The vibrations of texture

The Pacinian channel has been implicated in the perception of fine textures (Hollins et al. , Somatosens Mot Res 18: 253-262, 2001a). In the present study, we investigate candidate codes for Pacinian-mediated roughness perception. We use a Hall effect transducer to record the vibrations elicited in the skin when a set of textured surfaces is passively presented to the index finger. The peak frequency of the vibrations is found to decrease systematically as spatial period increases. The power of the vibrations--weighted according to the spectral sensitivity of the Pacinian system--increases with spatial period for all but the coarsest surfaces. By varying the scanning velocity, we manipulate the temporal and intensive characteristics of the texture-induced vibrations and assess the effect of the manipulation on perceived roughness. We find that doubling the scanning velocity does not result in the substantial decrease in roughness predicted by a frequency theory of vibrotactile roughness perception. On the other hand, the effects of speed on roughness match those of speed on power. We propose that the roughness of a fine surface (spatial period<200 &#55 m) is a function of the Pacinian-weighted power of the vibrations it elicits.     

Vibrotactile adaptation impairs discrimination of fine,but not coarse,textures

The effect of vibrotactile adaptation on the ability to discriminate textured surfaces was examined in three experiments. The surfaces were rectilinear arrays of pyramids produced by etching of silicon wafers. Adaptation to 100-Hz vibration severely hampered discrimination of surfaces with spatial periods below 100 &#119 m (Experiment 1), but had little effect on the discrimination of coarser textures (Experiment 2). To determine which vibrotactile channel—Rapidly Adapting or Pacinian—plays the larger role in mediating the discrimination of fine textures, widely separated adapting frequencies (10 and 250 Hz) were used in Experiment 3. The fact that high- but not low-frequency adaptation interfered with discrimination suggests that the Pacinian system contributes importantly to this ability. Taken as a whole, the results of this study strongly support the duplex theory of tactile texture perception, according to which different mechanisms—spatial and vibrotactile—mediate the perception of coarse and fine textures, respectively.     

The effect of surface wave propagation on neural responses to vibration in primate glabrous skin

Because tactile perception relies on the response of large populations of receptors distributed across the skin, we seek to characterize how a mechanical deformation of the skin at one location affects the skin at another. To this end, we introduce a novel non-contact method to characterize the surface waves produced in the skin under a variety of stimulation conditions. Specifically, we deliver vibrations to the fingertip using a vibratory actuator and measure, using a laser Doppler vibrometer, the surface waves at different distances from the locus of stimulation. First, we show that a vibration applied to the fingertip travels at least the length of the finger and that the rate at which it decays is dependent on stimulus frequency. Furthermore, the resonant frequency of the skin matches the frequency at which a subpopulation of afferents, namely Pacinian afferents, is most sensitive. We show that this skin resonance can lead to a two-fold increase in the strength of the response of a simulated afferent population. Second, the rate at which vibrations propagate across the skin is dependent on the stimulus frequency and plateaus at 7 m/s. The resulting delay in neural activation across locations does not substantially blur the temporal patterning in simulated populations of afferents for frequencies less than 200 Hz, which has important implications about how vibratory frequency is encoded in the responses of somatosensory neurons. Third, we show that, despite the dependence of decay rate and propagation speed on frequency, the waveform of a complex vibration is well preserved as it travels across the skin. Our results suggest, then, that the propagation of surface waves promotes the encoding of spectrally complex vibrations as the entire neural population is exposed to essentially the same stimulus. We also discuss the implications of our results for biomechanical models of the skin.     

Texture perception through direct and indirect touch: an analysis of perceptual space for tactile textures in two modes of exploration

