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Motor-imagery brain-computer interfaces vary widely between users and have little calibration data, and federated learning lets them share a model without uploading raw EEG. NEXUS-MI treats gateway synchronization as a joint learning-and-communication control problem: raw EEG and classifier heads stay local, while an edge coordinator maintains the shared backbone network. On the BCICIV-2a and OpenBMI datasets, communication-aware coordination cut server-to-client backbone traffic by about 42%, with small, implementation-dependent differences in cohort-average accuracy. Those averages masked individual vulnerability: on BCICIV-2a, losses relative to an ideal-link reference reached about 12 percentage points.

Participants steering a virtual avatar with a brain-computer interface reported a stronger sense that the avatar's body was their own when they imagined jogging than when they imagined opening their right hand, even though jogging imagery produced weaker EEG signals. Forward movement was driven by motor imagery-related sensorimotor rhythm event-related desynchronization from scalp EEG and direction by eye gaze, as participants guided a jogging avatar along a curved course before rating their embodiment in questionnaires. The researchers say neural signal strength and embodied experience can diverge, so the congruence between imagery and action should be weighed alongside standard decoding metrics.

Researchers at the University of California, San Francisco (UCSF), a public research university known for its neuroscience work, had two Parkinson's disease patients train at home with a brain-computer interface (BCI) airplane-simulator game, learning to down-regulate cortical beta activity and thereby control the intensity of their own deep brain stimulation (DBS). The work, posted as a preprint on medRxiv on August 17, 2026, points to BCI applications in neuromodulation and to more personalized treatment for Parkinson's and other conditions; its conclusions have not yet been peer reviewed.

Pascall Systems, Inc. received U.S. Food and Drug Administration (FDA) 510(k) clearance for its Pascall Sensor Unit (PSU1) on August 19, 2026, with the agency finding the device substantially equivalent. The device is a Class II medical device under regulation number 882.1400, classification name Non-Normalizing Quantitative Electroencephalograph Software.

On May 8, 2026, Apple notified the European Commission under Article 14 of the Digital Markets Act that it would, through a subsidiary, acquire certain assets of Sonera and offer jobs to and hire certain Sonera employees. The deal value was not disclosed and neither party has announced it; May 8 is the filing date, and no closing date has been made public. The Commission describes Sonera as a company developing chip-scale magnetic sensors. Founded in 2018 in Berkeley, California, as a University of California, Berkeley spinout, Sonera builds acoustically driven ferromagnetic resonance magnetic sensors that operate at room temperature and has raised about $20 million.

Researchers have mapped the brain-computer interface (BCI) attack surface along five dimensions (forged neural signals, desynchronization-based evasion, replay hijacking, "Vein Tapping" eavesdropping and embedded backdoors), which they group as "NERVE Attacks" and describe as orthogonal and together spanning the full BCI stack. Their EEGle framework, which the team is releasing to the community for building and verifying device security, surfaced 17 new neuro-specific attack instances and a stealth-versus-effectiveness trade-off in backdoor design. The authors warn that generative AI is lowering the barrier for non-expert attackers, with risks to cognitive autonomy, mental privacy and physical safety, from neural data exfiltration to malicious control of BCI-connected devices. The preprint, by Zahra Tarkhani, Georgios Akkogiounoglou, Lorena Qendro, Isabel Tscherniak and Anil Madhavapeddy, has not been peer reviewed.

Chronic stroke patients who used an at-home brain-computer interface (BCI) therapy system gained a mean 6.0 points on the Upper Extremity Fugl-Meyer Assessment after 12 weeks, versus 1.5 points for those on a home exercise program. Response rates were 55.5% and 9.6%, for a number needed to treat of 2.2. The trial also exposed the dropout problem in home-based studies: 17 of 42 control participants withdrew because they were dissatisfied with their group assignment.

Even when the eyes stay fixed on one point, the brain tracks moving objects in a video, and that tracking grows stronger with attention. But researchers at KU Leuven found that EEG tracking of an object's motion weakens the farther the object sits from the fixation point, meaning decoding methods that read attention from tracking strength may mistake where an object is for where attention is.

How can people with severe motor disorders bypass damaged nerve pathways and steer a robotic arm with their thoughts? This review traces the full signal chain: recording neural activity from the motor cortex, preprocessing it, extracting features, decoding it and generating continuous, discrete or multi-degree-of-freedom arm commands. The author compares signal acquisition in invasive, non-invasive and intravascular BCIs and argues that jointly optimizing signal quality, decoding algorithms and shared control is key to more natural and reliable arm operation, while noting that long-term stability, control accuracy and clinical safety remain limited.

Sleep spindles, brief bursts of brain rhythm during deep sleep linked to memory consolidation, further lowered the excitability of the motor pathway beyond the drop already seen in spindle-free N2/N3 sleep. Researchers timed magnetic pulses to the motor cortex using live EEG readings. Contrary to their hypothesis, a measure of local GABA-A inhibition did not change with spindles or their phase. The study is a preprint and has not been peer reviewed.