Journal of neural engineering最新文献

{"title":"Bayesian optimization of cortical neuroprosthetic vision using perceptual feedback.","authors":"Burcu Küçükoğlu, Leili Soo, David Leeftink, Fabrizio Grani, Cristina Soto Sanchez, Umut Güçlü, Marcel van Gerven, Eduardo Fernandez","doi":"10.1088/1741-2552/adeae9","DOIUrl":"10.1088/1741-2552/adeae9","url":null,"abstract":"<p><p><i>Objective.</i>The challenge in cortical neuroprosthetic vision is determining the optimal, safe stimulation patterns to evoke the desired light perceptions ('phosphenes') in blind individuals. Clinical studies gain insights into the perceptual characteristics of phosphenes through patient descriptions on provided stimulation protocols. However, the huge parameter space for multi-electrode stimulation makes it difficult to identify the optimality of the stimulation that lead to well-perceived phosphenes. A systematic search in the parameter space of the electrical stimulation is needed to achieve good perception. Bayesian optimization (BO) is a framework for finding optimal parameters efficiently. Using patient's perceptual feedback, a model of patient response based on iteratively generated stimulation protocols can be built to maximize perception quality.<i>Approach.</i>A patient implanted with an intracortical 96-channel microelectrode array in their visual cortex was iteratively presented with stimulation protocols, generated via BO vs. random generation (RG) in two separate experiments. Whereas standard BO methods do not scale well to problems with over a dozen inputs, we optimize a set of 40 electrode currents using trust region-based BO. The protocols determine the electrodes to stimulate and with how much current (0-50 <i>µ</i>A), on a total current limit of 500 <i>µ</i>A. The patient rated each stimulation's perceptual quality on a Likert scale, where 7 indicated the highest quality and 0 no perception.<i>Main results.</i>The patient ratings gradually converged on higher values with BO, compared to the RG experiment. BO gradually generated protocols with higher total current, in line with the patient preference for higher currents due to brighter phosphenes. Electrodes previously observed as effective in producing phosphene perception were chosen more by BO also with higher current allocation.<i>Significance.</i>This study demonstrates the power of BO in converging to optimal stimulation protocols based on patient feedback, providing an efficient search for stimulation parameters for clinical studies.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144556292","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":"Research on coding and decoding algorithm of binocular brain-controlled unmanned vehicle.","authors":"Fangzhou Xu, Yanbing Liu, Yanzi Li, Chao Zhang, Zhe Han, Tianzheng He, Xiaolin Xiao, Chao Feng, Jiancai Leng, Minpeng Xu","doi":"10.1088/1741-2552/ade829","DOIUrl":"10.1088/1741-2552/ade829","url":null,"abstract":"<p><p><i>Objective</i>. With the rapid development of brain-computer interface (BCI) technology, steady-state visual evoked potential (SSVEP) has emerged as an effective method for high-efficiency information transmission. However, traditional single-frequency stimulation methods face limitations in command set scalability and visual comfort.<i>Approach</i>. To address these issues, we propose a novel binocular SSVEP stimulation paradigm for brain-controlled unmanned vehicles. (UV) This system uses a checkerboard and phase encoding for stimulus presentation, encoding a single target with two frequencies to expand the command set. The frequencies are set between 30-35 Hz to enhance visual comfort. By leveraging polarized light technology, each eye receives distinct frequencies, suppressing intermodulation components and reducing the stimulated area for each eye. We also introduce an improved filter bank dual-frequency task-discriminant component analysis (FBD-TDCA) algorithm.<i>Main results</i>. Experimental results show that, in a 15-command simulation, only six frequencies successfully encoded all commands, achieving comparable performance to traditional single-frequency paradigms. Furthermore, the FBD-TDCA algorithm outperformed existing methods such as filter bank task-related component analysis and filter bank canonical correlation analysis, achieving a classification accuracy of 89.27% ± 3.67 and an information translate rate of 163.87 ± 14.32 bits min^-1, with statistical significance confirmed through paired<i>t</i>-tests. The system's practical application was further demonstrated in an online 12-command UV control task. Participants achieved an average classification accuracy of 90.34% ± 8.75%, with most maintaining low path deviation rates during navigation tasks.