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

Does Multi-Actuator Vibrotactile Feedback Within Tangible Objects Enrich VR Manipulation?

Rich, informative and realistic haptic feedback is key to enhancing Virtual Reality (VR) manipulation. Tangible objects provide convincing grasping and manipulation interactions with haptic feedback of e.g., shape, mass and texture properties. But these properties are static, and cannot respond to interactions in the virtual environment. On the other hand, vibrotactile feedback provides the opportunity for delivering dynamic cues rendering many different contact properties, such as impacts, object vibrations or textures. Handheld objects or controllers in VR are usually restricted to vibrating in a monolithic fashion. In this article, we investigate how spatialiazing vibrotactile cues within handheld tangibles could enable a wider range of sensations and interactions. We conduct a set of perception studies, investigating the extent to which spatialization of vibrotactile feedback within tangible objects is possible as well as the benefits of proposed rendering schemes leveraging multiple actuators in VR. Results show that vibrotactile cues from localized actuators can be discriminated and are beneficial for certain rendering schemes.

Sensory integration for neuroprostheses: from functional benefits to neural correlates

In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation-elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.

Encoding contact size using static and dynamic electrotactile finger stimulation: natural decoding vs. trained cues

Electrotactile stimulation through matrix electrodes is a promising technology to restore high-resolution tactile feedback in extended reality applications. One of the fundamental tactile effects that should be simulated is the change in the size of the contact between the finger and a virtual object. The present study investigated how participants perceive the increase of stimulation area when stimulating the index finger using static or dynamic (moving) stimuli produced by activating 1 to 6 electrode pads. To assess the ability to interpret the stimulation from the natural cues (natural decoding), without any prior training, the participants were instructed to draw the size of the stimulated area and identify the size difference when comparing two consecutive stimulations. To investigate if other "non-natural" cues can improve the size estimation, the participants were asked to enumerate the number of active pads following a training protocol. The results demonstrated that participants could perceive the change in size without prior training (e.g., the estimated area correlated with the stimulated area, p < 0.001; ≥ two-pad difference recognized with > 80% success rate). However, natural decoding was also challenging, as the response area changed gradually and sometimes in complex patterns when increasing the number of active pads (e.g., four extra pads needed for the statistically significant difference). Nevertheless, by training the participants to utilize additional cues the limitations of natural perception could be compensated. After the training, the mismatch in the activated and estimated number of pads was less than one pad regardless of the stimulus size. Finally, introducing the movement of the stimulus substantially improved discrimination (e.g., 100% median success rate to recognize ≥ one-pad difference). The present study, therefore, provides insights into stimulation size perception, and practical guidelines on how to modulate pad activation to change the perceived size in static and dynamic scenarios.

The auditory midbrain mediates tactile vibration sensing

Vibrations are ubiquitous in nature, shaping behavior across the animal kingdom. For mammals, mechanical vibrations acting on the body are detected by mechanoreceptors of the skin and deep tissues and processed by the somatosensory system, while sound waves traveling through air are captured by the cochlea and encoded in the auditory system. Here, we report that mechanical vibrations detected by the body's Pacinian corpuscle neurons, which are unique in their ability to entrain to high frequency (40-1000 Hz) environmental vibrations, are prominently encoded by neurons in the lateral cortex of the inferior colliculus (LCIC) of the midbrain. Remarkably, most LCIC neurons receive convergent Pacinian and auditory input and respond more strongly to coincident tactile-auditory stimulation than to either modality alone. Moreover, the LCIC is required for behavioral responses to high frequency mechanical vibrations. Thus, environmental vibrations captured by Pacinian corpuscles are encoded in the auditory midbrain to mediate behavior.

Biomimetic computer-to-brain communication enhancing naturalistic touch sensations via peripheral nerve stimulation

Artificial communication with the brain through peripheral nerve stimulation shows promising results in individuals with sensorimotor deficits. However, these efforts lack an intuitive and natural sensory experience. In this study, we design and test a biomimetic neurostimulation framework inspired by nature, capable of "writing" physiologically plausible information back into the peripheral nervous system. Starting from an in-silico model of mechanoreceptors, we develop biomimetic stimulation policies. We then experimentally assess them alongside mechanical touch and common linear neuromodulations. Neural responses resulting from biomimetic neuromodulation are consistently transmitted towards dorsal root ganglion and spinal cord of cats, and their spatio-temporal neural dynamics resemble those naturally induced. We implement these paradigms within the bionic device and test it with patients (ClinicalTrials.gov identifier NCT03350061). He we report that biomimetic neurostimulation improves mobility (primary outcome) and reduces mental effort (secondary outcome) compared to traditional approaches. The outcomes of this neuroscience-driven technology, inspired by the human body, may serve as a model for advancing assistive neurotechnologies.

Neuromorphic hardware for somatosensory neuroprostheses

In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies.

The neural basis of somatosensory temporal discrimination threshold as a paradigm for time processing in the sub-second range: An updated review

BACKGROUND AND OBJECTIVE

The temporal aspect of somesthesia is a feature of any somatosensory process and a pre-requisite for the elaboration of proper behavior. Time processing in the milliseconds range is crucial for most of behaviors in everyday life. The somatosensory temporal discrimination threshold (STDT) is the ability to perceive two successive stimuli as separate in time, and deals with time processing in this temporal range. Herein, we focus on the physiology of STDT, on a background of the anatomophysiology of somesthesia and the neurobiological substrates of timing.

METHODS

A review of the literature through PubMed & Cochrane databases until March 2023 was performed with inclusion and exclusion criteria following PRISMA recommendations.

RESULTS

1151 abstracts were identified. 4 duplicate records were discarded before screening. 957 abstracts were excluded because of redundancy, less relevant content or not English-written. 4 were added after revision. Eventually, 194 articles were included.

CONCLUSIONS

STDT encoding relies on intracortical inhibitory S1 function and is modulated by the basal ganglia-thalamic-cortical interplay through circuits involving the nigrostriatal dopaminergic pathway and probably the superior colliculus.

