Jennifer L. Collinger

Objective. High performance intracortical brain-computer interface (iBCI) control has been demonstrated in research settings, but performance can still vary within and between sessions. One potential source of this variability is the change in attentional load that comes from processing naturally occurring distractors such as thoughts, sounds, fatigue, or pain. To improve the consistency of iBCI performance in real-world environments where this sort of multi-tasking is inevitable, we must understand how shifts in attention can impact performance. Approach. Here we examined the effect of attentional load on iBCI performance and movement-related neural activity using a 2D cursor translation + click iBCI task paired with an N -Back working memory task to increase attentional load during dual-task performance. Two participants (P2 and P4) with tetraplegia completed the study while enrolled in a long-term clinical trial of an iBCI device. Common neural correlates of attention (theta and alpha band power) were measured with simultaneously recorded scalp electroencephalography (EEG). Main Results. While the EEG metrics and difficulty ratings suggested increased attentional load during dual-tasking, iBCI performance was quite robust across the various dual-tasking conditions. One participant, P2, experienced a small but significant increase in trial completion time and normalized path length during the mild attentional load condition compared to the moderate load condition. Signal quality differences between the two participants may have impacted the results, as P2 had lower signal quality and was therefore likely more vulnerable to attentional load. P4’s higher signal quality likely allowed him to accommodate increased attentional load without a drop in performance. Significance. Overall, iBCI performance appears to be robust to attentional load, but the complex trends observed here reflect a need for continued investigation of BCI use under different cognitive states to elucidate potential challenges and compensatory mechanisms across participants.

Background: Transcranial magnetic stimulation (TMS) has been proposed to support post-stroke motor recovery, but the response may depend on the task and motor-network status. We aimed to compare how premotor and parietal stimulation affects performance across reach directions with different movement demands, in preparation for therapeutic application of TMS. Methods: 16 participants with chronic subcortical stroke performed planar reaches with the KINARM exoskeleton toward distal and proximal targets. Before movement, a 10-Hz triple-pulse TMS train was delivered over bilateral dorsal or ventral premotor cortex (PMd, PMv) or dorsomedial posterior parietal cortex (PPC) at subthreshold and suprathreshold intensities. The parietal midline was used as the control target. Participant-level bootstrap confidence intervals assessed changes in trajectory straightness and smoothness relative to the control target and differences between reach directions. We compared motor-network activity and connectivity using task-based and resting-state functional magnetic resonance imaging (fMRI) data from participants with stroke and neurologically intact controls. To explore response variability, we tested associations between TMS response and motor impairment, resting-state connectivity, and the change in task-evoked activity at the stimulated region from planning to movement. Results: Suprathreshold PMd and PPC stimulation in both hemispheres improved trajectory straightness or smoothness during distal reaches relative to the control target. Suprathreshold contralesional PMd stimulation increased trajectory deviation and reduced smoothness during proximal reaches. Baseline performance during distal reaches was more closely related to motor impairment, and contralesional PMd effects were more favorable during distal than proximal reaches across all kinematic measures. Participants with stroke showed lower bilateral PMv activation during movement and stronger interhemispheric PPC connectivity. Only the change in task-evoked activity at the stimulated region from planning to movement was related to TMS response. Smaller changes relative to controls were associated with more favorable kinematic effects during distal reaches. Conclusions: Movements more affected after stroke were the most responsive to this type of stimulation. The response to TMS was also associated with task-evoked activity differences at the stimulated region between movement planning and execution. Neuromodulation may therefore be most effective when designed around both the pathophysiology of the cortical target and the type of movement. Trial registration: ClinicalTrials.gov, NCT04286516 . Registered 21 January 2020.

