2026-07-02 00:00 United States Netherlands Papers Foundations & Methods Translated from EN

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

Summary 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).

Why it matters ALS implant programs have no accepted way to predict who will actually be able to drive the device, so a structural MRI marker — if it survives peer review and a larger cohort — would change enrollment criteria before it changes surgery.

运动皮层灰质保留程度与ALS患者脑机接口控制能力相关 — Image: Nick Ramsey's Lab

BCIwiki (bciwiki.com) — Preservation of grey matter in the motor cortex is associated with the ability of people with amyotrophic lateral sclerosis (ALS) to control an implanted brain-computer interface (BCI), researchers at the Utrecht-BCI Lab, part of the UMC Utrecht Brain Center, reported in a preprint posted to medRxiv on June 23, 2026, with DOI 10.64898/2026.06.23.26355654.

The study, conducted by the Utrecht-BCI Lab, part of the Department of Neurology and Neurosurgery at UMC Utrecht, explored why some ALS patients are better able to control an ECoG-based implanted BCI than others. Led by Nick Ramsey, the team found that preservation of grey matter in the motor cortex is associated with higher-quality brain signals, suggesting that MRI-based measures could help identify suitable candidates for BCI implantation in the future.

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utrecht-bci.nl 2026-07-02

Johns Hopkins University Radboud University Nijmegen University Medical Center Utrecht Utrecht University Invasive BCI ALS ECoG United States Netherlands

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2026-08 University Medical Center Utrecht Utrecht Team Finds ECoG Grids Can Shrink up to 94% without Losing Decoding Accuracy 2026-04 Johns Hopkins University Johns Hopkins launches INTENT trial of implant that reads and stimulates brain to help paralyzed control devices 2026-01 Radboud University Nijmegen Researchers Say BCIs Should Decode User Goals, Not Motor Cortex Signals 2017-05 Johns Hopkins University Johns Hopkins begins early feasibility trial of bidirectional cortical neuroprosthesis

Johns Hopkins University → Radboud University Nijmegen → University Medical Center Utrecht → Utrecht University →

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