Vibrissal texture decoding

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Ehsan Arabzadeh et al. (2009), Scholarpedia, 4(4):6640. doi:10.4249/scholarpedia.6640 revision #150523 [link to/cite this article]
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Curator: Ehsan Arabzadeh

Texture is a central component of touch. To learn how contact with a surface gives rise to a sensation of texture, many laboratories have examined the vibrissae system of rodents – a highly efficient sensory system with well-studied structural organization [Kleinfeld 2006]. Vibrissal texture decoding summarizes current knowledge about how whisking on surfaces leads to texture sensation. The vibrissae system of rats presents a unique opportunity for investigating how sensory receptors generate signals through their interaction with the environment, and how the brain reads and interprets the afferent signals.

Contents

Anatomy and physiology

Figure 1: The arrangement of vibrissae on the snout and their topographic cortical representation

Rodents have a set of 30-some long whiskers on each side of the snout, together with short hairs packed more densely around the nose and mouth (Figure 1). The long whiskers, also called mystacial vibrissae, are the focus of this chapter. Several hundred primary afferent fibers innervate specialized receptors on each whisker shaft [Ebara et al. 2002], and these are excited by whisker movement. Signals travel along the sensory nerve, past the cell body in the trigeminal ganglion, and form synapses in the brain stem. The axons of second-order neurons cross the brain midline and travel to the thalamic somatosensory nuclei, where the second synapse is located. Thalamic neurons project to the primary somatosensory cortex, conveying information to layer IV cell populations as well as target populations in other layers (see [Kleinfeld, 2006]). Here, the whisker area – also known as barrel cortex – is arranged as a topographic map where neurons in a given barrel and its associated column respond most strongly to the corresponding whisker [Woolsey and van der Loos 1970]. Thus, sensory signals arising from individual whiskers are channeled through restricted population of neurons that can be identified and sampled by recording electrodes. The fact that the functional map, revealed by neuronal receptive fields, matches the readily visible anatomical map (the barrel field), makes this sensory system particularly attractive to neuroscientists.


Behavior

Figure 2: Behavioral paradigm from [von Heimendahl et al. 2007]. On each trial, the rat approached the texture plate (Rough or Smooth) which signaled the reward spout (Left or Right). After touching the texture (upper panel and the inset) the rat made a behavioral choice by turning towards one of the spouts (middle panel) and collected the water reward if the choice was correct (lower panel)
Along with olfaction, whisker touch represents the major channel through which rodents collect information from the nearby environment. The signals arise through an active process called whisking, a sweeping motion of the mystacial vibrissae forward and backward to encounter objects and palpate them [Berg and Kleinfeld 2003; Hill et al. 2008], often in conjunction with movement of the head [Mitchinson et al. 2007; Towal and Hartmann 2006]. Characterizing the way by which rats actively engage with a texture to extract its identity is an essential step in understanding vibrissal texture decoding.

Several laboratories have trained rats to distinguish between rough and smooth textures [Guic-Robles et al. 1989; Carvell and Simons 1990; Prigg et al. 2002; von Heimendahl et al. 2007; Ritt et al. 2008a]. When probed for their psychophysical discrimination threshold, the animals were able to discriminate a smooth surface from one with grooves that were 50 μ deep and spaced at 90 μ. They failed, though, for 15 μ deep, 50 μ spaced grooves [Carvell and Simons 1990]. In a similar texture discrimination task ([von Heimendahl et al. 2007] and Figure 2) using P100 sandpaper as a rough surface, the rats’ stereotypical discrimination behavior was filmed with a high-speed camera to quantify whisker use: Intervals of whisker contact with the texture were brief; in a typical trial, the rat made 1–3 touches per whisker of 24–62 ms duration each. The rat then began to withdraw its head, which the investigators took to be the first visible sign of its choice. The time from first contact to this moment of choice was 98–330 ms (interquartile ranges). Yet another similar study found that, when rats palpate a surface before their snout, typically only the more rostral (frontal) whiskers tend to reach the surface, and less often the (longer) more caudal ones [Ritt et al. 2008a].

Whisker kinetics

When a whisker’s tip or shaft makes contact with a texture, its movement changes; whisker motion signals report to the brain what the whiskers have contacted. How do whiskers interact with a textured object to prepare a meaningful message for the brain? This is an important question because the capacity of the behaving animal to discriminate between textures must be based upon (and can never exceed) the information contained in the movement signals.

