Journal of NeuroEngineering and Rehabilitation最新文献

{"title":"EEG-fMRI neurofeedback versus motor imagery after stroke, a randomized controlled trial.","authors":"Simon Butet, Mathis Fleury, Quentin Duché, Elise Bannier, Giulia Lioi, Lou Scotto di Covella, Emilie Lévêque-Le Bars, Anatole Lécuyer, Pierre Maurel, Isabelle Bonan","doi":"10.1186/s12984-025-01598-9","DOIUrl":"10.1186/s12984-025-01598-9","url":null,"abstract":"<p><p>Neurofeedback (NF), an advanced technique enabling self-regulation of brain activity, was used to enhance upper limb motor recovery in chronic stroke survivors. A comparison was conducted between the efficacy of NF versus motor imagery (MI) training without feedback. We hypothesized that employing a bimodal EEG-fMRI based NF training approach would ensure precise targeting, and incorporating progressive multi-target feedback would provide a more effective mean to enhance plasticity. Thirty stroke survivors, exhibiting partial upper-limb motor impairment with a Fugl-Meyer Assessment Upper Extremity score (FMA-UE) > 21 and partially functional corticospinal tract (CST) were randomly allocated to the NF and MI groups. The NF group (n = 15) underwent a bimodal EEG-fMRI NF training focused on regulating activity in ipsilesional motor areas (M1 and SMA), while the MI group (n = 15) engaged in MI training. Demographic and stroke clinical data were collected. The primary outcome measure was the post-intervention FMA-UE score. Change in bold activations in target regions, EEG and fMRI laterality index (LI) and fractional anisotropy (FA) asymmetry of the CST were assessed after the intervention in both groups (respectively ΔEEG LI, ΔMRI LI and ΔFA asymmetry) and correlated with FMA-UE improvement (ΔFMA). Participants from both groups completed the 5-week training, with the NF group successfully modulating their brain activity in target regions. FMA-UE improvement post-intervention tended to be higher in the NF group than in the MI group (p = 0.048), and FMA-UE increased significantly only in the NF group (p = 0.003 vs p = 0.633 for MI). This improvement persisted at one-month in the NF group (p = 0.029). Eight out 15 patients in the NF group positively responded (i.e., improved by at least for 4 points in FMA-UE) compared to 3 out 15 in the MI group. No significant between-group differences were found in the evolution of ipsilesional M1 (t = 1.43, p = 0.16) and SMA (t = 0.85, p = 0.40) activation maps. The NF group exhibited a more pronounced lateralisation in unimodal EEG LI (t = - 3.56, p = 0.0004) compared to the MI group, but no significant difference was observed for MRI LI. A non-significant difference in ΔFA asymmetry of the CST between the two groups was found (t = 25; p = 0,055). A non-significant correlation between unimodal ΔEEG LI and ΔFMA (r = 0.5; p = 0.058) was observed for the NF group. Chronic stroke survivors can effectively engage themselves in a NF task and can benefit from a bimodal EEG-fMRI NF training. This demonstrates potential for NF in enhancing upper-limb motor recovery more efficiently than MI training.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"67"},"PeriodicalIF":5.2,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11938649/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143710115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of high- versus moderate-intensity spatially distributed sequential stimulation in subjects with spinal cord injury: an isometric study.","authors":"Ehsan Jafari, Petar Kajganic, Vance Bergeron, Julie Di Marco, Amine Metani, Lana Popovic-Maneski","doi":"10.1186/s12984-025-01567-2","DOIUrl":"10.1186/s12984-025-01567-2","url":null,"abstract":"<p><p>For producing isometric contractions, spatially distributed sequential stimulation (SDSS) has been demonstrated to be superior to conventional single electrode stimulation (SES) in terms of fatigue reduction and the power output produced by the muscle. However, the impact of stimulation parameters, particularly stimulation intensity, on the effectiveness of SDSS is not sufficiently understood. The aim of this work is to compare the fatigue-reducing capabilities of SDSS at two significantly different electrical stimulation intensities in individuals with lower-limb motor-complete spinal cord injuries, in order to understand the impact of stimulation intensity on the effectiveness of SDSS. Two experiments were conducted, focusing on isometric contractions of the quadriceps muscle group (Experiment 1) and the vastus lateralis muscle (Experiment 2). The effectiveness of high-intensity SDSS was compared to that of moderate-intensity SDSS, with SES serving as a reference. Seven subjects with spinal cord injuries participated in the study. Fatigue and force metrics, including time to fatigue (TTF) and force-time integral (FTI), were analyzed for both electrical stimulation intensity levels. Statistical analysis indicated that the advantages of SDSS over SES in reducing muscle fatigue and enhancing force generation were significantly diminished at high intensity compared to moderate intensity. These findings provide valuable scientific insights into the practical applications of SDSS and contribute to a deeper understanding of its mechanisms in mitigating muscle fatigue. Further research is recommended to explore the effects of various stimulation parameters to optimize SDSS for different muscle groups and functional tasks.