Considerable information about the texture of objects can be perceived remotely through a probe. It is not clear, however, how texture perception with a probe compares with texture perception with the bare finger. Here we investigate the perception of a variety of textured surfaces encountered daily (e.g., corduroy, paper, and rubber) using the two scanning modes - direct touch through the finger and indirect touch through a probe held in the hand - in two tasks. In the first task, subjects rated the overall pair-wise dissimilarity of the textures. In the second task, subjects rated each texture along three continua, namely, perceived roughness, hardness, and stickiness of the surfaces, shown previously as the primary dimensions of texture perception in direct touch. From the dissimilarity judgment experiment, we found that the texture percept is similar though not identical in the two scanning modes. From the adjective rating experiments, we found that while roughness ratings are similar, hardness and stickiness ratings tend to differ between scanning conditions. These differences between the two modes of scanning are apparent in perceptual space for tactile textures based on multidimensional scaling (MDS) analysis. Finally, we demonstrate that three physical quantities, vibratory power, compliance, and friction carry roughness, hardness, and stickiness information, predicting perceived dissimilarity of texture pairs with indirect touch. Given that different types of texture information are processed by separate groups of neurons across direct and indirect touch, we propose that the neural mechanisms underlying texture perception differ between scanning modes.     

Texture perception through direct and indirect touch: An analysis of perceptual space for tactile textures in two modes of exploration

Considerable information about the texture of objects can be perceived remotely through a probe. It is not clear, however, how texture perception with a probe compares with texture perception with the bare finger. Here we investigate the perception of a variety of textured surfaces encountered daily (e.g., corduroy, paper, and rubber) using the two scanning modes—direct touch through the finger and indirect touch through a probe held in the hand—in two tasks. In the first task, subjects rated the overall pair-wise dissimilarity of the textures. In the second task, subjects rated each texture along three continua, namely, perceived roughness, hardness, and stickiness of the surfaces, shown previously as the primary dimensions of texture perception in direct touch. From the dissimilarity judgment experiment, we found that the texture percept is similar though not identical in the two scanning modes. From the adjective rating experiments, we found that while roughness ratings are similar, hardness and stickiness ratings tend to differ between scanning conditions. These differences between the two modes of scanning are apparent in perceptual space for tactile textures based on multidimensional scaling (MDS) analysis. Finally, we demonstrate that three physical quantities, vibratory power, compliance, and friction carry roughness, hardness, and stickiness information, predicting perceived dissimilarity of texture pairs with indirect touch. Given that different types of texture information are processed by separate groups of neurons across direct and indirect touch, we propose that the neural mechanisms underlying texture perception differ between scanning modes.     

Perception of the tactile texture of raised-dot patterns: a multidimensional analysis

An ALSCAL multidimensional scaling analysis in Euclidean space revealed that three orthogonal perceptual dimensions can account for the judged tactile dissimilarities of raised-dot patterns. Through magnitude estimates of various perceptual attributes, it was determined that the three dimensions consist of blur, roughness, and clarity. The only effect that selective adaptation of the Pacinian (P) channel had was to change the perceptual clarity of the raised dots against their background. Adaptation of the P channel with a 20 dB SL 250 Hz stimulus enhanced clarity. As indicated by magnitude estimates, adaptation of the P channel by the 250 Hz stimulus had no effect on the perceived roughness of the dot pattern but did cause the individual dots of the textured pattern to feel smoother. When the observer was required to estimate magnitude "overall roughness" defined as a combination of dot-pattern roughness and individual-dot roughness, adaptation of the P channel affected perceived roughness by reducing it. Taken as a whole, the results are consistent with the hypothesis that the NP channels and the P channel jointly influence the perception of textured surfaces.     

Responses from Area 3b of Somatosensory Cortex to Textured Surfaces during Active Touch in Primate

