On-going computation of whisking phase by mechanoreceptors

Interchangeable Role of Motor Cortex and Reafference for the Stable Execution of an Orofacial Action

Animals interact with their environment through mechanically active, mobile sensors. The efficient use of these sensory organs implies the ability to track their position; otherwise, perceptual stability or prehension would be profoundly impeded. The nervous system may keep track of the position of a sensorimotor organ via two complementary feedback mechanisms-peripheral reafference (external, sensory feedback) and efference copy (internal feedback). Yet, the potential contributions of these mechanisms remain largely unexplored. By training male rats to place one of their vibrissae within a predetermined angular range without contact, a task that depends on knowledge of vibrissa position relative to their face, we found that peripheral reafference is not required. The presence of motor cortex is not required either, except in the absence of peripheral reafference to maintain motor stability. Finally, the red nucleus, which receives descending inputs from motor cortex and cerebellum and projects to facial motoneurons, is critically involved in the execution of the vibrissa positioning task. All told, our results point toward the existence of an internal model that requires either peripheral reafference or motor cortex to optimally drive voluntary motion.SIGNIFICANCE STATEMENT How does an animal know where a mechanically active, mobile sensor lies relative to its body? We address this basic question in sensorimotor integration using the motion of the vibrissae in rats. We show that rats can learn to reliably position their vibrissae in the absence of sensory feedback or in the absence of motor cortex. Yet, when both sensory feedback and motor cortex are absent, motor precision is degraded. This suggests the existence of an internal model able to operate in closed- and open-loop modes, requiring either motor cortex or sensory feedback to maintain motor stability.

On the intrinsic curvature of animal whiskers

Facial vibrissae (whiskers) are thin, tapered, flexible, hair-like structures that are an important source of tactile sensory information for many species of mammals. In contrast to insect antennae, whiskers have no sensors along their lengths. Instead, when a whisker touches an object, the resulting deformation is transmitted to mechanoreceptors in a follicle at the whisker base. Previous work has shown that the mechanical signals transmitted along the whisker will depend strongly on the whisker's geometric parameters, specifically on its taper (how diameter varies with arc length) and on the way in which the whisker curves, often called "intrinsic curvature." Although previous studies have largely agreed on how to define taper, multiple methods have been used to quantify intrinsic curvature. The present work compares and contrasts different mathematical approaches towards quantifying this important parameter. We begin by reviewing and clarifying the definition of "intrinsic curvature," and then show results of fitting whisker shapes with several different functions, including polynomial, fractional exponent, elliptical, and Cesàro. Comparisons are performed across ten species of whiskered animals, ranging from rodents to pinnipeds. We conclude with a discussion of the advantages and disadvantages of using the various models for different modeling situations. The fractional exponent model offers an approach towards developing a species-specific parameter to characterize whisker shapes within a species. Constructing models of how the whisker curves is important for the creation of mechanical models of tactile sensory acquisition behaviors, for studies of comparative evolution, morphology, and anatomy, and for designing artificial systems that can begin to emulate the whisker-based tactile sensing of animals.

Demonstration of three-dimensional contact point determination and contour reconstruction during active whisking behavior of an awake rat

The rodent vibrissal (whisker) system has been studied for decades as a model of active touch sensing. There are no sensors along the length of a whisker; all sensing occurs at the whisker base. Therefore, a large open question in many neuroscience studies is how an animal could estimate the three-dimensional (3D) location at which a whisker makes contact with an object. In the present work we simulated the shape of a real rat whisker to demonstrate the existence of several unique mappings from triplets of mechanical signals at the whisker base to the three-dimensional whisker-object contact point. We then used high speed video to record whisker deflections as an awake rat whisked against a peg, and used the mechanics resulting from those deflections to extract the contact points along the peg surface. These results demonstrate that measurement of specific mechanical triplets at the base of a biological whisker can enable 3D contact point determination during natural whisking behavior. The approach is viable even though the biological whisker has non-ideal, non-planar curvature, and even given the rat’s real-world choices of whisking parameters. Visual intuition for the quality of the approach is provided in a video that shows the contour of the peg gradually emerging during active whisking behavior.