Revisiting a classical theory of sensory specificity: assessing consistency and stability of thermosensitive spots

Thermal sensitivity is not uniform across the skin, and is particularly high in small (∼1 mm2) regions termed "thermosensitive spots." These spots are thought to reflect the anatomical location of specialized thermosensitive nerve endings from single primary afferents. Thermosensitive spots provide foundational support for "labeled line" or specificity theory of sensory perception, which states that different sensory qualities are transmitted by separate and specific neural pathways. This theory predicts a highly stable relation between repetitions of a thermal stimulus and the resulting sensory quality, yet these predictions have rarely been tested systematically. Here, we present the qualitative, spatial, and repeatability properties of 334 thermosensitive spots on the dorsal forearm sampled across four separate sessions. In line with previous literature, we found that spots associated with cold sensations (112 cold spots, 34%) were more frequent than spots associated with warm sensations (41 warm spots, 12%). Still more frequent (165 spots, 49%) were spots that elicited inconsistent sensations when repeatedly stimulated by the same temperature. Remarkably, only 13 spots (4%) conserved their position between sessions. Overall, we show unexpected inconsistency of both the perceptual responses elicited by spot stimulation and of spot locations across time. These observations suggest reappraisals of the traditional view that thermosensitive spots reflect the location of individual thermosensitive, unimodal primary afferents serving as specific labeled lines for corresponding sensory qualities.NEW & NOTEWORTHY Thermosensitive spots are clustered rather than randomly distributed and have the highest density near the wrist. Surprisingly, we found that thermosensitive spots elicit inconsistent sensory qualities and are unstable over time. Our results question the widely believed notion that thermosensitive spots reflect the location of individual thermoreceptive, unimodal primary afferents that serve as labelled lines for corresponding sensory qualities.

Coding of self and environment by Pacinian neurons in freely moving animals

Pacinian corpuscle neurons are specialized low-threshold mechanoreceptors (LTMRs) that are tuned to detect high-frequency vibration (~40-2000 Hz), however it is unclear how Pacinians and other LTMRs encode mechanical forces encountered during naturalistic behavior. Here, we developed methods to record LTMRs in awake, freely moving mice. We find that Pacinians, but not other LTMRs, encode subtle vibrations of surfaces encountered by the animal, including low-amplitude vibrations initiated over two meters away. Strikingly, Pacinians are also highly active during a wide variety of natural behaviors, including walking, grooming, digging, and climbing. Pacinians in the hindlimb are sensitive enough to be activated by forelimb- or upper-body-dominant behaviors. Finally, we find that Pacinian LTMRs have diverse tuning and sensitivity. Our findings suggest a Pacinian population code for the representation of vibro-tactile features generated by self-initiated movements and low-amplitude environmental vibrations emanating from distant locations.

Effects of skin moisturization on various aspects of touch showing differences with age and skin site

The human body is encompassed by a thin layer of tissue, the skin, which is heterogenous and highly specialized to protect the body and encode interactions with the external world. There is a fundamental scientific drive to understand its function, coupled with the need to preserve skin as we age, which impacts on our physiological and psychological well-being. In the present study, we aimed to define differences in touch perception between age groups and with skin cream application. We investigated touch on the finger, the forearm and cheek in younger (20-28 years, n = 22) and older (65-75 years, n = 22) females. We measured skin hydration, touch detection, finger spatial discrimination, forearm tactile pleasantness together with electrodermal activity, and perceptual ratings about cream use, skin dryness, and cosmetic habits. Glabrous finger skin became drier and touch performance was impaired with age, but these aspects were preserved in hairy skin. Skin moisturization immediately increased hydration levels, but did not significantly change touch perception. We also found that touch appreciation increased with age. We conclude that reduced finger capacity may impact self-evaluation of the skin and that long-term skin care strategies should focus on hydrating the hand to preserve touch capacities.

Movement-related tactile gating in blindness

When we perform an action, self-elicited movement induces suppression of somatosensory information to the cortex, requiring a correct motor-sensory and inter-sensory (i.e. cutaneous senses, kinesthesia, and proprioception) integration processes to be successful. However, recent works show that blindness might impact some of these elements. The current study investigates the effect of movement on tactile perception and the role of vision in this process. We measured the velocity discrimination threshold in 18 sighted and 18 blind individuals by having them perceive a sequence of two movements and discriminate the faster one in passive and active touch conditions. Participants' Just Noticeable Difference (JND) was measured to quantify their precision. Results showed a generally worse performance during the active touch condition compared to the passive. In particular, this difference was significant in the blind group, regardless of the blindness duration, but not in the sighted one. These findings suggest that the absence of visual calibration impacts motor-sensory and inter-sensory integration required during movement, diminishing the reliability of tactile signals in blind individuals. Our work spotlights the need for intervention in this population and should be considered in the sensory substitution/reinforcement device design.

Sensory neuron activation from topical treatments modulates the sensorial perception of human skin

Neural signaling of skin sensory perception from topical treatments is often reported in subjective terms such as a sensation of skin "tightness" after using a cleanser or "softness" after applying a moisturizer. However, the mechanism whereby cutaneous mechanoreceptors and corresponding sensory neurons are activated giving rise to these perceptions has not been established. Here, we provide a quantitative approach that couples in vitro biomechanical testing and detailed computational neural stimulation modeling along with a comprehensive in vivo self-assessment survey to demonstrate how cutaneous biomechanical changes in response to treatments are involved in the sensorial perception of the human skin. Strong correlations are identified between reported perception up to 12 hours post treatment and changes in the computed neural stimulation from mechanoreceptors residing deep under the skin surface. The study reveals a quantitative framework for understanding the biomechanical neural activation mechanism and the subjective perception by individuals.

Toward a formal theory for computing machines made out of whatever physics offers

Approaching limitations of digital computing technologies have spurred research in neuromorphic and other unconventional approaches to computing. Here we argue that if we want to engineer unconventional computing systems in a systematic way, we need guidance from a formal theory that is different from the classical symbolic-algorithmic Turing machine theory. We propose a general strategy for developing such a theory, and within that general view, a specific approach that we call fluent computing. In contrast to Turing, who modeled computing processes from a top-down perspective as symbolic reasoning, we adopt the scientific paradigm of physics and model physical computing systems bottom-up by formalizing what can ultimately be measured in a physical computing system. This leads to an understanding of computing as the structuring of processes, while classical models of computing systems describe the processing of structures.

