A neural interface provides long-term stable natural touch perception

Tan, Daniel; Schiefer, Matthew A.; Keith, Michael W.; Anderson, James Robert; Tyler, Joyce; Tyler, Dustin J.

doi:10.1126/scitranslmed.3008669

Cited by 659 publications

(765 citation statements)

References 27 publications

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“…57). Also, the model will be valuable in neuroprosthetic applications that aim to restore the sense of touch through peripheral nerve interfaces (58)(59)(60). Indeed, the output of sensors on the prosthesis during object contact can be used as input to the simulated afferents, which then provide an accurate representation of how the nerve from an intact hand would respond to object contact.…”

Section: Discussionmentioning

confidence: 99%

Simulating tactile signals from the whole hand with millisecond precision

Saal

Delhaye

Rayhaun

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

212

251

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When we grasp and manipulate an object, populations of tactile nerve fibers become activated and convey information about the shape, size, and texture of the object and its motion across the skin. The response properties of tactile fibers have been extensively characterized in single-unit recordings, yielding important insights into how individual fibers encode tactile information. A recurring finding in this extensive body of work is that stimulus information is distributed over many fibers. However, our understanding of population-level representations remains primitive. To fill this gap, we have developed a model to simulate the responses of all tactile fibers innervating the glabrous skin of the hand to any spatiotemporal stimulus applied to the skin. The model first reconstructs the stresses experienced by mechanoreceptors when the skin is deformed and then simulates the spiking response that would be produced in the nerve fiber innervating that receptor. By simulating skin deformations across the palmar surface of the hand and tiling it with receptors at their known densities, we reconstruct the responses of entire populations of nerve fibers. We show that the simulated responses closely match their measured counterparts, down to the precise timing of the evoked spikes, across a wide variety of experimental conditions sampled from the literature. We then conduct three virtual experiments to illustrate how the simulation can provide powerful insights into population coding in touch. Finally, we discuss how the model provides a means to establish naturalistic artificial touch in bionic hands.mechanoreceptor | tactile afferent | somatosensory periphery | skin mechanics | computational model T he human hand is endowed with thousands of mechanoreceptors of different types distributed across the skin, each innervated by one or more large myelinated nerve fibers (1). These fibers convey detailed information about contact events and provide us with an exquisite sensitivity to the form and surface properties of grasped objects (2, 3). During object manipulation and tactile exploration, the glabrous skin of the hand undergoes complex spatiotemporal mechanical deformations, which in turn, drive very precise spiking responses in individual afferents. Coarse object features, such as edges and corners, are reflected in spatial patterns of activation in slowly adapting type I (SA1) and rapidly adapting (RA) fibers, which are densely packed in the fingertip (3, 4). At the same time, interactions with objects and surfaces elicit high-frequency, low-amplitude surface waves that propagate across the skin of the finger and palm and excite vibration-sensitive Pacinian (PC) afferents all over the hand (5-8).Recording the activity of tactile nerve fibers in monkeys or humans is technically difficult, is slow, and generally yields responses from a single unit at a time (9, 10). Although such recordings have yielded powerful insights into the neural basis of touch, they provide a limited window into the information that the hand c...

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Section: Discussionmentioning

confidence: 99%

Simulating tactile signals from the whole hand with millisecond precision

Saal

Delhaye

Rayhaun

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

212

251

View full text Add to dashboard Cite

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“…This represents a major conceptual advance because all previous studies on prosthesis ownership in amputees have relied on peripheral somatosensory stimulation; either in the form of tactile stimulation of the stump (4, 5) or a reinnervated patch of skin (6) or, possibly, the electrical stimulation of cuff electrodes chronically implanted in peripheral nerves (24,25). Thus, our results suggest that it is theoretically possible to bypass the peripheral nervous system entirely via direct cortical stimulation, which would enable patients who lack afferent input from a damaged or paralyzed limb (e.g., due to lesions of peripheral nerves or the spinal cord) to experience ownership of a neuroprosthetic device.…”

Section: Discussionmentioning

confidence: 99%

Ownership of an artificial limb induced by electrical brain stimulation

Collins

Guterstam

Cronin

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Replacing the function of a missing or paralyzed limb with a prosthetic device that acts and feels like one's own limb is a major goal in applied neuroscience. Recent studies in nonhuman primates have shown that motor control and sensory feedback can be achieved by connecting sensors in a robotic arm to electrodes implanted in the brain. However, it remains unknown whether electrical brain stimulation can be used to create a sense of ownership of an artificial limb. In this study on two human subjects, we show that ownership of an artificial hand can be induced via the electrical stimulation of the hand section of the somatosensory (SI) cortex in synchrony with touches applied to a rubber hand. Importantly, the illusion was not elicited when the electrical stimulation was delivered asynchronously or to a portion of the SI cortex representing a body part other than the hand, suggesting that multisensory integration according to basic spatial and temporal congruence rules is the underlying mechanism of the illusion. These findings show that the brain is capable of integrating "natural" visual input and direct cortical-somatosensory stimulation to create the multisensory perception that an artificial limb belongs to one's own body. Thus, they serve as a proof of concept that electrical brain stimulation can be used to "bypass" the peripheral nervous system to induce multisensory illusions and ownership of artificial body parts, which has important implications for patients who lack peripheral sensory input due to spinal cord or nerve lesions.body perception | electrical brain stimulation | neuroprosthetics | multisensory integration | self

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“…Natural and intuitive control of upper limb prostheses requires the establishment of a man-machine interface that explores the perception-action cycle directly based on biological signals [1][2][3] . These signals are processed to extract information about the user's intent and are translated into commands for the prosthesis.…”

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confidence: 99%

Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation

et al. 2017

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The intuitive control of upper - limb prostheses requires a man/machine interface that directly exploits biological signals. Here, we define and experimentally test an offline man/machine interface that takes advantage of the discharge timings of spinal moto r neurons. The motor - neuron behaviour is identified by deconvolution of the electrical activity of muscles reinnervated by nerves of a missing limb in patients with amputation at the shoulder or humeral level. We mapped the series of motor - neuron discharge s into control commands across multiple degrees of freedom via the offline application of direct proportional control, pattern recognition and musculoskeletal modelling. A series of experiments performed on six patients reveal that the man/machine interfac e has superior offline performance than conventional direct electromyographic control applied after targeted muscle innervation. The combination of surgical procedures, decoding and mapping into effective commands constitutes an interface with the output l ayers of the spinal cord circuitry that allows for the intuitive control of multiple degrees of freedom

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A neural interface provides long-term stable natural touch perception

Cited by 659 publications

References 27 publications

Simulating tactile signals from the whole hand with millisecond precision

Simulating tactile signals from the whole hand with millisecond precision

Ownership of an artificial limb induced by electrical brain stimulation

Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation

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