Touch is a team effort: interplay of submodalities in cutaneous sensibility

Somatosensory maps

Somatosensory areas containing topographic maps of the body surface are a major feature of parietal cortex. In primates, parietal cortex contains four somatosensory areas, each with its own map, with the primary cutaneous map in area 3b. Rodents have at least three parietal somatosensory areas. Maps are not isomorphic to the body surface, but magnify behaviorally important skin regions, which include the hands and face in primates, and the whiskers in rodents. Within each map, intracortical circuits process tactile information, mediate spatial integration, and support active sensation. Maps may also contain fine-scale representations of touch submodalities, or direction of tactile motion. Functional representations are more overlapping than suggested by textbook depictions of map topography. The whisker map in rodent somatosensory cortex is a canonic system for studying cortical microcircuits, sensory coding, and map plasticity. Somatosensory maps are plastic throughout life in response to altered use or injury. This chapter reviews basic principles and recent findings in primate, human, and rodent somatosensory maps.

Methodological considerations for a chronic neural interface with the cuneate nucleus of macaques

While the response properties of neurons in the somatosensory nerves and anterior parietal cortex have been extensively studied, little is known about the encoding of tactile and proprioceptive information in the cuneate nucleus (CN) or external cuneate nucleus (ECN), the first recipients of upper limb somatosensory afferent signals. The major challenge in characterizing neural coding in CN/ECN has been to record from these tiny, difficult-to-access brain stem structures. Most previous investigations of CN response properties have been carried out in decerebrate or anesthetized animals, thereby eliminating the well-documented top-down signals from cortex, which likely exert a strong influence on CN responses. Seeking to fill this gap in our understanding of somatosensory processing, we describe an approach to chronically implanting arrays of electrodes in the upper limb representation in the brain stem in primates. First, we describe the topography of CN/ECN in rhesus macaques, including its somatotopic organization and the layout of its submodalities (touch and proprioception). Second, we describe the design of electrode arrays and the implantation strategy to obtain stable recordings. Third, we show sample responses of CN/ECN neurons in brain stem obtained from awake, behaving monkeys. With this method, we are in a position to characterize, for the first time, somatosensory representations in CN and ECN of primates.NEW & NOTEWORTHY In primates, the neural basis of touch and of our sense of limb posture and movements has been studied in the peripheral nerves and in somatosensory cortex, but coding in the cuneate and external cuneate nuclei, the first processing stage for these signals in the central nervous system, remains an enigma. We have developed a method to record from these nuclei, thereby paving the way to studying how sensory information from the limb is encoded there.

The neural response properties and cortical organization of a rapidly adapting muscle sensory group response that overlaps with the frequencies that elicit the kinesthetic illusion

Kinesthesia is the sense of limb movement. It is fundamental to efficient motor control, yet its neurophysiological components remain poorly understood. The contributions of primary muscle spindles and cutaneous afferents to the kinesthetic sense have been well studied; however, potential contributions from muscle sensory group responses that are different than the muscle spindles have not been ruled out. Electrophysiological recordings in peripheral nerves and brains of male Sprague Dawley rats with a degloved forelimb preparation provide evidence of a rapidly adapting muscle sensory group response that overlaps with vibratory inputs known to generate illusionary perceptions of limb movement in humans (kinesthetic illusion). This group was characteristically distinct from type Ia muscle spindle fibers, the receptor historically attributed to limb movement sensation, suggesting that type Ia muscle spindle fibers may not be the sole carrier of kinesthetic information. The sensory-neural structure of muscles is complex and there are a number of possible sources for this response group; with Golgi tendon organs being the most likely candidate. The rapidly adapting muscle sensory group response projected to proprioceptive brain regions, the rodent homolog of cortical area 3a and the second somatosensory area (S2), with similar adaption and frequency response profiles between the brain and peripheral nerves. Their representational organization was muscle-specific (myocentric) and magnified for proximal and multi-articulate limb joints. Projection to proprioceptive brain areas, myocentric representational magnification of muscles prone to movement error, overlap with illusionary vibrational input, and resonant frequencies of volitional motor unit contraction suggest that this group response may be involved with limb movement processing.

Restoration of motor control and proprioceptive and cutaneous sensation in humans with prior upper-limb amputation via multiple Utah Slanted Electrode Arrays (USEAs) implanted in residual peripheral arm nerves

Background

Despite advances in sophisticated robotic hands, intuitive control of and sensory feedback from these prostheses has been limited to only 3-degrees-of-freedom (DOF) with 2 sensory percepts in closed-loop control. A Utah Slanted Electrode Array (USEA) has been used in the past to provide up to 81 sensory percepts for human amputees. Here, we report on the advanced capabilities of multiple USEAs implanted in the residual peripheral arm nerves of human amputees for restoring control of 5 DOF and sensation of up to 131 proprioceptive and cutaneous hand sensory percepts. We also demonstrate that USEA-restored sensory percepts provide a useful source of feedback during closed-loop virtual prosthetic hand control.

Methods

Two 100-channel USEAs were implanted for 4–5 weeks, one each in the median and ulnar arm nerves of two human subjects with prior long-duration upper-arm amputations. Intended finger and wrist positions were decoded from neuronal firing patterns via a modified Kalman filter, allowing subjects to control many movements of a virtual prosthetic hand. Additionally, USEA microstimulation was used to evoke numerous sensory percepts spanning the phantom hand. Closed-loop control was achieved by stimulating via an electrode of the ulnar-nerve USEA while recording and decoding movement via the median-nerve USEA.

