Benoit P. Delhaye

Texture-induced vibrations in the forearm during tactile exploration

Humans can detect and discriminate between fine variations of surface roughness using active touch. It is hitherto believed that roughness perception is mediated mostly by cutaneous and subcutaneous afferents located in the fingertips. However, recent findings have shown that following abolishment of cutaneous afferences resulting from trauma or pharmacological intervention, the ability of subjects to discriminate between textures roughness was not significantly altered. These findings suggest that the somatosensory system is able to collect textural information from other sources than fingertip afference. It follows that signals resulting of the interaction of a finger with a rough surface must be transmitted to stimulate receptor populations in regions far away from the contact. This transmission was characterized by measuring in the wrist vibrations originating at the fingertip and thus propagating through the finger, the hand and the wrist during active exploration of textured surfaces. The spectral analysis of the vibrations taking place in the forearm tissues revealed regularities that were correlated with the scanned surface and the speed of exploration. In the case of periodic textures, the vibration signal contained a fundamental frequency component corresponding to the finger velocity divided by the spatial period of the stimulus. This regularity was found for a wide range of textural length scales and scanning velocities. For non-periodic textures, the spectrum of the vibration did not contain obvious features that would enable discrimination between the different stimuli. However, for both periodic and non-periodic stimuli, the intensity of the vibrations could be related to the microgeometry of the scanned surfaces.

Dynamics of fingertip contact during the onset of tangential slip

Through highly precise perceptual and sensorimotor activities, the human tactile system continuously acquires information about the environment. Mechanical interactions between the skin at the point of contact and a touched surface serve as the source of this tactile information. Using a dedicated custom robotic platform, we imaged skin deformation at the contact area between the finger and a flat surface during the onset of tangential sliding movements in four different directions (proximal, distal, radial and ulnar) and with varying normal force and tangential speeds. This simple tactile event evidenced complex mechanics. We observed a reduction of the contact area while increasing the tangential force and proposed to explain this phenomenon by nonlinear stiffening of the skin. The deformations shape and amplitude were highly dependent on stimulation direction. We conclude that the complex, but highly patterned and reproducible, deformations measured in this study are a potential source of information for the central nervous system and that further mechanical measurement are needed to better understand tactile perceptual and motor performances.

The neural basis of perceived intensity in natural and artificial touch

Electrical connections between nerves and a prosthetic device enable amputees to discern precise, graded sensory intensity ranging from light touch to intense pressure. Perceived intensity: A touchy subject for neuroprostheses Without tactile sensory input, amputees discern a firm handshake from a bone-crushing grip by visual cues and learned behavior. Next-generation prostheses aim to lend a more natural feel to artificial touch by transmitting nuanced sensory feedback. Graczyk et al. looked at direct stimulation of the radial, ulnar, and median nerves via implanted electrodes in two amputees to understand how levels of intensity are perceived and how tactile sensory feedback is transmitted. By modulating the number of nerve fibers stimulated and the frequency of stimulation, sensory information could be transmitted such that the amputees could distinguish distinct levels of tactile intensity, that is, the difference between a 7 and a 10 on a scale of intensity. Electrical stimulation of sensory nerves is a powerful tool for studying neural coding because it can activate neural populations in ways that natural stimulation cannot. Electrical stimulation of the nerve has also been used to restore sensation to patients who have suffered the loss of a limb. We have used long-term implanted electrical interfaces to elucidate the neural basis of perceived intensity in the sense of touch. To this end, we assessed the sensory correlates of neural firing rate and neuronal population recruitment independently by varying two parameters of nerve stimulation: pulse frequency and pulse width. Specifically, two amputees, chronically implanted with peripheral nerve electrodes, performed each of three psychophysical tasks—intensity discrimination, magnitude scaling, and intensity matching—in response to electrical stimulation of their somatosensory nerves. We found that stimulation pulse width and pulse frequency had systematic, cooperative effects on perceived tactile intensity and that the artificial tactile sensations could be reliably matched to skin indentations on the intact limb. We identified a quantity we termed the activation charge rate (ACR), derived from stimulation parameters, that predicted the magnitude of artificial tactile percepts across all testing conditions. On the basis of principles of nerve fiber recruitment, the ACR represents the total population spike count in the activated neural population. Our findings support the hypothesis that population spike count drives the magnitude of tactile percepts and indicate that sensory magnitude can be manipulated systematically by varying a single stimulation quantity.

Surface strain measurements of fingertip skin under shearing.

The temporal evolution of surface strain, resulting from a combination of normal and tangential loading forces on the fingerpad, was calculated from high-resolution images. A customized robotic device loaded the fingertip with varying normal force, tangential direction and tangential speed. We observed strain waves that propagated from the periphery to the centre of the contact area. Consequently, different regions of the contact area were subject to varying degrees of compression, stretch and shear. The spatial distribution of both the strains and the strain energy densities depended on the stimulus direction. Additionally, the strains varied with the normal force level and were substantial, e.g. peak strains of 50% with a normal force of 5 N, i.e. at force levels well within the range of common dexterous manipulation tasks. While these observations were consistent with some theoretical predictions from contact mechanics, we also observed substantial deviations as expected given the complex geometry and mechanics of fingertips. Specifically, from in-depth analyses, we conclude that some of these deviations depend on local fingerprint patterns. Our data provide useful information for models of tactile afferent responses and background for the design of novel haptic interfaces.

