Importance of spike timing in touch: an analogy with hearing?

Encoding of Vibrotactile Stimuli by Mechanoreceptors in Rodent Glabrous Skin

Somatosensory coding in rodents has been mostly studied in the whisker system and hairy skin, whereas the function of low-threshold mechanoreceptors (LTMRs) in the rodent glabrous skin has received scant attention, unlike in primates where the glabrous skin has been the focus. The relative activation of different LTMR subtypes carries information about vibrotactile stimuli, as does the rate and temporal patterning of LTMR spikes. Rate coding depends on the probability of a spike occurring on each stimulus cycle (reliability), whereas temporal coding depends on the timing of spikes relative to the stimulus cycle (precision). Using in vivo extracellular recordings in male rats and mice of either sex, we measured the reliability and precision of LTMR responses to tactile stimuli including sustained pressure and vibration. Similar to other species, rodent LTMRs were separated into rapid-adapting (RA) or slow-adapting based on their response to sustained pressure. However, unlike the dichotomous frequency preference characteristic of RA1 and RA2/Pacinian afferents in other species, rodent RAs fell along a continuum. Fitting generalized linear models to experimental data reproduced the reliability and precision of rodent RAs. The resulting model parameters highlight key mechanistic differences across the RA spectrum; specifically, the integration window of different RAs transitions from wide to narrow as tuning preferences across the population move from low to high frequencies. Our results show that rodent RAs can support both rate and temporal coding, but their heterogeneity suggests that coactivation patterns play a greater role in population coding than for dichotomously tuned primate RAs.

Enhanced neural phase locking through audio-tactile stimulation

Numerous studies have underscored the close relationship between the auditory and vibrotactile modality. For instance, in the peripheral structures of both modalities, afferent nerve fibers synchronize their activity to the external sensory stimulus, thereby providing a temporal code linked to pitch processing. The Frequency Following Response is a neurological measure that captures this phase locking activity in response to auditory stimuli. In our study, we investigated whether this neural signal is influenced by the simultaneous presentation of a vibrotactile stimulus. Accordingly, our findings revealed a significant increase in phase locking to the fundamental frequency of a speech stimulus, while no such effects were observed at harmonic frequencies. Since phase locking to the fundamental frequency has been associated with pitch perceptual capabilities, our results suggests that audio-tactile stimulation might improve pitch perception in human subjects.

Absence of paresthesia during high-rate spinal cord stimulation reveals importance of synchrony for sensations evoked by electrical stimulation

Electrically activating mechanoreceptive afferents inhibits pain. However, paresthesia evoked by spinal cord stimulation (SCS) at 40-60 Hz becomes uncomfortable at high pulse amplitudes, limiting SCS "dosage." Kilohertz-frequency SCS produces analgesia without paresthesia and is thought, therefore, not to activate afferent axons. We show that paresthesia is absent not because axons do not spike but because they spike asynchronously. In a pain patient, selectively increasing SCS frequency abolished paresthesia and epidurally recorded evoked compound action potentials (ECAPs). Dependence of ECAP amplitude on SCS frequency was reproduced in pigs, rats, and computer simulations and is explained by overdrive desynchronization: spikes desychronize when axons are stimulated faster than their refractory period. Unlike synchronous spikes, asynchronous spikes fail to produce paresthesia because their transmission to somatosensory cortex is blocked by feedforward inhibition. Our results demonstrate how stimulation frequency impacts synchrony based on axon properties and how synchrony impacts sensation based on circuit properties.

Exploring retinal ganglion cells encoding to multi-modal stimulation using 3D microelectrodes arrays

Microelectrode arrays (MEA) are extensively utilized in encoding studies of retinal ganglion cells (RGCs) due to their capacity for simultaneous recording of neural activity across multiple channels. However, conventional planar MEAs face limitations in studying RGCs due to poor coupling between electrodes and RGCs, resulting in low signal-to-noise ratio (SNR) and limited recording sensitivity. To overcome these challenges, we employed photolithography, electroplating, and other processes to fabricate a 3D MEA based on the planar MEA platform. The 3D MEA exhibited several improvements compared to planar MEA, including lower impedance (8.73 ± 1.66 kΩ) and phase delay (-15.11° ± 1.27°), as well as higher charge storage capacity (CSC = 10.16 ± 0.81 mC/cm2), cathodic charge storage capacity (CSCc = 7.10 ± 0.55 mC/cm2), and SNR (SNR = 8.91 ± 0.57). Leveraging the advanced 3D MEA, we investigated the encoding characteristics of RGCs under multi-modal stimulation. Optical, electrical, and chemical stimulation were applied as sensory inputs, and distinct response patterns and response times of RGCs were detected, as well as variations in rate encoding and temporal encoding. Specifically, electrical stimulation elicited more effective RGC firing, while optical stimulation enhanced RGC synchrony. These findings hold promise for advancing the field of neural encoding.

Physiological noise facilitates multiplexed coding of vibrotactile-like signals in somatosensory cortex

Neurons can use different aspects of their spiking to simultaneously represent (multiplex) different features of a stimulus. For example, some pyramidal neurons in primary somatosensory cortex (S1) use the rate and timing of their spikes to, respectively, encode the intensity and frequency of vibrotactile stimuli. Doing so has several requirements. Because they fire at low rates, pyramidal neurons cannot entrain 1:1 with high-frequency (100 to 600 Hz) inputs and, instead, must skip (i.e., not respond to) some stimulus cycles. The proportion of skipped cycles must vary inversely with stimulus intensity for firing rate to encode stimulus intensity. Spikes must phase-lock to the stimulus for spike times (intervals) to encode stimulus frequency, but, in addition, skipping must occur irregularly to avoid aliasing. Using simulations and in vitro experiments in which mouse S1 pyramidal neurons were stimulated with inputs emulating those induced by vibrotactile stimuli, we show that fewer cycles are skipped as stimulus intensity increases, as required for rate coding, and that intrinsic or synaptic noise can induce irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because noise can modulate the reliability without disrupting the precision of spikes evoked by small-amplitude, fast-onset signals. Specifically, in the fluctuation-driven regime associated with sparse spiking, rate and temporal coding are both paradoxically improved by the strong synaptic noise characteristic of the intact cortex. Our results demonstrate that multiplexed coding by S1 pyramidal neurons is not only feasible under in vivo conditions, but that background synaptic noise is actually beneficial.

