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2026-08-07 00:00 Belgium Papers Movement & Control Translated from EN

Medial wall ECoG signals aid finger motor decoding

Summary Published in Journal of Neural Engineering on August 7, 2026, the study analyzed human electrocorticography data from four subjects to investigate medial wall contributions to finger movement decoding. Significantly above-chance finger movement detection was observed across multiple medial wall subregions, with local motor potentials and oscillatory power in the 8-12 Hz and 12-34 Hz bands contributing most strongly. Feature dynamics shared key properties with primary motor cortex, including pre-movement desynchronization, while also exhibiting region-specific positive or negative LMP modulations. Medial wall channels in two subjects enabled significant differentiation between individual fingers, and one subject showed decoding of both contralateral and ipsilateral finger movements, though this is a single case and preliminary.
Why it matters Explores the medial wall as a viable signal source for finger movement decoding, expanding candidate brain regions for invasive motor BCIs beyond lateral sensorimotor cortex.

BCIwiki (bciwiki.com) — The study was published in Journal of Neural Engineering on August 7, 2026. The authors analyzed human electrocorticography (ECoG) data from four subjects performing finger movements to investigate the contribution of medial wall regions to finger movement decoding. The researchers are from KU Leuven and Ghent University Hospital in Belgium.

Significantly above-chance finger movement detection was observed across multiple medial wall subregions, with local motor potentials (LMP) and oscillatory power in the 8-12 Hz and 12-34 Hz bands contributing most strongly to decoding performance. Feature dynamics shared key properties with primary motor cortex, including pre-movement desynchronization, while also exhibiting region-specific patterns such as anatomically dependent positive or negative LMP modulations.

Although movement detection was the dominant outcome, medial wall channels in two subjects enabled significant differentiation between individual fingers. In one subject, both contralateral and ipsilateral finger movements could be decoded with some generalization across hands, though this observation is based on a single case and should be interpreted as preliminary. The findings identify the medial wall as a viable source of motor-related signals for finger movement decoding, with potential for future invasive motor BCI applications.

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