*Result*: Initial experience with the precision neuroscience Layer 7 micro-electrocorticography interface for real-time intraoperative neural decoding.

Title:
Initial experience with the precision neuroscience Layer 7 micro-electrocorticography interface for real-time intraoperative neural decoding.
Authors:
Lehner KR; 1Department of Neurosurgery, Johns Hopkins Hospital, Baltimore., Luo S; 3Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland., Greene B; 3Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland., Angrick M; 2Department of Neurology, Johns Hopkins Hospital, Baltimore., Candrea D; 3Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland., Husari KS; 1Department of Neurosurgery, Johns Hopkins Hospital, Baltimore., Barth K; 4Precision Neuroscience, New York; and., Dister J; 4Precision Neuroscience, New York; and., Anushiravani R; 4Precision Neuroscience, New York; and., Miller JS; 4Precision Neuroscience, New York; and., Ho E; 4Precision Neuroscience, New York; and., Rincon-Torroella J; 1Department of Neurosurgery, Johns Hopkins Hospital, Baltimore., Rapoport B; 4Precision Neuroscience, New York; and.; 5Department of Neurosurgery, Mt. Sinai Hospital, New York, New York., Comair Y; 1Department of Neurosurgery, Johns Hopkins Hospital, Baltimore., Crone NE; 2Department of Neurology, Johns Hopkins Hospital, Baltimore.; 3Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.
Source:
Neurosurgical focus [Neurosurg Focus] 2026 Feb 01; Vol. 60 (2), pp. E3.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: American Association of Neurological Surgeons Country of Publication: United States NLM ID: 100896471 Publication Model: Print Cited Medium: Internet ISSN: 1092-0684 (Electronic) Linking ISSN: 10920684 NLM ISO Abbreviation: Neurosurg Focus Subsets: MEDLINE
Imprint Name(s):
Original Publication: Charlottesville, VA : American Association of Neurological Surgeons, c1996-
Contributed Indexing:
Keywords: brain-computer interface; brain-machine interface; cursor control; electrocorticography; intraoperative recordings; micro-electrocorticography; neural decoding; speech synthesis
Entry Date(s):
Date Created: 20260201 Date Completed: 20260201 Latest Revision: 20260201
Update Code:
20260202
DOI:
10.3171/2025.11.FOCUS25908
PMID:
41621103
Database:
MEDLINE

*Further Information*

*Objective: The aim of this study was to evaluate the feasibility of using the Layer 7 Cortical Interface, a high-density micro-electrocorticography (μECoG) array, for intraoperative neural recordings and real-time brain-computer interface (BCI) applications, including speech decoding and cursor control.
Methods: Four patients (age range 23-43 years) who underwent awake craniotomy for tumor resection near the eloquent cortex were enrolled. The Layer 7 µECoG device (1024 channels, approximately 1.5-cm2 coverage) was placed on the motor cortex following standard cortical mapping. Intraoperative tasks included a joystick-controlled center-out movement paradigm (n = 3) and an auditory-cued speech repetition task (n = 1). Neural data were recorded at 20 kHz, preprocessed, and used to train decoders intraoperatively. A transformer-based model was applied for real-time speech synthesis and a convolutional neural network was trained for speech classification, while a convolutional recurrent neural network was trained to classify 2D cursor direction.
Results: All 4 patients tolerated the procedure without device-related adverse events. The mean electrode impedances across 6 arrays (6144 channels) ranged from 1.21 to 1.99 MΩ, with 954-990 channels per array retained for analysis. In the speech task, a 4-word classification model achieved 77.5% accuracy, and a real-time synthesis model was able to distinguish speech and silence during approximately 20 minutes of data recording in the operating room. In the motor task, a 4-direction classification model achieved 78%-84% accuracy. Recordings remained stable during tumor resection.
Conclusions: The Layer 7 Cortical Interface device enabled high-resolution nonpenetrating cortical recordings that supported real-time speech classification and cursor control within the limited timeframe of an intraoperative session. These findings highlight the potential clinical applications of high-density µECoG for functional mapping, diagnostic assessment, and future chronic BCI systems for patients with motor and communication impairments.*