(1) The purpose of this experiment was to characterize the responses of neurons in somatosensory cortex while the hand was actively moved (stroked) across a textured surface. Surfaces consisted of horizontal gratings that varied by spatial period or ridge-groove ratio (roughness). Surfaces were attached to rectangular blocks. TOP and BOTTOM halves of each block could contain surfaces of different roughness. (2) Velocity and force of the stroke were behaviorally constrained within certain limits and continuously measured and recorded during the stroke. (3) Response samples for each neuron were obtained for repeated presentations of each surface. Statistical analyses consisted of analysis of variance and t tests across surfaces on the data of each neuron, and summary statistics on groups of neurons with similar response characteristics. The interaction effects of behavioral variables (velocity and force) were examined and found not to be significant. (4) The sample mainly consisted of rapidly adapting neurons in area 3b of somatosensory area I (SI). Three main response types were found: (a) GRADED cells showed a monotonic increase in firing rate to increasingly rougher surfaces. This effect was seen in one-third of cells studied and is consistent with other reports. These cells seem to code roughness in the magnitude of their response, (b) In some cells, response to a BOTTOM surface depended on the roughness of the preceding TOP surface. This is analogous to contrast in the visual system. These CONTRAST cells are a novel finding in the somatosensory system, (c) Some cells only responded to surfaces that were completely smooth. These “OFF”-response-type cells were seen in proximity to other cells that responded in a reciprocal fashion to surfaces with ridges, but not to smooth surfaces. SMOOTH cells did not respond to punctate or passively applied stimuli, and therefore could not be classified by adaptation of the responses. (5) An increase in firing rate as spatial period (roughness) increases (with a constant ratio of ridge to groove) seems contrary to vibratory models of texture perception. As spatial period increases, temporal frequency decreases, and thus “tuned” cells should show a decreased response rate. Yet GRADED cells showed an increased response. In addition, response varied on surfaces with different groove size, where spatial period, and thus temporal period, was constant. This suggests that in rapidly adapting neurons, at least for these simple surfaces, texture is coded by the magnitude of the firing rates rather than by its temporal fidelity. Reduced response to smoother surfaces does not exclude increased phase locking, however, so that GRADED cells may still be the same cells that respond to vibration.     

Roughness perception in tactile channels: Evidence for an opponent process in the sense of touch

Abstract

Magnitude estimates of the tactile roughness of raised-dot surfaces revealed that perceived overall roughness, defined as the combination of the perceived roughness of the dot pattern and the perceived roughness of the individual dots in the pattern, is an inverted U-shaped function of dot spacing, reaching a maximum at approximately 3.0?mm of dot separation. The hypothesis that Pacinian corpuscles are involved in roughness perception has been supported by the finding that selective adaptation of the Pacinian corpuscle (PC) channel with a 250-Hz stimulus at 20-dB SL results in a decrease in the perceived overall roughness of the raised-dot surface at the fingertip. The effect of PC channel adaptation on perceived overall roughness was attributable entirely to a reduction in the perceived roughness of the individual raised dots; PC adaptation had no effect on the perceived roughness of the raised-dot pattern. Selective adaptation of the slowly adapting type I (SA I) channel with a 5-Hz stimulus at 20-dB SL had the opposite effect of PC channel adaptation and resulted in an increase in the perceived roughness of the individual raised dots, and consequently the perceived overall roughness of the raised-dot surface. As was the case with PC channel adaptation, SA I channel adaptation had no effect on the perceived roughness of the pattern. Adaptation with a compound adapting stimulus containing 5- and 250-Hz components at 20-dB SL had no effect on perceived overall roughness, which suggests that the PC and SA I channels operate antagonistically in an opponent-process fashion in the perception of the microstructure of a textured surface. Neither PC adaptation nor SA I adaptation affected perceived pattern roughness, which suggests that pattern roughness is coded by relative rather than by absolute spatial variation in firing rate.     

Electromechanical model for object roughness perception during finger sliding

Touch allows us to gather abundant information in the world around us. However, how sensory cells embedded in the fingers convey texture information into their firing patterns is still poorly understood. Here, we develop an electromechanical model for roughness perception by incorporating main ingredients such as voltage-gated ion channels, active ion pumps, mechanosensitive channels, and cell deformation. The model reveals that sensory cells can convey texture wavelengths into the period of their firing patterns as the finger slides across object surfaces, but they can only convey a limited range of texture wavelengths. We also show that an increase in sliding speed broadens the decoding wavelength range at the cost of reduction of lower perception limits. Thus, a smaller sliding speed and a bigger contact force may be needed to successfully discern a smooth surface, consistent with previous psychophysical observations. Moreover, we show that cells with slowly adapting mechanosensitive channels can still fire action potentials under static loadings, indicating that slowly adapting mechanosensitive channels may contribute to the perception of coarse textures under static touch. Our work thus provides a new theoretical framework to study roughness perception and may have important implications for the design of electronic skin, artificial touch, and haptic interfaces.     