Hypotheses

Two hypotheses compete to explain which features of whisker motion vary according to texture. According to the "resonance hypothesis", a given texture drives mechanical resonance specifically in those whiskers that possess the resonance frequencies best matching the input frequency to the whisker. Input frequency is the product of the texture's spatial frequency with the whisker's speed of translation across the texture. On the rat's snout, whisker length increases systematically from the front to the back [Brecht et al. 1997; Neimark et al. 2003] generating a spatial gradient in frequency tuning [Neimark et al. 2003]. In an analogy to the cochlea—a frequency analyzer par excellence—the map-like projection from vibrissae to cortex causes each texture to excite a specific subset of barrels. The spatial pattern of activity in the barrel cortex thus encodes the spatial frequency spectrum of the contacted texture.

The "kinetic signature hypothesis" views resonance as an unavoidable consequence of the whisker structure (a tapered elastic beam), but not necessarily central to the sensation of texture. Instead, this view stresses the conversion of surface shape into trains of discrete motion events, sometimes called stick/slip events, by individual whiskers [Arabzadeh et al. 2005]. As a whisker contacts a textured surface, the grains produce irregularities in the movement trajectory. Among these irregularities, those with high-velocity (and high-acceleration) are hypothesized to encode textures by their occurrence, number, and possibly timing. Sensory receptors as well as barrel cortex neurons are tuned to the key features of the signature—the high velocity jumps over texture grains [Arabzadeh et al. 2005].

Whisker tracking experiments

To select between these hypotheses, whisker motion has been studied in the following preparations:

  • In contact with a rotating textured cylinder

Whisker motion was monitored when an anchored whisker (fixed boundary condition) was held in contact with a rotating cylinder [Neimark et al. 2003; Andermann et al. 2004; Moore and Andermann 2005; Ritt et al. 2008a]. The data were consistent with the resonance hypothesis: whiskers, according to their length, exhibited vibrations of maximal amplitude in contact with specific textures. Measurements, however, were made not during brief touches but rather when whiskers had reached a steady state vibration.

  • During head sweep

Rats were trained to touch a plate containing rough and smooth regions [Ritt et al. 2008a]. During a brief initial approach the rat identified the contacted texture, and subsequently made a head turn towards the reward port. High frame-rate videos showed, for the first time, the presence of high-velocity slip events in awake animals performing a discrimination task, with high velocity, high amplitude events occurring preferentially on the rough surface. The slip events were followed by microvibrations when mechanical energy transferred to the whisker by hitting, or being released from, the surface generated ringing at the resonance frequency (about 100-300 Hz) of the whisker. However, given the design of the experiment, the rats' head trajectory towards a reward location should be taken as the expression of a completed sensory decision, occurring only after critical texture information provided by the whisker signal has been integrated. The whisker movement analysis was likely dominated by the post-choice data, when displacements are greater and speeds faster. Therefore, the study provided interesting observations concerning whisker motion during high-speed translation across a surface, but did not speak to the question of which features of whisker motion inform the rat about texture. To find the behaviorally relevant features, it would have been essential to focus on the whiskers exactly when the rat did so—during the initial contact phase, when it performed the discrimination (Diamond et al., 2008b). In response to this observation, Ritt et al. reanalysed their data excluding the post-choice phase and reported the presence of whisker-specific micromotions during the pre-decision palpation phase (Ritt et al., 2008b). However, beyond being a characteristic of whisker, it was not specified to what extent these early micromotions were informative about the contacted texture.

  • Electrical whisking
Figure 3: Whisker trajectory and velocity profile measured when the whiskers moved through the air with no texture present (upper trace), and when the whiskers contacted texture P280 (middle trace) and texture P100 (lower trace). Adapted from [Arabzadeh et al. 2005].
In this paradigm [Arabzadeh et al. 2005], rats were anesthetized and "electrical whisking" was induced at 8 Hz by direct stimulation of the facial nerve, the motor bundle innervating the muscles of the whisker pad. Figure 3 shows the movement profile as the whisker moved either freely in the air or on sandpapers of different grades. Under free whisking condition, the trajectory was a smooth ellipsoid. In contrast, whisking across grainy surfaces produced irregularities in the trajectory; each texture was associated with a distinct trajectory, giving rise to the abovementioned hypothesis of "kinetic signatures". Kinetic signatures are best visualized in the velocity profile — that is, the temporal sequence of velocity features across the course of a whisk. When whiskers were not touching a texture but freely moving in air, their motion was continuous and fluid. But moving along the texture, the whisker tip tended to get fixed in place before bending and springing loose. This pattern of movement gave each texture a characteristic velocity profile – the number of high-velocity events and their temporal pattern differed across textures. The same findings have been reported in an additional study based on electrical whisking [Lottem and Azouz 2008]. Although these experiments show clear texture-dependent differences in whisker motion, they leave open the possibility that electrical whisking might differ from the animal’s own self-generated motion in some important way.
  • Whisking in awake animal