Results

Subjects controlled up to 12 degrees-of-freedom during informal, ‘freeform’ online movement decode sessions, and experienced up to 131 USEA-evoked proprioceptive and cutaneous sensations spanning the phantom hand. Independent control was achieved for a 5-DOF real-time decode that included flexion/extension of the thumb, index, middle, and ring fingers, and the wrist. Proportional control was achieved for a 4-DOF real-time decode. One subject used a USEA-evoked hand sensation as feedback to complete a 1-DOF closed-loop virtual-hand movement task. There were no observed long-term functional deficits due to the USEA implants.

Conclusions

Implantation of high-channel-count USEAs enables multi-degree-of-freedom control of virtual prosthetic hand movement and restoration of a rich selection of both proprioceptive and cutaneous sensory percepts spanning the hand during the short 4–5 week post-implant period. Future USEA use in longer-term implants and in closed-loop may enable restoration of many of the capabilities of an intact hand while contributing to a meaningful embodiment of the prosthesis.

Electronic supplementary material

The online version of this article (10.1186/s12984-017-0320-4) contains supplementary material, which is available to authorized users.

Tactile perception of the roughness of 3D-printed textures

Surface roughness is one of the most important qualities in haptic perception. Roughness is a major identifier for judgments of material composition, comfort, and friction and is tied closely to manual dexterity. Some attention has been given to the study of roughness perception in the past, but it has typically focused on noncontrollable natural materials or on a narrow range of artificial materials. The advent of high-resolution three-dimensional (3D) printing technology provides the ability to fabricate arbitrary 3D textures with precise surface geometry to be used in tactile studies. We used parametric modeling and 3D printing to manufacture a set of textured plates with defined element spacing, shape, and arrangement. Using active touch and two-alternative forced-choice protocols, we investigated the contributions of these surface parameters to roughness perception in human subjects. Results indicate that large spatial periods produce higher estimations of roughness (with Weber fraction = 0.19), small texture elements are perceived as rougher than large texture elements of the same wavelength, perceptual differences exist between textures with the same spacing but different arrangements, and roughness equivalencies exist between textures differing along different parameters. We posit that papillary ridges serve as tactile processing units, and neural ensembles encode the spatial profiles of the texture contact area to produce roughness estimates. The stimuli and the manufacturing process may be used in further studies of tactile roughness perception and in related neurophysiological applications. NEW & NOTEWORTHY Surface roughness is an integral quality of texture perception. We manufactured textures using high-resolution 3D printing, which allows precise specification of the surface spatial topography. In human psychophysical experiments we investigated the contributions of specific surface parameters to roughness perception. We found that textures with large spatial periods, small texture elements, and irregular, isotropic arrangements elicit the highest estimations of roughness. We propose that roughness correlates inversely with the total contacted surface area.

Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review

For those individuals with upper-extremity amputation, a daily normal living activity is no longer possible or it requires additional effort and time. With the aim of restoring their sensory and motor functions, theoretical and technological investigations have been carried out in the field of neuroprosthetic systems. For transmission of sensory feedback, several interfacing modalities including indirect (non-invasive), direct-to-peripheral-nerve (invasive), and cortical stimulation have been applied. Peripheral nerve interfaces demonstrate an edge over the cortical interfaces due to the sensitivity in attaining cortical brain signals. The peripheral nerve interfaces are highly dependent on interface designs and are required to be biocompatible with the nerves to achieve prolonged stability and longevity. Another criterion is the selection of nerves that allows minimal invasiveness and damages as well as high selectivity for a large number of nerve fascicles. In this paper, we review the nerve-machine interface modalities noted above with more focus on peripheral nerve interfaces, which are responsible for provision of sensory feedback. The invasive interfaces for recording and stimulation of electro-neurographic signals include intra-fascicular, regenerative-type interfaces that provide multiple contact channels to a group of axons inside the nerve and the extra-neural-cuff-type interfaces that enable interaction with many axons around the periphery of the nerve. Section Current Prosthetic Technology summarizes the advancements made to date in the field of neuroprosthetics toward the achievement of a bidirectional nerve-machine interface with more focus on sensory feedback. In the Discussion section, the authors propose a hybrid interface technique for achieving better selectivity and long-term stability using the available nerve interfacing techniques.

The neural code for tactile roughness in the somatosensory nerves

Roughness is the most salient perceptual dimension of surface texture but has no well-defined physical basis. We seek to determine the neural determinants of tactile roughness in the somatosensory nerves. Specifically, we record the patterns of activation evoked in tactile nerve fibers of anesthetized Rhesus macaques to a large and diverse set of natural textures and assess what aspect of these patterns of activation can account for psychophysical judgments of roughness, obtained from human observers. We show that perceived roughness is determined by the variation in the population response, weighted by fiber type. That is, a surface will feel rough to the extent that the activity varies across nerve fibers and varies across time within nerve fibers. We show that this variation-based neural code can account not only for magnitude estimates of roughness but also for roughness discrimination performance.NEW & NOTEWORTHY Our sense of touch endows us with an exquisite sensitivity to the microstructure of surfaces, the most salient aspect of which is roughness. We analyze the responses evoked in tactile fibers of monkeys by natural textures and compare them to judgments of roughness obtained for the same textures from human observers. We then describe how texture signals from three populations of nerve fibers are integrated to culminate in a percept of roughness.