Contribution of Interneuron Subtype-Specific GABAergic Signaling to Emergent Sensory Processing in Mouse Somatosensory Whisker Barrel Cortex

Mammalian neocortex is important for conscious processing of sensory information with balanced glutamatergic and GABAergic signaling fundamental to this function. Yet little is known about how this interaction arises despite increasing insight into early GABAergic interneuron (IN) circuits. To study this, we assessed the contribution of specific INs to the development of sensory processing in the mouse whisker barrel cortex, specifically the role of INs in early speed coding and sensory adaptation. In wild-type animals, both speed processing and adaptation were present as early as the layer 4 critical period of plasticity and showed refinement over the period leading to active whisking onset. To test the contribution of IN subtypes, we conditionally silenced action-potential-dependent GABA release in either somatostatin (SST) or vasoactive intestinal peptide (VIP) INs. These genetic manipulations influenced both spontaneous and sensory-evoked cortical activity in an age- and layer-dependent manner. Silencing SST + INs reduced early spontaneous activity and abolished facilitation in sensory adaptation observed in control pups. In contrast, VIP + IN silencing had an effect towards the onset of active whisking. Silencing either IN subtype had no effect on speed coding. Our results show that these IN subtypes contribute to early sensory processing over the first few postnatal weeks.

STDP and the distribution of preferred phases in the whisker system

Rats and mice use their whiskers to probe the environment. By rhythmically swiping their whiskers back and forth they can detect the existence of an object, locate it, and identify its texture. Localization can be accomplished by inferring the whisker’s position. Rhythmic neurons that track the phase of the whisking cycle encode information about the azimuthal location of the whisker. These neurons are characterized by preferred phases of firing that are narrowly distributed. Consequently, pooling the rhythmic signal from several upstream neurons is expected to result in a much narrower distribution of preferred phases in the downstream population, which however has not been observed empirically. Here, we show how spike timing dependent plasticity (STDP) can provide a solution to this conundrum. We investigated the effect of STDP on the utility of a neural population to transmit rhythmic information downstream using the framework of a modeling study. We found that under a wide range of parameters, STDP facilitated the transfer of rhythmic information despite the fact that all the synaptic weights remained dynamic. As a result, the preferred phase of the downstream neuron was not fixed, but rather drifted in time at a drift velocity that depended on the preferred phase, thus inducing a distribution of preferred phases. We further analyzed how the STDP rule governs the distribution of preferred phases in the downstream population. This link between the STDP rule and the distribution of preferred phases constitutes a natural test for our theory.

The distribution of preferred phases of whisking neurons in the somatosensory system of rats and mice presents a conundrum: a simple pooling model predicts a distribution that is an order of magnitude narrower than what is observed empirically. Here, we suggest that this non-trivial distribution may result from activity-dependent plasticity in the form of spike timing dependent plasticity (STDP). We show that under STDP, the synaptic weights do not converge to a fixed value, but rather remain dynamic. As a result, the preferred phases of the whisking neurons vary in time, hence inducing a non-trivial distribution of preferred phases, which is governed by the STDP rule. Our results imply that the considerable synaptic volatility which has long been viewed as a difficulty that needs to be overcome, may actually be an underlying principle of the organization of the central nervous system.

Continuous, multidimensional coding of 3D complex tactile stimuli by primary sensory neurons of the vibrissal system

Across all sensory modalities, first-stage sensory neurons are an information bottleneck: they must convey all information available for an animal to perceive and act in its environment. Our understanding of coding properties of primary sensory neurons in the auditory and visual systems has been aided by the use of increasingly complex, naturalistic stimulus sets. By comparison, encoding properties of primary somatosensory afferents are poorly understood. Here, we use the rodent whisker system to examine how tactile information is represented in primary sensory neurons of the trigeminal ganglion (Vg). Vg neurons have long been thought to segregate into functional classes associated with separate streams of information processing. However, this view is based on Vg responses to restricted stimulus sets which potentially underreport the coding capabilities of these neurons. In contrast, the current study records Vg responses to complex three-dimensional (3D) stimulation while quantifying the complete 3D whisker shape and mechanics, thereby beginning to reveal their full representational capabilities. The results show that individual Vg neurons simultaneously represent multiple mechanical features of a stimulus, do not preferentially encode principal components of the stimuli, and represent continuous and tiled variations of all available mechanical information. These results directly contrast with proposed codes in which subpopulations of Vg neurons encode select stimulus features. Instead, individual Vg neurons likely overcome the information bottleneck by encoding large regions of a complex sensory space. This proposed tiled and multidimensional representation at the Vg directly constrains the computations performed by more central neurons of the vibrissotrigeminal pathway.

