뇌-컴퓨터 인터페이스는 신경 조직과 외부 컴퓨팅 시스템 간의 직접적인 통신 경로로서, 기존의 신경근 출력 채널을 우회하여 기록된 뇌 활동을 장치 명령, 합성 음성 또는 복원된 감각 피드백으로 실시간 변환합니다.
이 분야는 침습성 정도에 따라 두 가지로 나뉩니다. 비침습적 방식에는 두피 뇌파검사(EEG)와 기능적 근적외선 검사가 있습니다. 분광학 — 수술적 위험 없이 신호를 획득할 수 있지만 공간 해상도와 신호 대 잡음비가 매우 제한적인 방식이 있습니다. 대뇌 피질 표면에 배치된 전기피질기록 그리드는 중간 단계에 해당하며, 유타 어레이와 뉴럴링크의 유연한 실 전극 시스템으로 대표되는 완전 피질내 접근 방식은 수술적 이식, 이물 반응 및 장기적인 전극 안정성 저하라는 단점을 감수해야 하지만 수백에서 수천 개의 뉴런에서 동시에 단일 뉴런 스파이크를 기록합니다.
신호 처리 파이프라인 — 스파이크 정렬, local field potential decomposition, and increasingly deep learning decoders trained on neural population dynamics — translate raw electrophysiology into high-dimensional control signals, with motor cortex decoding for cursor control and robotic limb actuation and speech area decoding for imagined or attempted speech synthesis representing the two most clinically advanced application tracks. 폐쇄 루프 신경 기록과 정확한 시점의 피질 또는 말초 신경 자극을 결합한 아키텍처는 뇌졸중 재활, 치료 저항성 우울증 및 간질 관리를 동시에 발전시키고 있습니다.
아래에 색인된 논문 및 특허는 전극 재료 과학, ASIC 프런트엔드 증폭기 설계, 디코더 알고리즘, 무선 신경 원격 측정, 생체 적합성 연구 등을 포괄합니다. clinical trial 침습성의 전체 범위에 걸친 결과:
본 자료는 전 세계 과학 온라인 저널에 게재된 뇌-컴퓨터 인터페이스(BCI) 관련 영문 논문 및 특허를 엄선하여 정리한 최신 자료입니다. BCI, 뇌-컴퓨터 인터페이스, 신경 인터페이스, 뇌피질전도, 피질내 전극 배열, 유타 배열, 뉴럴링크 임플란트, 스텐트로이드 BCI, EEG 기반 BCI 등의 키워드를 중심으로 분류 및 분석했습니다. 모터 cortex decoding, neural spike sorting, local field potential BCI, spiking neural network decoder, neural signal amplifier, closed-loop neurostimulation, BCI motor neuroprosthesis, speech BCI, imagined speech decoding, BCI cursor control, BCI communication device, neural decoder algorithm, BCI artifact rejection, flexible neural probe, biocompatible neural electrode and BCI long-term stability.
Neuronal avalanches as a predictive biomarker for guiding tailored BCI training programs
Published on 2026-05-29 by @MIT
Abstract: AbstractMotor imagery-based Brain-Computer Interfaces (BCIs) restore control in persons with motor impairments, but up to 30% of users struggle, a phenomenon known as “BCI inefficiency”. This study tackles a key limitation of current protocol: the use of fixed-length sessions training paradigms that ignore individual learning variability. We propose a novel approach based on neuronal avalanches, spatiotemporal cascades of brain activities, as biomarkers to characterize and predict user-speci[...]
Our summary: This study introduces neuronal avalanches as predictive biomarkers for personalized BCI training programs. It analyzes electroencephalography data to correlate avalanche characteristics with BCI performance. The findings support tailored approaches to enhance user success and reduce BCI inefficiency.
neuronal avalanches, BCI training, biomarkers, motor imagery
Publication
Large language models reveal the neural tracking of linguistic context in attended and unattended multi-talker speech
Published on 2026-05-07 by @MIT
Abstract: AbstractLarge language models (LLMs) capture long-range contextual structure in natural language and have recently been shown to align with the human brain’s contextualized linguistic encoding. This makes them a promising computational probe for studying how context-dependent linguistic information is represented during natural speech perception. Speech perception often occurs in multi-talker environments, where attention must dynamically select among competing streams, yet how contextual info[...]
Our summary: Large language models align with human brain encoding of linguistic context. The study explores how attention affects neural tracking of speech in multi-talker environments. Findings indicate that both attended and unattended speech streams contribute to neural predictions based on contextual information.
language models, neural tracking, speech perception, auditory attention
Publication
Suppression of inflammation associated with implants
Patent published on the 2026-05-07 in WO under Ref WO2026092500 by SUNMED THERAPEUTIC LTD [CN] (Sun Joseph [cn], Sun Dongxu [cn])
Abstract: Provided herein are methods and compositions for suppressing a foreign body reaction, such as an implant-associated inflammation in a subject, by using an anti-Galectin-3 antibody. Such methods and compositions can be used in various areas applications where an implant is introduced, such as in brain-computer interface (BCI).[...]