Auditory clicks elicit equivalent temporal frequency perception to tactile pulses: A cross-modal psychophysical study

Both hearing and touch are sensitive to the frequency of mechanical oscillations—sound waves and tactile vibrations, respectively. The mounting evidence of parallels in temporal frequency processing between the two sensory systems led us to directly address the question of perceptual frequency equivalence between touch and hearing using stimuli of simple and more complex temporal features. In a cross-modal psychophysical paradigm, subjects compared the perceived frequency of pulsatile mechanical vibrations to that elicited by pulsatile acoustic (click) trains, and vice versa. Non-invasive pulsatile stimulation designed to excite a fixed population of afferents was used to induce desired temporal spike trains at frequencies spanning flutter up to vibratory hum (>50 Hz). The cross-modal perceived frequency for regular test pulse trains of either modality was a close match to the presented stimulus physical frequency up to 100 Hz. We then tested whether the recently discovered “burst gap” temporal code for frequency, that is shared by the two senses, renders an equivalent cross-modal frequency perception. When subjects compared trains comprising pairs of pulses (bursts) in one modality against regular trains in the other, the cross-sensory equivalent perceptual frequency best corresponded to the silent interval between the successive bursts in both auditory and tactile test stimuli. These findings suggest that identical acoustic and vibrotactile pulse trains, regardless of pattern, elicit equivalent frequencies, and imply analogous temporal frequency computation strategies in both modalities. This perceptual correspondence raises the possibility of employing a cross-modal comparison as a robust standard to overcome the prevailing methodological limitations in psychophysical investigations and strongly encourages cross-modal approaches for transmitting sensory information such as translating pitch into a similar pattern of vibration on the skin.

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 spatial profile of skin indentation shapes tactile perception across stimulus frequencies

Multiple human sensory systems exhibit sensitivity to spatial and temporal variations of physical stimuli. Vision has evolved to offer high spatial acuity with limited temporal sensitivity, while audition has developed complementary characteristics. Neural coding in touch has been believed to transition from a spatial to a temporal domain in relation to surface scale, such that coarse features (e.g., a braille cell or corduroy texture) are coded as spatially distributed signals, while fine textures (e.g., fine-grit sandpaper) are encoded by temporal variation. However, the interplay between the two domains is not well understood. We studied tactile encoding with a custom-designed pin array apparatus capable of deforming the fingerpad at 5 to 80 Hz in each of 14 individual locations spaced 2.5 mm apart. Spatial variation of skin indentation was controlled by moving each of the pins at the same frequency and amplitude, but with phase delays distributed across the array. Results indicate that such stimuli enable rendering of shape features at actuation frequencies up to 20 Hz. Even at frequencies > 20 Hz, however, spatial variation of skin indentation continues to play a vital role. In particular, perceived roughness is affected by spatial variation within the fingerpad even at 80 Hz. We provide evidence that perceived roughness is encoded via a summary measure of skin displacement. Relative displacements in neighboring pins of less than 10 µm generate skin stretch, which regulates the roughness percept.

The burst gap is a peripheral temporal code for pitch perception that is shared across audition and touch

When tactile afferents were manipulated to fire in periodic bursts of spikes, we discovered that the perceived pitch corresponded to the inter-burst interval (burst gap) in a spike train, rather than the spike rate or burst periodicity as previously thought. Given that tactile frequency mechanisms have many analogies to audition, and indications that temporal frequency channels are linked across the two modalities, we investigated whether there is burst gap temporal encoding in the auditory system. To link this putative neural code to perception, human subjects (n = 13, 6 females) assessed pitch elicited by trains of temporally-structured acoustic pulses in psychophysical experiments. Each pulse was designed to excite a fixed population of cochlear neurons, precluding place of excitation cues, and to elicit desired temporal spike trains in activated afferents. We tested periodicities up to 150 Hz using a variety of burst patterns and found striking deviations from periodicity-predicted pitch. Like the tactile system, the duration of the silent gap between successive bursts of neural activity best predicted perceived pitch, emphasising the role of peripheral temporal coding in shaping pitch. This suggests that temporal patterning of stimulus pulses in cochlear implant users might improve pitch perception.

Data-Driven Playback of Natural Tactile Texture Via Broadband Friction Modulation

We used broadband electroadhesion to reproduce the friction force profile measured as a finger slid across a textured surface. In doing so, we were also able to reproduce with high fidelity the skin vibrations characteristic of that texture; however, we found that this did not reproduce the original perception. To begin, the reproduction felt weak. In order to maximize perceptual similarity between a real texture and its friction force playback, the vibratory magnitude of the latter must be scaled up on average ≈ 3X for fine texture and ≈ 5X for coarse texture samples. This additional gain appears to correlate with perceived texture roughness. Additionally, even with optimal scaling and high fidelity playback, subjects could identify which of two reproductions corresponds to a real texture with only 71 % accuracy, as compared to 95 % accuracy when using real texture alternatives. We conclude that while tribometry and vibrometry data can be useful for texture classification, they appear to contribute only partially to texture perception. We propose that spatially distributed excitation of skin within the fingerpad may play an additional key role, and may thus be able to contribute to high fidelity texture reproduction.

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.

Neural readout of a latency code in the active electrosensory system

The latency of spikes relative to a stimulus conveys sensory information across modalities. However, in most cases, it remains unclear whether and how such latency codes are utilized by postsynaptic neurons. In the active electrosensory system of mormyrid fish, a latency code for stimulus amplitude in electroreceptor afferent nerve fibers (EAs) is hypothesized to be read out by a central reference provided by motor corollary discharge (CD). Here, we demonstrate that CD enhances sensory responses in postsynaptic granular cells of the electrosensory lobe but is not required for reading out EA input. Instead, diverse latency and spike count tuning across the EA population give rise to graded information about stimulus amplitude that can be read out by standard integration of converging excitatory synaptic inputs. Inhibitory control over the temporal window of integration renders two granular cell subclasses differentially sensitive to information derived from relative spike latency versus spike count.

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.