Interactions of Whisking and Touch Signals in the Rat Brainstem

Perception is an active process, requiring the integration of both proprioceptive and exteroceptive information. In the rat's vibrissal system, a classical model for active sensing, the relative contribution of the two information streams was previously studied at the peripheral, thalamic, and cortical levels. Contributions of brainstem neurons were only indirectly inferred for some trigeminal nuclei according to their thalamic projections. The current work addressed this knowledge gap by performing the first comparative study of the encoding of proprioceptive whisking and exteroceptive touch signals in the oralis (SpVo), interpolaris (SpVi), and paratrigeminal (Pa5) brainstem nuclei. We used artificial whisking in anesthetized male rats, which allows a systematic analysis of the relative contribution of the proprioceptive and exteroceptive information streams along the ascending pathways in the absence of motor or cognitive top-down modulations. We found that (1) neurons in the rostral and caudal parts of the SpVi convey whisking and touch information, respectively, as predicted by their thalamic projections; (2) neurons in the SpVo encode both whisking and (primarily) touch information; and (3) neurons of the Pa5 encode a complex combination of whisking and touch information. In particular, the Pa5 contains a relatively large fraction of neurons that are inhibited by active touch, a response observed so far only in the thalamus. Overall, our systematic characterization of afferent responses to active touch in the trigeminal brainstem approves the hypothesized functions of SpVi neurons and presents evidence that SpVo and Pa5 neurons are involved in the processing of active vibrissal touch.SIGNIFICANCE STATEMENT The present work constitutes the first comparative study of the encoding of proprioceptive (whisking) and exteroceptive (touch) information in the rat's brainstem trigeminal nuclei, the first stage of vibrissal processing in the CNS. It shows that (1) as expected, the rostral and caudal interpolaris neurons convey primarily whisking and touch information, respectively; (2) the oralis nucleus, whose function was previously unknown, encodes both whisking and (primarily) touch touch information; (3) a subtractive computation, reported at the thalamic level, already occurs at the brainstem level; and (4) a novel afferent pathway probably ascends via the paratrigeminal nucleus, encoding both proprioceptive and exteroceptive information.

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.

Constraints on the deformation of the vibrissa within the follicle

Nearly all mammals have a vibrissal system specialized for tactile sensation, composed of whiskers growing from sensor-rich follicles in the skin. When a whisker deflects against an object, it deforms within the follicle and exerts forces on the mechanoreceptors inside. In addition, during active whisking behavior, muscle contractions around the follicle and increases in blood pressure in the ring sinus will affect the whisker deformation profile. To date, however, it is not yet possible to experimentally measure how the whisker deforms in an intact follicle or its effects on different groups of mechanoreceptors. The present study develops a novel model to predict vibrissal deformation within the follicle sinus complex. The model is based on experimental results from a previous ex vivo study on whisker deformation within the follicle, and on a new histological analysis of follicle tissue. It is then used to simulate whisker deformation within the follicle during passive touch and active whisking. Results suggest that the most likely whisker deformation profile is “S-shaped,” crossing the midline of the follicle right below the ring sinus. Simulations of active whisking indicate that an increase in overall muscle stiffness, an increase in the ratio between deep and superficial intrinsic muscle stiffness, and an increase in sinus blood pressure will all enhance tactile sensitivity. Finally, we discuss how the deformation profiles might map to the responses of primary afferents of each mechanoreceptor type. The mechanical model presented in this study is an important first step in simulating mechanical interactions within whisker follicles.