Our summary: Methods and compositions are described for suppressing implant-associated inflammation using an anti-Galectin-3 antibody. These approaches target the foreign body reaction in subjects receiving implants. Applications include areas like brain-computer interfaces (BCI).
anti-Galectin-3, inflammation suppression, foreign body reaction, implants
Patent
Towards the use of functional near-infrared spectroscopy as an assessment tool in disorders of consciousness
Published on 2026-04-30 by @MIT
Abstract: AbstractFunctional near-infrared spectroscopy (fNIRS) has emerged as a promising neuroimaging tool for assessing patients with disorders of consciousness (DoC). While functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have advanced the detection of covert brain function, their use is often constrained by accessibility, medical and physical contraindications, and practical limitations. fNIRS offers a portable, safe, and cost-effective alternative capable of measuring he[...]
Our summary: Functional near-infrared spectroscopy (fNIRS) is a promising tool for assessing disorders of consciousness (DoC). It provides a portable and cost-effective alternative to fMRI and EEG for measuring brain function. Future research should focus on validation, multimodal integration, and ethical access to enhance DoC care.
fNIRS, disorders of consciousness, neuroimaging, brain-computer interfaces
Publication
A reference-less level-crossing adc with a bump-based adaptive-bias comparator
Patent published on the 2026-04-22 in EP under Ref EP4730654 by IMEC VZW [BE] (Yang Xiaolin [be], Xing Xiaonan [be], Sawigun Chutham [be], Mora Lopez Carolina [be])
Abstract: This disclosure relates to a comparator circuit and an ADC circuit for a neural interface. The ADC circuit includes the comparator circuit. The comparator circuit comprises a comparator to receive a first and a second signal, and internally amplify the first and the second signal. A bump bias circuit of the comparator circuit receives the amplified first and second signal, and causes the comparator to operate at a higher power level when a difference between the amplified first and second signal[...]
Our summary: The disclosure describes a reference-less level-crossing ADC featuring a bump-based adaptive-bias comparator. The comparator amplifies two input signals and adjusts its power level based on their difference. The ADC includes two comparator circuits and switching circuits controlled by a control circuit for capacitor state management.
ADC, comparator, adaptive-bias, neural interface
Patent
All spectral frequencies of neural activity reveal semantic representation in the human anterior ventral temporal cortex
Published on 2026-04-17 by @MIT
Abstract: AbstractIntracranial electrophysiology offers a unique insight into the nature of information representation in the brain—it can be used to disentangle information encoded in gamma and high gamma frequencies from information encoded in lower frequencies. We used regularised logistic regression to decode animacy from time-frequency power and phase extracted from electrocorticography (ECoG) grid electrode data recorded on the surface of human ventral anterior temporal lobe (vATL). Power in gamma[...]
Our summary: Neural activity in the anterior ventral temporal cortex encodes semantic information across various spectral frequencies. Intracranial electrophysiology reveals that gamma and high gamma frequencies contribute to reliable decoding of animacy. A broader frequency range enhances decoding accuracy, supporting the concept of a local vATL hub interacting with distributed cortical spokes.
neural activity, semantic representation, electrocorticography, frequency decoding
Publication
Brain-computer interface system and method
Patent published on the 2026-03-26 in WO under Ref WO2026064733 by SCIENCE CORP [US] (Rostov Marat [us], Slager Nate [us], Walker Sage [us], Hodak Max [us], Sharpe Russell [us], Zhou Emma [us], Elsen Antonia [us])
Abstract: Variants of the system can include: a probe and an interface device. Variants of the method can include: configuring a signal pipeline and executing the signal pipeline. In variants, the system and/or method can function to record neural signals from a variety of brain-computer interface (BCI) probe devices. In a specific example, the system and/or method can enable high bandwidth neural recording and processing for BCI experiments.[...]
Our summary: The content describes a brain-computer interface system and method that includes a probe and an interface device. It details the configuration and execution of a signal pipeline to record neural signals from BCI devices. The system aims to enable high bandwidth neural recording and processing for BCI experiments.
brain-computer interface, neural signals, signal pipeline, high bandwidth
Patent
A novel hybrid BCI system combining single-channel SSVEP and PLR to improve classification accuracy and ITR
Published on 2026-03-24 by @OXFORD
Abstract: AbstractSteady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) have been widely studied because they provide high classification accuracy and information transfer rate (ITR) without requiring user training. To further enhance BCI performance, this study proposes a novel hybrid BCI that integrates single-channel SSVEP with the pupillary light reflex (PLR). Twelve healthy subjects participated in experiments involving three paradigms: SSVEP, PLR, and hybrid. Each sub[...]
Our summary: This study presents a hybrid BCI system that combines single-channel SSVEP and PLR to enhance classification accuracy and information transfer rate. The hybrid paradigm achieved a classification accuracy of 95.70%, outperforming both SSVEP and PLR methods. Results indicate that this approach can significantly improve BCI performance, potentially facilitating broader adoption.
BCI, SSVEP, PLR, classification
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