For many years brain-computer interfaces (BCI's) have been explored as a means of restoring communication to patients with Locked-In Syndrome (LIS), a devastating and often irreversible neurological condition in which cognition is intact but nearly all motor output from the brain is interrupted, effectively cutting off communication with the outside world. To date non-invasive BCI's (e.g. EEG) have had inadequate signal fidelity and spatial resolution, while invasive BCI's using microelectrode arrays in hand motor cortex have delivered cursor and multi-joint robotic control in controlled settings, but have been difficult to learn and have required frequent retraining of decoding models, due to instabilities in the microelectrode-tissue interface. High-density electrocorticographic (ECoG) recordings have been recently used by our team (JHU and University of Utrecht) and by others for real-time detection and classification of a variety of different upper limb movements and speech components. ECoG has sufficient spatial-temporal resolution and signal quality to decode the broadband high-gamma (~60-200 Hz) responses of native cortical representations for upper limb movements and speech. Speech representations are spatially distributed over several square centimeters, ideally suited for electrocorticography (ECoG), but impractical for MEA's. In a recent landmark paper in NEJM (Vansteensel et al. 2016) Dr. Ramsey's team in Utrecht demonstrated home use of a fully implantable wireless ECoG BCI by a patient with LIS, without supervision by researchers. To expand on the capabilities of this 4-channel system, our team proposes a first-in-human clinical trial to establish the safety and efficacy of an ECoG BCI with far more channels, implanted for 6 months. Based on the long-term safety and signal quality of ECoG demonstrated in neuromodulation for epilepsy (Neuropace RNS), we have an IDE for the proposed ?CortiCom System?, which uniquely combines a 128-channel HD- ECoG array (PMT Corp) with a transcutaneous pedestal connector and neural signal processor (Blackrock Microsystems). In this early feasibility trial, our team will pursue the following Aims/Milestones: 1. Demonstrate efficient and stable control of essential BCI functions (initiate BCI, call caregiver, and BCI menu navigation). CortiCom will use real-time decoding of attempted movements of different fingers, arm joints, and mouth and face muscles to control the critical BCI functions, e.g. caregiver calling (by 3 months), and menu navigation--Up/Down/Left/Right, Enter, and Back/Escape (6 commands). 2. Demonstrate efficient and stable operation of a keyword-based speech BCI. CortiCom will use low- latency detection and classification of attempted speech (keywords) to expand communication. Keyword decoding will use a hierarchical hybrid model to detect and classify keywords based on their unique spatial- temporal signatures of population activity. Keyword command vocabulary, based on communication value and ease of classification, will expand from 6 (by 3 months) to 20 or more keywords during the trial.

Public Health Relevance

This first-in-human early feasibility clinical trial (NCT03567213, ClinicalTrials.gov) will enroll up to 5 subjects to test the safety and efficacy of the CortiCom System, an implantable brain-computer interface (BCI) that is designed to restore communication to patients with Locked-In Syndrome (LIS). LIS is a devastating, often irreversible, neurological condition in which cognition is intact but nearly all motor output from the brain is interrupted, effectively cutting off communication with the outside world. This study will explore the potential capabilities of large, high density arrays of non-penetrating electrodes, implanted on the brain surface, to restore motor output and communication to patients with LIS and other severe motor impairments.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Exploratory/Developmental Cooperative Agreement Phase II (UH3)
Project #
1UH3NS114439-01
Application #
9879474
Study Section
Special Emphasis Panel (ZNS1)
Program Officer
Hudak, Eric Michael
Project Start
2020-09-15
Project End
2025-08-31
Budget Start
2020-09-15
Budget End
2021-08-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Neurology
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205