High-dimensional representation of texture in somatosensory cortex of primates

Crossmodal associations between naturally occurring tactile and sound textures

This study investigates the crossmodal associations between naturally occurring sound textures and tactile textures. Previous research has demonstrated the association between low-level sensory features of sound and touch, as well as higher-level, cognitively mediated associations involving language, emotions, and metaphors. However, stimuli like textures, which are found in both modalities have received less attention. In this study, we conducted two experiments: a free association task and a two alternate forced choice task using everyday tactile textures and sound textures selected from natural sound categories. The results revealed consistent crossmodal associations reported by participants between the textures of the two modalities. They tended to associate more sound textures (e.g., wood shavings and sandpaper) with tactile surfaces that were rated as harder, rougher, and intermediate on the sticky-slippery scale. While some participants based the auditory-tactile association on sensory features, others made the associations based on semantic relationships, co-occurrence in nature, and emotional mediation. Interestingly, the statistical features of the sound textures (mean, variance, kurtosis, power, autocorrelation, and correlation) did not show significant correlations with the crossmodal associations, indicating a higher-level association. This study provides insights into auditory-tactile associations by highlighting the role of sensory and emotional (or cognitive) factors in prompting these associations.

In your skin? Somatosensory cortex is purposely recruited to situate but not simulate vicarious touch

Previous studies of vicarious touch suggest that we automatically simulate observed touch experiences in our own body representation including primary and secondary somatosensory cortex (SCx). However, whether these early sensory areas are activated in a reflexive manner and the extent with which such SCx activations represent touch qualities, like texture, remains unclear. We measured event-related potentials (ERPs) of SCx's hierarchical processing stages, which map onto successive somatosensory ERP components, to investigate the timing of vicarious touch effects. In the first experiment, participants (n = 43) merely observed touch or no-touch to a hand; in the second, participants saw different touch textures (soft foam and hard rubber) either touching a hand (other-directed) or they were instructed that the touch was self-directed and to feel the touch. Each touch sequence was followed by a go/no-go task. We probed SCx activity and isolated SCx vicarious touch activations from visual carry over effects. We found that vicarious touch conditions (touch versus no-touch and soft versus hard) did not modulate early sensory ERP components (i.e. P50, N80); but we found effects on behavioural responses to the subsequent go/no-go stimulus consistent with post-perceptual effects. When comparing other- with self-directed touch conditions, we found that early and mid-latency components (i.e. P50, N80, P100, N140) were modulated consistent with early SCx activations. Importantly, these early sensory activations were not modulated by touch texture. Therefore, SCx is purposely recruited when participants are instructed to attend to touch; but such activation only situates, rather than fully simulates, the seen tactile experience in SCx.

Restoration of sensory information via bionic hands

Individuals who have lost the use of their hands because of amputation or spinal cord injury can use prosthetic hands to restore their independence. A dexterous prosthesis requires the acquisition of control signals that drive the movements of the robotic hand, and the transmission of sensory signals to convey information to the user about the consequences of these movements. In this Review, we describe non-invasive and invasive technologies for conveying artificial sensory feedback through bionic hands, and evaluate the technologies' long-term prospects.

A Goldilocks theory of cognitive control: Balancing precision and efficiency with low-dimensional control states

Cognitive control orchestrates interactions between brain regions, guiding the transformation of information to support contextually appropriate and goal-directed behaviors. In this review, we propose a hierarchical model of cognitive control where low-dimensional control states direct the flow of high-dimensional representations between regions. This allows cognitive control to flexibly adapt to new environments and maintain the representational capacity to capture the richness of the world.

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.