<i>Significance</i>. The proposed binocular SSVEP stimulation paradigm and FBD-TDCA algorithm address the limitations of traditional methods, offering enhanced command set scalability, improved visual comfort, and superior performance, paving the way for more efficient and user-friendly BCI applications in real-world scenarios.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144499964","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":"End-to-end learning of safe stimulation parameters for cortical neuroprosthetic vision.","authors":"Burcu Küçükoğlu, Bodo Rueckauer, Jaap de Ruyter van Steveninck, Maureen van der Grinten, Yağmur Güçlütürk, Pieter R Roelfsema, Umut Güçlü, Marcel van Gerven","doi":"10.1088/1741-2552/ade918","DOIUrl":"10.1088/1741-2552/ade918","url":null,"abstract":"<p><p><i>Objective.</i>Direct electrical stimulation of the brain via cortical visual neuroprostheses is a promising approach to restore basic sight for the visually impaired by inducing a percept of localized light called 'phosphenes'. Apart from the challenge of condensing complex sensory information into meaningful stimulation patterns at low temporal and spatial resolution, providing safe stimulation levels to the brain is crucial.<i>Approach.</i>We propose an end-to-end framework to learn optimal stimulation parameters (amplitude, pulse width and frequency) within safe biological constraints. The learned stimulation parameters are passed to a biologically plausible phosphene simulator which takes into account the size, brightness, and temporal dynamics of perceived phosphenes.<i>Main results.</i>Our experiments on naturalistic navigation videos demonstrate that constraining stimulation parameters to safe levels not only maintains task performance in image reconstruction from phosphenes but consistently results in more meaningful phosphene vision, while providing insights into the optimal range of stimulation parameters.<i>Significance.</i>Our study presents a stimulus-generating encoder that learns stimulation parameters (1) satisfying safety constraints, and (2) maximizing the combined objective of image reconstruction and phosphene interpretability with a highly realistic phosphene simulator accounting for temporal dynamics of stimulation. End-to-end learning of stimulation parameters this way enables enforcement of critical biological safety constraints as well as technical limits of the hardware at hand.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144513021","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":"SpikeSift: a computationally efficient and drift-resilient spike sorting algorithm.","authors":"V Georgiadis, P C Petrantonakis","doi":"10.1088/1741-2552/adee48","DOIUrl":"10.1088/1741-2552/adee48","url":null,"abstract":"<p><p><i>Objective.</i>Spike sorting is a fundamental step in analysing extracellular recordings, enabling the isolation of single-neuron activity. However, it remains a challenging problem because extracellular traces mix overlapping spikes from neighbouring cells and are marred by recording instabilities such as electrode drift. Numerous algorithms have been proposed, yet many struggle to balance accuracy and computational efficiency, limiting their practicality for today's large-scale datasets.<i>Approach.</i>In response, we introduce SpikeSift, a spike-sorting algorithm expressly designed to mitigate drift while running on standard CPUs. SpikeSift (i) partitions long recordings into shorter, relatively stationary segments, (ii) carries out spike detection and clustering simultaneously through an iterative detect-and-subtract scheme within each segment, and (iii) preserves neuronal identity across segments via a fast template-alignment stage that dispenses with continuous trajectory estimation.<i>Main results.</i>Extensive validation on paired intracellularly validated datasets and on biophysically realistic MEArec simulations-covering elevated noise, diverse drift profiles, ultra-short recordings and bursting activity-demonstrates that SpikeSift matches or exceeds the accuracy of state-of-the-art methods while completing sorting an order of magnitude faster on a single desktop core.<i>Significance.</i>The combination of high fidelity, drift resilience, and modest computational demand renders SpikeSift broadly accessible while preserving data quality for downstream neurophysiological analysis.