Measuring motor intent for BCI control-A comparative analysis of signal quality of simultaneously recorded vECoG and scalp EEG.

Both recording methods detected attempted movement in one participant. The implanted vascular signal was stronger in some conditions, but this does not establish broader clinical performance.

Chetty N, Bennett J, Schone HR, Fry A, Yoo PE, Lacomis D, Oxley TJ, Collinger JL, Putrino DF, Weber DJ.
Journal of neural engineering · Publication date: 2026-09-17
Added to site: 2026-09-17
DOI: 10.1088/1741-2552/ae9eef

First online publication date verified through PubMed and Crossref; print issue is dated October 2026.

Modalities

EEG, BCI

Clinical focus

Motor intent, Paralysis, Signal quality

Population

One person with severe upper-limb paralysis due to amyotrophic lateral sclerosis

Sample

One participant studied across two experimental sessions

Intervention / method

Simultaneous vascular electrocorticography and scalp EEG during visually cued attempted movement and motor imagery

Comparator

Within-participant comparison of vECoG and scalp EEG signal modulation and artifacts

Clinician summary

vECoG showed stronger per-channel motor modulation in some frequency bands and fewer ocular and cranial-muscle artifacts, while cardiac contamination was more prominent. Neither modality significantly localized left-versus-right ankle movement.

How to interpret the findings

Single-participant, two-session evidence cannot establish generalizability, long-term BCI accuracy, safety or comparative functional benefit.

Equipment and disclosures

Endovascular stent-electrode array and gel-cap scalp EEG recorded simultaneously; detailed commercial model information was not verified from the abstract.

Several authors list affiliations with Synchron Inc. Crossref lists NINDS, NSF graduate-fellowship and NIMH support; additional conflicts were not verified.

Related evidence

Compare findings from the same clinical area, including mixed results.

• Diff-ADN: A diffusion-guided artifact denoising network with deterministic residual refinement for EEG. · Positive with limitations