Biology subjects

Gaunt, R. A.

Publications and source records attributed to Gaunt, R. A..

8 recordsLinked to original sources

bioRxiv2026

Spatiotemporal encoding of touch signals in the human somatosensory and motor cortices

The sense of touch is fundamental for dexterous manipulation, object interaction, and body awareness. It is primarily processed in the somatosensory cortex (SC), yet our understanding of how tactile information is encoded at the level of neural populations and single neurons in humans remains limited. It is unclear how natural tactile signals are represented in SC and how they may be influenced by visual inputs, as well as how closely sensory and motor cortices interact during passive touch. Here, we investigated the neural basis of touch in the human SC using chronically implanted microelectrode arrays in three participants. By delivering controlled mechanical stimuli, we characterized neural responses to natural touch and mapped detailed somatotopic receptive fields (the patch of skin that elicits neural responses when stimulated) in humans, including multi-digit representations. Surprisingly, we also found strong, clearly somatotopic activation in the motor cortex (MC) during passive touch, even in the absence of movement, highlighting a tight and functionally relevant sensorimotor coupling. We further examined how vision shapes tactile processing by comparing neural activity during actual touch with and without vision, and during observation of touch on another persons hand. While touch to the participants hands elicited robust, event-locked, and somatotopically organized responses in the SC, observation of tactile actions alone did not produce significant activation, suggesting limited vicarious encoding at this level. These findings provide a detailed characterization of human touch processing at the level of neuronal populations and give insights for the design of microstimulation strategies of the SC for the restoration of touch.

neuroscience↗

bioRxiv2026

Distinct neural modes carry information about grasp force and phase in the sensorimotor cortex

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 StatementRestoring 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.

neuroscience↗

bioRxiv2025

SpIC3D imaging: Spinal In-situ Contrast 3D imaging

High-definition visualization techniques are critical for understanding the neuroanatomy of the spinal cord, an essential structure for sensorimotor and autonomic functions, in both healthy and pathological conditions. Magnetic resonance imaging (MRI) is a common method for visualizing neural structures in 3D. However, techniques for spinal cord MRI have historically achieved limited visualization of rootlets and nerves, especially at lower spinal levels, due to their highly complex and compact organization. Here we developed a spinal in-situ contrast 3D imaging (SpIC3D) method that allows visualization of spinal compartments in fixed animal and human specimens with ultra-high resolution at various spinal levels. Using SpIC3D, we achieved quantification of neuronal cell density in dorsal root ganglia, multi-segment identification of individual rootlets and roots, and volumetric reconstruction of multiple spinal structures for computational modeling. SpIC3D provides a basis for accelerated spinal pathology characterization and personalized spinal cord stimulation treatments.

neuroscience↗

bioRxiv2024

Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark

Intracortical brain-computer interfaces (iBCIs) can restore movement and communication abilities to individuals with paralysis by decoding their intended behavior from neural activity recorded with an implanted device. While this activity yields high-performance decoding over short timescales, neural data are often nonstationary, which can lead to decoder failure if not accounted for. To maintain performance, users must frequently recalibrate decoders, which requires the arduous collection of new neural and behavioral data. Aiming to reduce this burden, several approaches have been developed that either limit recalibration data requirements (few-shot approaches) or eliminate explicit recalibration entirely (zero-shot approaches). However, progress is limited by a lack of standardized datasets and comparison metrics, causing methods to be compared in an ad hoc manner. Here we introduce the FALCON benchmark suite (Few-shot Algorithms for COnsistent Neural decoding) to standardize evaluation of iBCI robustness. FALCON curates five datasets of neural and behavioral data that span movement and communication tasks to focus on behaviors of interest to modern-day iBCIs. Each dataset includes calibration data, optional few-shot recalibration data, and private evaluation data. We implement a flexible evaluation platform which only requires user-submitted code to return behavioral predictions on unseen data. We also seed the benchmark by applying baseline methods spanning several classes of possible approaches. FALCON aims to provide rigorous selection criteria for robust iBCI decoders, easing their translation to real-world devices. https://snel-repo.github.io/falcon/

neuroscience↗

bioRxiv2024

High-frequency amplitude-modulated sinusoidal stimulation induces desynchronized yet controllable neural firing