Many mammals rely on whiskers as a mode of tactile sensation, especially when exploring in darkness. Active, rhythmic protraction and retraction of the whiskers, commonly referred to as “whisking,” is observed among many whisker specialist animals. During whisker-based sensing, forces and moments generated by external stimuli are transmitted to the base of the whisker shaft inside the follicle. Within the follicle, the interaction between the whisker’s deformation and the surrounding tissue determines how different groups of mechanoreceptors will deform, thereby transducing the mechanical signals into electrical signals. However, it is not yet possible to experimentally measure this interaction in vivo. We therefore created a mechanical model of the follicle sinus complex to simulate whisker deformation within the follicle resulting from external whisker deflection. Our results provide the first estimate of whisker shape as it deforms in the follicle, during both passive touch and active whisking. In turn, these shape estimates allow us to predict how the whisker will deform against different types of mechanoreceptors at different locations within the follicle. In addition, we find that both intrinsic muscle contraction and an increase in blood pressure will improve the tactile sensitivity of the whisker system.

An elaborate sweep-stick code in rat barrel cortex

In rat barrel cortex, feature encoding schemes uncovered during broadband whisker stimulation are hard to reconcile with the simple stick-slip code observed during natural tactile behaviors, and this has hindered the development of a generalized computational framework. By designing broadband artificial stimuli to sample the inputs encoded under natural conditions, we resolve this disparity while markedly increasing the percentage of deep layer neurons found to encode whisker movements, as well as the diversity of these encoded features. Deep layer neurons encode two main types of events, sticks and sweeps, corresponding to high angular velocity bumps and large angular displacements with high velocity, respectively. Neurons can exclusively encode sticks or sweeps, or they can encode both, with or without direction selectivity. Beyond unifying coding theories from naturalistic and artificial stimulation studies, these findings delineate a simple and generalizable set of whisker movement features that can support a range of perceptual processes.

Touch: Fluctuating Waves of Perception

Does sensory input flow into the brain as a stream, or does it come in waves? New research shows that tactile information in the cortex rises and falls in phase with the forward and back motion of whiskers during surface exploration.

Cortical Coding of Whisking Phase during Surface Whisking

In rodent whisker sensation, whisker position signals, including whisking phase, are integrated with touch signals to enable spatially accurate tactile perception, but other functions of phase coding are unclear. We investigate how phase coding affects the neural coding of surface features during surface whisking. In mice performing rough-smooth discrimination, S1 units exhibit much stronger phase tuning during surface whisking than in prior studies of whisking in air. Among putative pyramidal cells, preferred phase tiles phase space, but protraction phases are strongly over-represented. Fast-spiking units are nearly all protraction tuned. This protraction bias increases the coding of stick-slip whisker events during protraction, suggesting that surface features are preferentially encoded during protraction. Correspondingly, protraction-tuned units encode rough-smooth texture better than retraction-tuned units and encode the precise spatial location of surface ridges with higher acuity. This suggests that protraction is the main information-gathering phase for high-resolution surface features, with phase coding organized to support this function.

Predictive whisker kinematics reveal context-dependent sensorimotor strategies

Animals actively move their sensory organs in order to acquire sensory information. Some rodents, such as mice and rats, employ cyclic scanning motions of their facial whiskers to explore their proximal surrounding, a behavior known as whisking. Here, we investigated the contingency of whisking kinematics on the animal's behavioral context that arises from both internal processes (attention and expectations) and external constraints (available sensory and motor degrees of freedom). We recorded rat whisking at high temporal resolution in 2 experimental contexts-freely moving or head-fixed-and 2 spatial sensory configurations-a single row or 3 caudal whiskers on each side of the snout. We found that rapid sensorimotor twitches, called pumps, occurring during free-air whisking carry information about the rat's upcoming exploratory direction, as demonstrated by the ability of these pumps to predict consequent head and body locomotion. Specifically, pump behavior during both voluntary motionlessness and imposed head fixation exposed a backward redistribution of sensorimotor exploratory resources. Further, head-fixed rats employed a wide range of whisking profiles to compensate for the loss of head- and body-motor degrees of freedom. Finally, changing the number of intact vibrissae available to a rat resulted in an alteration of whisking strategy consistent with the rat actively reallocating its remaining resources. In sum, this work shows that rats adapt their active exploratory behavior in a homeostatic attempt to preserve sensorimotor coverage under changing environmental conditions and changing sensory capacities, including those imposed by various laboratory conditions.