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"65"},"PeriodicalIF":5.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11931884/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Customization of manual wheelchair components: a state-of-the-art review.","authors":"Sameer More, Michelle Dunn, Shannon A Rios, Rachael McDonald","doi":"10.1186/s12984-025-01547-6","DOIUrl":"10.1186/s12984-025-01547-6","url":null,"abstract":"<p><p>Custom wheelchairs, tailored to users' unique needs, have gained increasing attention because of their potential to increase mobility, comfort, and overall quality of life for the people using them. Employing a state-of-the-art review methodology, this literature review systematically categorizes the existing body of research on the design and manufacture of customizable manual wheelchair components, identifies current practices, and suggests areas for further research. We found that the literature to date has focused on the design and manufacture of custom-contoured cushions, and few studies have focused on other components or wheelchair customization as a whole. Technological advances in the past decade have seen the move from manual, time-consuming customization processes to digital workflows with the support of design tools. Advanced technologies such as 3D scanning, parametric modeling, product configuration systems, and finite element analysis have emerged as tools for enhancing the performance and aesthetics of wheelchair components. While the published literature provides a valuable foundation, the field of wheelchair customization is rapidly evolving, driven by ongoing innovations from manufacturers. This review highlights the need for further research to bridge the gap between academic knowledge and real-world progress in the design and manufacturing of custom manual wheelchairs.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"66"},"PeriodicalIF":5.2,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11931783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143700730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wearable fall risk assessment by discriminating recessive weak foot individual.","authors":"Zhen Song, Jianlin Ou, Shibin Wu, Lin Shu, Qihan Fu, Xiangmin Xu","doi":"10.1186/s12984-025-01599-8","DOIUrl":"10.1186/s12984-025-01599-8","url":null,"abstract":"<p><strong>Background: </strong>Sensor-based technologies have been widely used in fall risk assessment. To enhance the model's robustness and reliability, it is crucial to analyze and discuss the factors contributing to the misclassification of certain individuals, enabling purposeful and interpretable refinement.</p><p><strong>Methods: </strong>This study identified an abnormal gait pattern termed \"Recessive weak foot (RWF),\" characterized by a discontinuous high-risk gait on the weak foot side, observed through weak foot feature space. This condition negatively affected the training and performance of fall risk assessment models. To address this, we proposed a trainable threshold method to discriminate individuals with this pattern, thereby enhancing the model's generalization performance. We conducted feasibility and ablation studies on two self-established datasets and tested the compatibility on two published gait-related Parkinson's disease (PD) datasets.</p><p><strong>Results: </strong>Guided by a customized index and the optimized adaptive thresholds, our method effectively screened out the RWF individuals. Specifically, after fine adaptation, the individual-specific models could achieve accuracies of 87.5% and 73.6% on an enhanced dataset. Compared to the baseline, the proposed two-stage model demonstrated improved performance, with an accuracy of 85.4% and sensitivity of 87.5%. In PD dataset, our method mitigated potential overfitting from low feature dimensions, increasing accuracy by 4.7%.</p><p><strong>Conclusions: </strong>Our results indicate the proposed method enhanced model generalization by allowing the model to account for individual differences in gait patterns and served as an effective tool for quality control, helping to reduce misdiagnosis. The identification of the RWF gait pattern prompted connections to related studies and theories, suggesting avenues for further research. Future investigations are needed to further explore the implications of this gait pattern and verify the method's compatibility.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"64"},"PeriodicalIF":5.