A Roadmap for Implanting Electrode Arrays to Evoke Tactile Sensations Through Intracortical Stimulation.

Intracortical microstimulation (ICMS) is a method for restoring sensation to people with paralysis as part of a bidirectional brain-computer interface (BCI) to restore upper limb function. Evoking tactile sensations of the hand through ICMS requires precise targeting of implanted electrodes. Here we describe the presurgical imaging procedures used to generate functional maps of the hand area of the somatosensory cortex and subsequent planning that guided the implantation of intracortical microelectrode arrays.

Evoking stable and precise tactile sensations via multi-electrode intracortical microstimulation of the somatosensory cortex.

Tactile feedback from brain-controlled bionic hands can be partially restored via intracortical microstimulation (ICMS) of the primary somatosensory cortex. In ICMS, the location of percepts depends on the electrode's location and the percept intensity depends on the stimulation frequency and amplitude. Sensors on a bionic hand can thus be linked to somatotopically appropriate electrodes, and the contact force of each sensor can be used to determine the amplitude of a stimulus.

A novel robot-assisted method for implanting intracortical sensorimotor devices for brain-computer interface studies: principles, surgical techniques, and challenges.

Precise anatomical implantation of a microelectrode array is fundamental for successful brain-computer interface (BCI) surgery, ensuring high-quality, robust signal communication between the brain and the computer interface. Robotic neurosurgery can contribute to this goal, but its application in BCI surgery has been underexplored. Here, the authors present a novel robot-assisted surgical technique to implant rigid intracortical microelectrode arrays for the BCI.

A dynamic subset of network interactions underlies tuning to natural movements in marmoset sensorimotor cortex.

Mechanisms of computation in sensorimotor cortex must be flexible and robust to support skilled motor behavior. Patterns of neuronal coactivity emerge as a result of computational processes. Pairwise spike-time statistical relationships, across the population, can be summarized as a functional network (FN) which retains single-unit properties.

How different immersive environments affect intracortical brain computer interfaces.

As brain-computer interface (BCI) research advances, many new applications are being developed. Tasks can be performed in different environments, and whether a BCI user can switch environments seamlessly will influence the ultimate utility of a clinical device. Here we investigate the importance of the immersiveness of the virtual environment used to train BCI decoders on the resulting decoder and its generalizability between environments.

A roadmap for implanting microelectrode arrays to evoke tactile sensations through intracortical microstimulation.

Intracortical microstimulation (ICMS) is a method for restoring sensation to people with paralysis as part of a bidirectional brain-computer interface to restore upper limb function. Evoking tactile sensations of the hand through ICMS requires precise targeting of implanted electrodes. Here we describe the presurgical imaging procedures used to generate functional maps of the hand area of the somatosensory cortex and subsequent planning that guided the implantation of intracortical microelectrode arrays.

A dynamic subset of network interactions underlies tuning to natural movements in marmoset sensorimotor cortex.

Mechanisms of computation in sensorimotor cortex must be flexible and robust to support skilled motor behavior. Patterns of neuronal coactivity emerge as a result of computational processes. Pairwise spike-time statistical relationships, across the population, can be summarized as a functional network (FN) which retains single-unit properties.

Microstimulation of human somatosensory cortex evokes task-dependent, spatially patterned responses in motor cortex.

The primary motor (M1) and somatosensory (S1) cortices play critical roles in motor control but the signaling between these structures is poorly understood. To fill this gap, we recorded - in three participants in an ongoing human clinical trial (NCT01894802) for people with paralyzed hands - the responses evoked in the hand and arm representations of M1 during intracortical microstimulation (ICMS) in the hand representation of S1. We found that ICMS of S1 activated some M1 neurons at short, fixed latencies consistent with monosynaptic activation.

Multiple regions of sensorimotor cortex encode bite force and gape.

The precise control of bite force and gape is vital for safe and effective breakdown and manipulation of food inside the oral cavity during feeding. Yet, the role of the orofacial sensorimotor cortex (OSMcx) in the control of bite force and gape is still largely unknown. The aim of this study was to elucidate how individual neurons and populations of neurons in multiple regions of OSMcx differentially encode bite force and static gape when subjects generated different levels of bite force at varying gapes.

Tessellation of artificial touch via microstimulation of human somatosensory cortex.

When we interact with objects, we rely on signals from the hand that convey information about the object and our interaction with it. A basic feature of these interactions, the locations of contacts between the hand and object, is often only available via the sense of touch. Information about locations of contact between a brain-controlled bionic hand and an object can be signaled via intracortical microstimulation (ICMS) of somatosensory cortex (S1), which evokes touch sensations that are localized to a specific patch of skin.

Dynamic structure of motor cortical neuron coactivity carries behaviorally relevant information.

Skillful, voluntary movements are underpinned by computations performed by networks of interconnected neurons in the primary motor cortex (M1). Computations are reflected by patterns of coactivity between neurons. Using pairwise spike time statistics, coactivity can be summarized as a ().

Biomechanical and Cortical Control of Tongue Movements During Chewing and Swallowing.