Roughness perception: A multisensory/crossmodal perspective

Roughness is a perceptual attribute typically associated with certain stimuli that are presented in one of the spatial senses. In auditory research, the term is typically used to describe the harsh effects that are induced by particular sound qualities (i.e., dissonance) and human/animal vocalizations (e.g., screams, distress cries). In the tactile domain, roughness is a crucial factor determining the perceptual features of a surface. The same feature can also be ascertained visually, by means of the extraction of pattern features that determine the haptic quality of surfaces, such as grain size and density. By contrast, the term roughness has rarely been applied to the description of those stimuli perceived via the chemical senses. In this review, we take a critical look at the putative meaning(s) of the term roughness, when used in both unisensory and multisensory contexts, in an attempt to answer two key questions: (1) Is the use of the term 'roughness' the same in each modality when considered individually? and (2) Do crossmodal correspondences involving roughness match distinct perceptual features or (at least on certain occasions) do they merely pick-up on an amodal property? We start by examining the use of the term in the auditory domain. Next, we summarize the ways in which the term roughness has been used in the literature on tactile and visual perception, and in the domain of olfaction and gustation. Then, we move on to the crossmodal context, reviewing the literature on the perception of roughness in the audiovisual, audiotactile, and auditory-gustatory/olfactory domains. Finally, we highlight some limitations of the reviewed literature and we outline a number of key directions for future empirical research in roughness perception.

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.

Touch, Texture and Haptic Feedback: A Review on How We Feel the World around Us

Touch is one most of the important aspects of human life. Nearly all interactions, when broken down, involve touch in one form or another. Recent advances in technology, particularly in the field of virtual reality, have led to increasing interest in the research of haptics. However, accurately capturing touch is still one of most difficult engineering challenges currently being faced. Recent advances in technology such as those found in microcontrollers which allow the creation of smaller sensors and feedback devices may provide the solution. Beyond capturing and measuring touch, replicating touch is also another unique challenge due to the complexity and sensitivity of the human skin. The development of flexible, soft-wearable devices, however, has allowed for the creating of feedback systems that conform to the human form factor with minimal loss of accuracy, thus presenting possible solutions and opportunities. Thus, in this review, the researchers aim to showcase the technologies currently being used in haptic feedback, and their strengths and limitations.

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

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

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

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

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

Global surface features contribute to human haptic roughness estimations

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

Printing dynamic color palettes and layered textures through modeling-guided stacking of electrochromic polymers

In printable electrochromic polymer (ECP) displays, a wide color gamut, precise patterning, and controllable color switching are important. However, it is a significant challenge to achieve such features synergistically. Here, we present a solution-processable ECP stacking scheme, where a crosslinker is co-processed with three primary ECPs (ECP-Cyan, ECP-Magenta, and ECP-Yellow), which endows the primary ECPs with solvent-resistant properties and allows them to be sequentially deposited. Via varying the film thickness of each ECP layer, a full-color palette can be constructed. The ECP stacking strategy is further integrated with photolithography. Delicate multilayer patterns with overhang and undercut textures can be generated, allowing information displays with spatial dimensionality. In addition, via modulating the stacking sequence, the electrochemical onset potentials of the ECP components can be synchronized to reduce unwanted intermediate colors that are often found in co-processed ECPs. Should specific color properties be desired, COMSOL modeling could be applied to guide the stacking. We believe that this ECP stacking strategy opens a new avenue for electrochromic printing and displays.

Perception and Appreciation of Tactile Objects: The Role of Visual Experience and Texture Parameters