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11924617/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143670188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Therapeutic and orthotic effects of an adaptive functional electrical stimulation system on gait biomechanics in participants with stroke.","authors":"Ruxin He, Yiqun Dong, You Li, Manxu Zheng, Shenghui Peng, Raymond Kai-Yu Tong, Rong Song","doi":"10.1186/s12984-025-01577-0","DOIUrl":"10.1186/s12984-025-01577-0","url":null,"abstract":"<p><strong>Background: </strong>In recent years, functional electrical stimulation (FES) has become a common intervention for stroke survivors to correct foot drop and improve gait biomechanics. While the orthotic effects of adaptive FES systems were well-documented, the center of pressure (COP) symmetry has been largely neglected. Furthermore, the long-term therapeutic effects of adaptive FES systems on gait biomechanics have received less attention. METHODS  : This study applied a timing- and intensity-adaptive functional electrical stimulation system for evaluation and training tests to address these limitations. In the evaluation test, eight participants with chronic stroke walked under three FES conditions: no stimulation (NS), adaptive FES to the tibialis anterior (SA-ILC SCS), and hybrid adaptive FES to the tibialis anterior and the gastrocnemius (SA-ILC DCS). Nine healthy subjects walked under the NS condition as the control group. In the training test, two participants with stroke took part in a 21-day training session under the SA-ILC DCS condition.</p><p><strong>Results: </strong>The results showed that the COP symmetry of participants with stroke in the SA-ILC SCS condition tended to improve compared to the NS condition, while the SA-ILC DCS condition showed significant improvement, approaching that of healthy subjects. After the 21-day treatment period, there was a tendency for improvement in the knee-ankle angle, anterior ground reaction force, and COP symmetry of both participants with stroke without assistance.</p><p><strong>Conclusion: </strong>The observed improvements can be attributed to the hybrid adaptive FES targeting the tibialis anterior and gastrocnemius muscles. This study demonstrates that the adaptive FES system offers promising walking assistance capabilities and significant clinical therapeutic potential.</p><p><strong>Trial registration: </strong>Ethics Committee of Zhujiang Hospital, Southern Medical University, 2022-KY-149-01. Registered 29 September 2022.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"62"},"PeriodicalIF":5.2,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11921576/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imu-based kinematic analysis to enhance upper limb motor function assessment in neuromuscular diseases.","authors":"Alessandra Favata, Roger Gallart-Agut, Luc van Noort, Jesica Exposito-Escudero, Julita Medina-Cantillo, Carme Torras, Daniel Natera-de Benito, Josep M Font-Llagunes, Rosa Pàmies-Vilà","doi":"10.1186/s12984-025-01602-2","DOIUrl":"10.1186/s12984-025-01602-2","url":null,"abstract":"<p><p>Duchenne muscular dystrophy (DMD) and spinal muscular atrophy (SMA) are neuromuscular diseases that lead to progressive muscle degeneration and weakness. Recent therapeutic advances for DMD and SMA highlight the need for accurate clinical evaluation. Traditionally, motor function of the upper limbs is assessed using motor function scales. However, these scales are influenced by clinician's interpretation and may lack accuracy. For this reason, clinicians are becoming interested in finding alternative solutions. In this context, Inertial Measurement Units (IMUs) have gained popularity, offering the possibility to quantitatively and objectively analyze motor function of patients to support clinicians' assessments. We analyzed upper limb kinematics of two groups of children with neuromuscular diseases, seventeen DMD patients and fifteen SMA patients, while performing the corresponding clinical assessment. These two groups were further subdivided into two categories (Category A and Category B), according to disease severity (Brooke scores <math><mrow><mo>≤</mo> <mn>2</mn></mrow> </math> and Brooke scores <math><mrow><mo>></mo> <mn>2</mn></mrow> </math> , respectively). The results were compared against a group of ten healthy children. The metrics showing the strongest correlation with the clinical score were the workspace area in the frontal and transverse plane (DMD: <math><mi>ρ</mi></math> = 0.94 and <math><mi>ρ</mi></math> = 0.90; SMA: <math><mi>ρ</mi></math> = 0.78 and <math><mi>ρ</mi></math> = 0.81) and the workspace volume (DMD: <math><mi>ρ</mi></math> = 0.92; SMA <math><mi>ρ</mi></math> = 0.81). Additionally, statistically significant differences were found not only between healthy children and those with neuromuscular disease, but also across severity levels within the patient group. These results represent a first step toward validating IMU-based systems to helping clinicians to accurately quantify the motor status of children with neuromuscular diseases. Furthermore, data collected with inertial sensors can provide clinicians with additional information not available through subjective observation.