Measuring the effects of attention to individual fingertips in somatosensory cortex using ultra-high field (7T) fMRI

Attention to sensory information has been shown to modulate the neuronal processing of that information. For example, visuospatial attention acts by modulating responses at retinotopically appropriate regions of visual cortex (Puckett and DeYoe, 2015; Tootell et al. 1998). Much less, however, is known about the neuronal processing associated with attending to other modalities of sensory information. One reason for this is that visual cortex is relatively large, and therefore easier to access non-invasively in humans using tools such as functional magnetic resonance imaging (fMRI). With high-resolution fMRI, however, it is now possible to access smaller cortical areas such as primary somatosensory cortex (Martuzzi et al., 2014; Sanchez-Panchuelo et al., 2010; Schweisfurth et al. 2014; Schweizer et al. 2008). Here, we combined a novel experimental design and high-resolution fMRI at ultra-high field (7T) to measure the effects of attention to tactile stimulation in primary somatosensory cortex, S1. We find that attention modulates somatotopically appropriate regions of S1, and importantly, that this modulation can be measured at the level of the cortical representation of individual fingertips.

Simulating tactile signals from the whole hand with millisecond precision

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.

A Mechanistic Link from GABA to Cortical Architecture and Perception

Understanding both the organization of the human cortex and its relation to the performance of distinct functions is fundamental in neuroscience. The primary sensory cortices display topographic organization, whereby receptive fields follow a characteristic pattern, from tonotopy to retinotopy to somatotopy [1]. GABAergic signaling is vital to the maintenance of cortical receptive fields [2]; however, it is unclear how this fine-grain inhibition relates to measurable patterns of perception [3, 4]. Based on perceptual changes following perturbation of the GABAergic system, it is conceivable that the resting level of cortical GABAergic tone directly relates to the spatial specificity of activation in response to a given input [5, 6, 7]. The specificity of cortical activation can be considered in terms of cortical tuning: greater cortical tuning yields more localized recruitment of cortical territory in response to a given input. We applied a combination of fMRI, MR spectroscopy, and psychophysics to substantiate the link between the cortical neurochemical milieu, the tuning of cortical activity, and variability in perceptual acuity, using human somatosensory cortex as a model. We provide data that explain human perceptual acuity in terms of both the underlying cellular and metabolic processes. Specifically, higher concentrations of sensorimotor GABA are associated with more selective cortical tuning, which in turn is associated with enhanced perception. These results show anatomical and neurochemical specificity and are replicated in an independent cohort. The mechanistic link from neurochemistry to perception provides a vital step in understanding population variability in sensory behavior, informing metabolic therapeutic interventions to restore perceptual abilities clinically.

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GABAergic tone correlates with perceptual acuity in the human somatosensory system

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This relationship is mediated by the tuning of activity in somatosensory cortex

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We explain perceptual acuity via the underlying cellular and metabolic processes

Multisensory components of rapid motor responses to fingertip loading

Tactile and muscle afferents provide critical sensory information for grasp control, yet the contribution of each sensory system during online control has not been clearly identified. More precisely, it is unknown how these two sensory systems participate in online control of digit forces following perturbations to held objects. To address this issue, we investigated motor responses in the context of fingertip loading, which parallels the impact of perturbations to held objects on finger motion and fingerpad deformation, and characterized surface recordings of intrinsic (first dorsal interosseous, FDI) and extrinsic (flexor digitorum superficialis, FDS) hand muscles based on statistical modeling. We designed a series of experiments probing the effects of peripheral stimulation with or without anesthesia of the finger, and of task instructions. Loading of the fingertip generated a motor response in FDI at ~60 ms following the perturbation onset, which was only driven by muscle stretch, as the ring-block anesthesia reduced the gain of the response occurring later than 90 ms, leaving responses occurring before this time unaffected. In contrast, the motor response in FDS was independent of the lateral motion of the finger. This response started at ~90 ms on average and was immediately adjusted to task demands. Altogether these results highlight how a rapid integration of partially distinct sensorimotor circuits supports rapid motor responses to fingertip loading.NEW & NOTEWORTHY To grasp and manipulate objects, the brain uses touch signals related to skin deformation as well as sensory information about motion of the fingers encoded in muscle spindles. Here we investigated how these two sensory systems contribute to feedback responses to perturbation applied to the fingertip. We found distinct response components, suggesting that each sensory system engages separate sensorimotor circuits with distinct functions and latencies.

Auditory adaptation improves tactile frequency perception

Our ability to process temporal frequency information by touch underlies our capacity to perceive and discriminate surface textures. Auditory signals, which also provide extensive temporal frequency information, can systematically alter the perception of vibrations on the hand. How auditory signals shape tactile processing is unclear; perceptual interactions between contemporaneous sounds and vibrations are consistent with multiple neural mechanisms. Here we used a crossmodal adaptation paradigm, which separated auditory and tactile stimulation in time, to test the hypothesis that tactile frequency perception depends on neural circuits that also process auditory frequency. We reasoned that auditory adaptation effects would transfer to touch only if signals from both senses converge on common representations. We found that auditory adaptation can improve tactile frequency discrimination thresholds. This occurred only when adaptor and test frequencies overlapped. In contrast, auditory adaptation did not influence tactile intensity judgments. Thus auditory adaptation enhances touch in a frequency- and feature-specific manner. A simple network model in which tactile frequency information is decoded from sensory neurons that are susceptible to auditory adaptation recapitulates these behavioral results. Our results imply that the neural circuits supporting tactile frequency perception also process auditory signals. This finding is consistent with the notion of supramodal operators performing canonical operations, like temporal frequency processing, regardless of input modality.NEW & NOTEWORTHY Auditory signals can influence the tactile perception of temporal frequency. Multiple neural mechanisms could account for the perceptual interactions between contemporaneous auditory and tactile signals. Using a crossmodal adaptation paradigm, we found that auditory adaptation causes frequency- and feature-specific improvements in tactile perception. This crossmodal transfer of aftereffects between audition and touch implies that tactile frequency perception relies on neural circuits that also process auditory frequency.