Sensory weighting of position and force feedback during pinching

Human hands are complex biomechanical systems that allow for dexterous tasks with many degrees of freedom. Coordination of the fingers is essential for many activities of daily living and involves integrating sensory signals. During this sensory integration, the central nervous system deals with the uncertainty of sensory signals. When handling compliant objects, force and position are related. Interactions with stiff objects result in reduced position changes and increased force changes compared to compliant objects. Literature has shown sensory integration of force and position at the shoulder. Nevertheless, differences in sensory requirements between proximal and distal joints may lead to different proprioceptive representations, hence findings at proximal joints cannot be directly transferred to distal joints, such as the digits. Here, we investigate the sensory integration of force and position during pinching. A haptic manipulator rendered a virtual spring with adjustable stiffness between the index finger and the thumb. Participants had to blindly reproduce a force against the spring. In both visual reference trials and blind reproduction trials, the relation between pinch force and spring compression was constant. However, by covertly changing the spring characteristics in catch trials into an adjusted force-position relation, the participants' weighting of force and position could be revealed. In agreement with previous studies on the shoulder, participants relied more on force sense in trials with higher stiffness. This study demonstrated stiffness-dependent sensory integration of force and position feedback during pinching.

Revealing the Meissner Corpuscles in Human Glabrous Skin Using In Vivo Non-Invasive Imaging Techniques

The presence of mechanoreceptors in glabrous skin allows humans to discriminate textures by touch. The amount and distribution of these receptors defines our tactile sensitivity and can be affected by diseases such as diabetes, HIV-related pathologies, and hereditary neuropathies. The quantification of mechanoreceptors as clinical markers by biopsy is an invasive method of diagnosis. We report the localization and quantification of Meissner corpuscles in glabrous skin using in vivo, non-invasive optical microscopy techniques. Our approach is supported by the discovery of epidermal protrusions which are co-localized with Meissner corpuscles. Index fingers, small fingers, and tenar palm regions of ten participants were imaged by optical coherence tomography (OCT) and laser scan microscopy (LSM) to determine the thickness of the stratum corneum and epidermis and to count the Meissner corpuscles. We discovered that regions containing Meissner corpuscles could be easily identified by LSM with an enhanced optical reflectance above the corpuscles, caused by a protrusion of the strongly reflecting epidermis into the stratum corneum with its weak reflectance. We suggest that this local morphology above Meissner corpuscles has a function in tactile perception.

Synchrony-Division Neural Multiplexing: An Encoding Model

Cortical neurons receive mixed information from the collective spiking activities of primary sensory neurons in response to a sensory stimulus. A recent study demonstrated an abrupt increase or decrease in stimulus intensity and the stimulus intensity itself can be respectively represented by the synchronous and asynchronous spikes of S1 neurons in rats. This evidence capitalized on the ability of an ensemble of homogeneous neurons to multiplex, a coding strategy that was referred to as synchrony-division multiplexing (SDM). Although neural multiplexing can be conceived by distinct functions of individual neurons in a heterogeneous neural ensemble, the extent to which nearly identical neurons in a homogeneous neural ensemble encode multiple features of a mixed stimulus remains unknown. Here, we present a computational framework to provide a system-level understanding on how an ensemble of homogeneous neurons enable SDM. First, we simulate SDM with an ensemble of homogeneous conductance-based model neurons receiving a mixed stimulus comprising slow and fast features. Using feature-estimation techniques, we show that both features of the stimulus can be inferred from the generated spikes. Second, we utilize linear nonlinear (LNL) cascade models and calculate temporal filters and static nonlinearities of differentially synchronized spikes. We demonstrate that these filters and nonlinearities are distinct for synchronous and asynchronous spikes. Finally, we develop an augmented LNL cascade model as an encoding model for the SDM by combining individual LNLs calculated for each type of spike. The augmented LNL model reveals that a homogeneous neural ensemble model can perform two different functions, namely, temporal- and rate-coding, simultaneously.

Skin properties and afferent density in the deterioration of tactile spatial acuity with age

Tactile sensitivity is affected by age, as shown by the deterioration of spatial acuity assessed with the two-point discrimination task. This is assumed to be partly a result of age-related changes of the peripheral somatosensory system. In particular, in the elderly, the density of mechanoreceptive afferents decreases with age and the skin tends to become drier, less elastic and less stiff. To assess to what degree mechanoreceptor density, skin hydration, elasticity and stiffness can account for the deterioration of tactile spatial sensitivity observed in the elderly, several approaches were combined, including psychophysics, measurements of finger properties, modelling and simulation of the response of first-order tactile neurons. Psychophysics confirmed that the Elderly group has lower tactile acuity than the Young group. Correlation and commonality analysis showed that age was the most important factor in explaining decreases in behavioural performance. Biological elasticity, hydration and finger pad area were also involved. These results were consistent with the outcome of simulations showing that lower afferent density and lower Young's modulus (i.e. lower stiffness) negatively affected the tactile encoding of stimulus information. Simulations revealed that these changes resulted in a lower build-up of task-relevant stimulus information. Importantly, the reduction in discrimination performance with age in the simulation was less than that observed in the psychophysical testing, indicating that there are additional peripheral as well as central factors responsible for age-related changes in tactile discrimination. KEY POINTS: Ageing effects on tactile perception involve the deterioration of spatial sensitivity, although the contribution of central and peripheral factors is not clear. We combined psychophysics, measurements of finger properties, modelling and simulation of the response of first-order tactile neurons to investigate to what extent skin elasticity, stiffness, hydration, finger pad area and afferent density can account for the lower spatial sensitivity observed in the elderly. Correlation and commonality analysis revealed that age was the most important factor to predict behavioural performance. Skin biological elasticity, hydration and finger pad area contributed to a lesser extent. The simulation of first-order tactile neuron responses indicated that reduction in afferent density plays a major role in the deterioration of tactile spatial acuity. Simulations also showed that lower skin stiffness and lower afferent density affect the build-up of stimulus information and the response of SA1 (i.e. type 1 slowly adapting fibres) and RA1 (i.e. type 1 rapidly adapting fibres) afferent fibres.

Non-rectangular neurostimulation waveforms elicit varied sensation quality and perceptive fields on the hand

Electrical stimulation of the nerves is known to elicit distinct sensations perceived in distal parts of the body. The stimulation is typically modulated in current with charge-balanced rectangular shapes that, although easily generated by stimulators available on the market, are not able to cover the entire range of somatosensory experiences from daily life. In this regard, we have investigated the effect of electrical neurostimulation with four non-rectangular waveforms in an experiment involving 11 healthy able-bodied subjects. Weiss curves were estimated and rheobase and chronaxie values were obtained showing increases in stimulation time required to elicit sensations for some waveforms. The localization of the sensations reported in the hand also appeared to differ between waveforms, although the total area did not vary significantly. Finally, the possibility of distinguishing different charge- and amplitude-matched stimuli was demonstrated through a two-alternative-forced-choice (2AFC) match-to-sample task, showing the ability of participants to successfully distinguish between waveforms with similar electrical characteristics but different shapes and charge transfer rates. This study provides evidence that, by using different waveforms to stimulate nerves, it is possible to affect not only the required charge to elicit sensations but also the sensation quality and its localization.