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610744","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":"Electrochemical stability and neural recording with sputtered ruthenium oxide electrodes subchronically in rat motor cortex.","authors":"Justin R Abbott, Eleanor N Jeakle, Yupeng Wu, Thomas J Smith, Negar Geramifard, Bitan Chakraborty, Mahasty Khajehzadeh, Sahana Dhananjayan, Ana G Hernandez-Reynoso, Joseph J Pancrazio, Stuart F Cogan","doi":"10.1088/1741-2552/adee49","DOIUrl":"10.1088/1741-2552/adee49","url":null,"abstract":"<p><p><i>Objective</i>. To investigate sputtered ruthenium oxide (RuO<i>_x</i>) as a low impedance coating for recording neural activity with intracortical microelectrode arrays (MEAs).<i>Approach.</i>RuO<i>_x</i>was sputtered onto active sites of amorphous silicon carbide (a-SiC) MEAs and evaluated electrochemically and as a recording electrode coating over 6 weeks in rat motor cortex. The RuO<i>_x</i>was 250 nm thick with a 200<i>μ</i>m²geometric electrode surface area. We performed weekly electrochemical impedance spectroscopy and cyclic voltammetry (CV) measurements and single-unit action potential recordings.<i>Main results.</i>From 1 to 6 weeks post-implantation, we observed that median 1 kHz impedance decreased from 1.06 MΩ to 0.68 MΩ, median 1 Hz impedance decreased from 24.5 MΩ to 20.7 MΩ, and median 30 kHz impedance remained constant at 0.19 MΩ. Linear regression fits indicated that the 1 kHz and 1 Hz impedance exhibited small decreases whereas the 30 kHz impedance values had no discernible trend. The CV-based charge storage capacity (CSC_c) also exhibited consistency over time. The median CSC_cat 50 mV s^-1was 24.3 mC cm^-2on week 1 and 20.1 mC cm^-2at week 6. At 50 000 mV s^-1sweep rate, the median CSC_cwas 2.4 mC cm^-2at 1 week and 2.8 mC cm^-2at 6 weeks. Regressions for both sweep rates exhibited no significant slope deviations from zero. Neural recordings spanning 6 weeks demonstrated consistent single unit action potential with a 75% single unit active-electrode-yield over 6 weeks. Median<i>V</i>_ppvalues on week 1 were 97.6<i>µ</i>V and 105<i>µ</i>V by week 6. The median and quartile signal-to-noise ratio (SNR) was 12 at week 1 and 12 at week 6. There were no deviations from zero on the regressions for both<i>V</i>_ppand SNR.<i>Significance.</i>The findings suggest that RuO<i>_x</i>is stable over subchronic implantation periods. Future research will explore long-term chronic performance and broader applications of RuO<i>_x</i>in neural interface devices.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278477/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610743","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":"Manipulation of neuronal activity by an artificial spiking neural network implemented on a closed-loop brain-computer interface in non-human primates.","authors":"Jonathan Mishler, Richy Yun, Steve Perlmutter, Rajesh P N Rao, Eberhard Fetz","doi":"10.1088/1741-2552/adec1c","DOIUrl":"10.1088/1741-2552/adec1c","url":null,"abstract":"<p><p><i>Objective.</i>Closed-loop brain-computer interfaces can be used to bridge, modulate, or repair damaged connections within the brain to restore functional deficits. Towards this goal, we demonstrate that small artificial spiking neural networks can be bidirectionally interfaced with single neurons (SNs) in the neocortex of non-human primates (NHPs) to create artificial connections between the SNs to manipulate their activity in predictable ways.<i>Approach.</i>Spikes from a small group of SNs were recorded from primary motor cortex of two awake NHPs during rest. The SNs were then interfaced with a small network of integrate-and-fire units (IFUs) that were programmed on a custom clBCI. Spikes from the SNs evoked excitatory and/or inhibitory postsynaptic potentials in the IFUs, which themselves spiked when their membrane potentials exceeded a predetermined threshold. Spikes from the IFUs triggered single pulses of intracortical microstimulation (ICMS) to modulate the activity of the cortical SNs.<i>Main results.</i>We show that the altered closed-loop dynamics within the cortex depends on several factors including the connectivity between the SNs and IFUs, as well as the precise timing of the ICMS. We additionally show that the closed-loop dynamics can reliably be modeled from open-loop measurements.<i>Significance.</i>Our results demonstrate a new type of hybrid biological-artificial neural system based on a clBCI that interfaces SNs in the brain with artificial IFUs to modulate biological activity in the brain. Our model of the closed-loop dynamics may be leveraged in the future to develop training algorithms that shape the closed-loop dynamics of networks in the brain to correct aberrant neural activity and rehabilitate damaged neural circuits.