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Brain-Computer Interface as Networking Entity in Body Area Networks
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Brain-Computer Interfaces by Electrical Cortex Activity: Challenges in Creating a Cognitive System for Mobile Devices Using Steady-State Visually Evoked Potentials
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Acquisition Of Balinese Imagined Spelling using Electroencephalogram (BISE) DatasetMendeley Data
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Improving EEG based brain computer interface emotion detection with EKO ALSTM model
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Boosted Harris Hawks Shuffled Shepherd Optimization Augmented Deep Learning based motor imagery classification for brain computer interface.
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fNIRS-based brain-computer interfaces: a review
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Toward a P300 based Brain-Computer Interface for aphasia rehabilitation after stroke: Presentation of theoretical considerations and a pilot feasibility study
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Optimal sensor set for MEG-based spontaneous and intended speech decoding toward practical communication
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Volitional Control of Neuromagnetic Coherence
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Comparison of the ERP-Based BCI Performance Among Chromatic (RGB) Semitransparent Face Patterns
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A Novel OpenBCI Framework for EEG-Based Neurophysiological Experiments
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Study of the Brain Functional Connectivity Processes During Multi-Movement States of the Lower Limbs
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- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
STARLI / TEN FLAGSHIP RESEARCH CONSTELLATION YULI · NANO × QUANTUM × REGENERATION × AI × BCI F001–F005 / 200 | Neural Nanomaterials | 777-page research working editions F001 Intelligent Nanomaterials for Neural Interfaces at the Limit Research identity: Charge-transfer integrity in compliant nanointerfaces. Endpoint: interfacial impedance [ohm]. Concealed discriminator: saline reference exchange. Conventional rival: standard platinum microelectrode matched for exposed area and recording bandwidth. F002 Programmable Neural Nanocomposites at the Limit Research identity: Programmability versus material heterogeneity. Endpoint: effective composite modulus [Pa]. Concealed discriminator: masked alignment reversal. Conventional rival: composition-matched nonprogrammable nanocomposite and classical Voigt/Reuss bounds. F003 Adaptive Conductive Nanonetworks for Neural Systems at the Limit Research identity: Adaptive conduction without hidden compensation. Endpoint: network conductance [S]. Concealed discriminator: pulse-duration scrambling. Conventional rival: fixed-resistance mesh and conventional redundant electrode network. F004 Ultraflexible Nanoelectrodes for BCI at the Limit Research identity: Flexibility must preserve electrical identity. Endpoint: fracture strain [1]. Concealed discriminator: unfamiliar soft phantom stiffness. Conventional rival: commercial flexible polymer electrode matched for electrical area and bending history. F005 Neural Tissue-Compatible Nanosurface Engineering at the Limit Research identity: Biological compatibility is not surface appearance. Endpoint: viable-cell fraction [%]. Concealed discriminator: wettability-matched control. Conventional rival: polished inert control and surface-chemistry-matched conventional coating. THE THREE-LETTER RESEARCH GATE PROTOCOL Each book proposes 30 distinct model functions, 82 chapters / 410 investigations, 200 independent test-entry contracts and 33 Phoenix study artifacts. Its Gates are letters to future researchers: Origin, Extreme Extrapolation and Future Research Plan. Literary possibility never substitutes for direct measurement. Evidence boundary: the YULI two-hundred-theme Word fixes each topic. STARLI F02 (DOI: 10.5281/zenodo.23486020) provides analogical engineering methods, not neurological efficacy evidence. External peer-reviewed materials and neural-interface methods remain separate sources. STARLI / TEN FLAGSHIP RESEARCH CONSTELLATION YULI · NANO × QUANTUM × REGENERATION × AI × BCI F006–F010 / 200 | Neural Nanomaterials | 777-page research working editions F006 Low-Inflammation Neural Nanointerfaces at the Limit Research identity: Low inflammation requires direct cellular evidence. Endpoint: inflammatory cytokine change [pg/mL]. Concealed discriminator: low-dose thermal staircase. Conventional rival: inert surface and commercially established low-reactivity reference under equal culture conditions. F007 Self-Healing Neural Nanoconductors at the Limit Research identity: Repaired conductance is not restored safety. Endpoint: conductance recovery [%]. Concealed discriminator: thermal stress after restoration. Conventional rival: qualified redundant conductor and conventional replaceable electrode trace. F008 Signal-Selective Neural Nanomaterials at the Limit Research identity: Signal selectivity must survive irrelevant sources. Endpoint: target-to-offtarget amplitude ratio [dB]. Concealed discriminator: independent signal generator. Conventional rival: matched passive electrode with conventional analogue/digital bandpass filtering. F009 Long-Term Stable Neural Nanoimplant Materials at the Limit Research identity: Long-term stability must be witnessed over time. Endpoint: time-to-impedance-failure [day]. Concealed