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"63"},"PeriodicalIF":5.2,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11921574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the cortical effect of false positive feedback on motor learning in motor imagery based rehabilitative BCI training.","authors":"Hojun Jeong, Minsu Song, Sung-Ho Jang, Jonghyun Kim","doi":"10.1186/s12984-025-01597-w","DOIUrl":"10.1186/s12984-025-01597-w","url":null,"abstract":"<p><strong>Background: </strong>Motor imagery-based brain-computer interface (MI-BCI) is a promising solution for neurorehabilitation. Many studies proposed that reducing false positive (FP) feedback is crucial for inducing neural plasticity by BCI technology. However, the effect of FP feedback on cortical plasticity induction during MI-BCI training is yet to be investigated.</p><p><strong>Objective: </strong>This study aims to validate the hypothesis that FP feedback affects the cortical plasticity of the user's MI during MI-BCI training by first comparing two different asynchronous MI-BCI paradigms (with and without FP feedback), and then comparing its effectiveness with that of conventional motor learning methods (passive and active training).</p><p><strong>Methods: </strong>Twelve healthy volunteers and four patients with stroke participated in the study. We implemented two electroencephalogram-driven asynchronous MI-BCI systems with different feedback conditions. The feedback was provided by a hand exoskeleton robot performing hand open/close task. We assessed the hemodynamic responses in two different feedback conditions and compared them with two conventional motor learning methods using functional near-infrared spectroscopy with an event-related design. The cortical effects of FP feedback were analyzed in different paradigms, as well as in the same paradigm via statistical analysis.</p><p><strong>Results: </strong>The MI-BCI without FP feedback paradigm induced higher cortical activation in MI, focusing on the contralateral motor area, compared to the paradigm with FP feedback. Additionally, within the same paradigm providing FP feedback, the task period immediately following FP feedback elicited a lower hemodynamic response in the channel located over the contralateral motor area compared to the MI-BCI paradigm without FP feedback (p = 0.021 for healthy people; p = 0.079 for people with stroke). In contrast, task trials where there was no FP feedback just before showed a higher hemodynamic response, similar to the MI-BCI paradigm without FP feedback (p = 0.099 for healthy people, p = 0.084 for people with stroke).</p><p><strong>Conclusions: </strong>FP feedback reduced cortical activation for the users during MI-BCI training, suggesting a potential negative effect on cortical plasticity. Therefore, minimizing FP feedback may enhance the effectiveness of rehabilitative MI-BCI training by promoting stronger cortical activation and plasticity, particularly in the contralateral motor area.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"61"},"PeriodicalIF":5.2,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11916930/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143657386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A motor unit action potential-based method for surface electromyography decomposition.","authors":"Chen Chen, Dongxuan Li, Miaojuan Xia","doi":"10.1186/s12984-025-01595-y","DOIUrl":"10.1186/s12984-025-01595-y","url":null,"abstract":"<p><strong>Objective: </strong>Surface electromyography (EMG) decomposition is crucial for identifying motor neuron activities by analyzing muscle-generated electrical signals. This study aims to develop and validate a novel motor unit action potential (MUAP)-based method for surface EMG decomposition, addressing the limitations of traditional blind source separation (BSS)-based techniques in computation complexity and motor unit (MU) tracking.</p><p><strong>Methods: </strong>Within the framework of the convolution kernel compensation algorithm, we developed a MUAP-based decomposition algorithm by reconstructing the MU filters from MUAPs and evaluated its performance using both simulated and experimental datasets. A systematic analysis was conducted on various factors affecting decomposition performance, including MU filter reconstruction methods, EMG covariance matrices, MUAP extraction techniques, and extending factors. The proposed method was subsequently compared to representative BSS-based techniques, such as convolution kernel compensation.</p><p><strong>Main results: </strong>The MUAP-based method significantly outperformed traditional BSS-based techniques in identifying more MUs and achieving better accuracy, particularly under noisy conditions. It demonstrated superior performance with increased signal complexity and effectively tracked motor units consistently across decompositions. In addition, directly applying the MU filters reconstructed from MUAPs to decomposition exhibited marked computational efficiency.</p><p><strong>Conclusion and significance: </strong>The MUAP-based method enhances EMG decomposition accuracy, robustness, and efficiency, offering reliable motor unit tracking and real-time processing capabilities. These advancements highlight its potential for clinical diagnostics and neurorehabilitation, representing a promising step forward in non-invasive motor neuron analysis.