Using fMRI to localize target regions for implanted brain-computer interfaces in locked-in syndrome.

OBJECTIVE: Electrocorticography (ECoG)-based brain-computer interface (BCI) systems have the potential to improve quality of life of people with locked-in syndrome (LIS) by restoring their ability to communicate independently. Before implantation of such a system, it is important to localize ECoG electrode target regions. Here, we assessed the predictive value of functional magnetic resonance imaging (fMRI) for the localization of suitable target regions on the sensorimotor cortex for ECoG-based BCI in people with locked-in syndrome. METHODS: Three people with locked-in syndrome were implanted with a chronic, fully implantable ECoG-BCI system. We compared pre-surgical fMRI activity with post-implantation ECoG activity from areas known to be active and inactive during attempted hand movement (sensorimotor hand region and dorsolateral prefrontal cortex, respectively). RESULTS: Results showed a spatial match between fMRI activity and changes in ECoG low and high frequency band power (10 - 30 and 65 - 95 Hz, respectively) during attempted movement. Also, we found that fMRI can be used to select a sub-set of electrodes that show strong task-related signal changes that are therefore likely to generate adequate BCI control. CONCLUSIONS: Our findings indicate that fMRI is a useful non-invasive tool for the pre-surgical workup of BCI implant candidates. SIGNIFICANCE: If these results are confirmed in more BCI studies, fMRI might be used for more efficient surgical BCI procedures with focused cortical coverage and lower participant burden.

Dorsolateral prefrontal cortex-based control with an implanted brain-computer interface.

The objective of this study was to test the feasibility of using the dorsolateral prefrontal cortex as a signal source for brain-computer interface control in people with severe motor impairment. We implanted two individuals with locked-in syndrome with a chronic brain-computer interface designed to restore independent communication. The implanted system (Utrecht NeuroProsthesis) included electrode strips placed subdurally over the dorsolateral prefrontal cortex. In both participants, counting backwards activated the dorsolateral prefrontal cortex consistently over the course of 47 and 22 months, respectively. Moreover, both participants were able to use this signal to control a cursor in one dimension, with average accuracy scores of 78 ± 9% (standard deviation) and 71 ± 11% (chance level: 50%), respectively. Brain-computer interface control based on dorsolateral prefrontal cortex activity is feasible in people with locked-in syndrome and may become of relevance for those unable to use sensorimotor signals for control.

Stability of a chronic implanted brain-computer interface in late-stage amyotrophic lateral sclerosis.

OBJECTIVE: We investigated the long-term functional stability and home use of a fully implanted electrocorticography (ECoG)-based brain-computer interface (BCI) for communication by an individual with late-stage Amyotrophic Lateral Sclerosis (ALS). METHODS: Data recorded from the cortical surface of the motor and prefrontal cortex with an implanted brain-computer interface device was evaluated for 36 months after implantation of the system in an individual with late-stage ALS. In addition, electrode impedance and BCI control accuracy were assessed. Key measures included frequency of use of the system for communication, user and system performance, and electrical signal characteristics. RESULTS: User performance was high consistently over the three years. Power in the high frequency band, used for the control signal, declined slowly in the motor cortex, but control over the signal remained unaffected by time. Impedance increased until month 5, and then remained constant. Frequency of home use increased steadily, indicating adoption of the system by the user. CONCLUSIONS: The implanted brain-computer interface proves to be robust in an individual with late-stage ALS, given stable performance and control signal for over 36 months. SIGNIFICANCE: These findings are relevant for the future of implantable brain-computer interfaces along with other brain-sensing technologies, such as responsive neurostimulation.

Spatiotemporal characteristics of electrocortical brain activity during mental calculation.

Mental calculation is a complex mental procedure involving a frontoparietal network of brain regions. Functional MRI (fMRI) studies have revealed interesting characteristics of these regions, but the precise function of some areas remains elusive. In the present study, we used electrocorticographic (ECoG) recordings to chronometrically assess the neuronal processes during mental arithmetic. A calculation task was performed during presurgical 3T fMRI scanning and subsequent ECoG monitoring. Mental calculation induced an increase in fMRI blood oxygen level dependent signal in prefrontal, parietal and lower temporo-occipital regions. The group-fMRI result was subsequently used to cluster the implanted electrodes into anatomically defined regions of interest (ROIs). We observed remarkable differences in high frequency power profiles between ROIs, some of which were closely associated with stimulus presentation and others with the response. Upon stimulus presentation, occipital areas were the first to respond, followed by parietal and frontal areas, and finally by motor areas. Notably, we demonstrate that the fMRI activation in the middle frontal gyrus/precentral gyrus is associated with two subfunctions during mental calculation. This finding reveals the significance of the temporal dynamics of neural ensembles within regions with an apparent uniform function. In conclusion, our results shed more light on the spatiotemporal aspects of brain activation during a mental calculation task, and demonstrate that the use of fMRI data to cluster ECoG electrodes is a useful approach for ECoG group analysis.