Theoretical Relationship Between Two Measures of Spike Synchrony: Correlation Index and Vector Strength

Information processing in the nervous system critically relies on temporally precise spiking activity. In the auditory system, various degrees of phase-locking can be observed from the auditory nerve to cortical neurons. The classical metric for quantifying phase-locking is the vector strength (VS), which captures the periodicity in neuronal spiking. More recently, another metric, called the correlation index (CI), was proposed to quantify the temporally reproducible response characteristics of a neuron. The CI is defined as the peak value of a normalized shuffled autocorrelogram (SAC). Both VS and CI have been used to investigate how temporal information is processed and propagated along the auditory pathways. While previous analyses of physiological data in cats suggested covariation of these two metrics, general characterization of their connection has never been performed. In the present study, we derive a rigorous relationship between VS and CI. To model phase-locking, we assume Poissonian spike trains with a temporally changing intensity function following a von Mises distribution. We demonstrate that VS and CI are mutually related via the so-called concentration parameter that determines the degree of phase-locking. We confirm that these theoretical results are largely consistent with physiological data recorded in the auditory brainstem of various animals. In addition, we generate artificial phase-locked spike sequences, for which recording and analysis parameters can be systematically manipulated. Our analysis results suggest that mismatches between empirical data and the theoretical prediction can often be explained with deviations from the von Mises distribution, including skewed or multimodal period histograms. Furthermore, temporal relations of spike trains across trials can contribute to higher CI values than predicted mathematically based on the VS. We find that, for most applications, a SAC bin width of 50 ms seems to be a favorable choice, leading to an estimated error below 2.5% for physiologically plausible conditions. Overall, our results provide general relations between the two measures of phase-locking and will aid future analyses of different physiological datasets that are characterized with these metrics.

Perceptual rivalry with vibrotactile stimuli

In perceptual rivalry, ambiguous sensory information leads to dynamic changes in the perceptual interpretation of fixed stimuli. This phenomenon occurs when participants receive sensory stimuli that support two or more distinct interpretations; this results in spontaneous alternations between possible perceptual interpretations. Perceptual rivalry has been widely studied across different sensory modalities including vision, audition, and to a limited extent, in the tactile domain. Common features of perceptual rivalry across various ambiguous visual and auditory paradigms characterize the randomness of switching times and their dependence on input strength manipulations (Levelt's propositions). It is still unclear whether the general characteristics of perceptual rivalry are preserved with tactile stimuli. This study aims to introduce a simple tactile stimulus capable of generating perceptual rivalry and explores whether general features of perceptual rivalry from other modalities extend to the tactile domain. Our results confirm that Levelt's proposition II extends to tactile bistability, and that the stochastic characteristics of irregular perceptual alternations agree with non-tactile modalities. An analysis of correlations between subsequent perceptual phases reveals a significant positive correlation at lag 1 (as found in visual bistability), and a negative correlation for lag 2 (in contrast with visual bistability).

Burst gap code predictions for tactile frequency are valid across the range of perceived frequencies attributed to two distinct tactile channels

Perceived frequency of vibrotactile stimuli can be divided into two distinctive cutaneous sensations-flutter (<60 Hz) and vibratory hum (>60 Hz), mediated by two different tactile afferent types [fast adapting type I (FA1) and fast adapting type II (FA2), respectively]. We recently demonstrated a novel form of neural coding in the human tactile system, where frequency perception of stimulus pulses grouped into periodic bursts in the flutter range depended on the duration of the silent gap between bursts, rather than the periodicity or mean impulse rate. Here, we investigated whether this interburst interval could also explain the perceived frequency of electrocutaneous pulse patterns delivered at frequencies above the flutter range. At stimulus rates of 50 to 190 pulses/s, the burst gap model correctly predicted the perceived frequency. This shows that the burst gap code represents a general coding strategy that spans the range of frequencies traditionally attributed to two different tactile channels.NEW & NOTEWORTHY We present evidence for a generalized frequency processing strategy on tactile afferent inputs that is shared across a broad range of frequencies extending beyond the flutter range, supporting the notion that spike timing has an important role in shaping tactile perception.

The temporal pattern of Intracortical Microstimulation pulses elicits distinct temporal and spatial recruitment of cortical neuropil and neurons

OBJECTIVE

The spacing or distribution of stimulation pulses of therapeutic neurostimulation waveforms-referred to here as the Temporal Pattern (TP)-has emerged as an important parameter for tuning the response to deep-brain stimulation and intracortical microstimulation (ICMS). While it has long been assumed that modulating the TP of ICMS may be effective by altering the rate coding of the neural response, it is unclear how it alters the neural response at the neural network level. The present study is designed to elucidate the neural response to TP at the network level.

APPROACH

We use in vivo two-photon imaging of ICMS in mice expressing the calcium sensor Thy1-GCaMP or the glutamate sensor hSyn-iGluSnFr to examine the layer II/III neural response to stimulations with different TPs. We study the neuronal calcium and glutamate response to TPs with the same average frequency (10Hz) and same total charge injection, but varying degrees of bursting. We also investigate one control pattern with an average frequency of 100Hz and 10X the charge injection.

MAIN RESULTS

Stimulation trains with the same average frequency (10 Hz) and same total charge injection but distinct temporal patterns recruits distinct sets of neurons. More-than-half (60% of 309 cells) prefer one temporal pattern over the other. Despite their distinct spatial recruitment patterns, both cells exhibit similar ability to follow 30s trains of both TPs without failing, and they exhibit similar levels of glutamate release during stimulation. Both neuronal calcium and glutamate release train to the bursting TP pattern (~21-fold increase in relative power at the frequency of bursting. Bursting also results in a statistically significant elevation in the correlation between somatic calcium activity and neuropil activity, which we explore as a metric for inhibitory-excitatory tone. Interestingly, soma-neuropil correlation during the bursting pattern is a statistically significant predictor of cell preference for TP, which exposes a key link between inhibitory-excitatory tone. Finally, using mesoscale imaging, we show that both TPs result in distal inhibition during stimulation, which reveals complex spatial and temporal interactions between temporal pattern and inhibitory-excitatory tone in ICMS.

SIGNIFICANCE

Our results may ultimately suggest that TP is a valuable parameter space to modulate inhibitory-excitatory tone as well as distinct network activity in ICMS. This presents a broader mechanism of action than rate coding, as previously thought. By implicating these additional mechanisms, TP may have broader utility in the clinic and should be pursued to expand the efficacy of ICMS therapies.