discriminator: late-cycle blind inspection. Conventional rival: conventional chronic-interface material with same ageing dose and endpoint thresholds. F010 Biodegradable Neural Interface Nanomaterials at the Limit Research identity: Biodegradability cannot conceal a lost function. Endpoint: dry-mass retention [%]. Concealed discriminator: second-lot monomer source. Conventional rival: stable reference interface and biodegradable polymer of established composition. SOURCE AND QUALITY CHARTER The 10 books are prospective nonclinical design working editions. Their original conjectures require independent experiments; unknown DOI identities, quantitative causal independence and professional mathematical review must not be reported as passed. Each volume preserves strong conventional baselines, blinded perturbations and hard-stop conditions. External reference examples: Tang et al., Nature Electronics (2023), DOI 10.1038/s41928-022-00913-9; Liu et al., Microsystems & Nanoengineering (2023), DOI 10.1038/s41378-022-00479-8; Shen et al., Nature Biomedical Engineering (2023), DOI 10.1038/s41551-023-01021-5. Join the STARLI Research Community · https://zenodo.org/communities/starli-research-gate/ We do not need to know which door future generations will choose to open. We only hope that when they open it, they will find a little light to guide their way. 🌈🚪✨
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- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
STARLI / YULI BCI 200 / FAMILY 06 QUANTUM NEURAL MAGNETOMETRY / TEN FLAGSHIP RESEARCH DESIGNS F051–F055 | FIVE DISTINCT SCIENTIFIC CONTRACTS F051 Quantum Magnetometry for Neural Activity at the Limit Primary endpoint: phantom magnetic-field amplitude error [fT]. Hidden perturbation: concealed low-frequency external-field insertion. Rival: remote power-line field coupling, rather than a neural-dipole field. F052 Diamond NV-Center Neural Magnetometry at the Limit Primary endpoint: noise-equivalent magnetic sensitivity [T/sqrt(Hz)]. Hidden perturbation: blinded fluorescence count-rate swap. Rival: more photons or optical heating, not spin readout improvement, explains the signal. F053 Optically Pumped Magnetometry for Brain Signals at the Limit Primary endpoint: OPM signal-to-noise ratio [dB]. Hidden perturbation: concealed residual shield gradient. Rival: common-mode shield or laser noise produces the apparent signal benefit. F054 Spatial Resolution of Quantum Magnetometer Arrays at the Limit Primary endpoint: array source-position RMSE [mm]. Hidden perturbation: blind removal of one magnetometer channel. Rival: interpolation smoothing or favorable source depth, rather than improved resolution. F055 Quantum-Assisted Neural Magnetic Field Inversion at the Limit Primary endpoint: magnetic source localization error [mm]. Hidden perturbation: concealed head-phantom conductivity swap. Rival: regularization choice or favored source prior generates an apparent localization gain. FAMILY METHOD / EXPLICIT NONCLINICAL BOUNDARY Each proposed 777-page volume contains 14 three-point research preface pages, 30 mathematical plates, 82 chapters/410 investigations, 200 distinct indexed research tests and 33 Phoenix concepts. Three future letters appear at each Research Gate. The source is an independently metered current dipole; OPM or NV readout does not itself prove neural function, clinical benefit or quantum advantage. STARLI / YULI BCI 200 / FAMILY 06 QUANTUM NEURAL MAGNETOMETRY / TEN FLAGSHIP RESEARCH DESIGNS F056–F060 | FIVE DISTINCT SCIENTIFIC CONTRACTS F056 Low-Field Quantum Neural Magnetometry at the Limit Primary endpoint: low-field calibration bias [pT]. Hidden perturbation: blind background-bias-field step. Rival: incomplete compensation of residual magnetic field masquerades as calibrated sensitivity. F057 Motion-Noise Suppression in Quantum Neural Sensing at the Limit Primary endpoint: residual motion-field mean-square [fT^2]. Hidden perturbation: blinded phantom head-motion injection. Rival: neural-like source signal is removed along with the motion component. F058 Quantum Magnetometry and EEG Fusion at the Limit Primary endpoint: OPM-to-EEG timing difference [ms]. Hidden perturbation: blinded trigger-clock offset. Rival: common stimulation trigger makes two signals seem synchronous without independent neural information. F059 Calibration Traceability in Quantum Neural Magnetometry at the Limit Primary endpoint: magnetic field expanded uncertainty [pT]. Hidden perturbation: blinded coil-constant replacement. Rival: common current-source error yields correlated agreement, not independent calibration. F060 Independent Validation of Quantum Neural Magnetometry at the Limit Primary endpoint: second-site magnetic reproduction error [fT]. Hidden perturbation: blind exchange of OPM model. Rival: shared calibration software or selected successful runs create false between-site agreement. EVIDENCE / DOIs / EXPLICIT OPEN REVIEW ITEMS Budker & Romalis (2007), DOI 10.1038/nphys566; Boto et al. (2018), DOI 10.1038/nature26147; four-channel OPM array (2024), DOI 10.1364/OE.517961; JCGM (2008), DOI 10.59161/JCGM100-2008E. Supplied STARLI F02 methods: 10.5281/zenodo.23486020. All flagship-specific results are untested; gate identities and formula adaptations still need expert review. Join the STARLI Research Community: https://zenodo.org/communities/starli-research-gate/ We do not need to know which door future generations will choose to open. We only hope that when they open it, they will find a little light to guide their way. 🌈🚪✨
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- supportingOpen access status: Normalized open-access status: open.