Encoding of Tactile Stimuli by Mechanoreceptors and Interneurons of the Medicinal Leech

For many animals processing of tactile information is a crucial task in behavioral contexts like exploration, foraging, and stimulus avoidance. The leech, having infrequent access to food, developed an energy efficient reaction to tactile stimuli, avoiding unnecessary muscle movements: The local bend behavior moves only a small part of the body wall away from an object touching the skin, while the rest of the animal remains stationary. Amazingly, the precision of this localized behavioral response is similar to the spatial discrimination threshold of the human fingertip, although the leech skin is innervated by an order of magnitude fewer mechanoreceptors and each midbody ganglion contains only 400 individually identified neurons in total. Prior studies suggested that this behavior is controlled by a three-layered feed-forward network, consisting of four mechanoreceptors (P cells), approximately 20 interneurons and 10 individually characterized motor neurons, all of which encode tactile stimulus location by overlapping, symmetrical tuning curves. Additionally, encoding of mechanical force was attributed to three types of mechanoreceptors reacting to distinct intensity ranges: T cells for touch, P cells for pressure, and N cells for strong, noxious skin stimulation. In this study, we provide evidences that tactile stimulus encoding in the leech is more complex than previously thought. Combined electrophysiological, anatomical, and voltage sensitive dye approaches indicate that P and T cells both play a major role in tactile information processing resulting in local bending. Our results indicate that tactile encoding neither relies on distinct force intensity ranges of different cell types, nor location encoding is restricted to spike count tuning. Instead, we propose that P and T cells form a mixed type population, which simultaneously employs temporal response features and spike counts for multiplexed encoding of touch location and force intensity. This hypothesis is supported by our finding that previously identified local bend interneurons receive input from both P and T cells. Some of these interneurons seem to integrate mechanoreceptor inputs, while others appear to use temporal response cues, presumably acting as coincidence detectors. Further voltage sensitive dye studies can test these hypotheses how a tiny nervous system performs highly precise stimulus processing.

Haptic adaptation to slant: No transfer between exploration modes

Human touch is an inherently active sense: to estimate an object's shape humans often move their hand across its surface. This way the object is sampled both in a serial (sampling different parts of the object across time) and parallel fashion (sampling using different parts of the hand simultaneously). Both the serial (moving a single finger) and parallel (static contact with the entire hand) exploration modes provide reliable and similar global shape information, suggesting the possibility that this information is shared early in the sensory cortex. In contrast, we here show the opposite. Using an adaptation-and-transfer paradigm, a change in haptic perception was induced by slant-adaptation using either the serial or parallel exploration mode. A unified shape-based coding would predict that this would equally affect perception using other exploration modes. However, we found that adaptation-induced perceptual changes did not transfer between exploration modes. Instead, serial and parallel exploration components adapted simultaneously, but to different kinaesthetic aspects of exploration behaviour rather than object-shape per se. These results indicate that a potential combination of information from different exploration modes can only occur at down-stream cortical processing stages, at which adaptation is no longer effective.

Neural Categorization of Vibrotactile Frequency in Flutter and Vibration Stimulations: An fMRI Study

As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.

Multiplexed Population Coding of Stimulus Properties by Leech Mechanosensory Cells

Sensory coding has long been discussed in terms of a dichotomy between spike timing and rate coding. However, recent studies found that in primate mechanoperception and other sensory systems, spike rates and timing of cell populations complement each other. They simultaneously carry information about different stimulus properties in a multiplexed way. Here, we present evidence for multiplexed encoding of tactile skin stimulation in the tiny population of leech mechanoreceptors, consisting of only 10 cells of two types with overlapping receptive fields. Each mechanoreceptor neuron of the leech varies spike count and response latency to both touch intensity and location, leading to ambiguous responses to different stimuli. Nevertheless, three different stimulus estimation techniques consistently reveal that the neuronal population allows reliable decoding of both stimulus properties. For the two mechanoreceptor types, the transient responses of T (touch) cells and the sustained responses of P (pressure) cells, the relative timing of the first spikes of two mechanoreceptors encodes stimulus location, whereas summed spike counts represent touch intensity. Differences between the cell types become evident in responses to combined stimulus properties. The best estimation performance for stimulus location is obtained from the relative first spike timing of the faster and temporally more precise T cells. Simultaneously, the sustained responses of P cells indicate touch intensity by summed spike counts and stimulus duration by the duration of spike responses. The striking similarities of these results with previous findings on primate mechanosensory afferents suggest multiplexed population coding as a general principle of somatosensation.

SIGNIFICANCE STATEMENT

Multiplexing, the simultaneous encoding of different stimulus properties by distinct neuronal response features, has recently been suggested as a mechanism used in several sensory systems, including primate somatosensation. While a rigorous experimental verification of the multiplexing hypothesis is difficult to accomplish in a complex vertebrate system, it is feasible for a small population of individually characterized leech neurons. Monitoring the responses of all four mechanoreceptors innervating a patch of skin revealed striking similarities between touch encoding in the primate and the leech: summed spike counts represent stimulus intensity, whereas relative timing of first spikes encodes stimulus location. These findings suggest that multiplexed population coding is a general mechanism of touch encoding common to species as different as man and worm.