Slowly activating outward membrane currents generate input-output sub-harmonic cross frequency coupling in neurons

A major challenge in understanding spike-time dependent information encoding in the neural system is the non-linear firing response to inputs of the individual neurons. Hence, quantitative exploration of the putative mechanisms of this non-linear behavior is fundamental to formulating the theory of information transfer in the neural system. The objective of this simulation study was to evaluate and quantify the effect of slowly activating outward membrane current, on the non-linearity in the output of a one-compartment Hodgkin-Huxley styled neuron. To evaluate this effect, the peak conductance of the slow potassium channel (g_K-slow) was varied from 0% to 200% of its normal value in steps of 33%. Both cross- and iso-frequency coupling between the input and the output of the simulated neuron was computed using a generalized coherence measure, i.e., n:m coherence. With increasing g_K-slow, the amount of sub-harmonic cross-frequency coupling, where the output frequencies (1-8 Hz) are lower than the input frequencies (15-35 Hz), increased progressively whereas no change in iso-frequency coupling was observed. Power spectral and phase-space analysis of the neuronal membrane voltage vs. slow potassium channel activation variable showed that the interaction of the slow channel dynamics with the fast membrane voltage dynamics generates the observed sub-harmonic coupling. This study provides quantitative insights into the role of an important membrane mechanism i.e. the slowly activating outward current in generating non-linearities in the output of a neuron.

A comprehensive model-based framework for optimal design of biomimetic patterns of electrical stimulation for prosthetic sensation

OBJECTIVE

Touch and proprioception are essential to motor function as shown by the movement deficits that result from the loss of these senses, e.g. due to neuropathy of sensory nerves. To achieve a high-performance brain-controlled prosthetic arm/hand thus requires the restoration of somatosensation, perhaps through intracortical microstimulation (ICMS) of somatosensory cortex (S1). The challenge is to generate patterns of neuronal activation that evoke interpretable percepts. We present a framework to design optimal spatiotemporal patterns of ICMS (STIM) that evoke naturalistic patterns of neuronal activity and demonstrate performance superior to four previous approaches.

APPROACH

We recorded multiunit activity from S1 during a center-out reach task (from proprioceptive neurons in Brodmann's area 2) and during application of skin indentations (from cutaneous neurons in Brodmann's area 1). We implemented a computational model of a cortical hypercolumn and used a genetic algorithm to design STIM that evoked patterns of model neuron activity that mimicked their experimentally-measured counterparts. Finally, from the ICMS patterns, the evoked neuronal activity, and the stimulus parameters that gave rise to it, we trained a recurrent neural network (RNN) to learn the mapping function between the physical stimulus and the biomimetic stimulation pattern, i.e. the sensory encoder to be integrated into a neuroprosthetic device.

MAIN RESULTS

We identified ICMS patterns that evoked simulated responses that closely approximated the measured responses for neurons within 50 µm of the electrode tip. The RNN-based sensory encoder generalized well to untrained limb movements or skin indentations. STIM designed using the model-based optimization approach outperformed STIM designed using existing linear and nonlinear mappings.

SIGNIFICANCE

The proposed framework produces an encoder that converts limb state or patterns of pressure exerted onto the prosthetic hand into STIM that evoke naturalistic patterns of neuronal activation.

Temporal patterns in electrical nerve stimulation: Burst gap code shapes tactile frequency perception

We have previously described a novel temporal encoding mechanism in the somatosensory system, where mechanical pulses grouped into periodic bursts create a perceived tactile frequency based on the duration of the silent gap between bursts, rather than the mean rate or the periodicity. This coding strategy may offer new opportunities for transmitting information to the brain using various sensory neural prostheses and haptic interfaces. However, it was not known whether the same coding mechanisms apply when using electrical stimulation, which recruits a different spectrum of afferents. Here, we demonstrate that the predictions of the burst gap coding model for frequency perception apply to burst stimuli delivered with electrical pulses, re-emphasising the importance of the temporal structure of spike patterns in neural processing and perception of tactile stimuli. Reciprocally, the electrical stimulation data confirm that the results observed with mechanical stimulation do indeed depend on neural processing mechanisms in the central nervous system, and are not due to skin mechanical factors and resulting patterns of afferent activation.

Auditory and tactile frequency representations are co-embedded in modality-defined cortical sensory systems

Sensory information is represented and elaborated in hierarchical cortical systems that are thought to be dedicated to individual sensory modalities. This traditional view of sensory cortex organization has been challenged by recent evidence of multimodal responses in primary and association sensory areas. Although it is indisputable that sensory areas respond to multiple modalities, it remains unclear whether these multimodal responses reflect selective information processing for particular stimulus features. Here, we used fMRI adaptation to identify brain regions that are sensitive to the temporal frequency information contained in auditory, tactile, and audiotactile stimulus sequences. A number of brain regions distributed over the parietal and temporal lobes exhibited frequency-selective temporal response modulation for both auditory and tactile stimulus events, as indexed by repetition suppression effects. A smaller set of regions responded to crossmodal adaptation sequences in a frequency-dependent manner. Despite an extensive overlap of multimodal frequency-selective responses across the parietal and temporal lobes, representational similarity analysis revealed a cortical "regional landscape" that clearly reflected distinct somatosensory and auditory processing systems that converged on modality-invariant areas. These structured relationships between brain regions were also evident in spontaneous signal fluctuation patterns measured at rest. Our results reveal that multimodal processing in human cortex can be feature-specific and that multimodal frequency representations are embedded in the intrinsically hierarchical organization of cortical sensory systems.

Introduction of a New In-Situ Measurement System for the Study of Touch-Feel Relevant Surface Properties

The touch-feel sensation of product surfaces arouses growing interest in various industry branches. To entangle the underlying physical and material parameters responsible for a specific touch-feel sensation, a new measurement system has been developed. This system aims to record the prime physical interaction parameters at a time, which is considered a necessary prerequisite for a successful physical description of the haptic sensation. The measurement setup enables one to measure the dynamic coefficient of friction, the macroscopic contact area of smooth and rough surfaces, the angle enclosed between the human finger and the soft-touch surfaces and the vibrations induced in the human finger during relative motion at a time. To validate the measurement stand, a test series has been conducted on two soft-touch surfaces of different roughness. While the individual results agree well with the literature, their combination revealed new insights. Finally, the investigation of the haptics of polymer coatings with the presented measuring system should facilitate the design of surfaces with tailor-made touch-feel properties.