Objective. Stent-electrode arrays enable endovascular brain–computer interfaces (BCI) by recording cortical neural activity from within the superior sagittal sinus and have recently been evaluated in an early feasibility clinical trial in the United States (ClinicalTrials.gov: NCT05035823). For a BCI to be viable, the signals need to be high quality to enable accurate decoding of user intent. Compared to electrodes placed on the scalp for electroencephalography (EEG), stent-electrode arrays lie closer to the cortical surface and would presumably offer higher signal quality yet a direct comparison of intravascular and scalp-based neural recordings in humans has not yet been investigated. Approach. We directly compared the signal quality of vascular electrocorticography (vECoG) versus scalp EEG signals in one participant with severe upper limb paralysis due to ALS. During two experimental sessions, the participant underwent simultaneous recording with the stent-electrode array and a scalp EEG using a gel cap. The participant was visually cued to attempt motor tasks, such as repeated flexion and extension of the ankles. Signal quality was assessed by quantifying motor modulation strength, differentiation of movement effort, and spatial lateralization. Noise metrics evaluated the relative impact of artifacts including 60 Hz line noise, electrocardiogram contamination, eye blinks, jaw clenching, and vocalization. Main results. Both recording modalities exhibited significant modulation during attempted movement relative to rest, with vECoG generally demonstrating significantly stronger modulation per channel in some frequency bands and conditions. Motor modulation was significantly reduced during motor imagery compared to overt movement in both modalities. Spatial source localization between left and right ankle movement did not reach significance for either modality. Each modality was vulnerable to some artifacts while generally unaffected by others. Scalp EEG showed large susceptibility to ocular artifacts and cranial muscle activity due to its proximity to superficial physiological sources, whereas vECoG exhibited prominent cardiac activity. Significance. Within this participant, the large modulation during attempted movement recorded with vECoG, unaffected by the attenuating effects of the skull, coupled with fewer artifacts in the frequency bands of interest, provides preliminary evidence that the stent-electrode arrays can acquire high quality neural signals that could support BCI control.

Humans perform a variety of complex hand movements to manipulate objects, requiring precise control of changing forces. Understanding the role of sensorimotor cortex and the cortical dynamics underlying these actions is crucial for developing interventions that restore dexterous hand function after injury or disease. In this study, two male individuals with tetraplegia resulting from cervical spinal cord injury attempted a series of isometric grasps. Neural activity was recorded from the motor and somatosensory cortices using intracortical microelectrode arrays while participants attempted to exert a static or ramping force up and down. Despite their inability to execute movement and limited afferent input, the spiking activity in motor and somatosensory cortex was modulated with the task. Within the neural response, we identified independent neural modes—distinct patterns of population-level neural activity that were informative about both the timing and magnitude of the attempted force. Moreover, distinct neural modes were observed during static and dynamic grasping conditions, suggesting independent control schemes for maintaining and changing forces. These modes were related to phases of the task, including the onset, offset, holding periods, as well as increasing and decreasing attempted forces. These results will inform the design of intracortical brain–computer interface (iBCI) systems that can leverage the patterns of grasp and force control evident in sensorimotor cortex during attempted movement to restore dexterous hand function.

Intracortical microstimulation (ICMS) of somatosensory cortex can restore a sense of touch to people with spinal cord injury. In this early feasibility clinical trial (NCT01894802), we evaluated the safety, efficacy, and longevity of ICMS because there is a paucity of such long-term studies in humans. This information is crucial to the development of clinical neuromodulation devices, particularly for restoring touch, hearing, and vision. ICMS was delivered to five participants with spinal cord injury who were each implanted with two Blackrock NeuroPort microelectrode arrays in the hand representation of Brodmann's area 1. Across implant durations spanning 2 to 10 years, we measured single-electrode detection thresholds, projected fields, quality reports, and electrode health characteristics. ICMS-related adverse events were documented throughout. More than 168 million ICMS pulses were delivered across a combined implant duration of 27 years without any serious adverse events or direct negative effects on electrode health. ICMS consistently evoked sensations localized to the hand. Rarely, sensations persisted for brief periods after stimulation offset (3 to 25 events across participants). ICMS detection thresholds increased slowly over time (about 3.5 microamperes per year), but 64 ± 13% of the electrodes still reliably evoked tactile sensations (about 21% decrease in functional electrodes), including 60% of the electrodes after 10 years in one participant. The quality and projected field coverage of ICMS-evoked sensations were both consistent. Delivering ICMS to the somatosensory cortex was safe and effective, consistently evoking informative somatosensory percepts as long as 10 years, demonstrating the clinical promise of ICMS for sensory restoration.