Perception of the tactile texture of raised-dot patterns: A multidimensional analysis

An ALSCAL multidimensional scaling analysis in Euclidean space revealed that three orthogonal perceptual dimensions can account for the judged tactile dissimilarities of raised-dot patterns. Through magnitude estimates of various perceptual attributes, it was determined that the three dimensions consist of blur, roughness, and clarity. The only effect that selective adaptation of the Pacinian (P) channel had was to change the perceptual clarity of the raised dots against their background. Adaptation of the P channel with a 20?dB SL 250?Hz stimulus enhanced clarity. As indicated by magnitude estimates, adaptation of the P channel by the 250?Hz stimulus had no effect on the perceived roughness of the dot pattern but did cause the individual dots of the textured pattern to feel smoother. When the observer was required to estimate magnitude “overall roughness” defined as a combination of dot-pattern roughness and individual-dot roughness, adaptation of the P channel affected perceived roughness by reducing it. Taken as a whole, the results are consistent with the hypothesis that the NP channels and the P channel jointly influence the perception of textured surfaces.     

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.     

Laser scanning reveals bryophyte canopy structure

We evaluated laser scanning as a method to provide depth measurements for bryophyte canopies at fine spatial scales to derive surface roughness (Lr), a structural parameter. Depths to the first vertical canopy contact were measured on 5 x 5 cm2 areas of 27 bryophyte canopies using a contact probe, a commercial laser scanner and a scanner employing a laser diode striper (LED scanner). Laser scanning adequately distinguished structural types, but scanner configuration led to differences in the magnitude of Lr. LED scanning did not damage photosystem II function in three bryophyte species, Bazzania trilobata, Sphagnum girgensohnii and Pleurozium schreberi, as evidenced by no change in the chlorophyll fluorescence parameter FV/FM following LED scanning, but a decrease when subjected to high light. A previously published boundary layer conductance model was parameterized with surface roughness values determined using a laser scanner and compared with the results obtained with contact probe measures. The resulting parameters of the functional models did not differ significantly from each other.     

Experiments on Ultrasonic Lubrication Using a Piezoelectrically-assisted Tribometer and Optical Profilometer

Friction and wear are detrimental to engineered systems. Ultrasonic lubrication is achieved when the interface between two sliding surfaces is vibrated at a frequency above the acoustic range (20 kHz). As a solid-state technology, ultrasonic lubrication can be used where conventional lubricants are unfeasible or undesirable. Further, ultrasonic lubrication allows for electrical modulation of the effective friction coefficient between two sliding surfaces. This property enables adaptive systems that modify their frictional state and associated dynamic response as the operating conditions change. Surface wear can also be reduced through ultrasonic lubrication. We developed a protocol to investigate the dependence of friction force reduction and wear reduction on the linear sliding velocity between ultrasonically lubricated surfaces. A pin-on-disc tribometer was built which differs from commercial units in that a piezoelectric stack is used to vibrate the pin at 22 kHz normal to the rotating disc surface. Friction and wear metrics including effective friction force, volume loss, and surface roughness are measured without and with ultrasonic vibrations at a constant pressure of 1 to 4 MPa and three different sliding velocities: 20.3, 40.6, and 87 mm/sec. An optical profilometer is utilized to characterize the wear surfaces. The effective friction force is reduced by 62% at 20.3 mm/sec. Consistently with existing theories for ultrasonic lubrication, the percent reduction in friction force diminishes with increasing speed, down to 29% friction force reduction at 87 mm/sec. Wear reduction remains essentially constant (49%) at the three speeds considered.     

Neuronal encoding of texture in the whisker sensory pathway

A major challenge of sensory systems neuroscience is to quantify brain activity underlying perceptual experiences and to explain this activity as the outcome of elemental neuronal response properties. Rats make extremely fine discriminations of texture by “whisking” their vibrissae across an object's surface, yet the neuronal coding underlying texture sensations remains unknown. Measuring whisker vibrations during active whisking across surfaces, we found that each texture results in a unique “kinetic signature” defined by the temporal profile of whisker velocity. We presented these texture-induced vibrations as stimuli while recording responses of first-order sensory neurons and neurons in the whisker area of cerebral cortex. Each texture is encoded by a distinctive, temporally precise firing pattern. To look for the neuronal coding properties that give rise to texture-specific firing patterns, we delivered horizontal and vertical whisker movements that varied randomly in time (“white noise”) and found that the response probabilities of first-order neurons and cortical neurons vary systematically according to whisker speed and direction. We applied the velocity-tuned spike probabilities derived from white noise to the sequence of velocity features in the texture to construct a simulated texture response. The close match between the simulated and real responses indicates that texture coding originates in the selectivity of neurons to elemental kinetic events.     