Coding source localization through inter-spike delay: modelling a cluster of Pacinian Corpuscles using time-division multiplexing approach

The Pacinian Corpuscle (PC) is the most sensitive mechanoreceptor in the human body found in clusters of two or three. We extended our previous model of an isolated-PC to a cluster-PC focussing on relative spike delay and displacement threshold for understanding how the stimulus location is coded. In our model, two PCs with Gaussian overlapping receptive fields are arranged beneath the skin model. For a spatiotemporal stimulus (vibration), the model response is proposed to be a time-division multiplexing of responses from two PCs within the cluster. While the spike rate characteristics and pole-zero plot of cluster-PC model show similarities with the isolated-PC model, the frequency response shows ripples after 1 kHz as the distance (d) between the PCs increases. The stimulus location [Formula: see text] and d influence the relative spike delay and the displacement threshold, but not the spike rate. The novel contributions from our model include prediction of (i) relative spike delay for various d, stimulus frequency (f), and ψ, (ii) spike rate characteristics for varying f, and (iii) displacement threshold curve as a function of frequency for various d. Although the physiological validation of the novel predictions is impractical, we have validated the relative spike delay and the displacement threshold curves with experimental data in the literature.

Closed Loop Application of Electroadhesion for Increased Precision in Texture Rendering

Tactile displays based on friction modulation offer wide-bandwidth forces rendered directly on the fingertip. However, due to a number of touch conditions (e.g., normal force, skin hydration) that result in variations in the friction force and the strength of modulation effect, the precision of the force rendering remains limited. In this paper we demonstrate a closed-loop electroadhesion method for precise playback of friction force profiles on a human finger and we apply this method to the tactile rendering of several textiles encountered in everyday life.

Detection and Identification of Pattern Information on an Electrostatic Friction Display

An electrostatic friction modulation device based on a tablet computer was used to present pattern stimuli to the fingertip for two tasks: detecting patches of friction and matching a frictional pattern to the visual image that produced it. In the detection task, friction patterns were displayed on zero, one two or three cells in a matrix. Errors, whether misses or false alarms, were few. Duration of target-present trials was a linear function of the number of patterns in the display. The intercept indicated an average of under 1 sec to test a location for the presence of a friction patch. The slope was 1.0 sec per item, representing the time to confirm friction change, verify the location, and report. In contrast to fast and accurate detection of friction modulation, identification of patterns by matching to a visual display was at chance, although the patterns were differentiated by form and scale. Given that the patterns fall within the normal acuity of the fingertip, along with previous evidence that fingertip motion per se does not preclude pattern recognition, it appears that the failure to match tactual patterns to visual images resides in processes inherent in information pickup from friction-modulation displays.

Tactile sensory channels over-ruled by frequency decoding system that utilizes spike pattern regardless of receptor type

The established view is that vibrotactile stimuli evoke two qualitatively distinctive cutaneous sensations, flutter (frequencies < 60 Hz) and vibratory hum (frequencies > 60 Hz), subserved by two distinct receptor types (Meissner's and Pacinian corpuscle, respectively), which may engage different neural processing pathways or channels and fulfil quite different biological roles. In psychological and physiological literature, those two systems have been labelled as Pacinian and non-Pacinian channels. However, we present evidence that low-frequency spike trains in Pacinian afferents can readily induce a vibratory percept with the same low frequency attributes as sinusoidal stimuli of the same frequency, thus demonstrating a universal frequency decoding system. We achieved this using brief low-amplitude pulsatile mechanical stimuli to selectively activate Pacinian afferents. This indicates that spiking pattern, regardless of receptor type, determines vibrotactile frequency perception. This mechanism may underlie the constancy of vibrotactile frequency perception across different skin regions innervated by distinct afferent types.

Somatosensory interactions reveal feature-dependent computations

Our ability to perceive and discriminate textures is based on the processing of high-frequency vibrations generated on the fingertip as it scans across a surface. Although much is known about the processing of vibration amplitude and frequency information when cutaneous stimulation is experienced at a single location on the body, how these stimulus features are processed when touch occurs at multiple locations is poorly understood. We evaluated participants’ ability to discriminate tactile cues (100–300 Hz) on one hand while they ignored distractor cues experienced on their other hand. We manipulated the relative positions of the hands to characterize how limb position influenced cutaneous touch interactions. In separate experiments, participants judged either the frequency or intensity of mechanical vibrations. We found that vibrations experienced on one hand always systematically modulated the perception of vibrations on the other hand. Notably, bimanual interaction patterns and their sensitivity to hand locations differed according to stimulus feature. Somatosensory interactions in intensity perception were only marked by attenuation that was invariant to hand position manipulations. In contrast, interactions in frequency perception consisted of both bias and sensitivity changes that were more pronounced when the hands were held in close proximity. We implemented models to infer the neural computations that mediate somatosensory interactions in the intensity and frequency dimensions. Our findings reveal obligatory and feature-dependent somatosensory interactions that may be supported by both feature-specific and feature-general operations.

NEW & NOTEWORTHY Little is known about the neural computations mediating feature-specific sensory interactions between the hands. We show that vibrations experienced on one hand systematically modulate the perception of vibrations felt on the other hand. Critically, interaction patterns and their dependence on the relative positions of the hands differed depending on whether participants judged vibration intensity or frequency. These results, which we recapitulate with models, imply that somatosensory interactions are mediated by feature-dependent neural computations.

Multisensory perceptual interactions between higher-order temporal frequency signals

Naturally occurring signals in audition and touch can be complex and marked by temporal variations in frequency and amplitude. Auditory frequency sweep processing has been studied extensively; however, much less is known about sweep processing in touch because studies have primarily focused on the perception of simple sinusoidal vibrations. Given the extensive interactions between audition and touch in the frequency processing of pure tone signals, we reasoned that these senses might also interact in the processing of higher-order frequency representations like sweeps. In a series of psychophysical experiments, we characterized the influence of auditory distractors on the ability of participants to discriminate tactile frequency sweeps. Auditory frequency sweeps systematically biased the tactile perception of sweep direction. Importantly, auditory cues exerted little influence on tactile sweep direction perception when the sounds and vibrations occupied different absolute frequency ranges or when the sounds consisted of intensity sweeps. Thus, audition and touch interact in frequency sweep perception in a frequency- and feature-specific manner. Our results demonstrate that audio-tactile interactions are not constrained to the processing of simple sinusoids. Because higher-order frequency representations may be synthesized from simpler representations, our findings imply that multisensory interactions in the temporal frequency domain span multiple hierarchical levels in sensory processing. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents

This work presents a pieces of Python code to rapidly simulate the spiking responses of large numbers of single cutaneous tactile afferents with millisecond precision. To simulate the spike responses of all the major types of cutaneous tactile afferents, we proposed an electromechanical circuit model, in which a two-channel filter was developed to characterize the mechanical selectivity of tactile receptors, and a spike synthesizer was designed to recreate the action potentials evoked in afferents. The parameters of this model were fitted using previous neurophysiological datasets. Several simulation examples were presented in this paper to reproduce action potentials, sensory adaptation, frequency characteristics and spiking timing for each afferent type. The results indicated that the simulated responses matched previous neurophysiological recordings well. The model allows for a real-time reproduction of the spiking responses of about 4,000 tactile units with a timing precision of <6 ms. The current work provides a valuable guidance to designing highly realistic tactile interfaces such as neuroprosthesis and haptic devices.