Regaining sensory feedback is critical for people living with limb amputation. Electrical stimulation of sensory fibers in peripheral nerves has been shown to restore focal percepts in the missing limb. However, conventional rectangular current pulses induce sensations often described as unnatural, likely due to the synchronous and periodic nature of activity they evoke. Here we introduce a fast-oscillating amplitude-modulated sinusoidal (FAMS) stimulation waveform that desynchronizes neural activity. Using computational modeling, we show that sinusoidal waveforms evoke asynchronous and irregular firing patterns, with frequency-dependent effects. Leveraging both low- and high-frequency mechanisms, FAMS exploits membrane nonlinearities to enhance neuron-specific differences. In a feline model of peripheral nerve stimulation, FAMS evoked activity that was more asynchronous than conventional rectangular pulses, while remaining easily controllable with simple stimulation parameters. Importantly, in human experiments using noninvasive stimulation of the median nerve, participants reported that FAMS evoked more natural sensations compared to rectangular biphasic pulses in a two-alternative forced-choice task. The preference for FAMS increased at higher intensities above sensory threshold, despite intensity-matched stimulation across waveform types. These findings provide evidence that reduced synchrony in afferent recruitment translates into more naturalistic and comfortable sensory percepts. Together, our results establish FAMS as a promising biomimetic stimulation strategy with potential for clinical applications in sensory feedback restoration. One Sentence SummaryA new electrical stimulation waveform allows for evoking and controlling more naturalistic neural activity than can be achieved with traditional stimulation waveforms.

bioengineering↗

bioRxiv2021

High-density spinal cord stimulation selectively activates lower urinary tract afferents

Epidural spinal cord stimulation (SCS) has recently been reported as a potential intervention to improve limb and autonomic functions, with lumbar stimulation improving locomotion and thoracic stimulation regulating blood pressure. We asked whether sacral SCS could be used to target the lower urinary tract. Here we show that high-density epidural SCS over the sacral spinal cord and cauda equina of anesthetized cats evokes responses in nerves innervating the bladder and urethra and that these nerves can be activated selectively. Sacral epidural SCS always recruited the pelvic and pudendal nerves and selectively recruited these nerves in all but one animal. Individual branches of the pudendal nerve were always recruited as well. Electrodes that selectively recruited specific peripheral nerves were spatially clustered on the arrays, suggesting anatomically organized sensory pathways. This selective recruitment demonstrates a mechanism to directly modulate bladder and urethral function through known reflex pathways, which could be used to restore bladder and urethral function after injury or disease.

bioengineering↗

bioRxiv2019

Approximating complex musculoskeletal biomechanics using multidimensional autogenerating polynomials

Computational models of the musculoskeletal system are scientific tools used to study human movement, quantify the effects of injury and disease, and plan surgical interventions. Additionally, these models could also be used to intuitively link biological control signals and realistic high-dimensional articulated prosthetic limbs. However, implementing fast and accurate musculoskeletal computations that can be used to control a prosthetic limb in real-time is a challenging problem. As muscles typically span multiple joints, the wrapping over complex geometrical constraints changes their moment arms and length as a function of joint angle and, thus, their ability to generate joint torques. As a result of these biomechanical complexities, calculating these muscle state variables in real-time is a difficult simulation problem. Here, we report a method to accurately and efficiently calculate these variables for the forearm muscles that actuate the hand and wrist across multiple postures. The posture dependent muscle geometry, moment arms and lengths of modeled muscles, were captured using autogenerating polynomials that expanded their optimal selection of terms using information measurements. The iterative process approximated 33 musculotendon actuators, each spanning up to 6 DOFs in an 18 DOF model of the human arm and hand, defined over the full physiological range of motion. Using these polynomials, the entire forearm anatomy could be computed in <10 {micro}s, which is far better than what is required for real-time performance, and with low errors in moment arms (below 5%) and lengths (below 0.4%). Moreover, we demonstrate that the number of elements in these autogenerating polynomials does not increase exponentially with the increase in complexity of muscles, increasing linearly instead. The similar structure and function of muscles are represented with specific invariant polynomial terms. Dimensionality reduction using the polynomial terms alone resulted in clusters comprised of muscles with similar functions, suggesting that the polynomials themselves captured biologically relevant features of muscle structure and function. We propose that this novel method of describing musculoskeletal biomechanics might further improve the applications of detailed and scalable models for the description of human movement.

physiology↗

bioRxiv2019

Restored tactile sensation improves neuroprosthetic arm control

Summary paragraphThe sense of touch is critical for skillful hand control1-3, but is largely missing for people who use prosthetic devices. Instead, prosthesis users rely heavily on visual feedback, even though state transitions that are necessary to skillfully interact with objects, such as object contact, are relayed more precisely through tactile feedback4-6. Here we show that restoring tactile sensory feedback, through intracortical microstimulation of the somatosensory cortex7, enables a person with a bidirectional intracortical brain-computer interface to improve their performance on functional object transport tasks completed with a neurally-controlled prosthetic limb. The participant had full visual feedback and had practiced the task for approximately two years prior to these experiments. Nevertheless, successful trial times on a commonly used clinical upper limb assessment task were reduced from a median time of 20.9 s (13.1 - 40.5 s interquartile range) to 10.2 s (5.4 - 18.1 s interquartile range) when vision was supplemented with microstimulation-evoked cutaneous percepts that were referred to different fingers and were graded in intensity based on real-time prosthesis contact forces. Faster completion times were primarily due to a reduction in the amount of time spent attempting to grasp objects. These results demonstrate the importance of tactile sensations in upper-limb control and the utility of creating bidirectional brain-computer interfaces to restore this stream of information using intracortical microstimulation.

clinical trials↗