High performance intracortical brain-computer interface (iBCI) control has been demonstrated in research settings, but performance can still vary within and between sessions. One potential source of this variability is the change in attentional load that comes from processing naturally occurring distractors such as thoughts, sounds, fatigue, or pain. To improve the consistency of iBCI performance in real-world environments where this sort of multi-tasking is inevitable, we must understand how shifts in attention can impact performance. Here we examined the effect of attentional load on iBCI performance and movement-related neural activity using a 2D cursor translation + click iBCI task paired with an N-Back working memory task to increase attentional load during dual-task performance. Two participants (P2 and P4) with tetraplegia completed the study while enrolled in a long-term clinical trial of an iBCI device (NCT1894802). Common neural correlates of attention (theta and alpha band power) were measured with simultaneously recorded scalp electroencephalography (EEG). While the EEG recordings and difficulty ratings suggested increased attentional load during dual tasking, iBCI performance was quite robust across the various dual tasking conditions. One participant, P2, experienced a small but significant increase in trial completion time and normalized path length during the mild attentional load condition. Signal quality differences between the two participants may have impacted the results, as P2 had lower signal quality and was therefore likely more vulnerable to attentional load. P4’s higher signal quality likely allowed him to accommodate increased attentional load without a drop in performance. Overall, iBCI performance appears to be robust to attentional load, but the complex trends observed here reflect a need for continued investigation of BCI use under different cognitive states to elucidate potential challenges and compensatory mechanisms across participants.

Dexterous hand function underlies many essential human activities, from tool use to expression through gestures. Coordinated digit movements are enabled by the intricate musculature of the hand and forearm, which also imposes mechanical coupling between the digits and wrist, constraining their independent control. It remains unclear whether motor cortex inherits these constraints in its activity or encodes digit and wrist independently. To address this problem, we asked individuals with intracortical microelectrode arrays implanted in motor cortex to attempt flexion and extension of individual digits, either in isolation or in combination with attempted wrist movements. We could accurately decode which digit was moving based on cortical recordings, and channels selective for digit identity were arranged somatotopically across the recording arrays. Nevertheless, the activity during flexion or extension overlapped between digits, and movement direction of a given digit could be reliably inferred by a decoder trained on movements of other digits. This directional signal was largely invariant to the digit’s initial posture. The population axis describing digit movement direction was aligned with the axes associated with wrist flexion-extension or pronation-supination. This alignment persisted during simultaneous wrist and digit movements, which complicated efforts to control them individually. However, by decoding wrist and digit motion from activity orthogonal to the shared direction axis, a participant was able to achieve continuous control of virtual hand movements with improved speed and reduced unintended movements. Together, the results identify both a code for digit identity and a low-dimensional flexion-extension signal which is shared across the digits and wrist. This arrangement is consistent with muscle-like biomechanical constraints on motor cortical activity, which must be accounted for to improve coordinated BCI control.