Bayesian prediction of psychophysical detection responses from spike activity in the rat sensorimotor cortex

Decoding of sensorimotor information is essential for brain-computer interfaces (BCIs) as well as in normal functioning organisms. In this study, Bayesian models were developed for the prediction of binary decisions of 10 awake freely-moving male/female rats based on neural activity in a vibrotactile yes/no detection task. The vibrotactile stimuli were 40-Hz sinusoidal displacements (amplitude: 200 µm, duration: 0.5 s) applied on the glabrous skin. The task was to depress the right lever for stimulus detection and left lever for stimulus-off condition. Spike activity was recorded from 16-channel microwire arrays implanted in the hindlimb representation of primary somatosensory cortex (S1), overlapping also with the associated representation in the primary motor cortex (M1). Single-/multi-unit average spike rate (R_d) within the stimulus analysis window was used as the predictor of the stimulus state and the behavioral response at each trial based on a Bayesian network model. Due to high neural and psychophysical response variability for each rat and also across subjects, mean R_d was not correlated with hit and false alarm rates. Despite the fluctuations in the neural data, the Bayesian model for each rat generated moderately good accuracy (0.60-0.90) and good class prediction scores (recall, precision, F1) and was also tested with subsets of data (e.g. regular vs. fast spike groups). It was generally observed that the models were better for rats with lower psychophysical performance (lower sensitivity index A'). This suggests that Bayesian inference and similar machine learning techniques may be especially helpful during the training phase of BCIs or for rehabilitation with neuroprostheses.

Population coding strategies in human tactile afferents

Sensory information is conveyed by populations of neurons, and coding strategies cannot always be deduced when considering individual neurons. Moreover, information coding depends on the number of neurons available and on the composition of the population when multiple classes with different response properties are available. Here, we study population coding in human tactile afferents by employing a recently developed simulator of mechanoreceptor firing activity. First, we highlight the interplay of afferents within each class. We demonstrate that the optimal afferent density to convey maximal information depends on both the tactile feature under consideration and the afferent class. Second, we find that information is spread across different classes for all tactile features and that each class encodes both redundant and complementary information with respect to the other afferent classes. Specifically, combining information from multiple afferent classes improves information transmission and is often more efficient than increasing the density of afferents from the same class. Finally, we examine the importance of temporal and spatial contributions, respectively, to the joint spatiotemporal code. On average, destroying temporal information is more destructive than removing spatial information, but the importance of either depends on the stimulus feature analysed. Overall, our results suggest that both optimal afferent innervation densities and the composition of the population depend in complex ways on the tactile features in question, potentially accounting for the variety in which tactile peripheral populations are assembled in different regions across the body.

The sensory ecology of primate food perception, revisited

Twenty years ago, Dominy and colleagues published "The sensory ecology of primate food perception," an impactful review that brought new perspectives to understanding primate foraging adaptations. Their review synthesized information on primate senses and explored how senses informed feeding behavior. Research on primate sensory ecology has seen explosive growth in the last two decades. Here, we revisit this important topic, focusing on the numerous new discoveries and lines of innovative research. We begin by reviewing each of the five traditionally recognized senses involved in foraging: audition, olfaction, vision, touch, and taste. For each sense, we provide an overview of sensory function and comparative ecology, comment on the state of knowledge at the time of the original review, and highlight advancements and lingering gaps in knowledge. Next, we provide an outline for creative, multidisciplinary, and innovative future research programs that we anticipate will generate exciting new discoveries in the next two decades.

The encoding of touch by somatotopically aligned dorsal column subdivisions

The somatosensory system decodes a range of tactile stimuli to generate a coherent sense of touch. Discriminative touch of the body depends on signals conveyed from peripheral mechanoreceptors to the brain through the spinal cord dorsal column and its brainstem target, the dorsal column nuclei (DCN)1,2. Models of somatosensation emphasize that fast-conducting low-threshold mechanoreceptors (LTMRs) innervating the skin drive the DCN3,4. However, postsynaptic dorsal column (PSDC) neurons within the spinal cord dorsal horn also collect mechanoreceptor signals and form a second major input to the DCN5-7. The significance of PSDC neurons and their contributions to the coding of touch have remained unclear since their discovery. Here we show that direct LTMR input to the DCN conveys vibrotactile stimuli with high temporal precision. Conversely, PSDC neurons primarily encode touch onset and the intensity of sustained contact into the high-force range. LTMR and PSDC signals topographically realign in the DCN to preserve precise spatial detail. Different DCN neuron subtypes have specialized responses that are generated by distinct combinations of LTMR and PSDC inputs. Thus, LTMR and PSDC subdivisions of the dorsal column encode different tactile features and differentially converge in the DCN to generate specific ascending sensory processing streams.

Coexisting neuronal coding strategies in the barrel cortex

During tactile sensation by rodents, whisker movements across surfaces generate complex whisker motions, including discrete, transient stick-slip events, which carry information about surface properties. The characteristics of these events and how the brain encodes this tactile information remain enigmatic. We found that cortical neurons show a mixture of synchronized and nontemporally correlated spikes in their tactile responses. Synchronous spikes convey the magnitude of stick-slip events by numerous aspects of temporal coding. These spikes show preferential selectivity for kinetic and kinematic whisker motion. By contrast, asynchronous spikes in each neuron convey the magnitude of stick-slip events by their discharge rates, response probability, and interspike intervals. We further show that the differentiation between these two types of activity is highly dependent on the magnitude of stick-slip events and stimulus and response history. These results suggest that cortical neurons transmit multiple components of tactile information through numerous coding strategies.

Peripheral neurostimulation for encoding artificial somatosensations

The direct neural stimulation of peripheral or central nervous systems has been shown as an effective tool to treat neurological conditions. The electrical activation of the nervous sensory pathway can be adopted to restore the artificial sense of touch and proprioception in people suffering from sensory-motor disorders. The modulation of the neural stimulation parameters has a direct effect on the electrically induced sensations, both when targeting the somatosensory cortex and the peripheral somatic nerves. The properties of the artificial sensations perceived, as their location, quality and intensity are strongly dependent on the direct modulation of pulse width, amplitude and frequency of the neural stimulation. Different sensory encoding schemes have been tested in patients showing distinct effects and outcomes according to their impact on the neural activation. Here, I reported the most adopted neural stimulation strategies to artificially encode somatosensation into the peripheral nervous system. The real-time implementation of these strategies in bionic devices is crucial to exploit the artificial sensory feedback in prosthetics. Thus, neural stimulation becomes a tool to directly communicate with the human nervous system. Given the importance of adding artificial sensory information to neuroprosthetic devices to improve their control and functionality, the choice of an optimal neural stimulation paradigm could increase the impact of prosthetic devices on the quality of life of people with sensorimotor disabilities.

