Journal of neural engineering最新文献

{"title":"5-year follow-up of a fully implanted brain-computer interface in a spinal cord injury patient.","authors":"Kevin C Davis, Kimberley R Wyse-Sookoo, Fouzia Raza, Benyamin Meschede-Krasa, Noeline W Prins, Letitia Fisher, Emery N Brown, Iahn Cajigas, Michael E Ivan, Jonathan R Jagid, Abhishek Prasad","doi":"10.1088/1741-2552/adc48c","DOIUrl":"10.1088/1741-2552/adc48c","url":null,"abstract":"<p><p>Spinal cord injury (SCI) affects over 250 000 individuals in the US. Brain-computer interfaces (BCIs) may improve quality of life by controlling external devices. Invasive intracortical BCIs have shown promise in clinical trials but degrade in the chronic period and tether patients to acquisition hardware. Alternatively, electrocorticography (ECoG) records data from electrodes on the cortex,<i>and studies evaluating fully implanted BCI-ECoG systems are scarce. Objective. We seek to address this need using a fully implanted ECoG-based BCI that allows for home use in SCI.</i><i>Approach.</i>The patient used a long-term BCI system, initially controlling an functional electrical stimulation orthosis in the lab and later using an external mechanical orthosis at home. To evaluate its long-term viability, electrode contact impedance, signal quality, and decoder performance were measured. Signal quality was assessed using signal-to-noise ratio and maximum bandwidth of the signal. Decoder performance was monitored using the area under the receiver operator characteristic curve (AUROC).<i>Main results.</i>The study analyzed data from the patient's home environment over 54 months, revealing that the device was used at home for 38 ± 24 min on average daily. After six months, we observed stable event-related desynchronization that aided in determining the onset of motor intention. The decoder's average AUROC across months was 0.959. Importantly, 40 months of the data collected was gather from the subject's home or community environment. The results indicate long-term ECoG recordings were stable for motor-imagery classification and motor control in the community environment in a case of an individual with SCI.<i>Significance.</i>This study presents the long-term feasibility and viability of an ECoG-based BCI system that persists in the home environment in a case of SCI. Future research should explore larger electrode counts with more participants to confirm this stability. Understanding these trends is crucial for clinical utility and chronic viability in broader patient populations.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feature extraction and prediction of spinal cord stimulation evoked compound action potentials in humans.","authors":"Seth König, Ahmed Ramadan, Disa Sullivan, Vasudha Goel, R Scott Stayner, David Schultz, Alexander B Herman, Theoden I Netoff, David P Darrow","doi":"10.1088/1741-2552/adbfbe","DOIUrl":"10.1088/1741-2552/adbfbe","url":null,"abstract":"<p><p><i>Objective.</i>Evoked compound action potentials (ECAPs) during spinal cord stimulation (SCS) may be useful in the treatment of chronic pain as a control signal for closed-loop neuromodulation. However, considerable inter-individual variability in evoked responses requires robust methods in order to realize effective, personalized pain management. These methods include artifact removal, feature extraction, classification, and prediction.<i>Approach.</i>We recorded ECAPs from eight participants with chronic pain undergoing an externalized trial with two percutaneous leads. The two most caudal electrodes were used for stimulation and the remaining electrodes were used for recording. Artifact-cleaned waveforms were clustered using principal component analysis and classified using a K-Nearest Neighbors classifier as non-ECAPs, ECAPs, or outlier (i.e. artifacts) to determine how well different features, including area under the curve (AUC) and peak-to-peak amplitude (P2P), discriminate between waveform classes. Finally, we used generalized linear mixed effects models to predict evoked response features and the probability of observing artifacts or ECAPs following individual stimulation pulses for different stimulation amplitudes, pulse widths, and polarities.<i>Main results.</i>AUC was better at discriminating between ECAPs and non-ECAPs than P2P (<i>d</i>' = 2.44 vs<i>d</i>' = 2.27) while most features were good at discriminating between ECAPs and artifacts (<i>d</i>' > 1.5). The application of an optimal AUC threshold was then used to analyze individual ECAPs at different stimulation amplitudes, pulse widths, and polarities. Interestingly, ECAPs could be evoked using ∼1.25 mA less current when using participant-specific, preferred stimulation polarities. Conversely, N1 latency consistently correlated with the location of the cathode.<i>Significance.</i>We developed an automated analysis pipeline for individual ECAPs during SCS. AUC was better than the widely used P2P for characterizing evoked responses. Furthermore, our modeling results provide a method for predicting how various stimulation parameters affect SCS responses in individual participants. The study registered on ClinicalTrials.gov (#NCT04938245).</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143618026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distinctive regional patterns of dynamic neural noise in cortical activity.","authors":"Andrea Scarciglia, Chiara Magliaro, Vincenzo Catrambone, Claudio Bonanno, Arti Ahluwalia, Gaetano Valenza","doi":"10.1088/1741-2552/adc33c","DOIUrl":"10.1088/1741-2552/adc33c","url":null,"abstract":"<p><p><i>Objective</i>. Neurons exhibit deterministic behavior influenced by stochastic cellular or extracellular components. Estimating this random component is challenging due to unknown underlying deterministic dynamics. In this study, we aim to estimate the neural random component, termed intrinsic dynamic neural noise, from experimental time series without prior assumptions on the underlying neural model.