Online speech synthesis using a chronically implanted brain-computer interface in an individual with ALS.

Recent studies have shown that speech can be reconstructed and synthesized using only brain activity recorded with intracranial electrodes, but until now this has only been done using retrospective analyses of recordings from able-bodied patients temporarily implanted with electrodes for epilepsy surgery. Here, we report online synthesis of intelligible words using a chronically implanted brain-computer interface (BCI) in a clinical trial participant (ClinicalTrials.gov, NCT03567213) with dysarthria due to amyotrophic lateral sclerosis (ALS). We demonstrate a reliable BCI that synthesizes commands freely chosen and spoken by the user from a vocabulary of 6 keywords originally designed to allow intuitive selection of items on a communication board. Our results show for the first time that a speech-impaired individual with ALS can use a chronically implanted BCI to reliably produce synthesized words that are intelligible to human listeners while preserving the participants voice profile.

Spatial-temporal functional mapping of language at the bedside with electrocorticography.

OBJECTIVE: To investigate the feasibility and clinical utility of using passive electrocorticography (ECoG) for online spatial-temporal functional mapping (STFM) of language cortex in patients being monitored for epilepsy surgery. METHODS: We developed and tested an online system that exploits ECoG's temporal resolution to display the evolution of statistically significant high gamma (70-110 Hz) responses across all recording sites activated by a discrete cognitive task. We illustrate how this spatial-temporal evolution can be used to study the function of individual recording sites engaged during different language tasks, and how this approach can be particularly useful for mapping eloquent cortex. RESULTS: Using electrocortical stimulation mapping (ESM) as the clinical gold standard for localizing language cortex, the average sensitivity and specificity of online STFM across 7 patients were 69.9% and 83.5%, respectively. Moreover, relative to regions of interest where discrete cortical lesions have most reliably caused language impairments in the literature, the sensitivity of STFM was significantly greater than that of ESM, while its specificity was also greater than that of ESM, though not significantly so. CONCLUSIONS: This study supports the feasibility and clinical utility of online STFM for mapping human language function, particularly under clinical circumstances in which time is limited and comprehensive ESM is impractical.

Electrocorticographic decoding of ipsilateral reach in the setting of contralateral arm weakness from a cortical lesion.

Brain machine interfaces have the potential for restoring motor function not only in patients with amputations or lesions of efferent pathways in the spinal cord and peripheral nerves, but also patients with acquired brain lesions such as strokes and tumors. In these patients the most efficient components of cortical motor systems are not available for BMI control. Here we had the opportunity to investigate the possibility of utilizing subdural electrocorticographic (ECoG) signals to control natural reaching movements under these circumstances. In a subject with a left arm monoparesis following resection of a recurrent glioma, we found that ECoG signals recorded in remaining cortex were sufficient for decoding kinematics of natural reach movements of the nonparetic arm, ipsilateral to the ECoG recordings. The relationship between the subject's ECoG signals and reach trajectory in three dimensions, two of which were highly correlated, was captured with a computationally simple linear model (mean Pearson's r in depth dimension= 0.68, in height= 0.73, in lateral= 0.24). These results were attained with only a small subset of 7 temporal/spectral neural signal features. The small subset of neural features necessary to attain high decoding results show promise for a restorative BMI controlled solely by ipsilateral ECoG signals.

Electrocorticographic amplitude predicts finger positions during slow grasping motions of the hand.

Four human subjects undergoing subdural electrocorticography for epilepsy surgery engaged in a range of finger and hand movements. We observed that the amplitudes of the low-pass filtered electrocorticogram (ECoG), also known as the local motor potential (LMP), over specific peri-Rolandic electrodes were correlated (p < 0.001) with the position of individual fingers as the subjects engaged in slow and deliberate grasping motions. A generalized linear model (GLM) of the LMP amplitudes from those electrodes yielded predictions for positions of the fingers that had a strong congruence with the actual finger positions (correlation coefficient, r; median = 0.51, maximum = 0.91), during displacements of up to 10 cm at the fingertips. For all the subjects, decoding filters trained on data from any given session were remarkably robust in their prediction performance across multiple sessions and days, and were invariant with respect to changes in wrist angle, elbow flexion and hand placement across these sessions (median r = 0.52, maximum r = 0.86). Furthermore, a reasonable prediction accuracy for grasp aperture was achievable with as few as three electrodes in all subjects (median r = 0.49; maximum r = 0.90). These results provide further evidence for the feasibility of robust and practical ECoG-based control of finger movements in upper extremity prosthetics.