Parallel Transformation of Tactile Signals in Central Circuits of Drosophila

To distinguish between complex somatosensory stimuli, central circuits must combine signals from multiple peripheral mechanoreceptor types, as well as mechanoreceptors at different sites in the body. Here, we investigate the first stages of somatosensory integration in Drosophila using in vivo recordings from genetically labeled central neurons in combination with mechanical and optogenetic stimulation of specific mechanoreceptor types. We identify three classes of central neurons that process touch: one compares touch signals on different parts of the same limb, one compares touch signals on right and left limbs, and the third compares touch and proprioceptive signals. Each class encodes distinct features of somatosensory stimuli. The axon of an individual touch receptor neuron can diverge to synapse onto all three classes, meaning that these computations occur in parallel, not hierarchically. Representing a stimulus as a set of parallel comparisons is a fast and efficient way to deliver somatosensory signals to motor circuits.

Fast-adapting mechanoreceptors are important for force control in precision grip but not for sensorimotor memory

Sensory feedback from cutaneous mechanoreceptors in the fingertips is important in effective object manipulation, allowing appropriate scaling of grip and load forces during precision grip. However, the role of mechanoreceptor subtypes in these tasks remains incompletely understood. To address this issue, psychophysical tasks that may specifically assess function of type I fast-adapting (FAI) and slowly adapting (SAI) mechanoreceptors were used with object manipulation experiments to examine the regulation of grip force control in an experimental model of graded reduction in tactile sensitivity (healthy volunteers wearing 2 layers of latex gloves). With gloves, tactile sensitivity decreased significantly from 1.9 ± 0.4 to 12.3 ± 2.2 μm in the Bumps task assessing function of FAI afferents but not in a grating orientation task assessing SAI afferents (1.6 ± 0.1 to 1.8 ± 0.2 mm). Six axis force/torque sensors measured peak grip (PGF) and load (PLF) forces generated by the fingertips during a grip-lift task. With gloves there was a significant increase of PGF (14 ± 6%), PLF (17 ± 5%), and grip and load force rates (26 ± 8%, 20 ± 8%). A variable-weight series task was used to examine sensorimotor memory. There was a 20% increase in PGF when the lift of a light object was preceded by a heavy relative to a light object. This relationship was not significantly altered when lifting with gloves, suggesting that the addition of gloves did not change sensorimotor memory effects. We conclude that FAI fibers may be important for the online force scaling but not for the buildup of a sensorimotor memory.

Investigating the Stability of Fine-Grain Digit Somatotopy in Individual Human Participants

Studies of human primary somatosensory cortex (S1) have placed a strong emphasis on the cortical representation of the hand and the propensity for plasticity therein. Despite many reports of group differences and experience-dependent changes in cortical digit somatotopy, relatively little work has considered the variability of these maps across individuals and to what extent this detailed functional architecture is dynamic over time. With the advent of 7 T fMRI, it is increasingly feasible to map such detailed organization noninvasively in individual human participants. Here, we extend the ability of ultra-high-field imaging beyond a technological proof of principle to investigate the intersubject variability of digit somatotopy across participants and the stability of this organization across a range of intervals. Using a well validated phase-encoding paradigm and an active task, we demonstrate the presence of highly reproducible maps of individual digits in S1, sharply contrasted by a striking degree of intersubject variability in the shape, extent, and relative position of individual digit representations. Our results demonstrate the presence of very stable fine-grain somatotopy of the digits in human S1 and raise the issue of population variability in such detailed functional architecture of the human brain. These findings have implications for the study of detailed sensorimotor plasticity in the context of both learning and pathological dysfunction. The simple task and 10 min scan required to derive these maps also raises the potential for this paradigm as a tool in the clinical setting.

SIGNIFICANCE STATEMENT

We applied ultra-high-resolution fMRI at 7 T to map sensory digit representations in the human primary somatosensory cortex (S1) at the level of individual participants across multiple time points. The resulting fine-grain maps of individual digits in S1 reveal the stability in this fine-grain functional organization over time, contrasted with the variability in these maps across individuals.

The Bayesian Decoding of Force Stimuli from Slowly Adapting Type I Fibers in Humans

It is well known that signals encoded by mechanoreceptors facilitate precise object manipulation in humans. It is therefore of interest to study signals encoded by the mechanoreceptors because this will contribute further towards the understanding of fundamental sensory mechanisms that are responsible for coordinating force components during object manipulation. From a practical point of view, this may suggest strategies for designing sensory-controlled biomedical devices and robotic manipulators. We use a two-stage nonlinear decoding paradigm to reconstruct the force stimulus given signals from slowly adapting type one (SA-I) tactile afferents. First, we describe a nonhomogeneous Poisson encoding model which is a function of the force stimulus and the force’s rate of change. In the decoding phase, we use a recursive nonlinear Bayesian filter to reconstruct the force profile, given the SA-I spike patterns and parameters described by the encoding model. Under the current encoding model, the mode ratio of force to its derivative is: 1.26 to 1.02. This indicates that the force derivative contributes significantly to the rate of change to the SA-I afferent spike modulation. Furthermore, using recursive Bayesian decoding algorithms is advantageous because it can incorporate past and current information in order to make predictions—consistent with neural systems—with little computational resources. This makes it suitable for interfacing with prostheses.

Control of Prosthetic Hands via the Peripheral Nervous System

This paper intends to provide a critical review of the literature on the technological issues on control and sensorization of hand prostheses interfacing with the Peripheral Nervous System (i.e., PNS), and their experimental validation on amputees. The study opens with an in-depth analysis of control solutions and sensorization features of research and commercially available prosthetic hands. Pros and cons of adopted technologies, signal processing techniques and motion control solutions are investigated. Special emphasis is then dedicated to the recent studies on the restoration of tactile perception in amputees through neural interfaces. The paper finally proposes a number of suggestions for designing the prosthetic system able to re-establish a bidirectional communication with the PNS and foster the prosthesis natural control.