Tongue function is vital for chewing and swallowing and lingual dysfunction is often associated with dysphagia. Better treatment of dysphagia depends on a better understanding of hyolingual morphology, biomechanics, and neural control in humans and animal models. Recent research has revealed significant variation among animal models in morphology of the hyoid chain and suprahyoid muscles which may be associated with variation in swallowing mechanisms.

Robust cortical encoding of 3D tongue shape during feeding in macaques.

Dexterous tongue deformation underlies eating, drinking, and speaking. The orofacial sensorimotor cortex has been implicated in the control of coordinated tongue kinematics, but little is known about how the brain encodes-and ultimately drives-the tongue's 3D, soft-body deformation. Here we combine a biplanar x-ray video technology, multi-electrode cortical recordings, and machine-learning-based decoding to explore the cortical representation of lingual deformation.

Interplay between external inputs and recurrent dynamics during movement preparation and execution in a network model of motor cortex.

The primary motor cortex has been shown to coordinate movement preparation and execution through computations in approximately orthogonal subspaces. The underlying network mechanisms, and the roles played by external and recurrent connectivity, are central open questions that need to be answered to understand the neural substrates of motor control. We develop a recurrent neural network model that recapitulates the temporal evolution of neuronal activity recorded from the primary motor cortex of a macaque monkey during an instructed delayed-reach task.

Propagating motor cortical patterns of excitability are ubiquitous across human and non-human primate movement initiation.

A spatiotemporal pattern of excitability propagates across the primary motor cortex prior to the onset of a reaching movement in non-human primates. If this pattern is a necessary component of voluntary movement initiation, it should be present across a variety of motor tasks, end-effectors, and even species. Here, we show that propagating patterns of excitability occur during the initiation of precision grip force and tongue protrusion in non-human primates, and even isometric wrist extension in a human participant.

Propagating spatiotemporal activity patterns across macaque motor cortex carry kinematic information.

Propagating spatiotemporal neural patterns are widely evident across sensory, motor, and association cortical areas. However, it remains unclear whether any characteristics of neural propagation carry information about specific behavioral details. Here, we provide the first evidence for a link between the direction of cortical propagation and specific behavioral features of an upcoming movement on a trial-by-trial basis.

Loss of oral sensation impairs feeding performance and consistency of tongue-jaw coordination.

Background: Individuals with impaired oral sensation report difficulty chewing, but little is known about the underlying changes to tongue and jaw kinematics. Methodological challenges impede the measurement of 3D tongue movement and its relationship to the gape cycle.

Objective: The aim of this study was to quantify the impact of loss of oral somatosensation on feeding performance, 3D tongue kinematics and tongue-jaw coordination.

Longevity and reliability of chronic unit recordings using the Utah, intracortical multi-electrode arrays.

Microelectrode arrays are standard tools for conducting chronic electrophysiological experiments, allowing researchers to simultaneously record from large numbers of neurons. Specifically, Utah electrode arrays (UEAs) have been utilized by scientists in many species, including rodents, rhesus macaques, marmosets, and human participants. The field of clinical human brain-computer interfaces currently relies on the UEA as a number of research groups have clearance from the United States Federal Drug Administration (FDA) for this device through the investigational device exemption pathway.

Chronic wireless neural population recordings with common marmosets.

Marmosets are an increasingly important model system for neuroscience in part due to genetic tractability and enhanced cortical accessibility, due to a lissencephalic neocortex. However, many of the techniques generally employed to record neural activity in primates inhibit the expression of natural behaviors in marmosets precluding neurophysiological insights. To address this challenge, we have developed methods for recording neural population activity in unrestrained marmosets across multiple ethological behaviors, multiple brain states, and over multiple years.

Neural population dynamics in motor cortex are different for reach and grasp.

Low-dimensional linear dynamics are observed in neuronal population activity in primary motor cortex (M1) when monkeys make reaching movements. This population-level behavior is consistent with a role for M1 as an autonomous pattern generator that drives muscles to give rise to movement. In the present study, we examine whether similar dynamics are also observed during grasping movements, which involve fundamentally different patterns of kinematics and muscle activations.

Integrating XMALab and DeepLabCut for high-throughput XROMM.

Marker tracking is a major bottleneck in studies involving X-ray reconstruction of moving morphology (XROMM). Here, we tested whether DeepLabCut, a new deep learning package built for markerless tracking, could be applied to videoradiographic data to improve data processing throughput. Our novel workflow integrates XMALab, the existing XROMM marker tracking software, and DeepLabCut while retaining each program's utility.

Decoding hand kinematics from population responses in sensorimotor cortex during grasping.

Objective: The hand-a complex effector comprising dozens of degrees of freedom of movement-endows us with the ability to flexibly, precisely, and effortlessly interact with objects. The neural signals associated with dexterous hand movements in primary motor cortex (M1) and somatosensory cortex (SC) have received comparatively less attention than have those associated with proximal upper limb control.

Approach: To fill this gap, we trained two monkeys to grasp objects varying in size and shape while tracking their hand postures and recording single-unit activity from M1 and SC.