Frontiers in neuroergonomics最新文献

{"title":"Physiological activation regimes reveal distinct autonomic mechanisms underlying operational performance under cognitive workload and stress.","authors":"Ludovica Di Pompeo, Michele Tritto, Francesco Romano, David Perpetuni, Daniela Cardone, Arcangelo Merla","doi":"10.3389/fnrgo.2026.1946611","DOIUrl":"10.3389/fnrgo.2026.1946611","url":null,"abstract":"<p><p>Human performance in safety-critical environments depends on the interaction between mental workload, stress, autonomic regulation, and behavior. This study investigated whether associations between heart rate variability (HRV) and performance varied across physiological activation ranges and operational contexts during a multi-task flight simulation implemented through the AeroStim platform. Forty-two healthy participants (25 ± 5 years) performed either a Workload-Only condition (WO; <i>n</i> = 20), comprising Tracking and System Monitoring tasks, or a Stress-Oriented condition (SO; <i>n</i> = 22), in which additional stress-inducing tasks were concurrently administered. ECG was continuously recorded using an EqVital wearable T-shirt. Linear and non-linear HRV indices were extracted and normalized within participants using Min-Max scaling. Gaussian Mixture Modeling of normalized SDNN identified three relative, subject-specific activation ranges (<i>Easy, Medium</i>, and <i>Hard</i>), with classification showing high stability across alternative normalization procedures. HRV-performance associations were assessed using Spearman correlations with permutation-based inference and Benjamini-Hochberg correction, while performance differences were evaluated using non-parametric tests. HRV-performance correlations varied across activation ranges and contexts; none passed FDR correction, so these should be considered exploratory. In WO, associations involved LF in the Easy range, SDNN, SD2, and LF in the Medium range, and SDNN, LF/HF, and Sample Entropy in the Hard range. In SO, associations in the Medium range extended to vagal, global variability, and non-linear complexity indices, while Hard-range associations mainly involved vagal and LF-related measures. Omission rate was lower at Medium than Easy activation in WO, providing partial support for an intermediate activation advantage, whereas no consistent performance optimum emerged across contexts. Between-condition comparisons revealed a robust speed-accuracy trade-off, with WO producing faster but less accurate responses and SO producing slower but more accurate responses. Sensitivity analysis further indicated that differences in exercise windows affected HRV metrics in a metric-dependent manner, with greater deviations generally observed for frequency-domain measures. The findings suggest that HRV-performance relationships are context- and activation-dependent rather than captured by a single universal marker. The results support the potential of regime-based, multimodal HRV monitoring for adaptive human-machine systems, while highlighting the need for standardized recording durations, independent autonomic markers, and validation across individuals and real operational environments.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1946611"},"PeriodicalIF":3.1,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13672659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149217966","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":"Visual cues in MI-BCI induce biases in EEG classification models with deep learning but not with standard machine learning.","authors":"David Trocellier, Simon Kojima, Bernard N'kaoua, Fabien Lotte","doi":"10.3389/fnrgo.2026.1804143","DOIUrl":"https://doi.org/10.3389/fnrgo.2026.1804143","url":null,"abstract":"<p><strong>Objective: </strong>Deep learning classification methods are increasingly popular in the brain-computer interface (BCI) field due to their ability to learn complex, non-linear representations from EEG data. Unlike traditional machine learning approaches, which typically rely on hand-crafted features, deep learning models autonomously extract spatio-temporal features directly from the raw or minimally preprocessed signal. However, this flexibility may come at the cost of reduced interpretability and increased susceptibility to confounding factors. This study aims to investigate whether the inclusion of task-related visual cues in the input EEG window biases deep learning models by leading them to exploit irrelevant features, thereby compromising their neurophysiological validity.</p><p><strong>Approach: </strong>This study investigates how including EEG signals measured during visual cue presentation on classification accuracy and feature extraction in motor imagery (MI)-based BCIs. Three classification pipelines were evaluated: CSP+LDA, a traditional machine learning approach; DeepConvNet, a convolutional neural network for EEG classification; and REVE, a Transformer-based EEG foundation model. All methods are trained and tested on two large scale open-access EEG datasets using two epoching strategies, with or without including the visual cue onset, to assess their impact on model performance and neurophysiological relevance. Attribution maps (e.g., Saliency maps) and CSP patterns are used to interpret the features learned by each model.</p><p><strong>Main results: </strong>Including the visual cue onset significantly improved the classification accuracy of DeepConvNet and REVE. However, attribution analysis showed that the model mainly relied on early parietal activations, most likely cue-related visual evoked potentials, rather than MI-related sensorimotor rhythms (ERD/ERS), which were more prominent when the cue onset was excluded. In contrast, CSP+LDA showed minimal accuracy changes across conditions, with consistent motor cortex activation patterns.