a polypeptide composed of 205 amino acid residues. This polypeptide has a theoretical isoelectric point of 5.85 and features a conserved structural domain unique to the NF-Y family. Quantitative fluorescence PCR results demonstrated that the <i>ZmNF-YB10</i> gene was differentially upregulated under drought and salt stress treatments but exhibited a negatively regulated expression pattern under alkali and cold stress treatments. Transgenic <i>Arabidopsis thaliana</i> subjected to drought and salt stress in soil showed greener leaves than wild-type <i>A. thaliana</i>. In addition, the overexpression lines showed reduced levels of hydrogen peroxide (H₂O₂), superoxide (O^2-), and malondialdehyde (MDA) and increased activities of peroxidase (POD), catalase (CAT), and superoxide dismutase (SOD). Western blot analysis revealed a distinct band at 21.8 kDa. Salt and drought tolerance analyses conducted in <i>E. coli</i> BL21 indicated a positive regulation. In yeast cells, <i>ZmNF-YB10</i> exhibited a biological function that enhances salt and drought tolerance. Protein interactions were observed among the <i>ZmNF-YB10</i>, <i>ZmNF-YC2</i>, and <i>ZmNF-YC4</i> genes. It is hypothesized that the <i>ZmNF-YB10, ZmNF-YC2</i>, and <i>ZmNF-YC4</i> genes may play a role in the response to abiotic stresses, such as drought and salt tolerance, in maize.</p>","PeriodicalId":54282,"journal":{"name":"Gm Crops & Food-Biotechnology in Agriculture and the Food Chain","volume":"16 1","pages":"28-45"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142883647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural oscillations predict flow experience.","authors":"Bingxin Lin, Baoshun Guo, Lingyun Zhuang, Dan Zhang, Fei Wang","doi":"10.1007/s11571-024-10205-x","DOIUrl":"10.1007/s11571-024-10205-x","url":null,"abstract":"<p><p>Flow experience, characterized by immersion in the activity at hand, provides a motivational boost and promotes positive behaviors. However, the oscillatory representations of flow experience are still poorly understood. In this study, the difficulty of the video game was adjusted to manipulate the individual's personalized flow or non-flow state, and EEG data was recorded throughout. Our results show that, compared to non-flow tasks, flow tasks exhibit higher theta power, moderate alpha power, and lower beta power, providing evidence for a focused yet effortless brain pattern during flow. Additionally, we employed Lasso regression to predict individual subjective flow scores based on neural data, achieving a correlation coefficient of 0.571 (<i>p</i> < 0.01) between the EEG-predicted scores and the actual self-reported scores. Our findings offer new insights into the oscillatory representation of flow and emphasize that flow, as a measure of individual experience quality, can be objectively and quantitatively predicted through neural oscillations.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"1"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11688267/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142920787","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}

{"title":"Aberrant regional neural fluctuations and functional connectivity in insomnia comorbid depression revealed by resting-state functional magnetic resonance imaging.","authors":"Shuang Wang, Bo Li, Minghe Xu, Chunlian Chen, Zhe Liu, Yuqing Ji, Shaowen Qian, Kai Liu, Gang Sun","doi":"10.1007/s11571-024-10206-w","DOIUrl":"https://doi.org/10.1007/s11571-024-10206-w","url":null,"abstract":"<p><p>Insomnia is a common mental illness seriously affecting people lives, that might progress to major depression. However, the neural mechanism of patients with CID comorbid MDD remain unclear. Combining fractional amplitude of low-frequency fluctuation (fALFF) and seed-based functional connectivity (FC), this study investigated abnormality in local and long-range neural activity of patients with CID comorbid MDD. Here, we acquired resting-state blood oxygenation level dependent (BOLD) data from 57 patients with CID comorbid MDD and 57 healthy controls (HC). Compared with the controls, patients with CID comorbid MDD exhibited abnormal functional activity in posterior cerebral cortex related to the visual cortex, including the middle occipital gyrus (MOG), the cuneus and the lingual gyrus, specifically, lower fALFF values in the right MOG, left cuneus, and right postcentral gyrus, increased FC between the right MOG and the left cerebellum, and decreased FC between the right MOG and the right lingual gyrus. Neuropsychological correlation analysis revealed that the decreased fALFF in the right MOG was negatively correlated with all the neuropsychological scores of insomnia and depression, reflecting common relationships with symptoms of CID and MDD. While the decreased fALFF of the left cuneus was distinctly correlated with the scores of depression related scales. The decreased FC between the right MOG and the right lingual gyrus was distinctly correlated with the scores of insomnia related scales. This study not only widened neuroimaging evidence that associated with insomnia and depressive symptoms of patients with CID comorbid MDD, but also provided new potential targets for clinical treatment.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"8"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11704111/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142945837","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}

