Academic Journal
Optimal positioning and size of high-density electrocorticography grids for speech brain-computer interfaces.
| Τίτλος: | Optimal positioning and size of high-density electrocorticography grids for speech brain-computer interfaces. |
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| Συγγραφείς: | Offenberg EC; Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands., Berezutskaya J; Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands., Müller L; Institute for Neurophysiology, Uniklinik RWTH Aachen, Aachen, Germany., Freudenburg ZV; Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands., Ramsey NF; Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands. Electronic address: n.f.ramsey@umcutrecht.nl., Vansteensel MJ; Department of Neurology and Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands. |
| Πηγή: | Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology [Clin Neurophysiol] 2026 Oct; Vol. 190, pp. 2111940. Date of Electronic Publication: 2026 Jun 01. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 100883319 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-8952 (Electronic) Linking ISSN: 13882457 NLM ISO Abbreviation: Clin Neurophysiol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Amsterdam : Elsevier, c1999- |
| Ιατρικοί όροι (MeSH): | Electrocorticography*/methods , Electrocorticography*/instrumentation , Speech*/physiology , Sensorimotor Cortex*/physiology , Brain-Computer Interfaces* , Electrodes, Implanted*, Humans ; Female ; Male ; Adult |
| Περίληψη: | Objective: Speech-based brain-computer interfaces (BCIs) can offer an intuitive communication method for those who have lost the ability to speak due to paralysis. Significant progress has been made in classifying individual words from high numbers of electrocorticographic (ECoG) electrodes on the sensorimotor cortex (SMC). As implantations of larger grids with more ECoG electrodes are associated with higher surgical risk, we investigated whether confined electrode configurations can match the classification accuracy of larger grids. Methods: We analyzed data from eight able-bodied participants with high-density ECoG grids (64 to 128 electrodes) performing a 12-word repetition task in Dutch. Results: Word pronunciation elicited high frequency band activity in two SMC foci: one ventral, one dorsal. Smaller, rectangular configurations with surface areas of 325 mm2 to 561 mm2 (32 electrodes) could achieve similar word classification accuracies as larger grids: 76 ± 16% versus 75 ± 17% across participants, respectively (practical chance level 16.7%). The best configurations were oriented vertically and centered on the central sulcus. Conclusion: These findings indicate that a 32-electrode ECoG grid placed optimally can be sufficient for achieving high word classification accuracy on a closed set of words. Significance: These findings support the targeted placement of small ECoG grids, reducing surgical demands on end users and justifying energy- and complexity-efficient designs of fully implantable BCI devices for individuals with severe paralysis. (Copyright © 2026 The Author(s). Published by Elsevier B.V. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: MJV is a consultant for GA Capital. There are no further conflicts of interest for any of the authors. |
| Contributed Indexing: | Keywords: Brain-computer interfaces; Electrocorticography; Feature selection; Machine learning; Neural decoding; Speech decoding |
| Entry Date(s): | Date Created: 20260609 Date Completed: 20260812 Latest Revision: 20260812 |
| Update Code: | 20260813 |
| DOI: | 10.1016/j.clinph.2026.2111940 |
| PMID: | 42263493 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1872-8952 |
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| DOI: | 10.1016/j.clinph.2026.2111940 |