Spatial patterns of cutaneous vibration during whole-hand haptic interactions

We investigated the propagation patterns of cutaneous vibration in the hand during interactions with touched objects. Prior research has highlighted the importance of vibrotactile signals during haptic interactions, but little is known of how vibrations propagate throughout the hand. Furthermore, the extent to which the patterns of vibrations reflect the nature of the objects that are touched, and how they are touched, is unknown. Using an apparatus comprised of an array of accelerometers, we mapped and analyzed spatial distributions of vibrations propagating in the skin of the dorsal region of the hand during active touch, grasping, and manipulation tasks. We found these spatial patterns of vibration to vary systematically with touch interactions and determined that it is possible to use these data to decode the modes of interaction with touched objects. The observed vibration patterns evolved rapidly in time, peaking in intensity within a few milliseconds, fading within 20-30 ms, and yielding interaction-dependent distributions of energy in frequency bands that span the range of vibrotactile sensitivity. These results are consistent with findings in perception research that indicate that vibrotactile information distributed throughout the hand can transmit information regarding explored and manipulated objects. The results may further clarify the role of distributed sensory resources in the perceptual recovery of object attributes during active touch, may guide the development of approaches to robotic sensing, and could have implications for the rehabilitation of the upper extremity.

Chronic recordings reveal tactile stimuli can suppress spontaneous activity of neurons in somatosensory cortex of awake and anesthetized primates

In somatosensory cortex, tactile stimulation within the neuronal receptive field (RF) typically evokes a transient excitatory response with or without postexcitatory inhibition. Here, we describe neuronal responses in which stimulation on the hand is followed by suppression of the ongoing discharge. With the use of 16-channel microelectrode arrays implanted in the hand representation of primary somatosensory cortex of New World monkeys and prosimian galagos, we recorded neuronal responses from single units and neuron clusters. In 66% of our sample, neuron activity tended to display suppression of firing when regions of skin outside of the excitatory RF were stimulated. In a small proportion of neurons, single-site indentations suppressed firing without initial increases in response to any of the tested sites on the hand. Latencies of suppressive responses to skin indentation (usually 12-34 ms) were similar to excitatory response latencies. The duration of inhibition varied across neurons. Although most observations were from anesthetized animals, we also found similar neuron response properties in one awake galago. Notably, suppression of ongoing neuronal activity did not require conditioning stimuli or multi-site stimulation. The suppressive effects were generally seen following single-site skin indentations outside of the neuron's minimal RF and typically on different digits and palm pads, which have not often been studied in this context. Overall, the characteristics of widespread suppressive or inhibitory response properties with and without initial facilitative or excitatory responses add to the growing evidence that neurons in primary somatosensory cortex provide essential processing for integrating sensory stimulation from across the hand.

Feeling form: the neural basis of haptic shape perception

The tactile perception of the shape of objects critically guides our ability to interact with them. In this review, we describe how shape information is processed as it ascends the somatosensory neuraxis of primates. At the somatosensory periphery, spatial form is represented in the spatial patterns of activation evoked across populations of mechanoreceptive afferents. In the cerebral cortex, neurons respond selectively to particular spatial features, like orientation and curvature. While feature selectivity of neurons in the earlier processing stages can be understood in terms of linear receptive field models, higher order somatosensory neurons exhibit nonlinear response properties that result in tuning for more complex geometrical features. In fact, tactile shape processing bears remarkable analogies to its visual counterpart and the two may rely on shared neural circuitry. Furthermore, one of the unique aspects of primate somatosensation is that it contains a deformable sensory sheet. Because the relative positions of cutaneous mechanoreceptors depend on the conformation of the hand, the haptic perception of three-dimensional objects requires the integration of cutaneous and proprioceptive signals, an integration that is observed throughout somatosensory cortex.

Rate and timing of cortical responses driven by separate sensory channels

The sense of touch comprises multiple sensory channels that each conveys characteristic signals during interactions with objects. These neural signals must then be integrated in such a way that behaviorally relevant information about the objects is preserved. To understand the process of integration, we implement a simple computational model that describes how the responses of neurons in somatosensory cortex—recorded from awake, behaving monkeys—are shaped by the peripheral input, reconstructed using simulations of neuronal populations that reproduce natural spiking responses in the nerve with millisecond precision. First, we find that the strength of cortical responses is driven by one population of nerve fibers (rapidly adapting) whereas the timing of cortical responses is shaped by the other (Pacinian). Second, we show that input from these sensory channels is integrated in an optimal fashion that exploits the disparate response behaviors of different fiber types.

DOI:http://dx.doi.org/10.7554/eLife.10450.001

Our sense of touch depends upon receptors in our skin that send signals to the brain about the objects with which we interact. Different types of touch receptors respond in different ways when we grasp and manipulate objects; for example, by altering the strength of their response or its timing.

Saal et al. have now investigated how neurons in a part of the brain called the somatosensory cortex, which processes touch signals from the hand, respond to the information from the different receptor types. First, recordings were made of the electrical activity of the touch receptors and the neurons in the brain of monkeys. Using this data, Saal et al. built computer models that allow the response of neurons in the brain to be predicted from the responses of the touch receptors.

The models showed that signals from different types of touch receptors shape the response of neurons in the brain in different ways. One receptor type controls how strong a neuron’s response will be, while another one controls the precise timing of the response. Further investigation revealed that this way of combining the signals from the different receptors preserves as much information as possible about objects and thereby helps the brain to process information acquired by touch quickly and efficiently.