Rapid geometric feature signaling in the simulated spiking activity of a complete population of tactile nerve fibers

Tactile feature extraction is essential to guide the dexterous manipulation of objects. The longstanding theory is that geometric features at each location of contact between hand and object are extracted from the spatial layout of the response of populations of tactile nerve fibers. However, recent evidence suggests that some features (e.g., edge orientation) are extracted very rapidly (<200 ms), casting doubt that this information relies on a spatial code, which ostensibly requires integrating responses over time. An alternative hypothesis is that orientation is conveyed in precise temporal spiking patterns. Here we simulate, using a recently developed and validated model, the responses of the two relevant subpopulations of tactile fibers from the entire human fingertip (~800 afferents) to edges indented into the skin. We show that edge orientation can be quickly (<50 ms) and accurately (<3°) decoded from the spatial pattern of activation across the afferent population, starting with the very first spike. Next, we implement a biomimetic decoder of edge orientation, consisting of a bank of oriented Gabor filters, designed to mimic the documented responses of cortical neurons. We find that the biomimetic approach leads to orientation decoding performance that approaches the limit set by optimal decoders and is actually more robust to changes in other stimulus features. Finally, we show that orientation signals, measured from single units in the somatosensory cortex of nonhuman primates (2 macaque monkeys, 1 female), follow a time course consistent with that of their counterparts in the nerve. We conclude that a spatial code is fast and accurate enough to support object manipulation. NEW & NOTEWORTHY The dexterous manipulation of objects relies on the rapid and accurate extraction of the objects' geometric features by the sense of touch. Here we simulate the responses of all the nerve fibers that innervate the fingertip when an edge is indented into the skin and characterize the time course over which signals about its orientation evolve in this neural population. We show that orientation can be rapidly and accurately decoded from the spatial pattern of afferent activation using spatial filters that mimic the response properties of neurons in cortical somatosensory neurons along a time course consistent with that observed in cortex. We conclude that the classical model of tactile feature extraction is rapid and accurate enough to support object manipulation.

Reciprocal Interactions Between Audition and Touch in Flutter Frequency Perception

In both audition and touch, sensory cues comprising repeating events are perceived either as a continuous signal or as a stream of temporally discrete events (flutter), depending on the events' repetition rate. At high repetition rates (>100 Hz), auditory and tactile cues interact reciprocally in pitch processing. The frequency of a cue experienced in one modality systematically biases the perceived frequency of a cue experienced in the other modality. Here, we tested whether audition and touch also interact in the processing of low-frequency stimulation. We also tested whether multisensory interactions occurred if the stimulation in one modality comprised click trains and the stimulation in the other modality comprised amplitude-modulated signals. We found that auditory cues bias touch and tactile cues bias audition on a flutter discrimination task. Even though participants were instructed to attend to a single sensory modality and ignore the other cue, the flutter rate in the attended modality is perceived to be similar to that of the distractor modality. Moreover, we observed similar interaction patterns regardless of stimulus type and whether the same stimulus types were experienced by both senses. Combined with earlier studies, our results suggest that the nervous system extracts and combines temporal rate information from multisensory environmental signals, regardless of stimulus type, in both the low- and high temporal frequency domains. This function likely reflects the importance of temporal frequency as a fundamental feature of our multisensory experience.

Memory for Random Time Patterns in Audition, Touch, and Vision

Perception deals with temporal sequences of events, like series of phonemes for audition, dynamic changes in pressure for touch textures, or moving objects for vision. Memory processes are thus needed to make sense of the temporal patterning of sensory information. Recently, we have shown that auditory temporal patterns could be learned rapidly and incidentally with repeated exposure [Kang et al., 2017]. Here, we tested whether rapid incidental learning of temporal patterns was specific to audition, or if it was a more general property of sensory systems. We used a same behavioral task in three modalities: audition, touch, and vision, for stimuli having identical temporal statistics. Participants were presented with sequences of acoustic pulses for audition, motion pulses to the fingertips for touch, or light pulses for vision. Pulses were randomly and irregularly spaced, with all inter-pulse intervals in the sub-second range and all constrained to be longer than the temporal acuity in any modality. This led to pulse sequences with an average inter-pulse interval of 166 ms, a minimum inter-pulse interval of 60 ms, and a total duration of 1.2 s. Results showed that, if a random temporal pattern re-occurred at random times during an experimental block, it was rapidly learned, whatever the sensory modality. Moreover, patterns first learned in the auditory modality displayed transfer of learning to either touch or vision. This suggests that sensory systems may be exquisitely tuned to incidentally learn re-occurring temporal patterns, with possible cross-talk between the senses.

Neural Basis of Touch and Proprioception in Primate Cortex

The sense of proprioception allows us to keep track of our limb posture and movements and the sense of touch provides us with information about objects with which we come into contact. In both senses, mechanoreceptors convert the deformation of tissues-skin, muscles, tendons, ligaments, or joints-into neural signals. Tactile and proprioceptive signals are then relayed by the peripheral nerves to the central nervous system, where they are processed to give rise to percepts of objects and of the state of our body. In this review, we first examine briefly the receptors that mediate touch and proprioception, their associated nerve fibers, and pathways they follow to the cerebral cortex. We then provide an overview of the different cortical areas that process tactile and proprioceptive information. Next, we discuss how various features of objects-their shape, motion, and texture, for example-are encoded in the various cortical fields, and the susceptibility of these neural codes to attention and other forms of higher-order modulation. Finally, we summarize recent efforts to restore the senses of touch and proprioception by electrically stimulating somatosensory cortex. © 2018 American Physiological Society. Compr Physiol 8:1575-1602, 2018.

