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University of Washington

8 entries
October 2026

Language Models Speed P300 Spellers by Up to 75%, Approaching Theoretical Limit

Researchers have shown that language models can raise typing speed on P300 spellers, the EEG-based BCIs that let people with severe paralysis such as ALS type by focusing on flashing characters, by up to about 45% with within-subject training and about 75% with cross-subject training compared with conventional methods. The spellers are slow and need individual calibration. Using EEG data from 78 subjects in simulation, the team compared several language models for word prediction. The best-performing models differed in architecture yet all came within 5% of the theoretical upper bound, suggesting that larger language models will yield little further gain and that brain signal decoding is now the bottleneck. The conclusions come from offline simulation, not testing by patients.
September 2026

Adaptive BCI Decoders Concentrate Task Information in Fewer Monkey Motor Neurons

After days of practicing a brain-computer interface with adaptive decoders, rhesus macaques needed significantly fewer motor cortex neurons to reach 80% task classification accuracy than in early sessions (p = 9.8 x 10^-4). Fixed decoders produced no such compaction. A neural network model suggests the adaptive decoders directly contribute to these more compact representations; the authors propose this may be because the decoders alter the error information used for credit assignment. The finding implies that assistive algorithms do not merely boost immediate BCI performance but actively reshape how the brain learns over time -- a consideration for real-world decoder design. The study used 128-channel microwire arrays in motor and premotor cortices of two monkeys and has not been tested in humans.
August 2026

Stanford's Palanker Wins Defense Health Agency Award for PRIMA Retinal Implant

Daniel Palanker, a Stanford professor and affiliate of the university's Wu Tsai Neurosciences Institute, has won the U.S. Defense Health Agency's Outstanding Research Accomplishment award for the PRIMA retinal implant, designed to restore central vision after photoreceptor loss. A 2-mm chip sits beneath the retina and is driven by infrared light from augmented-reality glasses, converting that light into current that stimulates the next layer of neurons. A 2025 paper in the New England Journal of Medicine reported that the device let legally blind patients with advanced dry age-related macular degeneration read letters and words, and the award recognizes its potential for military personnel with laser-damaged retinas.
July 2026

Soft Porous Brain Implants Reduce Glial Scarring and Guide Regeneration

Researchers at the University of Washington have built mechanically compliant, precision-porous brain implants and tested them in rat brains. At 4 weeks, the porous scaffolds drew less astrocyte encapsulation than solid hydrogel rods, softer hydrogels reduced pro-inflammatory macrophage polarization, and new blood vessels, neuronal markers and neurogenesis appeared inside the pores. The authors present the design as a route to limiting glial scarring and improving regeneration in implant-based central nervous system therapies.

Bayesian pooling: 13x energy, no practical gain

Researchers report a preprint, posted to arXiv on July 25, 2026 and not yet peer reviewed, that contrasts Bayesian complete-pooling models against frequentist baselines for cross-subject, left-hand versus right-hand motor imagery EEG classification across 20 datasets. Six frequentist pipelines were each paired with an analogous Bayesian pipeline sharing identical feature engineering and fit via Markov chain Monte Carlo posterior sampling. Bayesian complete-pooling produced statistically but not practically significant improvements in reliability and increased predictive uncertainty, with no significant differences in Brier score, resolution, or discrimination. Bayesian pipelines consumed roughly 13 times more energy than their frequentist counterparts, and the authors conclude that complete pooling alone offers limited practical benefit, pointing to partial pooling as a more promising direction.

UW Team Maps Uneven Reach Coding in Monkey Motor Cortex to Guide BCI Implant Placement

Researchers at the Center for Neurotechnology at the University of Washington recorded from two male monkeys with high-density laminar microelectrode arrays and found that reaching-related activity in frontal motor cortex is unevenly distributed both across the cortical surface and with depth. Target-direction information varied sharply between neural populations, but the amount of task information a population carried predicted which populations shared similar temporal dynamics. The authors say the pattern should inform where electrodes are placed in future brain-computer interface implants.
September 2025

Neuropixels Ultra Doubles Neuron Yield With 6-Micrometer Site Spacing

A Neuron paper describes Neuropixels Ultra, which packs 6,144 switchable recording sites at 6-micrometer center-to-center spacing while reading 384 channels simultaneously. In mouse visual cortex recordings, neuronal yield increased by more than twofold. The study also improved subcellular signal detection and cell-type classification, but it did not report simultaneous recording from 10,000 neurons.
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