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"60"},"PeriodicalIF":5.2,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11907793/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143634263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two decades of breakthroughs: charting the future of NeuroEngineering and Rehabilitation.","authors":"Paolo Bonato, David Reinkensmeyer, Mario Manto","doi":"10.1186/s12984-025-01580-5","DOIUrl":"10.1186/s12984-025-01580-5","url":null,"abstract":"<p><p>The Journal of NeuroEngineering and Rehabilitation (JNER) has become a major actor for the dissemination of knowledge in the scientific community, bridging the gaps between innovative neuroengineering and rehabilitation. Major fields of innovations have emerged these last 25 years, such as machine learning and the ongoing AI revolution, wearable technologies, human machine interfaces, robotics, advanced prosthetics, functional electrical stimulation and various neuromodulation techniques. With the major burden of disorders impacting on the central/peripheral nervous system and the musculoskeletal system both in adults and in children, successful tailored neurorehabilitation has become a major objective for the research and clinical community at a world scale. JNER contributes to this challenging goal, publishing groundbreaking cutting-edge research using the open access model. The multidisciplinary approaches at the crossroads of biomedical engineering, neuroscience, physical medicine and rehabilitation make of the journal a unique growing platform welcoming breakthrough discoveries to reshape the field and restore function.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"59"},"PeriodicalIF":5.2,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905428/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploration of working memory retrieval stage for mild cognitive impairment: time-varying causality analysis of electroencephalogram based on dynamic brain networks.","authors":"Yi Jiang, Zhiwei Guo, Xiaobo Zhou, Ning Jiang, Jiayuan He","doi":"10.1186/s12984-025-01594-z","DOIUrl":"10.1186/s12984-025-01594-z","url":null,"abstract":"<p><strong>Background: </strong>Mild Cognitive Impairment (MCI) is an intermediate stage between the expected cognitive decline of normal aging and Alzheimer's disease (AD). Its management is crucial for it helps intervene and slow the progression of cognitive decline to AD. However, the understanding of the MCI mechanism is not completely clear. As working memory (WM) damage is a common symptom of MCI, this study focused on the core stage of WM, i.e., the memory retrieval stage, to investigate information processing and the causality relationships among brain regions based on electroencephalogram (EEG) signals.</p><p><strong>Method: </strong>21 MCI and 20 normal cognitive control (NC) participants were recruited. The delayed matching sample paradigm with two different loads was employed to evaluate their WM functions. A time-varying network based on the Adaptive transfer function (ADTF) was constructed on the EEG of the memory retrieval trials.to perform the dynamic brain network analysis.</p><p><strong>Results: </strong>Our results showed that: (a) Behavioral data analysis: there were significant differences in accuracy and accuracy / reaction time between MCI and NC in tasks with memory load capacity of low load-four and high load-six, especially in tasks with memory load capacity of four. (b) Dynamic brain network analysis: there were significant differences in the dynamic changes of brain network patterns between the two groups during the memory retrieval stage of the WM task. Specifically, in low load WM tasks, the dynamic brain network changes of NC were more regular to accommodate for efficient information processing, with important core nodes showing a transition from bottom to up, while MCI did not display a regular dynamic brain network pattern. Further, the brain functional areas associated with low load WM disorders were mainly located in the left prefrontal lobe (FC1) and right occipital lobe (PO8). Compared with low load WM task, during the high load WM task, the dynamic brain network changes of NC during the memory retrieval stage were regular, and the core nodes exhibited a consistent transition phenomenon from up to bottom to up, which were not observed in MCI.</p><p><strong>Conclusions: </strong>Behavioral data in the low load WM task paradigm and abnormal electrophysiological signals in the left prefrontal (FC1) and right occipital lobes (PO8) could be used for MCI diagnosis. This is the first time based on large-scale dynamic network methods to investigate the dynamic network patterns of MCI memory retrieval stages under different load WM tasks, providing a new perspective on the neural mechanisms of WM deficits in MCI patients and providing some reference for the clinical intervention treatment of MCI-WM memory disorders.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"58"},"PeriodicalIF":5.2,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905461/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}