Temporal Pattern of Electrical Stimulation is a New Dimension of Therapeutic Innovation

Artificial activation of the nervous system requires selection of appropriate stimulation parameters including stimulation amplitude, stimulation pulse duration, and stimulation pulse repetition rate. The temporal pattern of stimulation, i.e., the timing between stimulation pulses, is a novel dimension of stimulation parameter tuning. The effects evoked by artificial activation of the nervous system are dependent on the pattern of stimulation, and different patterns of stimulation, even when delivered at the same average rate, evoke different functional effects, different changes in synaptic plasticity, and even different patterns of gene expression. Non-regular temporal patterns of stimulation offer the opportunity to improve the efficacy and efficiency of therapeutic stimulation as well as to manipulate other processes in the nervous system. The potential design space for sequences of varying interpulse intervals is exceedingly large and sound approaches to design stimulation patterns are required as an empirical approach is not practical.

The Application of Tactile, Audible, and Ultrasonic Forces to Human Fingertips Using Broadband Electroadhesion

We report an electroadhesive approach to controlling friction forces on sliding fingertips which is capable of producing vibrations across an exceedingly broad range of tactile, audible, and ultrasonic frequencies. Vibrations on the skin can be felt directly, and vibrations in the air can be heard emanating from the finger. Additionally, we report evidence from an investigation of the electrical dynamics of the system suggesting that an air gap at the skin/surface interface is primarily responsible for the induced electrostatic attraction underlying the electroadhesion effect. We developed an experimental apparatus capable of recording friction forces up to a frequency of 6 kHz, and used it to characterize two different electroadhesive systems, both of which exhibit flat force magnitude responses throughout the measurement range. These systems use custom electrical hardware to modulate a high frequency current and apply surprisingly low distortion, broadband forces to the skin. Recordings of skin vibrations with a laser Doppler vibrometer demonstrate the tactile capabilities of the system, while recordings of vibrations in the air with a MEMS microphone quantify the audible response and reveal the existence of ultrasonic forces applied to the skin via electronic friction modulation. Implications for surface haptic and audio-haptic displays are briefly discussed.

Human tactile detection of within- and inter-finger spatiotemporal phase shifts of low-frequency vibrations

When we touch an object, the skin copies its surface shape/texture, and this deformation pattern shifts according to the objects movement. This shift pattern directly encodes spatio-temporal “motion” information of the event, and has been detected in other modalities (e.g., inter-aural time differences for audition and first-order motion for vision). Since previous studies suggested that mechanoreceptor-afferent channels with small receptive field and slow temporal characteristics contribute to tactile motion perception, we tried to tap the spatio-temporal processor using low-frequency sine-waves as primitive probes in our previous study. However, we found that asynchrony of sine-wave pair presented on adjacent fingers was difficult to detect. Here, to take advantage of the small receptive field, we investigated within-finger motion and found above threshold performance when observers touched localized sine-wave stimuli with one finger. Though observers could not perceptually discriminate rightward from leftward motion, the adaptation occurred in a direction-sensitive way: the motion/asynchronous detection was impaired by adapting to asynchronous stimuli moving in the same direction. These findings are consistent with a possibility that human can directly encode short-range spatio-temporal patterns of skin deformation by using phase-shifted low-frequency components, in addition to detecting short- and long-range motion using energy shifts of high-frequency components.

Modulation frequency as a cue for auditory speed perception

Unlike vision, the mechanisms underlying auditory motion perception are poorly understood. Here we describe an auditory motion illusion revealing a novel cue to auditory speed perception: the temporal frequency of amplitude modulation (AM-frequency), typical for rattling sounds. Naturally, corrugated objects sliding across each other generate rattling sounds whose AM-frequency tends to directly correlate with speed. We found that AM-frequency modulates auditory speed perception in a highly systematic fashion: moving sounds with higher AM-frequency are perceived as moving faster than sounds with lower AM-frequency. Even more interestingly, sounds with higher AM-frequency also induce stronger motion aftereffects. This reveals the existence of specialized neural mechanisms for auditory motion perception, which are sensitive to AM-frequency. Thus, in spatial hearing, the brain successfully capitalizes on the AM-frequency of rattling sounds to estimate the speed of moving objects. This tightly parallels previous findings in motion vision, where spatio-temporal frequency of moving displays systematically affects both speed perception and the magnitude of the motion aftereffects. Such an analogy with vision suggests that motion detection may rely on canonical computations, with similar neural mechanisms shared across the different modalities.

Steady-State EEG and Psychophysical Measures of Multisensory Integration to Cross-Modally Synchronous and Asynchronous Acoustic and Vibrotactile Amplitude Modulation Rate

According to thetemporal principleof multisensory integration, cross-modal synchronisation of stimulus onset facilitates multisensory integration. This is typically observed as a greater response to multisensory stimulation relative to the sum of the constituent unisensory responses (i.e.,superadditivity). The aim of the present study was to examine whether the temporal principle extends to the cross-modal synchrony of amplitude-modulation (AM) rate. It is well established that psychophysical sensitivity to AM stimulation is strongly influenced by AM rate where the optimum rate differs according to sensory modality. This rate-dependent sensitivity is also apparent from EEG steady-state response (SSR) activity, which becomes entrained to the stimulation rate and is thought to reflect neural processing of the temporal characteristics of AM stimulation. In this study we investigated whether cross-modal congruence of AM rate reveals both psychophysical and EEG evidence of enhanced multisensory integration. To achieve this, EEG SSR and psychophysical sensitivity to simultaneous acoustic and/or vibrotactile AM stimuli were measured at cross-modally congruent and incongruent AM rates. While the results provided no evidence of superadditive multisensory SSR activity or psychophysical sensitivity, the complex pattern of results did reveal a consistent correspondence between SSR activity and psychophysical sensitivity to AM stimulation. This indicates that entrained EEG activity may provide a direct measure of cortical activity underlying multisensory integration. Consistent with the temporal principle of multisensory integration, increased vibrotactile SSR responses and psychophysical sensitivity were found for cross-modally congruent relative to incongruent AM rate. However, no corresponding increase in auditory SSR or psychophysical sensitivity was observed for cross-modally congruent AM rates. This complex pattern of results can be understood in terms of the likely influence of theprinciple of inverse effectivenesswhere the temporal principle of multisensory integration was only evident in the context of reduced perceptual sensitivity for the vibrotactile but not the auditory modality.