The Sensorimotor Basis of Whisker-Guided Anteroposterior Object Localization in Head-Fixed Mice

Active tactile perception combines directed motion with sensory signals to generate mental representations of objects in space. Competing models exist for how mice use these signals to determine the precise location of objects along their face. We tested six of these models using behavioral manipulations and statistical learning in head-fixed mice. Trained mice used a whisker to locate a pole in a continuous range of locations along the anteroposterior axis. Mice discriminated locations to ≤0.5 mm (<2°) resolution. Their motor program was noisy, adaptive to touch, and directed to the rewarded range. This exploration produced several sets of sensorimotor features that could discriminate location. Integration of two features, touch count and whisking midpoint at touch, was the simplest model that explained behavior best. These results show how mice locate objects at hyperacute resolution using a learned motor strategy and minimal set of mentally accessible sensorimotor features.

Focal neocortical lesions impair distant neuronal information processing

KEY POINTS

Parts of the fields of neuroscience and neurology consider the neocortex to be a functionally parcelled structure. Viewed through such a conceptual filter, there are multiple clinical observations after localized stroke lesions that seem paradoxical. We tested the effect that localized stroke-like lesions have on neuronal information processing in a part of the neocortex that is distant to the lesion using animal experiments. We find that the distant lesion degrades the quality of neuronal information processing of tactile input patterns in primary somatosensory cortex. The findings suggest that even the processing of primary sensory information depends on an intact neocortical network, with the implication that all neocortical processing may rely on widespread interactions across large parts of the cortex.

ABSTRACT

Recent clinical studies report a surprisingly weak relationship between the location of cortical brain lesions and the resulting functional deficits. From a neuroscience point of view, such findings raise questions as to what extent functional localization applies in the neocortex and to what extent the functions of different regions depend on the integrity of others. Here we provide an in-depth analysis of the changes in the function of the neocortical neuronal networks after distant focal stroke-like lesions in the anaesthetized rat. Using a recently introduced high resolution analysis of neuronal information processing, consisting of pre-set spatiotemporal patterns of tactile afferent activation against which the neuronal decoding performance can be quantified, we found that stroke-like lesions in distant parts of the cortex significantly degraded the decoding performance of individual neocortical neurons in the primary somatosensory cortex (decoding performance decreased from 30.9% to 24.2% for n = 22 neurons, Wilcoxon signed rank test, P = 0.028). This degrading effect was not due to changes in the firing frequency of the neuron (Wilcoxon signed rank test, P = 0.499) and was stronger the higher the decoding performance of the neuron, indicating a specific impact on the information processing capacity in the cortex. These findings suggest that even primary sensory processing depends on widely distributed cortical networks and could explain observations of focal stroke lesions affecting a large range of functions.

Sensorimotor processing in the rodent barrel cortex

Tactile sensory information from facial whiskers provides nocturnal tunnel-dwelling rodents, including mice and rats, with important spatial and textural information about their immediate surroundings. Whiskers are moved back and forth to scan the environment (whisking), and touch signals from each whisker evoke sparse patterns of neuronal activity in whisker-related primary somatosensory cortex (wS1; barrel cortex). Whisking is accompanied by desynchronized brain states and cell-type-specific changes in spontaneous and evoked neuronal activity. Tactile information, including object texture and location, appears to be computed in wS1 through integration of motor and sensory signals. wS1 also directly controls whisker movements and contributes to learned, whisker-dependent, goal-directed behaviours. The cell-type-specific neuronal circuitry in wS1 that contributes to whisker sensory perception is beginning to be defined.

Coding of whisker motion across the mouse face

Haptic perception synthesizes touch with proprioception, the sense of body position. Humans and mice alike experience rich active touch of the face. Because most facial muscles lack proprioceptor endings, the sensory basis of facial proprioception remains unsolved. Facial proprioception may instead rely on mechanoreceptors that encode both touch and self-motion. In rodents, whisker mechanoreceptors provide a signal that informs the brain about whisker position. Whisking involves coordinated orofacial movements, so mechanoreceptors innervating facial regions other than whiskers could also provide information about whisking. To define all sources of sensory information about whisking available to the brain, we recorded spikes from mechanoreceptors innervating diverse parts of the face. Whisker motion was encoded best by whisker mechanoreceptors, but also by those innervating whisker pad hairy skin and supraorbital vibrissae. Redundant self-motion responses may provide the brain with a stable proprioceptive signal despite mechanical perturbations during active touch.