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565583","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":"Intuitive omnidirectional vibrotactile feedback from a sensorized insole for lower-limb prostheses users: a preliminary assessment.","authors":"Romain Valette, Sabina Manz, Jose Gonzalez-Vargas, Strahinja Dosen","doi":"10.1088/1741-2552/ade343","DOIUrl":"10.1088/1741-2552/ade343","url":null,"abstract":"<p><p><i>Objective.</i>Non-invasive solutions for providing artificial sensory feedback to lower-limb prosthesis users are compact and convenient for clinical translation because they do not require additional surgery. However, they are mostly simpler feedback schemes characterized by limited information bandwidth and low spatial resolution. Additionally, feedback is often assessed using specialized tasks and conditions, which sometimes promote the use of feedback, limiting comprehensive psychophysical and ecological insights.<i>Approach.</i>This study introduces OmniFeel, a novel feedback system composed of eight vibration motors and a sensorized insole, to intuitively convey omnidirectional foot pressure information. It was evaluated psychophysically to test pattern recognition (static and dynamic) and holistically by tracking biomechanical, gaze, task load, and user experience outcome measures during an ecological walking task that resembled real-life scenarios. The holistic assessment included walking in a building (overground walking, stairs) with and without a parallel cognitive task, and with and without feedback. Ten able-bodied participants, two participants with transtibial amputations (TT1 and TT2), and one with transfemoral amputation (TF1) took part in both assessments.<i>Main results.</i>The feedback scheme was easy to interpret, with a high success rate in recognizing six static and four dynamic spatial patterns, even before systematic training (81.5 ± 7.87% and 95.75 ± 4.42%, respectively). Functional evaluation demonstrated that feedback decreased the task load in most conditions and participants. During single-tasking, all participants benefited from the feedback by needing to look less at the floor. In two participants with lower-limb amputation, the feedback also improved stance time symmetry (from 55.88% to 74.34% in TF1 and 65.41% to 74.71% in TT2) and substantially increased confidence in TF1, especially in stair ambulation.<i>Significance.</i>These preliminary results demonstrate that OmniFeel feedback conveys rich yet easy to interpret information about the foot sole pressure, which has the potential to enhance lower-limb prosthesis use in real-life settings.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144268270","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":"Simulated prosthetic vision confirms checkerboard as an effective raster pattern for epiretinal implants.","authors":"Justin M Kasowski, Apurv Varshney, Roksana Sadeghi, Michael Beyeler","doi":"10.1088/1741-2552/adecc4","DOIUrl":"10.1088/1741-2552/adecc4","url":null,"abstract":"<p><p><i>Objective.</i>Spatial scheduling of electrode activation ('rastering') is essential for safely operating high-density retinal implants, yet its perceptual consequences remain poorly understood. This study systematically evaluates the impact of raster patterns, or spatial arrangements of sequential electrode activation, on performance and perceived difficulty in simulated prosthetic vision (SPV). By addressing this gap, we aimed to identify patterns that optimize functional vision in retinal implants.<i>Approach.</i>Sighted participants completed letter recognition and motion discrimination tasks under four raster patterns (horizontal, vertical, checkerboard, and random) using an immersive SPV system. The simulations emulated epiretinal implant perception and employed psychophysically validated models of electrode activation, phosphene appearance, nonlinear spatial summation, and temporal dynamics, ensuring realistic representation of prosthetic vision. Performance accuracy and self-reported difficulty were analyzed to assess the effects of raster patterning.<i>Main results.</i>The checkerboard pattern consistently outperformed other raster patterns, yielding significantly higher accuracy and lower difficulty ratings across both tasks. The horizontal and vertical patterns introduced biases aligned with apparent motion artifacts, while the checkerboard minimized such effects. Random patterns resulted in the lowest performance, underscoring the importance of structured activation. Notably, checkerboard matched performance in the 'No Raster' condition, despite conforming to groupwise safety constraints.