This exploratory study was designed to examine the effects of visual experience and specific texture parameters on both discriminative and aesthetic aspects of tactile perception. To this end, the authors conducted two experiments using a novel behavioral (ranking) approach in blind and (blindfolded) sighted individuals. Groups of congenitally blind, late blind, and (blindfolded) sighted participants made relative stimulus preference, aesthetic appreciation, and smoothness or softness judgment of two-dimensional (2D) or three-dimensional (3D) tactile surfaces through active touch. In both experiments, the aesthetic judgment was assessed on three affective dimensions, Relaxation, Hedonics, and Arousal, hypothesized to underlie visual aesthetics in a prior study. Results demonstrated that none of these behavioral judgments significantly varied as a function of visual experience in either experiment. However, irrespective of visual experience, significant differences were identified in all these behavioral judgments across the physical levels of smoothness or softness. In general, 2D smoothness or 3D softness discrimination was proportional to the level of physical smoothness or softness. Second, the smoother or softer tactile stimuli were preferred over the rougher or harder tactile stimuli. Third, the 3D affective structure of visual aesthetics appeared to be amodal and applicable to tactile aesthetics. However, analysis of the aesthetic profile across the affective dimensions revealed some striking differences between the forms of appreciation of smoothness and softness, uncovering unanticipated substructures in the nascent field of tactile aesthetics. While the physically softer 3D stimuli received higher ranks on all three affective dimensions, the physically smoother 2D stimuli received higher ranks on the Relaxation and Hedonics but lower ranks on the Arousal dimension. Moreover, the Relaxation and Hedonics ranks accurately overlapped with one another across all the physical levels of softness/hardness, but not across the physical levels of smoothness/roughness. These findings suggest that physical texture parameters not only affect basic tactile discrimination but differentially mediate tactile preferences, and aesthetic appreciation. The theoretical and practical implications of these novel findings are discussed.

Sensory computations in the cuneate nucleus of macaques

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

The neural mechanisms of manual dexterity

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

The interaction between motion and texture in the sense of touch

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

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

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

Information about contact force and surface texture is mixed in the firing rates of cutaneous afferent neurons

Cutaneous mechanoreceptors in our hands gather information about the objects we handle. Tactile fibers encode mixed information about contact events and object properties. Neural coding in tactile afferents is typically studied by varying a single aspect of tactile stimuli, avoiding the confounds of real-world haptic interactions. We instead record responses of small populations of dorsal root ganglia (DRG) neurons to variable tactile stimuli and find that neurons primarily respond to force, though some texture information can be detected. Tactile nerve fibers convey information about many features of haptic interactions, including the force and speed of contact, as well as the texture and shape of the objects being handled. How we perceive these object features is relatively unaffected by the forces and movements we use when interacting with the object. Because signals related to contact events and object properties are mixed in the responses of tactile fibers, our ability to disentangle these different components of our tactile experience implies that they are demultiplexed as they propagate along the neuraxis. To understand how texture and contact mechanics are encoded together by tactile fibers, we studied the activity of multiple neurons recorded simultaneously in the cervical DRG of two anesthetized rhesus monkeys while textured surfaces were applied to the glabrous skin of the fingers and palm using a handheld probe. A transducer at the tip of the textured probe measured contact forces as tactile stimuli were applied at different locations on the finger-pads and palm. We examined how a sample population of DRG neurons encode force and texture and found that firing rates of individual neurons are modulated by both force and texture. In particular, slowly adapting (SA) neurons were more responsive to force than texture, and rapidly adapting (RA) neurons were more responsive to texture than force. Although force could be decoded accurately throughout the entire contact interval, texture signals were most salient during onset and offset phases of the contact interval.NEW & NOTEWORTHY Cutaneous mechanoreceptors in our hands gather information about the objects we handle. Tactile fibers encode mixed information about contact events and object properties. Neural coding in tactile afferents is typically studied by varying a single aspect of tactile stimuli, avoiding the confounds of real-world haptic interactions. We instead record responses of small populations of DRG neurons to variable tactile stimuli and find that neurons primarily respond to force, though some texture information can be detected.

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.