</p><p><strong>Significance: </strong>These findings demonstrate that higher classification performance does not necessarily imply neurophysiological validity. In particular, deep learning models may exploit confounding signals, such as visual cue processing, which undermines their interpretability and applicability in asynchronous or real-world BCIs, in which there is no such cue. We advocate for systematically applying explainability tools in BCI research to ensure classifiers rely on task-relevant brain activity. Additionally, we emphasize the importance of excluding visual cue periods from EEG segments containing reposenses evoked by the visual cue onset from the input to deep learning models.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1804143"},"PeriodicalIF":3.1,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13656310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149187497","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":"The challenges of magnetic resonance imaging and the promise of portable neurotechnology for advancing scientific discovery about neurodevelopmental disorders.","authors":"Nancy Raitano Lee","doi":"10.3389/fnrgo.2026.1884952","DOIUrl":"10.3389/fnrgo.2026.1884952","url":null,"abstract":"","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1884952"},"PeriodicalIF":3.1,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642835/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149140089","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":"I think, therefore I hit: EEG parameters predict performance in complex cognitive tasks.","authors":"Anneke Hamann, Julia Schön, Nils Carstengerdes","doi":"10.3389/fnrgo.2026.1894934","DOIUrl":"10.3389/fnrgo.2026.1894934","url":null,"abstract":"<p><p>In recent years, operator state assessment has gained much attention in the aviation domain. The ability to assess or even predict performance from behavioral or physiological data offers the possibility to tailor training schedules and assistance systems to the human operators' needs. Yet, to date, there is still no valid or reliable method for such an assessment. In the present study, we present evidence that brain activity recorded via electroencephalography (EEG) can be used to predict complex cognitive task performance. 26 participants performed multiple rounds of a dual n-back task and the complex Space Fortress Game while their brain activity was recorded via EEG. Results from multiple linear regression analyses indicate that Space Fortress Game performance could be predicted reasonably well from EEG Power Spectral Density parameters from the same game, a previous game and from the dual n-back task. Our findings show that it is possible to use data from task training and even from dissimilar, less complex tasks to predict complex task performance (in offline analyses after data collection). They also underline the utility of using EEG measurements for operator state monitoring.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1894934"},"PeriodicalIF":3.1,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642727/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149139811","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":"Using a surrogate human digital twin to model embodied perception and cognition for neuroergonomics.","authors":"Tajbeed A Chowdhury, Alexander L Francis, Daniel J Strauss","doi":"10.3389/fnrgo.2026.1939412","DOIUrl":"https://doi.org/10.3389/fnrgo.2026.1939412","url":null,"abstract":"<p><p>Understanding and predicting human behavior in dynamic, multisensory environments is one of the central challenges in neuroergonomics and human-centered artificial intelligence. Computational neuroscience provides mechanistic theories of perception, attention, and decision-making, but these insights have not yet been fully integrated into real-time digital representations of human physical behavior. Conversely, Human Digital Twins (HDTs) can successfully represent human physical characteristics, especially biomechanics and physiology, but remain limited in capturing the added complexities of embodied perception and cognition. Here, we introduce the concept of a Surrogate Human Digital Twin (S-HDT), emphasizing the necessarily approximate nature of the proposed surrogate model. Drawing upon active inference theory and consideration of evolutionary priors, the S-HDT operates as a generative model, continuously computing hidden states of cognition within a human model and predicting their trajectories under a changing environment. We argue that a S-HDT can serve as a computational approximation of embodied human perception and cognition as they function in modern multisensory environments. We present a proof-of-concept S-HDT simulating aspects of human attention and motivation mechanisms within complex sensory environments. The simulation illustrates the behavior of selected components of our proposed framework rather than providing empirical validation of human cognitive-state prediction. Future work should focus on multimodal human-data validation, and application-specific operationalization. This framework opens new opportunities for investigating neuroergonomic system design, human-centered artificial intelligence, and adaptive human-machine interaction.