Cortical modulation of sensory flow during active touch in the rat whisker system

Sensory gating, where responses to stimuli during sensor motion are reduced in amplitude, is a hallmark of active sensing systems. In the rodent whisker system, sensory gating has been described only at the thalamic and cortical stages of sensory processing. However, does sensory gating originate at an even earlier synaptic level? Most importantly, is sensory gating under top-down or bottom-up control? To address these questions, we used an active touch task in behaving rodents while recording from the trigeminal sensory nuclei. First, we show that sensory gating occurs in the brainstem at the first synaptic level. Second, we demonstrate that sensory gating is pathway-specific, present in the lemniscal but not in the extralemniscal stream. Third, using cortical lesions resulting in the complete abolition of sensory gating, we demonstrate its cortical dependence. Fourth, we show accompanying decreases in whisking-related activity, which could be the putative gating signal.

During active touch, sensory responses to object touch are gated at the level of thalamus and cortex. Here, the authors report gating at the level of the brainstem and show that an intact somatosensory cortex is essential for this response modulation.

Slip-Based Coding of Local Shape and Texture in Mouse S1

Tactile objects have both local geometry (shape) and broader macroscopic texture, but how these different spatial scales are simultaneously encoded during active touch is unknown. In the whisker system, we tested for a shared code based on localized whisker micromotions (stick-slips) and slip-evoked spikes. We trained mice to discriminate smooth from rough surfaces, including ridged gratings and sandpaper. Whisker slips locked to ridges and evoked temporally precise spikes (<10 ms jitter) in somatosensory cortex (S1) that could resolve ridges with ∼1 mm accuracy. Slip-sensitive neurons also encoded touch and texture. On rough surfaces, both slip-evoked spikes and an additional non-slip signal elevated mean firing rate, allowing accurate rough-smooth texture decoding from population firing rate. Eighteen percent of neurons were selective among rough surfaces. Thus, slips elicit spatially and temporally precise spiking in S1 that simultaneously encodes local shape (ridges) and is integrated into a macroscopic firing rate code for roughness.

What Do Sensory Organs Tell the Brain?

Understanding how perception emerges depends on the understanding of sensory acquisition by sensory organs. In this issue of Neuron, Severson et al. (2017) present a brilliant leap towards understanding active sensory coding by mechanoreceptors.

Organization of sensory feature selectivity in the whisker system

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Neurons in the whisker system are selective to spatial and dynamical properties – features – of sensory stimuli.

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At each stage of the pathway, different neurons encode distinct features, generating a rich population representation.

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Whisker touch is robustly represented; neurons respond to touch-driven fast fluctuations in forces at the whisker base.

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Cortical neurons have more complex and context-dependent selectivity than subcortical, e.g., to collective whisker motion.

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Understanding how these signals are integrated to construct whisker-mediated percepts requires further research.

Our sensory receptors are faced with an onslaught of different environmental inputs. Each sensory event or encounter with an object involves a distinct combination of physical energy sources impinging upon receptors. In the rodent whisker system, each primary afferent neuron located in the trigeminal ganglion innervates and responds to a single whisker and encodes a distinct set of physical stimulus properties – features – corresponding to changes in whisker angle and shape and the consequent forces acting on the whisker follicle. Here we review the nature of the features encoded by successive stages of processing along the whisker pathway. At each stage different neurons respond to distinct features, such that the population as a whole represents diverse properties. Different neuronal types also have distinct feature selectivity. Thus, neurons at the same stage of processing and responding to the same whisker nevertheless play different roles in representing objects contacted by the whisker. This diversity, combined with the precise timing and high reliability of responses, enables populations at each stage to represent a wide range of stimuli. Cortical neurons respond to more complex stimulus properties – such as correlated motion across whiskers – than those at early subcortical stages. Temporal integration along the pathway is comparatively weak: neurons up to barrel cortex (BC) are sensitive mainly to fast (tens of milliseconds) fluctuations in whisker motion. The topographic organization of whisker sensitivity is paralleled by systematic organization of neuronal selectivity to certain other physical features, but selectivity to touch and to dynamic stimulus properties is distributed in “salt-and-pepper” fashion.

