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Utrecht University

3 entries
August 2026

Utrecht Team Finds ECoG Grids Can Shrink up to 94% without Losing Decoding Accuracy

Researchers at University Medical Center Utrecht's Brain Center in the Netherlands and collaborators exhaustively tested every rectangular subgrid inside 32-, 64- and 128-channel ECoG arrays recorded from nine people with epilepsy. Grid area could be cut by 75% to 94% without meaningful loss of hand-movement classification accuracy, as long as the remaining electrodes sat over informative cortex; below a critical area of about 60 mm², performance fell sharply. The study appeared in the journal Neuroinformatics on August 7, 2026.
July 2026

Preprint: MRI Grey Matter Loss May Predict Who Can Control an ECoG BCI in ALS

A preprint from the Utrecht-BCI Lab at the UMC Utrecht Brain Center in the Netherlands, the invasive-BCI group led by Nick Ramsey, asks why some people with ALS control an implanted brain-computer interface (BCI) better than others. It found that preservation of grey matter in the motor cortex is associated with higher-quality brain signals, suggesting an MRI-based measure could help identify who is a suitable candidate for implantation. The preprint was posted to medRxiv on June 23, 2026 (DOI 10.64898/2026.06.23.26355654).
June 2026

Utrecht Team Finds Well-Placed 32-Electrode ECoG Grid Matches Larger Arrays for Speech BCI

A team led by the UMC Utrecht Brain Center in the Netherlands analyzed 8 participants with high-density electrocorticography (ECoG) grids of 64 to 128 electrodes and found that a well-positioned 32-electrode grid classified 12 Dutch words with 76 ± 16% accuracy, comparable to 75 ± 17% for the larger grids. The best placement was vertical and centered on the central sulcus. Speech brain-computer interfaces aim to restore communication to people paralyzed and unable to speak, but larger grids carry higher surgical risk. The participants were not paralyzed and testing was limited to a fixed word set.
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