# Brain-Computer Interfaces Domain: Neuroscience & Brain-Computer Interfaces · 280 papers indexed · newest 2026-10-27 Speech and handwriting neuroprostheses, high-channel-count intracortical arrays, endovascular and minimally invasive BCIs and closed-loop stimulation. Key concepts: brain-computer interface, neuroprosthesis, speech decoding, intracortical, neural decoding ## Most influential - **[A high-performance speech neuroprosthesis](https://space-kitty.com/papers/doi:10.1038/s41586-023-06377-x)**. Francis R. Willett, Erin M. Kunz, Chaofei Fan et al. · 2023 · Nature (doi:10.1038/s41586-023-06377-x · 578 citations). Source: > Speech brain-computer interfaces (BCIs) have the potential to restore rapid communication to people with paralysis by decoding neural activity evoked by attempted speaking movements into text or sound. Early demonstrations, while promising, have not yet achieved accuracies high enough for communication of unconstrainted sentences from a large vocabulary. Here, we demonstrate the first speech-to-text BCI that records spiking activity from intracortical microelectrode arrays. Enabled by these high-resolution recordings, our study participant, who can no longer speak intelligibly due amyotrophic … > _Abstract excerpt by Francis R. Willett et al., CC-BY, https://doi.org/10.1038/s41586-023-06377-x; truncated._ - **[Brain computer interfaces, a review](https://space-kitty.com/papers/doi:10.3390/s120201211)**. Nicolas-Alonso LF, Gomez-Gil J · 2012 · Sensors (Basel, Switzerland) (doi:10.3390/s120201211 · 715 citations). Source: > A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature ext… > _Abstract excerpt by Nicolas-Alonso LF et al., CC-BY, https://doi.org/10.3390/s120201211; truncated._ - **[An Accurate and Rapidly Calibrating Speech Neuroprosthesis](https://space-kitty.com/papers/doi:10.1056/nejmoa2314132)**. Nicholas S. Card, Maitreyee Wairagkar, Carrina Iacobacci et al. · 2024 · New England Journal of Medicine (doi:10.1056/nejmoa2314132 · 243 citations). Source: - **[fNIRS-based brain-computer interfaces: a review](https://space-kitty.com/papers/doi:10.3389/fnhum.2015.00003)**. Naseer N, Hong KS · 2015 · Frontiers in human neuroscience (doi:10.3389/fnhum.2015.00003 · 404 citations). Source: > A brain-computer interface (BCI) is a communication system that allows the use of brain activity to control computers or other external devices. It can, by bypassing the peripheral nervous system, provide a means of communication for people suffering from severe motor disabilities or in a persistent vegetative state. In this paper, brain-signal generation tasks, noise removal methods, feature extraction/selection schemes, and classification techniques for fNIRS-based BCI are reviewed. The most common brain areas for fNIRS BCI are the primary motor cortex and the prefrontal cortex. In relation … > _Abstract excerpt by Naseer N et al., CC-BY, https://doi.org/10.3389/fnhum.2015.00003; truncated._ - **[High performance communication by people with paralysis using an intracortical brain-computer interface](https://space-kitty.com/papers/doi:10.7554/elife.18554)**. Pandarinath C, Nuyujukian P, Blabe CH et al. · 2017 · eLife (doi:10.7554/elife.18554 · 388 citations). Source: > Brain-computer interfaces (BCIs) have the potential to restore communication for people with tetraplegia and anarthria by translating neural activity into control signals for assistive communication devices. While previous pre-clinical and clinical studies have demonstrated promising proofs-of-concept (Serruya et al., 2002; Simeral et al., 2011; Bacher et al., 2015; Nuyujukian et al., 2015; Aflalo et al., 2015; Gilja et al., 2015; Jarosiewicz et al., 2015; Wolpaw et al., 1998; Hwang et al., 2012; Spüler et al., 2012; Leuthardt et al., 2004; Taylor et al., 2002; Schalk et al., 2008; Moran, 2010… - **[BCI for stroke rehabilitation: motor and beyond](https://space-kitty.com/papers/doi:10.1088/1741-2552/aba162)**. Mane R, Chouhan T, Guan C · 2020 · Journal of neural engineering (doi:10.1088/1741-2552/aba162 · 237 citations). Source: > Stroke is one of the leading causes of long-term disability among adults and contributes to major socio-economic burden globally. Stroke frequently results in multifaceted impairments including motor, cognitive and emotion deficits. In recent years, brain-computer interface (BCI)-based therapy has shown promising results for post-stroke motor rehabilitation. In spite of the success received by BCI-based interventions in the motor domain, non-motor impairments are yet to receive similar attention in research and clinical settings. Some preliminary encouraging results in post-stroke cognitive re… > _Abstract excerpt by Mane R et al., CC-BY, https://doi.org/10.1088/1741-2552/aba162; truncated._ - **[EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy](https://space-kitty.com/papers/doi:10.1093/gigascience/giz002)**. Lee MH, Kwon OY, Kim YJ et al. · 2019 · GigaScience (doi:10.1093/gigascience/giz002 · 235 citations). Source: > Background