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Eight Sichuan provincial departments in southwestern China led by the Department of Economy and Information Technology issued the Action Plan for Breakthroughs in the Brain-Computer Interface and Human-Machine Interaction Industry in Sichuan (2025-2030) on May 12, 2025. The plan is unusual in making surgical volume a headline metric, targeting 3,000 invasive BCI procedures a year by 2030, along with services for more than 100,000 patients a year with neurodegenerative disease, psychiatric conditions and drug or digital addiction, and rehabilitation device use exceeding 20,000 sessions a year. By 2027 it aims to complete development and medical device registration of three invasive and five non-invasive products, carry out the province's first invasive BCI operation, serve more than 50,000 patients a year, and cultivate 10 chain-leading firms, 100 specialised SMEs and 200 innovative smaller enterprises. Chengdu, Mianyang, Deyang and Nanchong are named as host cities.

The study proposes a discriminative, geometry-aware dimensionality reduction method on the Riemannian manifold for symmetric positive definite (SPD) matrices in EEG classification, aimed at boosting discrimination while reducing information loss. On BCI Competition IV Dataset 1 and Dataset 2a, the method improved classification accuracy by 5.0% and 19.38% respectively, indicating robust performance is retained after dimensionality reduction.

Shanghai's science commission issued a BCI industry action plan centering on medical-grade scenarios, with a clinical timeline for invasive and semi-invasive products.

Three Beijing agencies jointly issued a BCI action plan targeting 3-5 globally influential leaders and around 100 innovative SMEs by 2030.

NeuroXess and Huashan Hospital reported a single-patient test of a 256-channel flexible implantable BCI. In postoperative training, decoding accuracy reached 71% across 142 commonly used Mandarin syllables, with per-character latency below 100 milliseconds. The participant had a language-area tumor and epilepsy, so the company-reported result does not establish performance in people who have lost speech.

Austrian company g.tec medical engineering GmbH has registered a brain-computer interface rehabilitation trial in Parkinson's disease on ClinicalTrials.gov as NCT06690931, first posted on November 15, 2024 and marked completed as of the entry's September 3, 2026 update. It evaluates recoveriX PRO, which pairs motor imagination with functional electrical stimulation (FES) and virtual reality feedback, the user wearing an EEG cap whose recorded neural activity drives the feedback devices, and it asks whether the therapy significantly improves motor function, whether it outperforms standard treatment, and whether it is equally safe. The BCI group trains six times a week for four weeks, 24 sessions in all, while the control group gets the same schedule of FES and VR without EEG monitoring; no results are posted in the registry entry.

Synchron reported 12-month results from the U.S. COMMAND early feasibility study in six people with severe chronic bilateral upper-limb paralysis. All participants met the primary safety endpoint of no device-related serious adverse event causing death or permanent increased disability, and motor-intent signals were converted into digital actions throughout the study. The disclosure was not a two-year pivotal-trial report.

California's SB 1223, enacted in 2024, amended the CCPA to classify neural data as sensitive personal information alongside genetic and biometric data.

Neuralink said thread retraction in its first PRIME participant temporarily reduced BCI performance before the threads stabilized and performance recovered. For the second implant, the team reduced brain motion during surgery and narrowed the gap between the implant and the brain surface. The company reported no thread retraction in the second participant at the time, but it did not publish channel-attrition rates or a formal interim safety report.

The University of Miami has opened a clinical trial testing whether a brain-computer interface can decode upper-limb motor intention from EEG or ECoG and use it both to trigger epidural spinal cord stimulation (ESCS) and to control assistive devices in people with spinal cord injury. The study was first posted on August 1, 2024, and is recruiting.