In vivo microstimulation with cathodic and anodic asymmetric waveforms modulates spatiotemporal calcium dynamics in cortical neuropil and pyramidal neurons of male mice

Electrical stimulation has been critical in the development of an understanding of brain function and disease. Despite its widespread use and obvious clinical potential, the mechanisms governing stimulation in the cortex remain largely unexplored in the context of pulse parameters. Modeling studies have suggested that modulation of stimulation pulse waveform may be able to control the probability of neuronal activation to selectively stimulate either cell bodies or passing fibers depending on the leading polarity. Thus, asymmetric waveforms with equal charge per phase (i.e., increasing the leading phase duration and proportionately decreasing the amplitude) may be able to activate a more spatially localized or distributed population of neurons if the leading phase is cathodic or anodic, respectively. Here, we use two-photon and mesoscale calcium imaging of GCaMP6s expressed in excitatory pyramidal neurons of male mice to investigate the role of pulse polarity and waveform asymmetry on the spatiotemporal properties of direct neuronal activation with 10-Hz electrical stimulation. We demonstrate that increasing cathodic asymmetry effectively reduces neuronal activation and results in a more spatially localized subpopulation of activated neurons without sacrificing the density of activated neurons around the electrode. Conversely, increasing anodic asymmetry increases the spatial spread of activation and highly resembles spatiotemporal calcium activity induced by conventional symmetric cathodic stimulation. These results suggest that stimulation polarity and asymmetry can be used to modulate the spatiotemporal dynamics of neuronal activity thus increasing the effective parameter space of electrical stimulation to restore sensation and study circuit dynamics.

Low-Dimensional Spatiotemporal Dynamics Underlie Cortex-wide Neural Activity

Cognition arises from the dynamic flow of neural activity through the brain. To capture these dynamics, we used mesoscale calcium imaging to record neural activity across the dorsal cortex of awake mice. We found that the large majority of variance in cortex-wide activity (∼75%) could be explained by a limited set of ∼14 "motifs" of neural activity. Each motif captured a unique spatiotemporal pattern of neural activity across the cortex. These motifs generalized across animals and were seen in multiple behavioral environments. Motif expression differed across behavioral states, and specific motifs were engaged by sensory processing, suggesting the motifs reflect core cortical computations. Together, our results show that cortex-wide neural activity is highly dynamic but that these dynamics are restricted to a low-dimensional set of motifs, potentially allowing for efficient control of behavior.

Differential effects of the mode of touch, active and passive, on experience-driven plasticity in the S1 cutaneous digit representation of adult macaque monkeys

This study compared the receptive field (RF) properties and firing rates of neurons in the cutaneous hand representation of primary somatosensory cortex (areas 3b, 1, and 2) of 9 awake, adult macaques that were intensively trained in a texture discrimination task using active touch (fingertips scanned over the surfaces using a single voluntary movement), passive touch (surfaces displaced under the immobile fingertips), or both active and passive touch. Two control monkeys received passive exposure to the same textures in the context of a visual discrimination task. Training and recording extended over 1–2 yr per animal. All neurons had a cutaneous receptive field (RF) that included the tips of the stimulated digits (D3 and/or D4). In area 3b, RFs were largest in monkeys trained with active touch, smallest in those trained with passive touch, and intermediate in those trained with both; i.e., the mode of touch differentially modified the cortical representation of the stimulated fingers. The same trends were seen in areas 1 and 2, but the changes were not significant, possibly because a second experience-driven influence was seen in areas 1 and 2, but not in area 3b: smaller RFs with passive exposure to irrelevant tactile inputs compared with recordings from one naive hemisphere. We suggest that added feedback during active touch and higher cortical firing rates were responsible for the larger RFs with behavioral training; this influence was tempered by periods of more restricted sensory feedback during passive touch training in the active + passive monkeys.

NEW & NOTEWORTHY We studied experience-dependent sensory cortical plasticity in relation to tactile discrimination of texture using active and/or passive touch. We showed that neuronal receptive fields in primary somatosensory cortex, especially area 3b, are largest in monkeys trained with active touch, smallest in those trained with passive touch, and intermediate in those trained using both modes of touch. Prolonged, irrelevant tactile input had the opposite influence in areas 1 and 2, favoring smaller receptive fields.