Closed-loop stimulation of lateral cervical spinal cord in upper-limb amputees to enable sensory discrimination: a case study

Modern myoelectric prosthetic hands have multiple independently controllable degrees of freedom, but require constant visual attention to use effectively. Somatosensory feedback provides information not available through vision alone and is essential for fine motor control of our limbs. Similarly, stimulation of the nervous system can potentially provide artificial somatosensory feedback to reduce the reliance on visual cues to efficiently operate prosthetic devices. We have shown previously that epidural stimulation of the lateral cervical spinal cord can evoke tactile sensations perceived as emanating from the missing arm and hand in people with upper-limb amputation. In this case study, two subjects with upper-limb amputation used this somatotopically-matched tactile feedback to discriminate object size and compliance while controlling a prosthetic hand. With less than 30 min of practice each day, both subjects were able to use artificial somatosensory feedback to perform a subset of the discrimination tasks at a success level well above chance. Subject 1 was consistently more adept at determining object size (74% accuracy; chance: 33%) while Subject 2 achieved a higher accuracy level in determining object compliance (60% accuracy; chance 33%). In each subject, discrimination of the other object property was only slightly above or at chance level suggesting that the task design and stimulation encoding scheme are important determinants of which object property could be reliably identified. Our observations suggest that changes in the intensity of artificial somatosensory feedback provided via spinal cord stimulation can be readily used to infer information about object properties with minimal training.

The neural basis of tactile texture perception

Running our fingers across a textured surface gives rise to two types of skin deformations, each transduced by different tactile nerve fibers. Coarse features produce large-scale skin deformations whose spatial configuration is reflected in the spatial pattern of activation of some tactile fibers. Scanning a finely textured surface elicits vibrations in the skin, which in turn evoked temporally patterned responses in other fibers. These two neural codes-spatial and temporal-drive a spectrum of neural response properties in somatosensory cortex: At one extreme, neurons are sensitive to spatial patterns and encode coarse features; at the other extreme, neurons are sensitive to vibrations and encode fine features. While the texture responses of nerve fibers are dependent on scanning speed, those of cortical neurons are less so, giving rise to a speed invariant texture percept. Neurons in high-level somatosensory cortices combine information about texture with information about task variables.

The evaluation of tactile dysfunction in the hand in type 1 diabetes: a novel method based on haptics

AIMS

We present an innovative method based on haptics for the evaluation of the sense of touch in the hand, in people affected by type 1 diabetes.

METHODS

Forty individuals affected by diabetes and 20 healthy controls took part in the study; the diabetes group was further divided into two subgroups based on vibration sensitivity in the lower limb. By means of a novel haptic device, tactile sensitivity in the fingertip was measured as the ability of the participants to discriminate slip motion speed.

RESULTS

Tactile sensitivity was significantly lower in individuals affected by diabetes as compared to controls. Depending on the subgroup, the difference from the controls was equal to 0.11 (95% CI from 0.029 to 0.186) and to 0.267 (95% CI from 0.198 to 0.336). Within the diabetes group, tactile sensitivity correlated with vibration sensitivity in the upper (p = 0.001) and lower limb (p = 0.003). A significant relationship between nerve conduction parameters and tactile sensitivity was found (p = 0.03). Finally, we combined the different predictors (clinical, vibratory and electroneurography data) by using cluster analysis; tactile sensitivity was found to be significantly different between different clusters (p = 0.004).

CONCLUSIONS

Early signs of tactile dysfunction in the hand were found in individuals affected by diabetes, even in absence of diabetic neuropathy. The protocol presented in this study is a promising tool for the assessment of tactile dysfunction in the hand in people affected by type 1 diabetes.

Beyond language: The unspoken sensory-motor representation of the tongue in non-primates, non-human and human primates

The English idiom "on the tip of my tongue" commonly acknowledges that something is known, but it cannot be immediately brought to mind. This phrase accurately describes sensorimotor functions of the tongue, which are fundamental for many tongue-related behaviors (e.g., speech), but often neglected by scientific research. Here, we review a wide range of studies conducted on non-primates, non-human and human primates with the aim of providing a comprehensive description of the cortical representation of the tongue's somatosensory inputs and motor outputs across different phylogenetic domains. First, we summarize how the properties of passive non-noxious mechanical stimuli are encoded in the putative somatosensory tongue area, which has a conserved location in the ventral portion of the somatosensory cortex across mammals. Second, we review how complex self-generated actions involving the tongue are represented in more anterior regions of the putative somato-motor tongue area. Finally, we describe multisensory response properties of the primate and non-primate tongue area by also defining how the cytoarchitecture of this area is affected by experience and deafferentation.

Skin and Mechanoreceptor Contribution to Tactile Input for Perception: A Review of Simulation Models

We review four current computational models that simulate the response of mechanoreceptors in the glabrous skin to tactile stimulation. The aim is to inform researchers in psychology, sensorimotor science and robotics who may want to implement this type of quantitative model in their research. This approach proves relevant to understanding of the interaction between skin response and neural activity as it avoids some of the limitations of traditional measurement methods of tribology, for the skin, and neurophysiology, for tactile neurons. The main advantage is to afford new ways of looking at the combined effects of skin properties on the activity of a population of tactile neurons, and to examine different forms of coding by tactile neurons. Here, we provide an overview of selected models from stimulus application to neuronal spiking response, including their evaluation in terms of existing data, and their applicability in relation to human tactile perception.

Normal and tangential forces combine to convey contact pressure during dynamic tactile stimulation

Humans need to accurately process the contact forces that arise as they perform everyday haptic interactions such as sliding the fingers along a surface to feel for bumps, sticky regions, or other irregularities. Several different mechanisms are possible for how the forces on the skin could be represented and integrated in such interactions. In this study, we used a force-controlled robotic platform and simultaneous ultrasonic modulation of the finger-surface friction to independently manipulate the normal and tangential forces during passive haptic stimulation by a flat surface. To assess whether the contact pressure on their finger had briefly increased or decreased during individual trials in this broad stimulus set, participants did not rely solely on either the normal force or the tangential force. Instead, they integrated tactile cues induced by both components. Support-vector-machine analysis classified physical trial data with up to 75% accuracy and suggested a linear perceptual mechanism. In addition, the change in the amplitude of the force vector predicted participants' responses better than the change of the coefficient of dynamic friction, suggesting that intensive tactile cues are meaningful in this task. These results provide novel insights about how normal and tangential forces shape the perception of tactile contact.