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1939412"},"PeriodicalIF":3.1,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13634809/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149121837","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":"Neuromarketing and the gaming consumer: a systematic review of attention, emotion, and memory in player engagement and retention.","authors":"Sandra Jimenez-Duarte, Guillermo Castilla-Cebrian","doi":"10.3389/fnrgo.2026.1918889","DOIUrl":"10.3389/fnrgo.2026.1918889","url":null,"abstract":"<p><p>The global video game industry has overtaken other cultural sectors in scale, intensifying competition for player attention, engagement, and long-term retention. Increasingly, firms pair digital marketing with neuromarketing, a set of methods drawn from cognitive neuroscience that measure attention, emotion, and memory to understand the implicit processes underlying consumer decisions. Yet evidence on how these approaches shape retention in gaming, and on how their effects can be validly measured, remains fragmented. This systematic review, following PRISMA 2020, synthesizes 54 studies published between 2009 and 2025, identified through Boolean searching of three bibliographic databases and supplemented by citation tracking. Studies were eligible if they addressed this intersection in video game contexts, or in adjacent consumer settings serving as methodological models; each was appraised for risk of bias by two reviewers independently, using AMSTAR 2, JBI and CASP instruments according to design, and common criteria of sampling clarity, procedural transparency and replicability for quantitative studies. The corpus combined quantitative-empirical (64.8%), mixed or theoretical (25.9%), and qualitative (9.3%) designs, of which 51.9% were rated high quality. Two complementary measurement streams emerged: behavioral and self-report approaches, and physiological or neuromarketing approaches using electroencephalography, eye-tracking, galvanic skin response, and facial coding. Across studies, implicit indices of attention allocation, affective response, and memory encoding were associated with engagement and with antecedents of retention beyond self-report. Studies reporting attention and engagement outcomes more often favored neuromarketing-informed approaches, but this evidence is largely associational rather than based on direct comparison with conventional campaigns, and reported magnitudes varied too widely to pool. Convergent evidence linked visual congruence, narrative and emotional design, parasocial influencer relationships, community co-creation, and algorithmic personalization to sustained play. Three limitations recur: a reliance on cross-sectional rather than longitudinal designs, the limited ecological validity of laboratory measurement, and a geographic concentration in Western Europe, North America, and East Asia. We further distinguish static neuromarketing measurement from dynamic, neuromarketing-informed design, arguing that the latter raises distinct ethical concerns for autonomy, biometric data, and vulnerable players. The review offers an integrative framework for studying the gaming consumer and sets out priorities for ecologically valid, ethically governed research.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1918889"},"PeriodicalIF":3.1,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13601311/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149043196","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":"Material context moderates the occupation-adjusted association between Visualization and prefrontal hemodynamics during naturalistic design: an exploratory wearable fNIRS study.","authors":"Yusuke Nagamori, Fumika Suzuki, Mika Isobe, Haruhi Miyoshi, Towa Shikata, Takuo Ando, Kazaru Yaegashi","doi":"10.3389/fnrgo.2026.1928775","DOIUrl":"10.3389/fnrgo.2026.1928775","url":null,"abstract":"<p><p>It remains unclear whether individual differences in a design-related disposition relate to prefrontal hemodynamics during naturalistic design, and whether the material context of the task moderates any such association. We addressed this using the Visualization subscale of the design attitude measure (DAM), a preference for externalizing ideas visually that we treat here as a continuous disposition beyond the designer job label. Thirty-nine working adults completed an open-ended block-building chair-design task using a constrained material set and a broader, higher-variety material set. Prefrontal total-hemoglobin change was recorded with a wearable two-channel fNIRS device (NeU HOT-2000; Fp1/Fp2; a single 810-nm wavelength; 10 Hz), and each self-paced trial was resampled onto a common proportional-time axis. Visualization was higher in designers than non-designers (<i>d</i> = 1.07). After adjusting for occupation, higher Visualization was associated with a greater broad-constrained Fp2 difference. This Condition × Visualization interaction was localized to a single window at 60-79% of the proportional timeline at Fp2 (cluster-corrected <i>p</i> = 0.013), with no cluster at Fp1; however, the formal between-channel comparison was not significant, so channel specificity was not established. Within this window, the effect remained significant in all 39 leave-one-out refits. The positive simple slope was present under the broad set but not the constrained set; the broad set was also rated as less difficult, more enjoyable, and more conducive to idea generation. Adjusting for occupation increased the whole-design estimate from β = +0.11 to +0.19, because occupation and Visualization related to the Fp2 difference in opposite directions (at a given Visualization level, designer status was associated with a smaller broad-constrained difference), a statistical suppression that separates the visual-externalization disposition from the occupational label; this whole-design estimate was sensitive to one participant. The findings indicate a material-context-dependent association between Visualization (a continuous disposition rather than a proxy for the designer category) and the prefrontal hemodynamic signal, and call for preregistered replication. De-identified data are openly available.