{"title":"Reconstruction and application of multilayer brain network for juvenile myoclonic epilepsy based on link prediction.","authors":"Ming Ke, Xinyi Yao, Peihui Cao, Guangyao Liu","doi":"10.1007/s11571-024-10191-0","DOIUrl":"https://doi.org/10.1007/s11571-024-10191-0","url":null,"abstract":"<p><p>Juvenile myoclonic epilepsy (JME) exhibits abnormal functional connectivity of brain networks at multiple frequencies. We used the multilayer network model to address the heterogeneous features at different frequencies and assess the mechanisms of functional integration and segregation of brain networks in JME patients. To address the possibility of false edges or missing edges during network construction, we combined multilayer networks with link prediction techniques. Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 40 JME patients and 40 healthy controls. The Multilayer Network framework is utilized to integrate information from different frequency bands and to fuse similarity metrics for link prediction. Finally, calculate the entropy of the multiplex degree and multilayer clustering coefficient of the reconfigured multilayer frequency network. The results showed that the multilayer brain network of JME patients had significantly reduced ability to integrate and separate information and significantly correlated with severity of JME symptoms. This difference was particularly evident in default mode network (DMN), motor and somatosensory network (SMN), and auditory network (AN). In addition, significant differences were found in the precuneus, suboccipital gyrus, middle temporal gyrus, thalamus, and insula. Results suggest that JME patients have abnormal brain function and reduced cross-frequency interactions. This may be due to changes in the distribution of connections within and between the DMN, SMN, and AN in multiple frequency bands, resulting in unstable connectivity patterns. The generation of these changes is related to the pathological mechanisms of JME and may exacerbate cognitive and behavioral problems in patients.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-024-10191-0.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"7"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703786/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142945880","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}

{"title":"Unraveling the functional complexity of the locus coeruleus-norepinephrine system: insights from molecular anatomy to neurodynamic modeling.","authors":"Chun-Wang Su, Fan Yang, Runchen Lai, Yanhai Li, Hadia Naeem, Nan Yao, Si-Ping Zhang, Haiqing Zhang, Youjun Li, Zi-Gang Huang","doi":"10.1007/s11571-024-10208-8","DOIUrl":"10.1007/s11571-024-10208-8","url":null,"abstract":"<p><p>The locus coeruleus (LC), as the primary source of norepinephrine (NE) in the brain, is central to modulating cognitive and behavioral processes. This review synthesizes recent findings to provide a comprehensive understanding of the LC-NE system, highlighting its molecular diversity, neurophysiological properties, and role in various brain functions. We discuss the heterogeneity of LC neurons, their differential responses to sensory stimuli, and the impact of NE on cognitive processes such as attention and memory. Furthermore, we explore the system's involvement in stress responses and pain modulation, as well as its developmental changes and susceptibility to stressors. By integrating molecular, electrophysiological, and theoretical modeling approaches, we shed light on the LC-NE system's complex role in the brain's adaptability and its potential relevance to neurological and psychiatric disorders.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"29"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11757662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045808","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}

{"title":"Altered effective connectivity within brain lesioned regions and cognitive impairment after stroke.","authors":"Jing Zhang, Hui Tang, Lijun Zuo, Hao Liu, Zixiao Li, Jing Jing, Yongjun Wang, Tao Liu","doi":"10.1007/s11571-024-10209-7","DOIUrl":"10.1007/s11571-024-10209-7","url":null,"abstract":"<p><p>Poststroke cognitive impairments (PSCI) reflect widespread network dysfunction due to structural damage, abnormal neural activity, or abnormal connections in affected brain regions. The exact influence of these lesioned regions on the related functional network and their role in PSCI remains unclear. We recruited 35 first-time stroke patients who had basal ganglia infarcts and PSCI, along with 29 age-matched healthy controls. We utilized T1-weighted imaging to inspect structural damage with regional gray matter volume (GMV). Resting-state fMRI data were utilized to examine spontaneous activities with regional Wavelet-ALFF metric, investigate dynamic functional connectivity (dFC) by seeding the region with damaged GMV, and further study effective connectivity within the abnormal dFC network and its impact on PSCI. In comparison to HC, patients showed significant reduced GMV in the bilateral Rolandic operculum (ROL), along with notable abnormal Wavelet-ALFF values in the right Precuneus (PCUN) and left Cerebellum_9 (CER9). Particularly, an abnormal dFC network seeded in the left ROL, demonstrating significantly differential between PSCI and HC groups and remaining consistent across all time windows, was observed. This abnormal dFC network comprised the left ROL as the seed region, the right ROL, bilateral PCUN, bilateral CER9, right Superior Temporal Gyrus (STG), and right Parahippocampal Gyrus (PHG). Notably, in patients, impaired functions across various cognitive domains significantly influenced the altered effective connections among the abnormal regions, particularly impacting the connections between structurally damaged regions and those with abnormal spontaneous activity. These findings suggest that altered effective connectivity networks within lesioned regions may contribute to deficits in various cognitive domains in PSCI.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-024-10209-7.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"36"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11794930/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143364024","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}