What the whiskers tell the brain

A fundamental question in the investigation of any sensory system is what physical signals drive its sensory neurons during natural behavior. Surprisingly, in the whisker system, it is only recently that answers to this question have emerged. Here, we review the key developments, focussing mainly on the first stage of the ascending pathway - the primary whisker afferents (PWAs). We first consider a biomechanical framework, which describes the fundamental mechanical forces acting on the whiskers during active sensation. We then discuss technical progress that has allowed such mechanical variables to be estimated in awake, behaving animals. We discuss past electrophysiological evidence concerning how PWAs function and reinterpret it within the biomechanical framework. Finally, we consider recent studies of PWAs in awake, behaving animals and compare the results to related studies of the cortex. We argue that understanding 'what the whiskers tell the brain' sheds valuable light on the computational functions of downstream neural circuits, in particular, the barrel cortex.

Surround Integration Organizes a Spatial Map during Active Sensation

During active sensation, sensors scan space in order to generate a representation of the outside world. However, since spatial coding in sensory systems is typically addressed by measuring receptive fields in a fixed, sensor-based coordinate frame, the cortical representation of scanned space is poorly understood. To address this question, we probed spatial coding in the rodent whisker system using a combination of two-photon imaging and electrophysiology during active touch. We found that surround whiskers powerfully transform the cortical representation of scanned space. On the single-neuron level, surround input profoundly alters response amplitude and modulates spatial preference in the cortex. On the population level, surround input organizes the spatial preference of neurons into a continuous map of the space swept out by the whiskers. These data demonstrate how spatial summation over a moving sensor array is critical to generating population codes of sensory space.

Active Touch and Self-Motion Encoding by Merkel Cell-Associated Afferents

Touch perception depends on integrating signals from multiple types of peripheral mechanoreceptors. Merkel-cell associated afferents are thought to play a major role in form perception by encoding surface features of touched objects. However, activity of Merkel afferents during active touch has not been directly measured. Here, we show that Merkel and unidentified slowly adapting afferents in the whisker system of behaving mice respond to both self-motion and active touch. Touch responses were dominated by sensitivity to bending moment (torque) at the base of the whisker and its rate of change and largely explained by a simple mechanical model. Self-motion responses encoded whisker position within a whisk cycle (phase), not absolute whisker angle, and arose from stresses reflecting whisker inertia and activity of specific muscles. Thus, Merkel afferents send to the brain multiplexed information about whisker position and surface features, suggesting that proprioception and touch converge at the earliest neural level.

Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons

Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.

Whisking mechanics and active sensing

We describe recent advances in quantifying the three-dimensional (3D) geometry and mechanics of whisking. Careful delineation of relevant 3D reference frames reveals important geometric and mechanical distinctions between the localization problem ('where' is an object) and the feature extraction problem ('what' is an object). Head-centered and resting-whisker reference frames lend themselves to quantifying temporal and kinematic cues used for object localization. The whisking-centered reference frame lends itself to quantifying the contact mechanics likely associated with feature extraction. We offer the 'windowed sampling' hypothesis for active sensing: that rats can estimate an object's spatial features by integrating mechanical information across whiskers during brief (25-60ms) windows of 'haptic enclosure' with the whiskers, a motion that resembles a hand grasp.

Whiskers aid anemotaxis in rats

Observation of terrestrial mammals suggests that they can follow the wind (anemotaxis), but the sensory cues underlying this ability have not been studied. We identify a significant contribution to anemotaxis mediated by whiskers (vibrissae), a modality previously studied only in the context of direct tactile contact. Five rats trained on a five-alternative forced-choice airflow localization task exhibited significant performance decrements after vibrissal removal. In contrast, vibrissal removal did not disrupt the performance of control animals trained to localize a light source. The performance decrement of individual rats was related to their airspeed threshold for successful localization: animals that found the task more challenging relied more on the vibrissae for localization cues. Following vibrissal removal, the rats deviated more from the straight-line path to the air source, choosing sources farther from the correct location. Our results indicate that rats can perform anemotaxis and that whiskers greatly facilitate this ability. Because air currents carry information about both odor content and location, these findings are discussed in terms of the adaptive significance of the interaction between sniffing and whisking in rodents.