Artificial SA-I, RA-I and RA-II/vibrotactile afferents for tactile sensing of texture

Robot touch can benefit from how humans perceive tactile textural information, from the stimulation mode to which tactile channels respond, then the tactile cues and encoding. Using a soft biomimetic tactile sensor (the TacTip) based on the physiology of the dermal-epidermal boundary, we construct two biomimetic tactile channels based on slowly adapting SA-I and rapidly adapting RA-I afferents, and introduce an additional sub-modality for vibrotactile information with an embedded microphone interpreted as an artificial RA-II channel. These artificial tactile channels are stimulated dynamically with a set of 13 artificial rigid textures comprising raised-bump patterns on a rotating drum that vary systematically in roughness. Methods employing spatial, spatio-temporal and temporal codes are assessed for texture classification insensitive to stimulation speed. We find: (i) spatially encoded frictional cues provide a salient representation of texture; (ii) a simple transformation of spatial tactile features to model natural afferent responses improves the temporal coding; and (iii) the harmonic structure of induced vibrations provides a pertinent code for speed-invariant texture classification. Just as human touch relies on an interplay between slowly adapting (SA-I), rapidly adapting (RA-I) and vibrotactile (RA-II) channels, this tripartite structure may be needed for future robot applications with human-like dexterity, from prosthetics to materials testing, handling and manipulation.

Texture is encoded in precise temporal spiking patterns in primate somatosensory cortex

Humans are exquisitely sensitive to the microstructure and material properties of surfaces. In the peripheral nerves, texture information is conveyed via two mechanisms: coarse textural features are encoded in spatial patterns of activation that reflect their spatial layout, and fine features are encoded in highly repeatable, texture-specific temporal spiking patterns evoked as the skin moves across the surface. Here, we examined whether this temporal code is preserved in the responses of neurons in somatosensory cortex. We scanned a diverse set of everyday textures across the fingertip of awake macaques while recording the responses evoked in individual cortical neurons. We found that temporal spiking patterns are highly repeatable across multiple presentations of the same texture, with millisecond precision. As a result, texture identity can be reliably decoded from the temporal patterns themselves, even after information carried in the spike rates is eliminated. However, the combination of rate and timing is more informative than either code in isolation. The temporal precision of the texture response is heterogenous across cortical neurons and depends on the submodality composition of their input and on their location along the somatosensory neuraxis. Furthermore, temporal spiking patterns in cortex dilate and contract with decreases and increases in scanning speed, respectively, and this systematic relationship between speed and patterning may contribute to the observed perceptual invariance to speed. Finally, we find that the quality of a texture percept can be better predicted when these temporal patterns are taken into consideration. We conclude that high-precision spike timing complements rate-based signals to encode texture in somatosensory cortex.

Neuroscientists seek to understand how neuronal signals carry information and drive perception. Here, the authors show that millisecond-level spike timing in somatosensory cortex is informative about texture and shapes the evoked sensory experience.

Frequency Shapes the Quality of Tactile Percepts Evoked through Electrical Stimulation of the Nerves

Electrical stimulation of the peripheral nerves of human participants provides a unique opportunity to study the neural determinants of perceptual quality using a causal manipulation. A major challenge in the study of neural coding of touch has been to isolate the role of spike timing-at the scale of milliseconds or tens of milliseconds-in shaping the sensory experience. In the present study, we address this question by systematically varying the pulse frequency (PF) of electrical stimulation pulse trains delivered to the peripheral nerves of seven participants with upper and lower extremity limb loss via chronically implanted neural interfaces. We find that increases in PF lead to systematic increases in perceived frequency, up to ∼50 Hz, at which point further changes in PF have little to no impact on sensory quality. Above this transition frequency, ratings of perceived frequency level off, the ability to discriminate changes in PF is abolished, and verbal descriptors selected to characterize the sensation change abruptly. We conclude that sensation quality is shaped by temporal patterns of neural activation, even if these patterns are imposed on a fixed neural population, but this temporal patterning can only be resolved up to ∼50 Hz. These findings highlight the importance of spike timing in shaping the quality of a sensation and will contribute to the development of encoding strategies for conveying touch feedback through bionic hands and feet.SIGNIFICANCE STATEMENT A major challenge in the study of neural coding of touch has been to understand how temporal patterns in neuronal responses shape the sensory experience. We address this question by varying the pulse frequency (PF) of electrical pulse trains delivered through implanted nerve interfaces in seven amputees. We concomitantly vary pulse width to separate the effect of changing PF on sensory quality from its effect on perceived magnitude. We find that increases in PF lead to increases in perceived frequency, a qualitative dimension, up to ∼50 Hz, beyond which changes in PF have little impact on quality. We conclude that temporal patterning in the neuronal response can shape quality and discuss the implications for restoring touch via neural interfaces.

Global surface features contribute to human haptic roughness estimations

Previous studies have paid special attention to the relationship between local features (e.g., raised dots) and human roughness perception. However, the relationship between global features (e.g., curved surface) and haptic roughness perception is still unclear. In the present study, a series of roughness estimation experiments was performed to investigate how global features affect human roughness perception. In each experiment, participants were asked to estimate the roughness of a series of haptic stimuli that combined local features (raised dots) and global features (sinusoidal-like curves). Experiments were designed to reveal whether global features changed their haptic roughness estimation. Furthermore, the present study tested whether the exploration method (direct, indirect, and static) changed haptic roughness estimations and examined the contribution of global features to roughness estimations. The results showed that sinusoidal-like curved surfaces with small periods were perceived to be rougher than those with large periods, while the direction of finger movement and indirect exploration did not change this phenomenon. Furthermore, the influence of global features on roughness was modulated by local features, regardless of whether raised-dot surfaces or smooth surfaces were used. Taken together, these findings suggested that an object’s global features contribute to haptic roughness perceptions, while local features change the weight of the contribution that global features make to haptic roughness perceptions.