Key considerations in designing a somatosensory neuroprosthesis

In recent years, a consensus has emerged that somatosensory feedback needs to be provided for upper limb neuroprostheses to be useful. An increasingly promising approach to sensory restoration is to electrically stimulate neurons along the somatosensory neuraxis to convey information about the state of the prosthetic limb and about contact with objects. To date, efforts toward artificial sensory feedback have consisted mainly of demonstrating that some sensory information could be conveyed using a small number of stimulation patterns, generally delivered through single electrodes. However impressive these achievements are, results from different studies are hard to compare, as each research team implements different stimulation patterns and tests the elicited sensations differently. A critical question is whether different stimulation strategies will generalize from contrived laboratory settings to activities of daily living. Here, we lay out some key specifications that an artificial somatosensory channel should meet, discuss how different approaches should be evaluated, and caution about looming challenges that the field of sensory restoration will face.

Simulating tactile signals from the whole hand with millisecond precision

Significance When we grasp an object, thousands of tactile nerve fibers become activated and inform us about its physical properties (e.g., shape, size, and texture). Although the properties of individual fibers have been described, our understanding of how object information is encoded in populations of fibers remains primitive. To fill this gap, we have developed a simulation of tactile fibers that incorporates much of what is known about skin mechanics and tactile nerve fibers. We show that simulated fibers match biological ones across a wide range of conditions sampled from the literature. We then show how this simulation can reveal previously unknown ways in which populations of nerve fibers cooperate to convey sensory information and discuss the implications for bionic hands. 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.

Sensory adaptation to electrical stimulation of the somatosensory nerves

OBJECTIVE Sensory systems adapt their sensitivity to ambient stimulation levels to improve their responsiveness to changes in stimulation. The sense of touch is also subject to adaptation, as evidenced by the desensitization produced by prolonged vibratory stimulation of the skin. Electrical stimulation of nerves elicits tactile sensations that can convey feedback for bionic limbs. In this study, we investigate whether artificial touch is also subject to adaptation, despite the fact that the peripheral mechanotransducers are bypassed. APPROACH Using well-established psychophysical paradigms, we characterize the time course and magnitude of sensory adaptation caused by extended electrical stimulation of the residual somatosensory nerves in three human amputees implanted with cuff electrodes. MAIN RESULTS We find that electrical stimulation of the nerve also induces perceptual adaptation that recovers after cessation of the stimulus. The time course and magnitude of electrically-induced adaptation are equivalent to their mechanically-induced counterparts. SIGNIFICANCE We conclude that, in natural touch, the process of mechanotransduction is not required for adaptation, and artificial touch naturally experiences adaptation-induced adjustments of the dynamic range of sensations. Further, as it does for native hands, adaptation confers to bionic hands enhanced sensitivity to changes in stimulation and thus a more natural sensory experience.

Robo-Psychophysics: Extracting Behaviorally Relevant Features from the Output of Sensors on a Prosthetic Finger

Efforts are underway to restore sensorimotor function in amputees and tetraplegic patients using anthropomorphic robotic hands. For this approach to be clinically viable, sensory signals from the hand must be relayed back to the patient. To convey tactile feedback necessary for object manipulation, behaviorally relevant information must be extracted in real time from the output of sensors on the prosthesis. In the present study, we recorded the sensor output from a state-of-the-art bionic finger during the presentation of different tactile stimuli, including punctate indentations and scanned textures. Furthermore, the parameters of stimulus delivery (location, speed, direction, indentation depth, and surface texture) were systematically varied. We developed simple decoders to extract behaviorally relevant variables from the sensor output and assessed the degree to which these algorithms could reliably extract these different types of sensory information across different conditions of stimulus delivery. We then compared the performance of the decoders to that of humans in analogous psychophysical experiments. We show that straightforward decoders can extract behaviorally relevant features accurately from the sensor output and most of them outperform humans.

Perception of partial slips under tangential loading of the fingertip

During tactile exploration, partial slips occur systematically at the periphery of fingertip-object contact prior to full slip. Although the mechanics of partial slips are well characterized, the perception of such events is unclear. Here, we performed psychophysical experiments to assess partial slip detection ability on smooth transparent surfaces. In these experiments, the index fingertip of human subjects was stroked passively by a smooth, transparent glass plate while we imaged the contact slipping against the glass. We found that subjects were able to detect fingertip slip before full slip occurred when, on average, only 48% of the contact area was slipping. Additionally, we showed that partial slips and plate displacement permitted slip detection, but that the subjects could not rely on tangential force to detect slipping of the plate. Finally, we observed that, keeping the normal contact force constant, slip detection was impeded when the plate was covered with a hydrophobic coating dramatically lowering the contact friction and therefore the amount of fingertip deformation. Together, these results demonstrate that partial slips play an important role in fingertip slip detection and support the hypothesis that the central nervous system relies on them to adjust grip force during object manipulation.

Neural Basis of Touch and Proprioception in Primate Cortex

The sense of proprioception allows us to keep track of our limb posture and movements and the sense of touch provides us with information about objects with which we come into contact. In both senses, mechanoreceptors convert the deformation of tissues-skin, muscles, tendons, ligaments, or joints-into neural signals. Tactile and proprioceptive signals are then relayed by the peripheral nerves to the central nervous system, where they are processed to give rise to percepts of objects and of the state of our body. In this review, we first examine briefly the receptors that mediate touch and proprioception, their associated nerve fibers, and pathways they follow to the cerebral cortex. We then provide an overview of the different cortical areas that process tactile and proprioceptive information. Next, we discuss how various features of objects-their shape, motion, and texture, for example-are encoded in the various cortical fields, and the susceptibility of these neural codes to attention and other forms of higher-order modulation. Finally, we summarize recent efforts to restore the senses of touch and proprioception by electrically stimulating somatosensory cortex.