Intracortical brain-computer interfaces (BCIs) are used to decode motor intent from neural population activity; their main clinical application is to restore function for individuals with motor or communication deficits. However, when trying to reconstruct movement trajectories, such as in computer cursor control, even state-of-the-art decoders fall short of able-bodied performance during online BCI control. This calls for alternative approaches to improve the usability of motor BCIs. Here, we leveraged an error signal, i.e. a neural correlate of faulty motor control that can be detected from neural activity. By detecting this error signal in parallel to performing movement decoding, it is possible to perform error modulation, i.e. real-time error detection and correction during a closed-loop motor BCI task. We analyzed data from four individuals with upper limb impairment due to cervical spinal cord injury who each used an intracortical BCI to perform a continuous cursor control task with visual feedback. A classifier was trained to detect the error signal and was used to perform online error detection during BCI control to limit ongoing errors (defined as movement of the controller away from its target) without requiring any specific action from the participants. Our contribution is three-fold. First, we show that the error signal has a pre-error component. Cortical activity was already significantly modulated before the onset of the kinematically-defined error, theoretically allowing for earlier detection. Second, we show that error modulation significantly improves performance during online BCI control of cursor kinematics. Finally, we show that the error signal can be robustly leveraged across contexts, as error modulation improves performance in more complex motor tasks (involving for instance grasp and drag actions) or other environments without task-specific calibration. Overall, our results suggest that the error signal can be robustly disentangled from motor intent in cortical activity, and that even a simple linear classifier can enable error modulation in parallel to a continuous kinematic decoder, yielding more reliable and accurate BCI control.

Humans perform a variety of complex hand movements to manipulate objects, requiring precise control of changing forces. Understanding the role of sensorimotor cortex and the cortical dynamics underlying these actions is crucial for developing interventions that restore dexterous hand function after injury or disease. In this study, two individuals with tetraplegia resulting from cervical spinal cord injury attempted a series of isometric grasps. Neural activity was recorded from the motor and somatosensory cortices using intracortical microelectrode arrays while participants attempted to exert a static force or to ramp force up and down. Despite their inability to execute movement, and with limited afferent input, the spiking activity in motor and somatosensory cortex was modulated with the task. Within the neural response we identified independent neural modes - distinct patterns of population-level neural activity - that were informative about both the timing and magnitude of the force. Moreover, distinct neural modes were observed during static and dynamic grasping conditions, suggesting independent control schemes for maintaining and changing forces. These modes were related to phases of the task, including the onset, offset, holding periods, as well as phases of increasing and decreasing force. These results will inform the design of intracortical brain-computer interface (iBCI) systems that can leverage these naturally occurring patterns of grasp and force control to restore dexterous hand function. Significance Statement: Restoring dexterous hand function after injury remains a major challenge, partly due to an incomplete understanding of the cortical dynamics underlying grasping and force control. In this study, we investigated neural activity within the motor and somatosensory cortices of individuals with tetraplegia attempting to perform grasps to different target forces with varying temporal profiles. We identified distinct neural modes modulated during specific phases of grasp that encode force information throughout the task. These findings suggest that brain-computer interfaces could leverage these native neural modes to restore grasping and force modulation.

Most individuals with tetraplegia retain some myoelectric function in their forearms, which offers the possibility of using surface electromyographic (sEMG) control for human-computer interaction (HCI). We demonstrate the potential of this approach by showing that people with motor-complete (n=5) and motor-incomplete (n=2) tetraplegia can accurately control myoelectric activity in their forearm to perform discrete button-click and continuous positioning tasks. These control inputs were mapped to the firing rate of motor units detected by a wireless wristband sensor designed for everyday use. Participants completed four testing sessions to assess their speed and accuracy. Motor units that displayed a wide dynamic range in their firing rate performed best during tasks requiring continuous, single-axis control. Interestingly, the level of impairment did not affect performance on the clicking and 1D cursor control tasks. However, those with motor-incomplete injuries showed greater independent control over two motor units than participants with motor-complete injuries, who exhibited stronger coupling between units. Participants also confirmed the practical utility of the device, successfully placing and removing the sEMG wristband on their own and consistently rating it as comfortable and easy to manage. These findings are significant because they offer the first demonstration of motor unit-based control in individuals with cervical spinal cord injury (SCI) using a fully wearable wristband interface, highlighting the feasibility of moving these systems out of the lab and into daily life.