Objective neuromodulation basis for intrafascicular artificial somatosensation through carbon nanotube yarn electrodes

BACKGROUND

Intrafascicular electrical stimulation has been extensively adopted to achieve sensory feedback for limb amputees. Axon-like carbon nanotube yarn (CNTy) electrodes with both promising flexibility and spatial selectivity index (SSI) can be fascinating alternatives to generate artificial somatosensation.

NEW METHOD

Here we systematically disclose objective neuromodulation basis for artificial somatosensation through intrafascicular CNTy electrodes. CNTy electrodes with different exposed lengths were utilized for electrically stimulating tibial nerves in twelve rats. Somatosensory evoked potentials (SEPs) were recorded synchronously using an epidural thirty-channel electrode array. Spatiotemporal characteristics of SEPs were analyzed as current pulse amplitude (PA), pulse width (PW) and pulse frequency (PF) varied.

RESULTS

The current thresholds at 1Hz exhibit the lowest means when compared with those at 4 and 8Hz for most CNTy electrodes (20/28). For all the electrodes, amplitudes of SEPs and activated areas of perceptive fields increase with PWs and PAs rising, and decrease remarkably with PFs from 1 to 8Hz. Latencies of P1 and N1 of SEP peaks gradually reduced with PWs and PAs advancing. Considering high SSIs, relatively stable current thresholds, wider variation ranges of sensory magnitudes and optimal stability of perceptive fields, the L-200 μm electrodes are preferable for neuromodulation with PFs of 1 - 8Hz, PWs of 100 - 800 μs and PAs of 2 - 64 μA.

COMPARISON WITH EXISTING METHODS

New-type CNTy electrodes possess both promising flexibility and SSI when compared with other neural interfaces. We systematically explore objective neuromodulation basis for artificial somatosensation through CNTy electrodes for the first time.

CONCLUSIONS

Significantly higher SSIs, lower current and charge thresholds exist for CNTy electrodes in comparison with other peripheral-nerve interfaces. This study can, for the first time, lay a solid neuromodulation foundation for CNTy electrodes to achieve fine sensory feedback.

Object Recognition via Evoked Sensory Feedback during Control of a Prosthetic Hand

Haptic and proprioceptive feedback is critical for sensorimotor integration when we use our hand to perform daily tasks. Here, we evaluated how externally evoked haptic and proprioceptive feedback and myoelectric control strategies affected the recognition of object properties when participants controlled a prosthetic hand. Fingertip haptic sensation was elicited using a transcutaneous nerve stimulation grid to encode the prosthetic's fingertip forces. An array of tactors elicited patterned vibratory stimuli to encode tactile-proprioceptive kinematic information of the prosthetic finger joint. Myoelectric signals of the finger flexor and extensor were used to control the position or velocity of joint angles of the prosthesis. Participants were asked to perform object property (stiffness and size) recognition, by controlling the prosthetic hand with concurrent haptic and tactile-proprioceptive feedback. With the evoked feedback, intact and amputee participants recognized the object stiffness and size at success rates ranging from 50% to 100% in both position and velocity control with no significant difference across control schemes. Our findings show that evoked somatosensory feedback in a non-invasive manner can facilitate closed-loop control of the prosthetic hand and allowed for simultaneous recognition of different object properties. The outcomes can facilitate our understanding on the role of sensory feedback during bidirectional human-machine interactions, which can potentially promote user experience in object interactions using prosthetic hands.

Control of Mammalian Locomotion by Somatosensory Feedback

When animals walk overground, mechanical stimuli activate various receptors located in muscles, joints, and skin. Afferents from these mechanoreceptors project to neuronal networks controlling locomotion in the spinal cord and brain. The dynamic interactions between the control systems at different levels of the neuraxis ensure that locomotion adjusts to its environment and meets task demands. In this article, we describe and discuss the essential contribution of somatosensory feedback to locomotion. We start with a discussion of how biomechanical properties of the body affect somatosensory feedback. We follow with the different types of mechanoreceptors and somatosensory afferents and their activity during locomotion. We then describe central projections to locomotor networks and the modulation of somatosensory feedback during locomotion and its mechanisms. We then discuss experimental approaches and animal models used to investigate the control of locomotion by somatosensory feedback before providing an overview of the different functional roles of somatosensory feedback for locomotion. Lastly, we briefly describe the role of somatosensory feedback in the recovery of locomotion after neurological injury. We highlight the fact that somatosensory feedback is an essential component of a highly integrated system for locomotor control. © 2021 American Physiological Society. Compr Physiol 11:1-71, 2021.

Sensory computations in the cuneate nucleus of macaques

Tactile nerve fibers fall into a few classes that can be readily distinguished based on their spatiotemporal response properties. Because nerve fibers reflect local skin deformations, they individually carry ambiguous signals about object features. In contrast, cortical neurons exhibit heterogeneous response properties that reflect computations applied to convergent input from multiple classes of afferents, which confer to them a selectivity for behaviorally relevant features of objects. The conventional view is that these complex response properties arise within the cortex itself, implying that sensory signals are not processed to any significant extent in the two intervening structures-the cuneate nucleus (CN) and the thalamus. To test this hypothesis, we recorded the responses evoked in the CN to a battery of stimuli that have been extensively used to characterize tactile coding in both the periphery and cortex, including skin indentations, vibrations, random dot patterns, and scanned edges. We found that CN responses are more similar to their cortical counterparts than they are to their inputs: CN neurons receive input from multiple classes of nerve fibers, they have spatially complex receptive fields, and they exhibit selectivity for object features. Contrary to consensus, then, the CN plays a key role in processing tactile information.

Cortical responses to touch reflect subcortical integration of LTMR signals

Current models to explain how signals emanating from cutaneous mechanoreceptors generate representations of touch are based on comparisons of the tactile responses of mechanoreceptor subtypes and neurons in somatosensory cortex^1-8. Here we used mouse genetic manipulations to investigate the contributions of peripheral mechanoreceptor subtypes to cortical responses to touch. Cortical neurons exhibited remarkably homogeneous and transient responses to skin indentation that resembled rapidly adapting (RA) low-threshold mechanoreceptor (LTMR) responses. Concurrent disruption of signals from both Aβ RA-LTMRs and Aβ slowly adapting (SA)-LTMRs eliminated cortical responses to light indentation forces. However, disruption of either LTMR subtype alone caused opposite shifts in cortical sensitivity but otherwise largely unaltered tactile responses, indicating that both subtypes contribute to normal cortical responses. Selective optogenetic activation of single action potentials in Aβ RA-LTMRs or Aβ SA-LTMRs drove low-latency responses in most mechanically sensitive cortical neurons. Similarly, most somatosensory thalamic neurons were also driven by activation of Aβ RA-LTMRs or Aβ SA-LTMRs. These findings support a model in which signals from physiologically distinct mechanoreceptor subtypes are extensively integrated and transformed within the subcortical somatosensory system to generate cortical representations of touch.