Emergence of an Invariant Representation of Texture in Primate Somatosensory Cortex

A major function of sensory processing is to achieve neural representations of objects that are stable across changes in context and perspective. Small changes in exploratory behavior can lead to large changes in signals at the sensory periphery, thus resulting in ambiguous neural representations of objects. Overcoming this ambiguity is a hallmark of human object recognition across sensory modalities. Here, we investigate how the perception of tactile texture remains stable across exploratory movements of the hand, including changes in scanning speed, despite the concomitant changes in afferent responses. To this end, we scanned a wide range of everyday textures across the fingertips of rhesus macaques at multiple speeds and recorded the responses evoked in tactile nerve fibers and somatosensory cortical neurons (from Brodmann areas 3b, 1, and 2). We found that individual cortical neurons exhibit a wider range of speed-sensitivities than do nerve fibers. The resulting representations of speed and texture in cortex are more independent than are their counterparts in the nerve and account for speed-invariant perception of texture. We demonstrate that this separation of speed and texture information is a natural consequence of previously described cortical computations.

Creating a neuroprosthesis for active tactile exploration of textures

Intracortical microstimulation (ICMS) of the primary somatosensory cortex (S1) can produce percepts that mimic somatic sensation and, thus, has potential as an approach to sensorize prosthetic limbs. However, it is not known whether ICMS could recreate active texture exploration-the ability to infer information about object texture by using one's fingertips to scan a surface. Here, we show that ICMS of S1 can convey information about the spatial frequencies of invisible virtual gratings through a process of active tactile exploration. Two rhesus monkeys scanned pairs of visually identical screen objects with the fingertip of a hand avatar-controlled first via a joystick and later via a brain-machine interface-to find the object with denser virtual gratings. The gratings consisted of evenly spaced ridges that were signaled through individual ICMS pulses generated whenever the avatar's fingertip crossed a ridge. The monkeys learned to interpret these ICMS patterns, evoked by the interplay of their voluntary movements and the virtual textures of each object, to perform a sensory discrimination task. Discrimination accuracy followed Weber's law of just-noticeable differences (JND) across a range of grating densities; a finding that matches normal cutaneous sensation. Moreover, 1 monkey developed an active scanning strategy where avatar velocity was integrated with the ICMS pulses to interpret the texture information. We propose that this approach could equip upper-limb neuroprostheses with direct access to texture features acquired during active exploration of natural objects.

Feeling fooled: Texture contaminates the neural code for tactile speed

Motion is an essential component of everyday tactile experience: most manual interactions involve relative movement between the skin and objects. Much of the research on the neural basis of tactile motion perception has focused on how direction is encoded, but less is known about how speed is. Perceived speed has been shown to be dependent on surface texture, but previous studies used only coarse textures, which span a restricted range of tangible spatial scales and provide a limited window into tactile coding. To fill this gap, we measured the ability of human observers to report the speed of natural textures—which span the range of tactile experience and engage all the known mechanisms of texture coding—scanned across the skin. In parallel experiments, we recorded the responses of single units in the nerve and in the somatosensory cortex of primates to the same textures scanned at different speeds. We found that the perception of speed is heavily influenced by texture: some textures are systematically perceived as moving faster than are others, and some textures provide a more informative signal about speed than do others. Similarly, the responses of neurons in the nerve and in cortex are strongly dependent on texture. In the nerve, although all fibers exhibit speed-dependent responses, the responses of Pacinian corpuscle–associated (PC) fibers are most strongly modulated by speed and can best account for human judgments. In cortex, approximately half of the neurons exhibit speed-dependent responses, and this subpopulation receives strong input from PC fibers. However, speed judgments seem to reflect an integration of speed-dependent and speed-independent responses such that the latter help to partially compensate for the strong texture dependence of the former.

Our ability to sense the speed at which a surface moves across our skin is highly unreliable and depends on the texture of the surface. This study shows that speed illusions can be predicted from the responses of a specific population of nerve fibers and of their downstream targets; because the skin is too sparsely innervated to compute tactile speed accurately, the nervous system relies on a heuristic to estimate it.