Future experiments will examine how touch is represented in two structures that lie between the receptors and the somatosensory cortex: one in the brainstem, the other in a brain region called the thalamus.

DOI:http://dx.doi.org/10.7554/eLife.10450.002

The tactile speed aftereffect depends on the speed of adapting motion across the skin rather than other spatiotemporal features

After prolonged exposure to a surface moving across the skin, this felt movement appears slower, a phenomenon known as the tactile speed aftereffect (tSAE). We asked which feature of the adapting motion drives the tSAE: speed, the spacing between texture elements, or the frequency with which they cross the skin. After adapting to a ridged moving surface with one hand, participants compared the speed of test stimuli on adapted and unadapted hands. We used surfaces with different spatial periods (SPs; 3, 6, 12 mm) that produced adapting motion with different combinations of adapting speed (20, 40, 80 mm/s) and temporal frequency (TF; 3.4, 6.7, 13.4 ridges/s). The primary determinant of tSAE magnitude was speed of the adapting motion, not SP or TF. This suggests that adaptation occurs centrally, after speed has been computed from SP and TF, and/or that it reflects a speed cue independent of those features in the first place (e.g., indentation force). In a second experiment, we investigated the properties of the neural code for speed. Speed tuning predicts that adaptation should be greatest for speeds at or near the adapting speed. However, the tSAE was always stronger when the adapting stimulus was faster (242 mm/s) than the test (30-143 mm/s) compared with when the adapting and test speeds were matched. These results give no indication of speed tuning and instead suggest that adaptation occurs at a level where an intensive code dominates. In an intensive code, the faster the stimulus, the more the neurons fire.

Peripheral vs. central determinants of vibrotactile adaptation

Long-lasting mechanical vibrations applied to the skin induce a reversible decrease in the perception of vibration at the stimulated skin site. This phenomenon of vibrotactile adaptation has been studied extensively, yet there is still no clear consensus on the mechanisms leading to vibrotactile adaptation. In particular, the respective contributions of 1) changes affecting mechanical skin impedance, 2) peripheral processes, and 3) central processes are largely unknown. Here we used direct electrical stimulation of nerve fibers to bypass mechanical transduction processes and thereby explore the possible contribution of central vs. peripheral processes to vibrotactile adaptation. Three experiments were conducted. In the first, adaptation was induced with mechanical vibration of the fingertip (51- or 251-Hz vibration delivered for 8 min, at 40× detection threshold). In the second, we attempted to induce adaptation with transcutaneous electrical stimulation of the median nerve (51- or 251-Hz constant-current pulses delivered for 8 min, at 1.5× detection threshold). Vibrotactile detection thresholds were measured before and after adaptation. Mechanical stimulation induced a clear increase of vibrotactile detection thresholds. In contrast, thresholds were unaffected by electrical stimulation. In the third experiment, we assessed the effect of mechanical adaptation on the detection thresholds to transcutaneous electrical nerve stimuli, measured before and after adaptation. Electrical detection thresholds were unaffected by the mechanical adaptation. Taken together, our results suggest that vibrotactile adaptation is predominantly the consequence of peripheral mechanoreceptor processes and/or changes in biomechanical properties of the skin.

The role of vibration in tactile speed perception

The relative motion between the surface of an object and our fingers produces patterns of skin deformation such as stretch, indentation, and vibrations. In this study, we hypothesized that motion-induced vibrations are combined with other tactile cues for the discrimination of tactile speed. Specifically, we hypothesized that vibrations provide a critical cue to tactile speed on surfaces lacking individually detectable features like dots or ridges. Thus masking vibrations unrelated to slip motion should impair the discriminability of tactile speed, and the effect should be surface-dependent. To test this hypothesis, we measured the precision of participants in discriminating the speed of moving surfaces having either a fine or a ridged texture, while adding masking vibratory noise in the working range of the fast-adapting mechanoreceptive afferents. Vibratory noise significantly reduced the precision of speed discrimination, and the effect was much stronger on the fine-textured than on the ridged surface. On both surfaces, masking vibrations at intermediate frequencies of 64 Hz (65-μm peak-to-peak amplitude) and 128 Hz (10 μm) had the strongest effect, followed by high-frequency vibrations of 256 Hz (1 μm) and low-frequency vibrations of 32 Hz (50 and 25 μm). These results are consistent with our hypothesis that slip-induced vibrations concur to the discrimination of tactile speed.

Tactile cues significantly modulate the perception of sweat-induced skin wetness independently of the level of physical skin wetness

Humans sense the wetness of a wet surface through the somatosensory integration of thermal and tactile inputs generated by the interaction between skin and moisture. However, little is known on how wetness is sensed when moisture is produced via sweating. We tested the hypothesis that, in the absence of skin cooling, intermittent tactile cues, as coded by low-threshold skin mechanoreceptors, modulate the perception of sweat-induced skin wetness, independently of the level of physical wetness. Ten males (22 yr old) performed an incremental exercise protocol during two trials designed to induce the same physical skin wetness but to induce lower (TIGHT-FIT) and higher (LOOSE-FIT) wetness perception. In the TIGHT-FIT, a tight-fitting clothing ensemble limited intermittent skin-sweat-clothing tactile interactions. In the LOOSE-FIT, a loose-fitting ensemble allowed free skin-sweat-clothing interactions. Heart rate, core and skin temperature, galvanic skin conductance (GSC), and physical (w(body)) and perceived skin wetness were recorded. Exercise-induced sweat production and physical wetness increased significantly [GSC: 3.1 μS, SD 0.3 to 18.8 μS, SD 1.3, P < 0.01; w(body): 0.26 no-dimension units (nd), SD 0.02, to 0.92 nd, SD 0.01, P < 0.01], with no differences between TIGHT-FIT and LOOSE-FIT (P > 0.05). However, the limited intermittent tactile inputs generated by the TIGHT-FIT ensemble reduced significantly whole-body and regional wetness perception (P < 0.01). This reduction was more pronounced when between 40 and 80% of the body was covered in sweat. We conclude that the central integration of intermittent mechanical interactions between skin, sweat, and clothing, as coded by low-threshold skin mechanoreceptors, significantly contributes to the ability to sense sweat-induced skin wetness.