The neural mechanisms of manual dexterity

The hand endows us with unparalleled precision and versatility in our interactions with objects, from mundane activities such as grasping to extraordinary ones such as virtuoso pianism. The complex anatomy of the human hand combined with expansive and specialized neuronal control circuits allows a wide range of precise manual behaviours. To support these behaviours, an exquisite sensory apparatus, spanning the modalities of touch and proprioception, conveys detailed and timely information about our interactions with objects and about the objects themselves. The study of manual dexterity provides a unique lens into the sensorimotor mechanisms that endow the nervous system with the ability to flexibly generate complex behaviour.

The interaction between motion and texture in the sense of touch

Besides providing information on elementary properties of objects, like texture, roughness, and softness, the sense of touch is also important in building a representation of object movement and the movement of our hands. Neural and behavioral studies shed light on the mechanisms and limits of our sense of touch in the perception of texture and motion, and of its role in the control of movement of our hands. The interplay between the geometrical and mechanical properties of the touched objects, such as shape and texture, the movement of the hand exploring the object, and the motion felt by touch, will be discussed in this article. Interestingly, the interaction between motion and textures can generate perceptual illusions in touch. For example, the orientation and the spacing of the texture elements on a static surface induces the illusion of surface motion when we move our hand on it or can elicit the perception of a curved trajectory during sliding, straight hand movements. In this work we present a multiperspective view that encompasses both the perceptual and the motor aspects, as well as the response of peripheral and central nerve structures, to analyze and better understand the complex mechanisms underpinning the tactile representation of texture and motion. Such a better understanding of the spatiotemporal features of the tactile stimulus can reveal novel transdisciplinary applications in neuroscience and haptics.

Effects of receptor density on the tactile perception of roughness: implications for neural mechanisms of texture perception

Aim of the study: The purpose of this study was to investigate the effects of receptor density in the glabrous skin of the hand on the perception of the roughness of a textured surface.Materials and methods: This was done by having observers make magnitude estimates of the perceived roughness of raised-dot surfaces at the fingertip, with its high receptor density, and the thenar eminence, with its much lower receptor density.Results: Judgments of perceived roughness averaged over the inter-dot spacings (0.8-5.9 mm) employed in the study did not differ significantly between the two sites, which suggested that roughness perception is not exclusively dependent upon a neural code involving variation in the activity levels of the nerve fibers of spatially distributed receptors, as is the case in spatial discrimination tasks such as spatial-gap detection, grove-orientation discrimination and letter recognition. This hypothesis was further supported by the finding that the elimination of temporal cues by preventing movement of the skin over the raised-dot surface drastically impaired judgments of perceived roughness at the thenar but had little effect on judgments of perceived roughness at the fingertip.Conclusion: These findings suggested that the neural code for perceived roughness at the fingertip is mediated primarily by spatial variation in the activity levels of spatially distributed receptors whereas the neural code for perceived roughness at the thenar is mediated primarily by temporal variation in the activity levels of individual receptors.

Perception of microstimulation frequency in human somatosensory cortex

Microstimulation in the somatosensory cortex can evoke artificial tactile percepts and can be incorporated into bidirectional brain–computer interfaces (BCIs) to restore function after injury or disease. However, little is known about how stimulation parameters themselves affect perception. Here, we stimulated through microelectrode arrays implanted in the somatosensory cortex of two human participants with cervical spinal cord injury and varied the stimulus amplitude, frequency, and train duration. Increasing the amplitude and train duration increased the perceived intensity on all tested electrodes. Surprisingly, we found that increasing the frequency evoked more intense percepts on some electrodes but evoked less-intense percepts on other electrodes. These different frequency–intensity relationships were divided into three groups, which also evoked distinct percept qualities at different stimulus frequencies. Neighboring electrode sites were more likely to belong to the same group. These results support the idea that stimulation frequency directly controls tactile perception and that these different percepts may be related to the organization of somatosensory cortex, which will facilitate principled development of stimulation strategies for bidirectional BCIs.

A touch of hierarchy: population receptive fields reveal fingertip integration in Brodmann areas in human primary somatosensory cortex

Several neuroimaging studies have shown the somatotopy of body part representations in primary somatosensory cortex (S1), but the functional hierarchy of distinct subregions in human S1 has not been adequately addressed. The current study investigates the functional hierarchy of cyto-architectonically distinct regions, Brodmann areas BA3, BA1, and BA2, in human S1. During functional MRI experiments, we presented participants with vibrotactile stimulation of the fingertips at three different vibration frequencies. Using population Receptive Field (pRF) modeling of the fMRI BOLD activity, we identified the hand region in S1 and the somatotopy of the fingertips. For each voxel, the pRF center indicates the finger that most effectively drives the BOLD signal, and the pRF size measures the spatial somatic pooling of fingertips. We find a systematic relationship of pRF sizes from lower-order areas to higher-order areas. Specifically, we found that pRF sizes are smallest in BA3, increase slightly towards BA1, and are largest in BA2, paralleling the increase in visual receptive field size as one ascends the visual hierarchy. Additionally, we find that the time-to-peak of the hemodynamic response in BA3 is roughly 0.5 s earlier compared to BA1 and BA2, further supporting the notion of a functional hierarchy of subregions in S1. These results were obtained during stimulation of different mechanoreceptors, suggesting that different afferent fibers leading up to S1 feed into the same cortical hierarchy.

Of mice and monkeys: Somatosensory processing in two prominent animal models

Our understanding of the neural basis of somatosensation is based largely on studies of the whisker system of mice and rats and the hands of macaque monkeys. Results across these animal models are often interpreted as providing direct insight into human somatosensation. Work on these systems has proceeded in parallel, capitalizing on the strengths of each model, but has rarely been considered as a whole. This lack of integration promotes a piecemeal understanding of somatosensation. Here, we examine the functions and morphologies of whiskers of mice and rats, the hands of macaque monkeys, and the somatosensory neuraxes of these three species. We then discuss how somatosensory information is encoded in their respective nervous systems, highlighting similarities and differences. We reflect on the limitations of these models of human somatosensation and consider key gaps in our understanding of the neural basis of somatosensation.