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.

The Effect of Contact Force on the Responses of Tactile Nerve Fibers to Scanned Textures

The perception of fine textures relies on highly precise and repeatable spiking patterns evoked in tactile afferents. These patterns have been shown to depend not only on the surface microstructure and material but also on the speed at which it moves across the skin. Interestingly, the perception of texture is independent of scanning speed, implying the existence of downstream neural mechanisms that correct for scanning speed in interpreting texture signals from the periphery. What force is applied during texture exploration also has negligible effects on how the surface is perceived, but the consequences of changes in contact force on the neural responses to texture have not been described. In the present study, we measure the signals evoked in tactile afferents of macaques to a diverse set of textures scanned across the skin at two different contact forces and find that responses are largely independent of contact force over the range tested. We conclude that the force invariance of texture perception reflects the force independence of texture representations in the nerve.

Learning and recognition of tactile temporal sequences by mice and humans

The world around us is replete with stimuli that unfold over time. When we hear an auditory stream like music or speech or scan a texture with our fingertip, physical features in the stimulus are concatenated in a particular order. This temporal patterning is critical to interpreting the stimulus. To explore the capacity of mice and humans to learn tactile sequences, we developed a task in which subjects had to recognise a continuous modulated noise sequence delivered to whiskers or fingertips, defined by its temporal patterning over hundreds of milliseconds. GO and NO-GO sequences differed only in that the order of their constituent noise modulation segments was temporally scrambled. Both mice and humans efficiently learned tactile sequences. Mouse sequence recognition depended on detecting transitions in noise amplitude; animals could base their decision on the earliest information available. Humans appeared to use additional cues, including the duration of noise modulation segments.

DOI:http://dx.doi.org/10.7554/eLife.27333.001

Speed invariance of tactile texture perception

The nervous system achieves stable perceptual representations of objects despite large variations in the activity patterns of sensory receptors. Here, we explore perceptual constancy in the sense of touch. Specifically, we investigate the invariance of tactile texture perception across changes in scanning speed. Texture signals in the nerve have been shown to be highly dependent on speed: temporal spiking patterns in nerve fibers that encode fine textural features contract or dilate systematically with increases or decreases in scanning speed, respectively, resulting in concomitant changes in response rate. Nevertheless, texture perception has been shown, albeit with restricted stimulus sets and limited perceptual assays, to be independent of scanning speed. Indeed, previous studies investigated the effect of scanning speed on perceived roughness, only one aspect of texture, often with impoverished stimuli, namely gratings and embossed dot patterns. To fill this gap, we probe the perceptual constancy of a wide range of textures using two different paradigms: one that probes texture perception along well-established sensory dimensions independently and one that probes texture perception as a whole. We find that texture perception is highly stable across scanning speeds, irrespective of the texture or the perceptual assay. Any speed-related effects are dwarfed by differences in percepts evoked by different textures. This remarkable speed invariance of texture perception stands in stark contrast to the strong dependence of the texture responses of nerve fibers on scanning speed. Our results imply neural mechanisms that compensate for scanning speed to achieve stable representations of surface texture.NEW & NOTEWORTHY Our brain forms stable representations of objects regardless of viewpoint, a phenomenon known as invariance that has been described in several sensory modalities. Here, we explore invariance in the sense of touch and show that the tactile perception of texture does not depend on scanning speed. This perceptual constancy implies neural mechanisms that extract information about texture from the response of nerve fibers such that the resulting neural representation is stable across speeds.

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.

Spike Timing Matters in Novel Neuronal Code Involved in Vibrotactile Frequency Perception

Skin vibrations sensed by tactile receptors contribute significantly to the perception of object properties during tactile exploration [1-4] and to sensorimotor control during object manipulation [5]. Sustained low-frequency skin vibration (<60 Hz) evokes a distinct tactile sensation referred to as flutter whose frequency can be clearly perceived [6]. How afferent spiking activity translates into the perception of frequency is still unknown. Measures based on mean spike rates of neurons in the primary somatosensory cortex are sufficient to explain performance in some frequency discrimination tasks [7-11]; however, there is emerging evidence that stimuli can be distinguished based also on temporal features of neural activity [12, 13]. Our study's advance is to demonstrate that temporal features are fundamental for vibrotactile frequency perception. Pulsatile mechanical stimuli were used to elicit specified temporal spike train patterns in tactile afferents, and subsequently psychophysical methods were employed to characterize human frequency perception. Remarkably, the most salient temporal feature determining vibrotactile frequency was not the underlying periodicity but, rather, the duration of the silent gap between successive bursts of neural activity. This burst gap code for frequency represents a previously unknown form of neural coding in the tactile sensory system, which parallels auditory pitch perception mechanisms based on purely temporal information where longer inter-pulse intervals receive higher perceptual weights than short intervals [14]. Our study also demonstrates that human perception of stimuli can be determined exclusively by temporal features of spike trains independent of the mean spike rate and without contribution from population response factors.

Edge orientation signals in tactile afferents of macaques

The orientation of edges indented into the skin has been shown to be encoded in the responses of neurons in primary somatosensory cortex in a manner that draws remarkable analogies to their counterparts in primary visual cortex. According to the classical view, orientation tuning arises from the integration of untuned input from thalamic neurons with aligned but spatially displaced receptive fields (RFs). In a recent microneurography study with human subjects, the precise temporal structure of the responses of individual mechanoreceptive afferents to scanned edges was found to carry information about their orientation. This putative mechanism could in principle contribute to or complement the classical rate-based code for orientation. In the present study, we further examine orientation information carried by mechanoreceptive afferents of Rhesus monkeys. To this end, we record the activity evoked in cutaneous mechanoreceptive afferents when edges are indented into or scanned across the skin. First, we confirm that information about the edge orientation can be extracted from the temporal patterning in afferent responses of monkeys, as is the case in humans. Second, we find that while the coarse temporal profile of the response can be predicted linearly from the layout of the RF, the fine temporal profile cannot. Finally, we show that orientation signals in tactile afferents are often highly dependent on stimulus features other than orientation, which complicates putative decoding strategies. We discuss the challenges associated with establishing a neural code at the somatosensory periphery, where afferents are exquisitely sensitive and nearly deterministic.