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1928775"},"PeriodicalIF":3.1,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13601332/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149043202","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":"From signal to construct evidence: multimodal consumer-wearable sensing in real general-aviation flight.","authors":"Rongbing Xu, Shi Cao, Michael Barnett-Cowan, Gulnaz Bulbul, Suzanne Kearns, Ewa Niechwiej-Szwedo","doi":"10.3389/fnrgo.2026.1911259","DOIUrl":"10.3389/fnrgo.2026.1911259","url":null,"abstract":"<p><p>We asked how far multimodal consumer-wearable signals recorded during real general-aviation flight can be treated as construct-relevant measurement rather than as records of motion, posture, or task structure. Forty pilots flew five standardized maneuvers in a Cessna 172 while frontal electroencephalography (EEG and AF7/AF8), cardiac activity, electrodermal activity (EDA), eye movements, skin temperature, and flight dynamics were recorded, with segments paired with pilot self-reports and the four in-air maneuvers additionally paired with instructor competency ratings. We assembled three nested tiers of evidence, namely, known-groups sensitivity, within-person convergent evidence, and criterion-related association, and then tested prediction in held-out pilots. Signal quality supported inference, with trial-level availability from 85% to 97%. Self-reported stress varied across maneuvers (<i>H</i> = 61.1), but because maneuver order was largely fixed this variation is confounded with elapsed time, fatigue, physical dynamics, and sensor settling, and therefore cannot establish that any signal is specific to stress. Within-person convergence was strongest for cardiac (mean heart rate <i>r</i> _rm =.57) and oculomotor (saccade and fixation rates <i>r</i> _rm =.39) channels, with phasic EDA and frontal theta adding weaker support. Criterion-tier associations were re-examined with leave-one-pilot-out and wild cluster bootstrap inference: Kinematic and electrodermal associations held, whereas every frontal theta/alpha association proved to rest on individual pilots and did not survive. In cross-validation with tuning nested inside each training fold, sensor features did not exceed a maneuver-only baseline across pilots. Low-cost cardiac and oculomotor channels are the most promising basis for within-person stress monitoring, while pilot-general prediction will require individual calibration, stronger reference measures, and larger samples.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1911259"},"PeriodicalIF":3.1,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13574616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148979245","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":"The ethical, legal and social issues of neuroergonomics in the workplace.","authors":"Sherry I Brandt-Rauf, Paul W Brandt-Rauf","doi":"10.3389/fnrgo.2026.1923291","DOIUrl":"10.3389/fnrgo.2026.1923291","url":null,"abstract":"<p><p>In the near future it is anticipated that neuroergonomic technologies will be widely deployed in multiple real-world applications including many work environments. Neuroergonomics will be especially relevant in an increasingly knowledge-based, technology-driven economy where there will likely be significant incentives to apply it to increase worker productivity. However, this accelerating convergence of the brain, technology and work also raises serious issues including the privacy rights of workers' neural data and the protection of workers from coercion and discrimination over the use of the technology. Current ethical, legal and social frameworks are inadequate and unprepared to optimally deal with these issues which are rapidly being outpaced by the technological advances.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1923291"},"PeriodicalIF":3.1,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13553836/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148922453","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":"Beyond flickering: introducing code-modulated motion visual evoked potentials for brain-computer interfacing.","authors":"Hanneke A Scheppink, Rainer Herpers, Jordy Thielen, Ivan Volosyak","doi":"10.3389/fnrgo.2026.1884144","DOIUrl":"10.3389/fnrgo.2026.1884144","url":null,"abstract":"<p><p>This study presents a novel code-modulated motion visual evoked potential (c-MVEP) paradigm for brain-computer interfacing (BCI). To avoid the visual discomfort and fatigue often associated with traditional flickering stimuli, this paradigm uses pseudo-random sequences to visually stimulate objects using motion. We conducted offline and online experiments, to investigate signal characteristics and evaluate practical feasibility, respectively. In the offline experiment, EEG data were recorded and compared during sequential stimulation of a single target under four conditions: c-MVEP, code-modulated visual evoked potential (c-VEP), steady-state motion visual evoked potential (SSMVEP), and steady-state visual evoked potential (SSVEP). The c-MVEP evoked similar temporal and broadband spectral responses as c-VEP, with a comparable signal-to-noise ratio (SNR), although c-MVEP responses were more focused in the lower frequency range. While SSMVEP and SSVEP both showed clear harmonic oscillations, SSVEP yielded higher SNRs. Spatially, both motion-based stimulations peaked at Oz but spread across multiple electrodes, whereas both flicker-based stimulations were more localized at Oz. In the online experiment, we evaluated a four-target BCI using the same four conditions, testing the practical feasibility of the c-MVEP paradigm. The c-MVEP BCI reached a mean accuracy of 85.67% with an average selection time of 2.61 s, which was significantly lower than c-VEP (97.81%; 1.15 s) and SSVEP (93.42%; 1.94 s), but significantly higher than SSMVEP (64.91%; 4.18 s). The subjective ratings revealed no clear preference between the motion- and flicker-based paradigms, indicating comparable user comfort. Overall, this study demonstrates the strong potential of the newly proposed c-MVEP paradigm. By providing an effective, non-flickering alternative to traditional c-VEP and SSVEP, c-MVEP offers a highly viable approach for user-friendly BCI applications.</p>","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"7 ","pages":"1884144"},"PeriodicalIF":3.1,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13538422/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148889912","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}