<i>Significance.</i>This is the first quantitative, task-based evaluation of raster patterns in SPV. Checkerboard-style scheduling enhances perceptual clarity without increasing computational load, offering a low-overhead, clinically relevant strategy for improving usability in next-generation retinal prostheses.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12264973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144585921","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":"Personalizing brain stimulation: continual learning for sleep spindle detection.","authors":"Milo Sobral, Hugo R Jourde, S Ehsan M Bajestani, Emily B J Coffey, Giovanni Beltrame","doi":"10.1088/1741-2552/adebb1","DOIUrl":"10.1088/1741-2552/adebb1","url":null,"abstract":"<p><p><i>Objective.</i>Personalized stimulation, in which algorithms used to detect neural events adapt to a user's unique neural characteristics, may be crucial to enable optimized and consistent stimulation quality for both fundamental research and clinical applications. Precise stimulation of sleep spindles-transient patterns of brain activity that occur during non rapid eye movement sleep that are involved in memory consolidation-presents an exciting frontier for studying memory functions; however, this endeavour is challenged by the spindles' fleeting nature, inter-individual variability, and the necessity of real-time detection.<i>Approach.</i>We tackle these challenges using a novel continual learning framework. Using a pre-trained model capable of both online classification of sleep stages and spindle detection, we implement an algorithm that refines spindle detection, tailoring it to the individual throughout one or more nights without manual intervention.<i>Main results.</i>Our methodology achieves accurate, subject-specific targeting of sleep spindles and enables advanced closed-loop stimulation studies. While fine-tuning alone offers minimal benefits for single nights, our approach combining weight averaging demonstrates significant improvement over multiple nights, effectively mitigating catastrophic forgetting.<i>Significance.</i>This work represents an important step towards signal-level personalization of brain stimulation that can be applied to different brain stimulation paradigms including closed-loop brain stimulation, and to different neural events. Applications in fundamental neuroscience may enhance the investigative potential of brain stimulation to understand cognitive processes such as the role of sleep spindles in memory consolidation, and may lead to novel therapeutic applications.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144562374","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":"Motion artifact suppression method based on adaptive time-varying homogeneous field correction for OPM-MEG.","authors":"Chunhui Wang, Fuzhi Cao, Wen Li, Wenli Wang, Yong Li, Nan An, Min Xiang, Xiaolin Ning","doi":"10.1088/1741-2552/adec1d","DOIUrl":"10.1088/1741-2552/adec1d","url":null,"abstract":"<p><p><i>Objective.</i>Optically pumped magnetometer-based magnetoencephalography (OPM-MEG) offers significant advantages over traditional systems based on superconducting quantum interference devices, including flexibility and the ability to record brain activity without cryogenic cooling. However, OPM-MEG is highly susceptible to motion artifacts due to its sensitivity to external magnetic field fluctuations.<i>Approach.</i>To address this challenge, we propose an Adaptive Time-varying (ATH) Homogeneous field correction (HFC) method, which integrates time-varying HFC with adaptive filtering to suppress head motion artifacts. The ATH method estimates background magnetic field components induced by head movements and dynamically adjusts filter parameters to minimize discrepancies between measured signals and predicted background fields.<i>Main results.</i>We evaluated the ATH method through simulation studies and median nerve stimulation OPM-MEG experiments, demonstrating its effectiveness in enhancing signal quality and robustness across various experimental conditions.<i>Significance.</i>ATH offers an effective solution for motion artifact suppression in OPM-MEG systems. Its robustness under diverse conditions supports broader application in research and clinical settings.</p>","PeriodicalId":94096,"journal":{"name":"Journal of neural engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565584","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}