<i>Approach</i>. The method relies on the nonlinear approximate entropy profile and was evaluated using synthetic data from Izhikevich's models and simulated calcium dynamics driven by dynamical noise. We then applied the method to experimental time series from calcium imaging in mice and zebrafish brain regions, as well as electrophysiological data from a 128-channel cortical probe in anesthetized rats.<i>Main results</i>. The results show region-specific behavior, with higher dynamic neural noise in the somatosensory cortex of mice and anterior telencephalic area of zebrafish. Furthermore, neuronal stochasticity is greater in genetically encodedCa2+indicators than inCa2+dyes, and neural noise increases with recording depth.<i>Significance</i>. These findings offer insights into neural dynamics and suggest dynamic noise as a key biomarker.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":"22 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143804743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photoacoustic detection of genetically encoded fluorophores for neuronal subtype identification.","authors":"Joel Lusk, Ethan Marschall, Christopher Miranda, Christina Aridi, Barbara Smith","doi":"10.1088/1741-2552/adb6d7","DOIUrl":"10.1088/1741-2552/adb6d7","url":null,"abstract":"<p><p><i>Objective.</i>Elucidating neurological processes in the mammalian brain requires improved methods for imaging and detecting neuronal subtypes. Transgenic mouse models utilizing Cre/lox recombination have been developed to selectively label neuronal subtypes with fluorophores, however, light-scattering attenuation of both excitation light and emission light limits their effective range of detection.<i>Approach</i>. To overcome these limitations, this study investigates the use of a near-infrared fluorophore, iRFP713, for subtype labeling of neurons found within brain regions that are typically inaccessible by optical methods. Towards this goal, a custom photoacoustic (PA) system is developed for detection of iRFP in neurons in brain slices, expressed via Cre/lox, and within<i>in vitro</i>cell culture.<i>Main results</i>. In this study, a custom system is developed to detect iRFP in neuronal cells both in brain slices and<i>in vitro</i>. Furthermore, this work validates iRFP expression in the brains of transgenic mice and neuronal cell culture.<i>Significance</i>. Combining iRFP with advanced imaging and detection strategies, such as PA microscopy, is critical for expanding the type and variety of neurons that scientists can observe within the mammalian brain.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grid-based transcutaneous spinal cord stimulation: probing neuromodulatory effect in spinal flexion reflex circuits.","authors":"Hyungtaek Kim, Subaryani Soedirdjo, Yu-Chen Chung, Kathryn Gray, Sofia Rita Fernandes, Yasin Y Dhaher","doi":"10.1088/1741-2552/adc6bd","DOIUrl":"10.1088/1741-2552/adc6bd","url":null,"abstract":"<p><p><i>Objective.</i>Non-invasive spinal stimulation has the potential to modulate spinal excitability. This study explored the modulatory capacity of sub-motor grid-based transcutaneous spinal cord stimulation (tSCS) applied to the lumbar spinal cord in neurologically intact participants. Our objective was to examine the effect of grid spinal stimulation on polysynaptic reflex pathways involving motoneurons and interneurons likely activated by A<i>β</i>/<i>δ</i>fiber-mediated cutaneous afferents.<i>Approach.</i>Stimulation was delivered using two grid electrode montages, generating a net electric field in transverse or diagonal directions. We administered tSCS with the center of the grid aligned with the T10-T11 spinous process. Participants were seated for the 20 min stimulation duration. At 30 min after the cessation of spinal stimulation, we examined neuromodulatory effects on spinal circuit excitability in the tibialis anterior muscle by employing the classical flexion reflex paradigms. Additionally, we evaluated spinal motoneuron excitability using the<i>H</i>-reflex paradigm in the soleus muscle to explore the differential effects of tSCS on the polysynaptic versus monosynaptic reflex pathway and to test the spatial extent of the grid stimulation.<i>Main results.</i>Our findings indicated significant neuromodulatory effects on the flexion reflex, resulting in a net inhibitory effect, regardless of the grid electrode montages. Our data further indicated that the flexion reflex duration was significantly shortened only by the diagonal montage.<i>Significance.</i>Our results suggest that grid-based tSCS may specifically modulate spinal activities associated with polysynaptic flexion reflex pathways, with the potential for grid-specific targeted neuromodulation.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974257/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143744665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DP-MP: a novel cross-subject fatigue detection framework with DANN-based prototypical representation and mix-up pairwise learning.","authors":"Xiaopeng He, Haoyu Li, Peng Yu, Hao Wu, Badong Chen","doi":"10.1088/1741-2552/ad618a","DOIUrl":"10.1088/1741-2552/ad618a","url":null,"abstract":"<p><p><i>Objective</i>. Electroencephalography (EEG) is widely recognized as an effective method for detecting fatigue. However, practical applications of EEG for fatigue detection in real-world scenarios are often challenging, particularly in cases involving subjects not included in the training datasets, owing to bio-individual differences and noisy labels. This study aims to develop an effective framework for cross-subject fatigue detection by addressing these challenges.