Chronic Implantation of Planar Microelectrode Arrays as a Brain-Computer Interface: A Technical Note and Operational Workflow
Year: 2026
Type: article
Study design: Case Report
Abstract: BACKGROUND AND OBJECTIVES: Chronic implantation of brain-computer interface facilitates stable, high-fidelity neuronal recordings over extended periods of time. Planar microelectrode arrays [Utah arrays (UAs)] are commonly used for intracortical signal acquisition. Here, we describe the surgical workflow for chronic implantation of multiple UAs in 2 patients and report safety and signal-quality outcomes. METHODS: Two patients (MB, MM) underwent chronic UA implantation within a translational research program. Preoperative planning included magnetic resonance imaging and navigated transcranial magnetic stimulation mapping for localization of functional targets. MB presented with aphasia after a left hemisphere media territory stroke 6 years before implantation and received 4 UAs in speech-related areas. MM presented with tetraparesis after a high level spinal cord injury and received 4 UAs in areas related to grasping functionality, totaling 256 intracortical electrodes for each patient. RESULTS: The duration of the chronic implantation has currently amounted to 41 months for MB and 4 months for MM. Optimal signal quality has been recorded in MB in 3 of 4 UAs and in MM in all UAs. After 15 months, MB suffered from wound breakdown, necessitating surgical debridement and intravenous antibiotic treatment. Unimpaired signal acquisition resumed after the wound had healed, and no further complications from UA implantation were recorded otherwise. CONCLUSION: Chronic implantation of UAs across distinct cortical areas is safe. A standardized workflow-combining imaging-based functional navigated transcranial magnetic stimulation mapping, intraoperative neuronavigation, and structured postoperative surveillance-supports reliable, long-term intracortical signal acquisition.
Source: Operative Neurosurgery
Institutions: TUM Klinikum, Technical University of Munich
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W7161973902