Multimodal Interactions between Proprioceptive and Cutaneous Signals in Primary Somatosensory Cortex

The classical view of somatosensory processing holds that proprioceptive and cutaneous inputs are conveyed to cortex through segregated channels, initially synapsing in modality-specific areas 3a (proprioception) and 3b (cutaneous) of primary somatosensory cortex (SI). These areas relay their signals to areas 1 and 2 where multimodal convergence first emerges. However, proprioceptive and cutaneous maps have traditionally been characterized using unreliable stimulation tools. Here, we employed a mechanical stimulator that reliably positioned animals' hands in different postures and presented tactile stimuli with superb precision. Single-unit recordings in SI revealed that most neurons responded to cutaneous and proprioceptive stimuli, including cells in areas 3a and 3b. Multimodal responses were characterized by linear and nonlinear effects that emerged during early (∼20 ms) and latter (> 100 ms) stages of stimulus processing, respectively. These data are incompatible with the modality specificity model in SI, and provide evidence for distinct mechanisms of multimodal processing in the somatosensory system.

Hand-in-hand advances in biomedical engineering and sensorimotor restoration

BACKGROUND

Living in a multisensory world entails the continuous sensory processing of environmental information in order to enact appropriate motor routines. The interaction between our body and our brain is the crucial factor for achieving such sensorimotor integration ability. Several clinical conditions dramatically affect the constant body-brain exchange, but the latest developments in biomedical engineering provide promising solutions for overcoming this communication breakdown.

NEW METHOD

The ultimate technological developments succeeded in transforming neuronal electrical activity into computational input for robotic devices, giving birth to the era of the so-called brain-machine interfaces. Combining rehabilitation robotics and experimental neuroscience the rise of brain-machine interfaces into clinical protocols provided the technological solution for bypassing the neural disconnection and restore sensorimotor function.

RESULTS

Based on these advances, the recovery of sensorimotor functionality is progressively becoming a concrete reality. However, despite the success of several recent techniques, some open issues still need to be addressed.

COMPARISON WITH EXISTING METHOD(S)

Typical interventions for sensorimotor deficits include pharmaceutical treatments and manual/robotic assistance in passive movements. These procedures achieve symptoms relief but their applicability to more severe disconnection pathologies is limited (e.g. spinal cord injury or amputation).

CONCLUSIONS

Here we review how state-of-the-art solutions in biomedical engineering are continuously increasing expectances in sensorimotor rehabilitation, as well as the current challenges especially with regards to the translation of the signals from brain-machine interfaces into sensory feedback and the incorporation of brain-machine interfaces into daily activities.

Human skin wetness perception: psychophysical and neurophysiological bases

The ability to perceive thermal changes in the surrounding environment is critical for survival. However, sensing temperature is not the only factor among the cutaneous sensations to contribute to thermoregulatory responses in humans. Sensing skin wetness (i.e. hygrosensation) is also critical both for behavioral and autonomic adaptations. Although much has been done to define the biophysical role of skin wetness in contributing to thermal homeostasis, little is known on the neurophysiological mechanisms underpinning the ability to sense skin wetness. Humans are not provided with skin humidity receptors (i.e., hygroreceptors) and psychophysical studies have identified potential sensory cues (i.e. thermal and mechanosensory) which could contribute to sensing wetness. Recently, a neurophysiological model of human wetness sensitivity has been developed. In helping clarifying the peripheral and central neural mechanisms involved in sensing skin wetness, this model has provided evidence for the existence of a specific human hygrosensation strategy, which is underpinned by perceptual learning via sensory experience. Remarkably, this strategy seems to be shared by other hygroreceptor-lacking animals. However, questions remain on whether these sensory mechanisms are underpinned by specific neuromolecular pathways in humans. Although the first study on human wetness perception dates back to more than 100 years, it is surprising that the neurophysiological bases of such an important sensory feature have only recently started to be unveiled. Hence, to provide an overview of the current knowledge on human hygrosensation, along with potential directions for future research, this review will examine the psychophysical and neurophysiological bases of human skin wetness perception.

The vision of Hsiao on somatosensation

The goal of this review is to start to consolidate and distill the substantial body of research that comprises the published work of the late Professor Steven S. Hsiao. The studies of Hsiao began by demonstrating the receptive field properties of somatosensory neurons, progressed to describing cortical feature selectivity, and then eventually elevated the field to hopes of tapping into natural neural codes with artificial somatosensory feedback. With ongoing analogies to contemporaneous studies in visual neuroscience, the research results and writings of Hsiao have provided the fields of haptics and somatosensory neurophysiology with the conceptual tools needed to allow profound progress. Specifically, Hsiao suggested that slowly adapting tactile form perception could be restored with cortical microstimulation, rapidly adapting slip reflexes should be relegated to low-level, hard-wired prosthetic components, and Pacinian-corpuscle spatiotemporal population responses could potentially be decoded/encoded to provide information about interactions of hands and hand-held instruments with external objects. Future studies will be guided by these insightful reports from Hsiao.