<i>Approach</i>. In this study, we propose a novel framework, termed DP-MP, for cross-subject fatigue detection, which utilizes a domain-adversarial neural network-based prototypical representation in conjunction with Mix-up pairwise learning. Our proposed DP-MP framework aims to mitigate the impact of bio-individual differences by encoding fatigue-related semantic structures within EEG signals and exploring shared fatigue prototype features across individuals. Notably, to the best of our knowledge, this work is the first to conceptualize fatigue detection as a pairwise learning task, thereby effectively reducing the interference from noisy labels. Furthermore, we propose the Mix-up pairwise learning (MixPa) approach in the field of fatigue detection, which broadens the advantages of pairwise learning by introducing more diverse and informative relationships among samples.<i>Main results</i>. Cross-subject experiments were conducted on two benchmark databases, SEED-VIG and FTEF, achieving state-of-the-art performance with average accuracies of 88.14%and 97.41%, respectively. These promising results demonstrate our model's effectiveness and excellent generalization capability.<i>Significance</i>. This is the first time EEG-based fatigue detection has been conceptualized as a pairwise learning task, offering a novel perspective to this field. Moreover, our proposed DP-MP framework effectively tackles the challenges of bio-individual differences and noisy labels in the fatigue detection field and demonstrates superior performance. Our work provides valuable insights for future research, promoting the practical application of brain-computer interfaces for fatigue detection.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141581950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simplified control of neuromuscular stimulation systems for restoration of reach with limb stiffness as a modifiable degree of freedom.","authors":"Tyler R Johnson, Chase A Haddix, A Bolu Ajiboye, Dawn M Taylor","doi":"10.1088/1741-2552/adc9e3","DOIUrl":"https://doi.org/10.1088/1741-2552/adc9e3","url":null,"abstract":"<p><strong>Objective: </strong>Brain-controlled functional electrical stimulation (FES) of the upper limb has been used to restore arm function to paralyzed individuals in the lab. Able-bodied individuals naturally modulate limb stiffness throughout movements and in anticipation of perturbations. Our goal is to develop, via simulation, a framework for incorporating stiffness modulation into the currently-used 'lookup-table-based' FES control systems while addressing several practical issues: 1) optimizing stimulation across muscles with overlap in function, 2) coordinating stimulation across joints, and 3) minimizing errors due to fatigue. Our calibration process also needs to account for when current spread causes additional muscles to become activated.&#xD;Approach: We developed an analytical framework for building a lookup-table-based FES controller and simulated the clinical process of calibrating and using the arm. A computational biomechanical model of a human paralyzed arm responding to stimulation was used for simulations with six muscles controlling the shoulder and elbow in the horizontal plane. Both joints had multiple muscles with overlapping functional effects, as well as biarticular muscles to reflect complex interactions between joints. Performance metrics were collected in silico, and real-time use was demonstrated with a Rhesus macaque using its cortical signals to control the computational arm model in real time.&#xD;Main Results: By explicitly including stiffness as a definable degree of freedom in the lookup table, our analytical approach was able to achieve all our performance criteria. While using more empirical data during controller parameterization produced more accurate lookup tables, interpolation between sparsely sampled points (e.g., 20 degree angular intervals) still produced good results with median endpoint position errors of less than 1 cm-a range that should be easy to correct for with real-time visual feedback.&#xD;Significance: Our simplified process for generating an effective FES controller now makes translating upper limb FES systems into mainstream clinical practice closer to reality. &#xD.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143805251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing age-related proprioceptive changes through active and passive tasks: implications for stroke assessment.","authors":"Erick Carranza, Sreten Franovic, Amy Boos, Elvira Pirondini","doi":"10.1088/1741-2552/adc6bc","DOIUrl":"10.1088/1741-2552/adc6bc","url":null,"abstract":"<p><p><i>Objective.</i>Voluntary control of motor actions requires precise regulation of proprioceptive and somatosensory functions. While aging is known to impair sensory processing, its effect on proprioception remains unclear. Previous studies report conflicting findings on whether passive proprioception (i.e. during externally driven movements) declines with age, and research on age-related changes in active proprioception (i.e. during voluntary movements) remains limited, particularly in the upper limb. Understanding these changes is critical for identifying and preventing impairments that may affect movement performance and mobility, particularly in neurological conditions such as stroke or Parkinson's disease.