Key considerations in designing a somatosensory neuroprosthesis

Delhaye, Benoit P.; Saal, Hannes P.; Bensmaı̈a, Sliman J.

doi:10.1016/j.jphysparis.2016.11.001

Cited by 28 publications

(23 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In human amputees, stimulation via implanted peripheral nerve electrodes can provide the ability to sense passive elbow joint positions and finger movements(12, 14), and movement feedback in closed-loop motor control was feasible and effective in functional single participant and single percept demonstrations of concept(15, 16). However, a comprehensive functional and perceptual framework for kinesthesia in applied prosthetic systems is still lacking(2, 13, 17, 18). …”

Section: Introductionmentioning

confidence: 99%

Illusory movement perception improves motor control for prosthetic hands

et al. 2018

View full text Add to dashboard Cite

To effortlessly complete an intentional movement, the brain needs feedback from the body regarding the movement’s progress. This largely non-conscious kinesthetic sense helps the brain to learn relationships between motor commands and outcomes to correct movement errors. Prosthetic systems for restoring function have predominantly focused on controlling motorized joint movement. Without the kinesthetic sense, however, these devices do not become intuitively controllable. Here we report a method for endowing human amputees with a kinesthetic perception of dexterous robotic hands. Vibrating the muscles used for prosthetic control via a neural-machine interface produced the illusory perception of complex grip movements. Within minutes, three amputees integrated this kinesthetic feedback and improved movement control. Combining intent, kinesthesia, and vision instilled participants with a sense of agency over the robotic movements. This feedback approach for closed-loop control opens a pathway to seamless integration of minds and machines.

show abstract

Section: Introductionmentioning

confidence: 99%

Illusory movement perception improves motor control for prosthetic hands

et al. 2018

View full text Add to dashboard Cite

show abstract

“…We anticipate that the model will be an important tool in somatosensory research to characterize the peripheral representation of tactile stimuli. The model will also be useful in providing somatosensory feedback through interfaces with the peripheral nerve for use in neuroprosthetic devices by converting the output of touch sensors on the prosthesis into biomimetic afferent responses, which can then be implemented through electrical stimulation (11)(12)(13).…”

mentioning

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.

Self Cite

212

251

View full text Add to dashboard Cite

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...

show abstract

“…Other features predicting the success of a forebrain locus is that TMIS produces sensations like those evoked by the peripheral stimuli and that graded TMIS can selectively activate units of isorepresentation [10,19]. TMIS evoked sensations over the smallest unit of isorepresentation (e.g., part of a digit) commonly remained constant at several steps of increasing current, a Plateau (Figure 2D–G) [20,107].…”

Section: Segmentation Within Vcmentioning

confidence: 99%

“…Patients with amputations are unable to carry out these behaviors but could regain these abilities with the aid of an active prosthesis. Input of the type produced by cutaneous receptors on active prostheses upon sensory neural structures could improve sensory and motor function, and the functionality of active prosthesis in patients with amputations [9,10]. …”

Section: Introductionmentioning

confidence: 99%

“…These properties will demonstrate units of isorepresentation, so that Threshold Stimulation at Microampere current levels (TMIS) can produce discrete sensations or modify movements of isolated parts of the body. Third, TMIS presented in a pattern should produce the natural sensation, which can be graded by the parameters of stimulation [10,19]. Finally, the somatotopy and modality of the sensations evoked by stimulation of the sensory locus by the signal from the sensor should be comparable before and after a major injury, such as an amputation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Human Thalamic Somatosensory Nucleus (Ventral Caudal, Vc) as a Locus for Stimulation by INPUTS from Tactile, Noxious and Thermal Sensors on an Active Prosthesis

Chien

Korzeniewska

Colloca

et al. 2017

Sensors

View full text Add to dashboard Cite

The forebrain somatic sensory locus for input from sensors on the surface of an active prosthesis is an important component of the Brain Machine Interface. We now review the neuronal responses to controlled cutaneous stimuli and the sensations produced by Threshold Stimulation at Microampere current levels (TMIS) in such a locus, the human thalamic Ventral Caudal nucleus (Vc). The responses of these neurons to tactile stimuli mirror those for the corresponding class of tactile mechanoreceptor fiber in the peripheral nerve, and TMIS can evoke sensations like those produced by the stimuli that optimally activate each class. These neuronal responses show a somatotopic arrangement from lateral to medial in the sequence: leg, arm, face and intraoral structures. TMIS evoked sensations show a much more detailed organization into anterior posteriorly oriented rods, approximately 300 microns diameter, that represent smaller parts of the body, such as parts of individual digits. Neurons responding to painful and thermal stimuli are most dense around the posterior inferior border of Vc, and TMIS evoked pain sensations occur in one of two patterns: (i) pain evoked regardless of the frequency or number of spikes in a burst of TMIS; and (ii) the description and intensity of the sensation changes with increasing frequencies and numbers. In patients with major injuries leading to loss of somatic sensory input, TMIS often evokes sensations in the representation of parts of the body with loss of sensory input, e.g., the phantom after amputation. Some patients with these injuries have ongoing pain and pain evoked by TMIS of the representation in those parts of the body. Therefore, thalamic TMIS may produce useful patterned somatotopic feedback to the CNS from sensors on an active prosthesis that is sometimes complicated by TMIS evoked pain in the representation of those parts of the body.

show abstract

Key considerations in designing a somatosensory neuroprosthesis

Cited by 28 publications

References 83 publications

Illusory movement perception improves motor control for prosthetic hands

Illusory movement perception improves motor control for prosthetic hands

Simulating tactile signals from the whole hand with millisecond precision

Human Thalamic Somatosensory Nucleus (Ventral Caudal, Vc) as a Locus for Stimulation by INPUTS from Tactile, Noxious and Thermal Sensors on an Active Prosthesis

Contact Info

Product

Resources

About