Electroencephalography (EEG)-based brain-computer interface (BCI) systems are mainly divided into three major paradigms: motor imagery (MI), event-related potential (ERP), and steady-state visually evoked potential (SSVEP). Here, we present a BCI dataset that includes the three major BCI paradigms with a large number of subjects over multiple sessions. In addition, information about the psychological and physiological conditions of BCI users was obtained using a questionnaire, and task-unrelated parameters such as resting state, artifacts, and electromyography of both arms were also… > _Abstract excerpt by Lee MH et al., CC-BY, https://doi.org/10.1093/gigascience/giz002; truncated._ - **[Progress in Brain Computer Interfaces: Challenges and Trends](https://space-kitty.com/papers/arxiv:1901.03442)**. Simanto Saha, Khondaker A. Mamun, Khawza Ahmed et al. · 2019 · Frontiers in systems neuroscience (arXiv:1901.03442 · doi:10.3389/fnsys.2021.578875 · 396 citations). Source: > Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming and artificial intelligence. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and nonlinear brain dynamics and related feature extraction and classifi… - **[An electrocorticographic brain interface in an individual with tetraplegia](https://space-kitty.com/papers/doi:10.1371/journal.pone.0055344)**. Wang W, Collinger JL, Degenhart AD et al. · 2013 · PloS one (doi:10.1371/journal.pone.0055344 · 233 citations). Source: > Brain-computer interface (BCI) technology aims to help individuals with disability to control assistive devices and reanimate paralyzed limbs. Our study investigated the feasibility of an electrocorticography (ECoG)-based BCI system in an individual with tetraplegia caused by C4 level spinal cord injury. ECoG signals were recorded with a high-density 32-electrode grid over the hand and arm area of the left sensorimotor cortex. The participant was able to voluntarily activate his sensorimotor cortex using attempted movements, with distinct cortical activity patterns for different segments of th… - **[Pathology of pain and its implications for therapeutic interventions](https://space-kitty.com/papers/doi:10.1038/s41392-024-01845-w)**. Cao B, Xu Q, Shi Y et al. · 2024 · Signal transduction and targeted therapy (doi:10.1038/s41392-024-01845-w · 153 citations). Source: > Pain is estimated to affect more than 20% of the global population, imposing incalculable health and economic burdens. Effective pain management is crucial for individuals suffering from pain. However, the current methods for pain assessment and treatment fall short of clinical needs. Benefiting from advances in neuroscience and biotechnology, the neuronal circuits and molecular mechanisms critically involved in pain modulation have been elucidated. These research achievements have incited progress in identifying new diagnostic and therapeutic targets. In this review, we first introduce fundam… > _Abstract excerpt by Cao B et al., CC-BY, https://doi.org/10.1038/s41392-024-01845-w; truncated._ - **[An instantaneous voice-synthesis neuroprosthesis](https://space-kitty.com/papers/doi:10.1038/s41586-025-09127-3)**. Maitreyee Wairagkar, Nicholas S. Card, Tyler S. Singer-Clark et al. · 2025 · Nature (doi:10.1038/s41586-025-09127-3 · 98 citations). Source: - **[Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain-computer interface](https://space-kitty.com/papers/doi:10.1088/1741-2560/10/4/046003)**. LaFleur K, Cassady K, Doud A et al. · 2013 · Journal of neural engineering (doi:10.1088/1741-2560/10/4/046003 · 229 citations). Source: > Objective At the balanced intersection of human and machine adaptation is found the optimally functioning brain-computer interface (BCI). In this study, we report a novel experiment of BCI controlling a robotic quadcopter in three-dimensional (3D) physical space using noninvasive scalp electroencephalogram (EEG) in human subjects. We then quantify the performance of this system using metrics suitable for asynchronous BCI. Lastly, we examine the impact that the operation of a real world device has on subjects' control in comparison to a 2D virtual cursor task. Approach Five human subjects were … > _Abstract excerpt by LaFleur K et al., CC-BY, https://doi.org/10.1088/1741-2560/10/4/046003; truncated._ - **[Noninvasive Electroencephalogram Based Control of a Robotic Arm for Reach and Grasp Tasks](https://space-kitty.com/papers/doi:10.1038/srep38565)**. Meng J, Zhang S, Bekyo A et al. · 2016 · Scientific reports (doi:10.1038/srep38565 · 216 citations). Source: > Brain-computer interface (BCI) technologies aim to provide a bridge between the human brain and external devices. Prior research using non-invasive BCI to control virtual objects, such as computer cursors and virtual helicopters, and real-world objects, such as wheelchairs and quadcopters, has demonstrated the promise of BCI technologies. However, controlling a robotic arm to complete reach-and-grasp tasks efficiently using non-invasive BCI has yet to be shown. In this