Thresholds for the perception of hand-transmitted vibration: dependence on contact area and contact location

The detection of vibration applied to the glabrous skin of the hand varies with contact conditions. Three experiments have been conducted to relate variations in the perception of hand-transmitted vibration to previously reported properties of tactile channels. The effects of a surround around the area of contact, the size of the area of contact, the location of the area of contact, the contact force, and the hand posture on perception of thresholds were determined for 8-500 Hz vibration. Removal of a surround around a contact area on the fingertip elevated thresholds of the NP II channel (FA I fibres) at frequencies less than 31.5 Hz and reduced thresholds of the Pacinian channel (FA II fibres) at frequencies greater than about 63 Hz. When no surround was present, thresholds reduced systematically as the contact area increased from the fingertip to the whole hand at frequencies from 16 to 125 Hz, although the decrease was not inversely proportional to the increase in contact area. The results are partly explained by spatial summation in the Pacinian channel (FA II fibres) and the involvement of the NP II channel (SA II) with some influence of biodynamic responses and contact pressures. There were regional differences in sensitivity over the hand within the NP I channel but not within the Pacinian channel: the NP I thresholds (less than 31.5 Hz) decreased from proximal to distal regions of the hand, whereas the Pacinian thresholds (125 Hz) were independent of contact location over the hand.     

Surface roughness affects the running speed of tropical canopy ants

Cursorial central‐place foragers like ants are expected to minimize travel costs by choosing the least resistive pathways to food resources. Tropical arboreal and semi‐arboreal ants locomote over a variety of plant surfaces, and their choice of pathways is selective. We measured the roughness of tree trunk and liana stem surfaces using laser scanning technology, and explored its consequences for running speed in various ant taxa. The average amplitude of tree trunk surface roughness differed interspecifically, and ranged from 1.4–2.2 mm among three common tree species (Anacardium excelsum, Alseis blackiana, and Dipteryx panamensis). The roughness of liana stems also varied interspecifically (among Tontelea ovalifolia, Bauhinia sp. and Paullinia sp.) and was an order of magnitude lower than tree surface roughness (mean amplitude ranged 0.09–0.19 mm). Field observations of various ant species foraging on tree trunks and liana stems, and on dowels covered with sandpaper, showed that their running speed declined with increasing amplitude of roughness. The effect of roughness on running speed was strongest for mid‐sized ants (Azteca trigona and Dolichoderus bispinosus). The accumulation rate of ants at baits did not vary with tree surface roughness, but was significantly lower on moss‐covered versus moss‐free bark. Collectively, these results indicate that the quality of plant substrates can influence the foraging patterns of arboreal ants, but likely is more important for resource discovery than for dominance on bare tree surfaces.     

Effect of surface roughness on slip flows in hydrophobic and hydrophilic microchannels by molecular dynamics simulation

The influences of surface roughness on the boundary conditions for a simple fluid flowing over hydrophobic and hydrophilic surfaces are investigated by molecular dynamics (MD) simulation. The degree of slip is found to decrease with surface roughness for both the hydrophobic and hydrophilic surfaces. The flow rates measured in hydrophobic channels are larger than those in hydrophilic channels with the presence of slip velocity at the walls. The simulation results of flow rate are correlated with the theoretical predictions according to the assumption of no slip boundary condition. The slip boundary condition also strongly depends on the shear rate near the surface. For hydrophobic surfaces, apparent fluid slips are observed on smooth and rough surfaces. For simple fluids flowing over a hydrophobic surface, the slip length increases linearly with shear rate for both the smooth and rough surfaces. Alternately, the slip length has a power law dependence on the shear rate for the cases of hydrophilic surfaces. It is observed that there is a no-slip boundary condition only when shear rate is low, and partial slip occurs when it exceeds a critical level.     