- supportingPublication license: A publication license was supplied: https://creativecommons.org/licenses/by/4.0/legalcode. Presence improves reuse transparency, not research validity.
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- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
STARLI / YULI — F145/200 — Family 15: Regenerative BCI Co-Design 再生腦機介面微環境調控極限 Microenvironment Control In Regenerative BCI At The Limit Research position. This prospective, nonclinical Research Working Edition investigates Microenvironment oxygen concentration deviation [mg/L] in a hydrogel-electrode coculture testbed with a calibrated, independently acquired measurement reference. It proposes a scaffold–electrode–tissue causal model; it does not report completed experiments, animal studies, clinical efficacy, or validated regeneration. Testable claim. With acquisition time, authorized specimens, electrode exposure and reference assays matched, a preregistered joint-interface candidate is compared against an independently tuned conventional scaffold with a separate nonregenerative electrode. The masked challenge is concealed restriction of microfluidic flow; the chief rival is oxygen probe positioning causes apparent gradients. The primary candidate relation is Delta_C_O2 = C_target - C_measured. Interpretation requires Target and measured concentrations must share sampling time, spatial point, temperature and dissolved-oxygen calibration. Research architecture. The volume contains 30 mathematical and engineering diagnostic plates, 82 chapters with 410 one-page investigations, 200 Research Gates with three scientific letters per gate, and 33 Phoenix Answer Embryos. Methods include impedance and material-interface metrology, orthogonal biological witnesses, preregistered blinded tests, uncertainty propagation, negative-result retention, and independent reconstruction. Limitations and evidence. Escalating inflammation, premature material disintegration, loss of independent electrical reference, or revoked sample authorization are hard stops. Candidate mechanisms and formulas are not new confirmed physical laws. Foundational source identity was checked for Yuk, H., Wu, J., Zhao, X. (Nature Reviews Materials 7, 935-952 (2022)), DOI 10.1038/s41578-022-00483-4; Bierman-Duquette, R. D. et al. (Advanced Healthcare Materials 11(7), e2101577 (2022)), DOI 10.1002/adhm.202101577; these publications do not validate the new integrated hypothesis. Deep semantic distinctness across chapters and Gates requires specialist review. Author: 33 / STARLI–YULI Research Institute 36. Version v1.0; 2026-11-06. Join the STARLI Research Community Explore more than 100 interdisciplinary research themes and follow the evolving STARLI Research Gate community: https://zenodo.org/communities/starli-research-gate/
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STARLI / TEN-FLAGSHIP RESEARCH CONSTELLATION YULI · NANO × QUANTUM × REGENERATION × AI × BCI F011–F015 / 200 | Family 02: Neural Regeneration Scaffolds F011 Nanofibrous Neural Regeneration Scaffolds at the Limit Core: nanofiber anisotropy × neurite extension × reference-controlled cytocompatibility. Endpoint: neurite extension length [micrometer]. Blind challenge: masked fiber-axis rotation. Strong baseline: randomly oriented polymer nanofiber and flat inert substrate under identical culture conditions. F012 Programmable Axonal Guidance Nanostructures at the Limit Core: reversible cue programming × axonal directionality × orthogonal geometry readout. Endpoint: axonal directional coherence [dimensionless]. Blind challenge: hidden groove-angle crossover. Strong baseline: static patterned guidance grooves and unpatterned stiffness-matched gel. F013 Neural Stem Cell Nanomicroenvironments at the Limit Core: extracellular matrix cues × stem-cell identity × longitudinal differentiation tracing. Endpoint: lineage-marker-positive cell fraction [percent]. Blind challenge: concealed integrin-blocking dose. Strong baseline: defined-medium monolayer and composition-matched nonstructured hydrogel. F014 Nanotopology and Synaptic Reconstruction at the Limit Core: surface nanotopology × synaptic apposition × electrophysiology confirmation. Endpoint: synaptic colocalization density [per square millimeter]. Blind challenge: concealed nanoridge wavelength. Strong baseline: flat and microscale-patterned controls with independent synaptic-functional recordings. F015 Conductive Hydrogels for Neural Regeneration at the Limit Core: hydrated network conduction × tissue-compatible mechanics × independent neural readout. Endpoint: scaffold bulk conductivity [siemens per meter]. Blind challenge: hidden