<i>Approach.</i>We refined a robotic protocol to assess upper-limb active proprioception and validated its robustness and reliability over multiple sessions. Using this protocol, we compared the performance between young and elderly neurologically healthy adults during both active and passive proprioceptive tasks.<i>Main results.</i>Elderly participants exhibited a significant decline in accuracy when sensing limb position in both active and passive proprioceptive tasks, whereas their precision remained unchanged. These findings indicate that aging primarily affects proprioceptive accuracy rather than variability in position sense.<i>Significance.</i>Our findings contribute to the ongoing debate on age-related proprioceptive decline and highlight the importance of distinguishing between active and passive proprioception. Furthermore, our validated robotic protocol provides a reliable tool for assessing proprioception, with potential applications in studying neurological conditions in clinical settings.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143744663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fascicle-selective kilohertz-frequency neural conduction block with longitudinal intrafascicular electrodes.","authors":"Louis Regnacq, Anil K Thota, Arianna Ortega Sanabria, Laura McPherson, Sylvie Renaud, Olivier Romain, Yannick Bornat, James J Abbas, Ranu Jung, Florian Kölbl","doi":"10.1088/1741-2552/adc62a","DOIUrl":"10.1088/1741-2552/adc62a","url":null,"abstract":"<p><p><i>Objective.</i>Electrical stimulation of peripheral nerves is used to treat a variety of disorders and conditions. While conventional biphasic pulse stimulation typically induces neural activity in fibers, kilohertz (kHz) continuous stimulation can block neural conduction, offering a promising alternative to drug-based therapies for alleviating abnormal neural activity. This study explores strategies to enhance the selectivity and control of high-frequency neural conduction block using intrafascicular electrodes.<i>Approach. In vivo</i>experiments were conducted in a rodent model to assess the effects of kHz stimulation delivered via longitudinal intrafascicular electrodes (LIFEs) on motor axons within the tibial and common peroneal fascicles of the sciatic nerve.<i>Main results.</i>We demonstrated that a progressive and selective block of neural conduction is achievable with LIFEs. We showed that the amount of neural conduction block can be tuned by adjusting the amplitude and frequency of kHz stimulation. Additionally, we achieved interfascicular selectivity with intrafascicular electrodes, with this selectivity being modulated by the kHz stimulation frequency. We also observed a small amount of onset response spillover, which could be minimized by increasing the blocking stimulus frequency. Muscle fatigue was quantified during kHz continuous stimulation and compared to control scenarios, revealing that the muscle was able to recover from fatigue during the block, confirming a true block of motor neurons.<i>Significance.</i>Our findings show that kHz stimulation using LIFEs can be precisely controlled to achieve selective conduction block. By leveraging existing knowledge from conventional stimulation techniques, this approach allows for the development of stimulation protocols that effectively block abnormal neural patterns with reduced side effects.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11969234/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supervised autoencoder denoiser for non-stationarity in multi-session EEG-based BCI.","authors":"Avin Ofer, Almagor Ophir, Noah Yoav, Rosipal Roman, Shriki Oren","doi":"10.1088/1741-2552/adc48e","DOIUrl":"10.1088/1741-2552/adc48e","url":null,"abstract":"<p><p><i>Objective.</i>Non-stationarity in electroencephalogram (EEG) signals poses significant challenges for the performance and implementation of brain-computer interfaces (BCIs).<i>Approach.</i>In this study, we propose a novel method for cross-session BCI tasks that employs a supervised autoencoder to reduce session-specific information while preserving task-related signals. Our approach compresses high-dimensional EEG inputs and reconstructs them, thereby mitigating non-stationary variability in the data. In addition to unsupervised minimization of the reconstruction error, the objective function of the network includes two supervised terms to ensure that the latent representations exclude session identity information and are optimized for subsequent classification.<i>Main results.</i>Evaluation across three different motor imagery datasets demonstrates that our approach effectively addresses domain adaptation challenges, outperforming both naïve cross-session and within-session methods.<i>Significance.</i>Our method eliminates the need for data from new sessions, making it fully unsupervised concerning new session data and reducing the necessity for recalibration with each session. Furthermore, the reduction of session-specific information in the reconstructed signals indicates that our approach effectively denoises non-stationary signals, thereby enhancing the accuracy of BCI models. Future applications could extend this model to a broader range of BCI tasks and explore the residual signals to investigate sources of non-stationary brain components and other cognitive processes.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}