Increasing neural network robustness improves match to macaque V1 eigenspectrum,spatial frequency preference and predictivity

Task-optimized convolutional neural networks (CNNs) show striking similarities to the ventral visual stream. However, human-imperceptible image perturbations can cause a CNN to make incorrect predictions. Here we provide insight into this brittleness by investigating the representations of models that are either robust or not robust to image perturbations. Theory suggests that the robustness of a system to these perturbations could be related to the power law exponent of the eigenspectrum of its set of neural responses, where power law exponents closer to and larger than one would indicate a system that is less susceptible to input perturbations. We show that neural responses in mouse and macaque primary visual cortex (V1) obey the predictions of this theory, where their eigenspectra have power law exponents of at least one. We also find that the eigenspectra of model representations decay slowly relative to those observed in neurophysiology and that robust models have eigenspectra that decay slightly faster and have higher power law exponents than those of non-robust models. The slow decay of the eigenspectra suggests that substantial variance in the model responses is related to the encoding of fine stimulus features. We therefore investigated the spatial frequency tuning of artificial neurons and found that a large proportion of them preferred high spatial frequencies and that robust models had preferred spatial frequency distributions more aligned with the measured spatial frequency distribution of macaque V1 cells. Furthermore, robust models were quantitatively better models of V1 than non-robust models. Our results are consistent with other findings that there is a misalignment between human and machine perception. They also suggest that it may be useful to penalize slow-decaying eigenspectra or to bias models to extract features of lower spatial frequencies during task-optimization in order to improve robustness and V1 neural response predictivity.     

Moving from spatially segregated to transparent motion: A modelling approach

Motion transparency, in which patterns of moving elements group together to give the impression of lacy overlapping surfaces, provides an important challenge to models of motion perception. It has been suggested that we perceive transparent motion when the shape of the velocity histogram of the stimulus is bimodal. To investigate this further, random-dot kinematogram motion sequences were created to simulate segregated (perceptually spatially separated) and transparent (perceptually overlapping) motion. The motion sequences were analysed using the multi-channel gradient model (McGM) to obtain the speed and direction at every pixel of each frame of the motion sequences. The velocity histograms obtained were found to be quantitatively similar and all were bimodal. However, the spatial and temporal properties of the velocity field differed between segregated and transparent stimuli. Transparent stimuli produced patches of rightward and leftward motion that varied in location over time. This demonstrates that we can successfully differentiate between these two types of motion on the basis of the time varying local velocity field. However, the percept of motion transparency cannot be based simply on the presence of a bimodal velocity histogram.     

Multiple parietal operculum subdivisions in humans: tactile activation maps

We focused the present analysis on blood-oxygen-level-dependent responses evoked in four architectonic subdivisions of human posterior parietal operculum (PO) during two groups of tasks involving either vibrotactile stimulation or rubbing different surfaces against the right index finger pad. Activity localized in previously defined parietal opercular subdivisions, OP 1-4, was co-registered to a standard cortical surface-based atlas. Four vibrotactile stimulation tasks involved attention to the parameters of paired vibrations: (1) detect rare target trials when vibration frequencies matched; (2) select the presentation order of the vibration with a higher frequency or (3) longer duration; and (4) divide attention between frequency and duration before selecting stimulus order. Surface stimulation tasks involved various discriminations of different surfaces: (1) smooth surfaces required no discrimination; (2) paired horizontal gratings required determination of the direction of roughness change; (3) paired shapes entailed identifying matched and unmatched shapes; (4) raised letters involved letter recognition. The results showed activity in multiple somatosensory subdivisions bilaterally in human PO that are plausibly homologues of somatosensory areas previously described in animals. All tasks activated OP 1, but in vibrotactile tasks foci were more restricted compared to moving surface tasks. Greater spatial extents of activity especially in OP 1 and 4 when surfaces rubbed the finger pad did not support previously reported somatotopy of the second finger representation in "S2". The varied activity distributions across OP subdivisions may reflect low-level perceptual and/or cognitive processing differences between tasks.