BCIwiki — Brain-computer interface news, research and industry database

A review published on August 20, 2026 in npj Biomedical Innovations proposes brain-inspired brain-computer interfaces (BI-BCIs), a framework that unifies neuromorphic computing with BCI design to make neurotechnology lower-power, smaller and capable of closed-loop operation. The authors, from Aarhus University, Stanford University, the University of Southern Denmark, the University of Genoa, Forschungszentrum Jülich and RWTH Aachen University, say the approach could advance neuroprosthetics and neuromodulation for neurological disorders.

BCI research has long been slowed by inconsistent data formats, divergent decoder implementations and incompatible deployment toolchains. BCIJelly standardizes 18 BCI datasets into inputs ready for AI training and integrates 15 benchmark decoders and 80 reusable modules. Its automated architecture search generates task-specific decoders without manual design and can extend into a large language model-driven closed-loop mode that supports single-task, multitask and cross-species decoder design; the system also offers interactive visualization software that requires no coding. A single-command pipeline compiles trained decoders onto neuromorphic hardware, cutting power consumption 30- to 50-fold while maintaining decoding performance. The work has been validated in humans, macaques and mice across five paradigms: motor, visual, speech, emotion and auditory. It is a preprint that has not been peer reviewed.

DRDNet separates spatial EEG features into two temporal views, models them with a bidirectional Mamba encoder and a Transformer, and then combines them through dynamic fusion and LSTM aggregation. On a public dataset, it reached 67.74% accuracy for imagined Chinese-character strokes and 62.51% for imagined pinyin vowels, outperforming seven EEG-decoding baselines.

A Stanford program is recording brain activity in psychiatric inpatients at millisecond precision, combining noninvasive electrode arrays with deep brain recording electrodes to trace the circuits behind schizoaffective disorder, borderline personality disorder, autism and cancer-induced depression. The Human Neural Circuitry program, led by neuroscientist Karl Deisseroth at the Wu Tsai Neurosciences Institute, has run for three years and moves data over fiber-optic and copper links fast enough for round trips of under half a millisecond, allowing the system to sense and respond in a closed loop. Deisseroth said the key innovation is getting results at millisecond precision, which he called a crucial step toward understanding complex psychiatric symptoms.

Published in Neural Regeneration Research on August 18, 2026, the study conducted a bibliometric analysis of 3173 articles from the Web of Science Core Collection on post-stroke limb motor dysfunction and functional recovery from 2016 to 2025, by authors from Beijing Rehabilitation Hospital, Capital Medical University. The field is in a period of rapid expansion, with technology-assisted rehabilitation as the dominant trend and robot-assisted training and virtual reality as the two major technological keywords. Burst literature analysis revealed three hotspot phases, with the recent phase (2020 to present) covering neuromodulation (brain-computer interface and non-invasive brain stimulation), global disease burden and public health policy. Highly cited studies focus on comparative efficacy, robot-assisted training, brain-computer interfaces, vagus nerve stimulation and prediction of rehabilitation outcomes.

Chinese insurers have begun introducing BCI-related coverage. Shanghai's 2026 Hu-huibao plan added up to 150,000 yuan for out-of-pocket materials used in inpatient BCI surgery, PICC Property and Casualty underwrote an invasive-BCI surgical accident policy for the Second Affiliated Hospital of Zhejiang University School of Medicine, and China Pacific Property Insurance covered patients receiving Neuracle's NEO implant at Huashan Hospital.

Researchers report that a BCI-controlled sixth-finger neurofeedback intervention improved motor function in stroke: after 8 sessions (2 weeks) of motor-imagery BCI training, 14 patients gained an average of 7.9 points on FMA-UE and 7.1 on the Barthel Index, with 9 of 14 reaching the 6.6-point minimally clinically important difference. EEG tracking across the full intervention showed a two-phase ERD trend that strengthened in week one and narrowed to the contralateral sensorimotor area in week two, and resting-state functional connectivity rose afterward, correlating with motor gains. The authors say the work offers longitudinal evidence on neuroplasticity in stroke rehabilitation.

Six Fujian government departments jointly issued a provincial BCI action plan for 2026–2030. It calls for key technical breakthroughs, more than five innovative small and medium-sized companies, one cross-strait joint laboratory and two provincial innovation platforms by 2027; by 2030, Fujian aims to have 30 companies, a complete industry chain and an industry worth more than 3 billion yuan.