filler-percolation fraction. Strong baseline: composition-matched nonconductive hydrogel and commercial electrode under equal hydration. SCIENTIFIC INHERITANCE AND GATE CONTRACT Each volume follows the 777-page research book architecture: 14 distinct front-matter arguments, 30 formulas, 82 chapters and 410 individual investigations, 200 experimentally discriminating Research Gates and 33 Phoenix candidates. The three-letter prose is a gift to future scientists, not evidence that an experiment occurred. The source F02 publication supplies engineering rules for distinguishing apparent recovery from verified function. It is not evidence of neuronal regeneration. The YULI atlas fixes the ten independent research themes. STARLI / TEN-FLAGSHIP RESEARCH CONSTELLATION YULI · NANO × QUANTUM × REGENERATION × AI × BCI F016–F020 / 200 | Family 02: Neural Regeneration Scaffolds F016 Intelligent Remodeling of Neural Injury Microenvironments at the Limit Core: bounded milieu feedback × inflammation markers × independent cellular phenotype. Endpoint: cytokine reduction in culture [nanogram per milliliter]. Blind challenge: masked cytokine spiking. Strong baseline: static intervention and vehicle-matched hydrogel with the same cell count. F017 Self-Assembling 3D Neural Nanoscaffolds at the Limit Core: programmable assembly forces × 3D pore topology × qualified cell ingress. Endpoint: connected pore volume fraction [percent]. Blind challenge: masked fiber-length distribution. Strong baseline: templated 3D porous scaffold and static porogen fabrication with matched solids. F018 Bioelectric-Coupled Neural Nanoscaffolds at the Limit Core: electric field exposure × axon steering × electrochemical dose restraint. Endpoint: field-linked neurite direction change [degree]. Blind challenge: concealed polarity reversal. Strong baseline: unstimulated matched scaffold and conventional low-field electrode control. F019 Scaffold Degradation and Neural Function Preservation at the Limit Core: enzymatic scaffold erosion × mechanical support transfer × cellular function qualification. Endpoint: function retained during degradation [percent]. Blind challenge: masked enzyme activity titration. Strong baseline: nondegrading scaffold and controlled-rate degradable reference matched for initial stiffness. F020 Cross-Laboratory Validation of Neural Regeneration Scaffolds at the Limit Core: batch and site effects × metrological traceability × blind external reconstruction. Endpoint: between-laboratory standardized effect contrast [dimensionless standardized difference]. Blind challenge: blind site-label permutation. Strong baseline: standardized two-site ring trial and single-site frozen-protocol baseline. EVIDENCE AND SCIENTIFIC LIMITS These are prospective, nonclinical working editions. Efficacy, model causality and long-term safety require independent experiments. Published methods (Bierman-Duquette et al., DOI 10.1002/adhm.202101577; Yuk et al., DOI 10.1038/s41578-022-00483-4; Dawit et al., DOI 10.1039/D4BM00048J) do not validate these new design hypotheses. Join the STARLI Research Community · https://zenodo.org/communities/starli-research-gate/ We do not need to know which door future generations will choose to open. We only hope that when they open it, they will find a little light to guide their way. 🌈🚪✨
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Thought-Driven AI: A Neuro-Intent Computing Framework for Direct Human–AI Interaction Through Neural Signal Interpretation and Autonomous Task Orchestration
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Advanced methods for BCI-EEG processing for improved classification performance and reproducibility
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User Adapted Brain-Computer Interface
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Contribution to the understanding of mental task BCI performances using predictive computational models
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Brain-computer interface for communication and control purpose
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Challenge and Ethical Concerns in Brain-Computer Interface Application
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Interface cerveau-ordinateur (BCI) : un moyen de communication alternative dans la SLA
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Neurophysiologically Interpretable Brain-Computer Interfaces for Neurological Disorders: From Decoders to Reliable & User-Centered Systems
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Vers une BCI utilisable en dehors du milieu clinique
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