Whisking Kinematics Enables Object Localization in Head-Centered Coordinates Based on Tactile Information from a Single Vibrissa

During active tactile exploration with their whiskers (vibrissae), rodents can rapidly orient to an object even though there are very few proprioceptors in the whisker muscles. Thus a long-standing question in the study of the vibrissal system is how the rat can localize an object in head-centered coordinates without muscle-based proprioception. We used a three-dimensional model of whisker bending to simulate whisking motions against a peg to investigate the possibility that the 3D mechanics of contact from a single whisker are sufficient for localization in head-centered coordinates. Results show that for nearly all whiskers in the array, purely tactile signals at the whisker base - as would be measured by mechanoreceptors, in whisker-centered coordinates - could be used to determine the location of a vertical peg in head-centered coordinates. Both the "roll" and the "elevation" components of whisking kinematics contribute to the uniqueness and resolution of the localization. These results offer an explanation for a behavioral study showing that rats can more accurately determine the horizontal angle of an object if one column, rather than one row, of whiskers is spared.

Decoupling kinematics and mechanics reveals coding properties of trigeminal ganglion neurons in the rat vibrissal system

Tactile information available to the rat vibrissal system begins as external forces that cause whisker deformations, which in turn excite mechanoreceptors in the follicle. Despite the fundamental mechanical origin of tactile information, primary sensory neurons in the trigeminal ganglion (Vg) have often been described as encoding the kinematics (geometry) of object contact. Here we aimed to determine the extent to which Vg neurons encode the kinematics vs. mechanics of contact. We used models of whisker bending to quantify mechanical signals (forces and moments) at the whisker base while simultaneously monitoring whisker kinematics and recording single Vg units in both anesthetized rats and awake, body restrained rats. We employed a novel manual stimulation technique to deflect whiskers in a way that decouples kinematics from mechanics, and used Generalized Linear Models (GLMs) to show that Vg neurons more directly encode mechanical signals when the whisker is deflected in this decoupled stimulus space.

DOI:http://dx.doi.org/10.7554/eLife.13969.001

Animals must gather sensory information from the world around them and act on that information. Specialized sensory cells convert physical information from the environment into electrical signals that the brain can interpret. In the case of hearing, this physical information consists of changes in air pressure, and for vision, it is patterns of light bouncing off of objects.

Rodents rely heavily on touch information from their whiskers to explore their world. When a whisker touches an object, it deforms and bends. The first neurons to respond to whisker touch – so called primary sensory neurons – represent contact between the whisker and the object in the form of electrical signals, but exactly how they do this is unclear.

One possibility is that primary sensory neurons encode the movement of the whisker itself. Whenever a whisker touches an object, the whisker is deflected in a particular direction by a particular amount and at a particular speed. These movement-related features are referred to as the “kinematic” properties of whisker-object contact. Alternatively, these whisker sensory neurons might be more concerned with the forces at the base of the whisker caused by object contact. These forces are the “mechanical” properties of whisker-object contact.

Bush, Schroeder et al. set out to determine whether the electrical response of these whisker sensory neurons mainly encode kinematic or mechanical information. However, these two types of information are often closely related to each other: put simply, small whisker movements tend to accompany small forces and vice versa. Bush, Schroeder et al. therefore devised a method to deliver touch stimuli to the whiskers in a way that separates kinematic from mechanical information. Mathematical models were then developed to compare how well the neurons represent each type of information. The models showed that whisker sensory neurons generally encode mechanical signals more directly than kinematic ones.

This information adds to our understanding of how animals learn about the world through their senses. However, the analysis of Bush, Schroeder et al. relies on the long-standing simplification that whisker motion is two-dimensional, whereas in reality whiskers move in three dimensions. Therefore, a future challenge is to examine how sensory neurons represent information about touch, such as the location or shape of an object, during three-dimensional whisker-object contact.

DOI:http://dx.doi.org/10.7554/eLife.13969.002