study, we found that a group of 13 human subjects could willingly modulate brain activity to control a robotic arm with high a… > _Abstract excerpt by Meng J et al., CC-BY, https://doi.org/10.1038/srep38565; truncated._ - **[The lab streaming layer for synchronized multimodal recording](https://space-kitty.com/papers/doi:10.1162/imag.a.136)**. Kothe C, Shirazi SY, Stenner T et al. · 2025 · Imaging neuroscience (Cambridge, Mass.) (doi:10.1162/imag.a.136 · 132 citations). Source: > Accurately recording the interactions of humans or other organisms with their environment and other agents requires synchronized data access via multiple instruments, often running independently using different clocks. Active, hardware-mediated solutions are often infeasible or prohibitively costly to build and run across arbitrary collections of input systems. The Lab Streaming Layer (LSL) framework offers a software-based approach to synchronizing data streams based on per-sample time stamps and time synchronization across a common local area network (LAN). Built from the ground up for neuro… > _Abstract excerpt by Kothe C et al., CC-BY, https://doi.org/10.1162/imag.a.136; truncated._ - **[Towards reconstructing intelligible speech from the human auditory cortex](https://space-kitty.com/papers/doi:10.1038/s41598-018-37359-z)**. Hassan Akbari, Bahar Khalighinejad, Jose L. Herrero et al. · 2019 · Scientific Reports (doi:10.1038/s41598-018-37359-z · 221 citations). Source: > Auditory stimulus reconstruction is a technique that finds the best approximation of the acoustic stimulus from the population of evoked neural activity. Reconstructing speech from the human auditory cortex creates the possibility of a speech neuroprosthetic to establish a direct communication with the brain and has been shown to be possible in both overt and covert conditions. However, the low quality of the reconstructed speech has severely limited the utility of this method for brain-computer interface (BCI) applications. To advance the state-of-the-art in speech neuroprosthesis, we combine… > _Abstract excerpt by Hassan Akbari et al., CC-BY, https://doi.org/10.1038/s41598-018-37359-z; truncated._ ## Newest - **[The geometry of cognition: from neural populations to neurotechnology](https://space-kitty.com/papers/arxiv:2610.36541)**. Lucas Bayones, Devika Narain, Roman Rossi-Pool · 2026 (arXiv:2610.36541). Source: - **[Neuronal Identity as an Organizational Basis for Analyzing Neural Population Dynamics](https://space-kitty.com/papers/arxiv:2610.36745)**. Seungjae Han, Joshua Yedam You, Soi Kim et al. · 2026 (arXiv:2610.36745). Source: - **[MtReNIRS: A Self-Supervised Foundation Model for Transferable Neurovascular Representations](https://space-kitty.com/papers/arxiv:2610.36159)**. Tony Chae, Kleanthis Avramidis, Dimitra Emmanouilidou et al. · 2026 (arXiv:2610.36159). Source: - **[ORBITAL: Optimization of Robust Brain--Computer Inference Through Architecture-Aware Low-Precision Compression](https://space-kitty.com/papers/arxiv:2610.36411)**. Saim Rehman, Muhammad Shafique · 2026 (arXiv:2610.36411). Source: - **[From confidence to caution: conformal gating for cross-session motor imagery brain-computer interfaces](https://space-kitty.com/papers/doi:10.1088/1741-2552/aead26)**. Xing S, Nagarajan A · 2026 · Journal of neural engineering (doi:10.1088/1741-2552/aead26). Source: - **[Memory-Augmented Online Test-Time Adaptation for EEG Motor Imagery via Perturbation Consistency and Confidence Calibration](https://space-kitty.com/papers/arxiv:2610.30422)**. Kunkun Zhang, Kehao Wu, Zhitao Chen et al. · 2026 · IEEE Transactions on Instrumentation and Measurement (arXiv:2610.30422 · doi:10.1109/tim.2026.3736160). Source: - **[Ultra high-density, 4096-channel intraoperative neurophysiological brain mapping for functional localization of the human central sulcus](https://space-kitty.com/papers/doi:10.1088/1741-2552/aea70f)**. Skular AF, Tostaeva G, Ho E et al. · 2026 · Journal of neural engineering (doi:10.1088/1741-2552/aea70f). Source: - **[NeuroAct: Advancing EEG Analysis and Decoding via Dual-Loop Autonomous Research](https://space-kitty.com/papers/arxiv:2610.25211)**. Wei Xiong, Jiangtong Li, Han Zhao et al. · 2026 (arXiv:2610.25211). Source: - **[TriRouter: Sparse-to-Dense Electrode-Space Routing for Robust EEG Motor Imagery Decoding](https://space-kitty.com/papers/arxiv:2610.23665)**. Ying Zhou, Yaoxin, Mengting Liu · 2026 (arXiv:2610.23665). Source: - **[An exploration in mental health care: The launch of China's first psychiatric noninvasive brain-computer interface (BCI) and neuromodulation clinic](https://space-kitty.com/papers/doi:10.1002/gps3.70069)**. Wei Y, Cui H, Zhu J et al. · 2026 · General psychiatry (doi:10.1002/gps3.70069). Source: --- Space Kitty Archive · https://space-kitty.com · API: https://space-kitty.com/api/v1 · MCP: https://space-kitty.com/mcp · Premium: $0.20/request via x402 (Base Sepolia (testnet)). Metadata: arXiv (CC0), OpenAlex (CC0), Europe PMC (CC BY/CC0 works), ClinicalTrials.gov.