Additional experiments were carried out [Wolfe et al. 2008] to determine whether the encoding of texture under awake behaving conditions is more consistent with the resonance hypothesis or the kinetic signature hypothesis. Wolfe et al. trained rats to whisk against sandpapers and whisker motion was recorded by an optic sensor. Similar to the electrical whisking data, moving along the texture, the whiskers' trajectory was characterized by an irregular, skipping motion: the whisker tip tended to get fixed in place ("stick"), before bending and springing loose ("slip") only to get stuck again, reminiscent of the motion seen during electrical whisking. On progressively coarser textures there were progressively more high speed and high acceleration stick-slip events; on progressively smoother textures there were progressively more low speed and low acceleration stick-slip events. So the ratio of the number of high to low magnitude events gave a remarkably fine kinetic signature of the contacted texture. It is also significant that one candidate encoding mechanism could be ruled out: ringing at the resonance frequency carried no information about texture in the experimental conditions of Wolfe.

Outcome

Although original experiments with the rotating cylinder were consistent with the resonance hypothesis [Neimark et al. 2003; Andermann et al. 2004; Moore and Andermann 2005;], further experiments [Ritt et al. 2008a; Wolfe et al. 2008] showed that texture-specific ringing does not generalize to an actively whisking animal. In natural settings when the whisker palpates the texture (instead of the texture moving against an end-fixed whisker), after detaching from the texture the whisker sometimes vibrates at its resonance frequency but this "ringing" is characteristic of the whisker, not of the texture.

Figure 4: Comparison of whisker motion profiles collected under different conditions. Adapted from Diamond et al. 2008a
Any argument for the kinetic signature hypothesis would be bolstered by the demonstration that kinetic signatures can robustly encode textures under different behavioral conditions. Because whisking is an actively controlled sensory-motor behavior, its parameters vary from moment to moment. Moreover, a rat may encounter the textured surface to the side of its snout [Wolfe et al. 2008], in front of the snout [Carvell and Simons 1990; von Heimendahl et al. 2007; Ritt et al. 2008a], or on the ground. Can a single encoding mechanism work under all these conditions? To answer this it is useful to compare the whisker motion obtained under two very different settings: electrical whisking [Arabzadeh et al. 2005] versus Wolfe et al.’s behavioral experiment [Wolfe et al. 2008]. In the case of electrical whisking, textures were positioned 7 mm from the snout (about 20 mm in Wolfe) and whiskers moved in a plane parallel to the textured surface (orthogonal in Wolfe). Despite the diversity of conditions, the same encoding mechanism was found in both studies: each texture generated a kinetic signature, a distinct motion pattern folded into the whisker trajectory. Observing side-by-side traces of whisker velocity obtained from the two studies reveals a striking similarity (Figure 4). Large amplitude slip/stick events were also observed in the behavioral paradigm used by Ritt el al, as rats turned their head towards a reward port and whiskers swept over a surface in front of the rat [Ritt et al., 2008a]. More recently, it has been found that kinetic signatures obtained during electric whisking are highly informative about texture identity even when varying key parameters such as whisking frequency and distance of the surface from the follicle [Lottem and Azouz 2008].

Though currently there is no evidence to support the hypothesis that the full set of whiskers encodes texture the way that the basilar membrane encodes acoustic frequency [Neimark et al. 2003; Andermann et al. 2004], there remain several possible interpretations for resonance-related microvibrations, among them are the following three examples. First, they may play a role when there is a sustained, driving input with constant relative translation between the whisker and the surface. An example might be a rat running down a tunnel with textured walls – concrete versus metal. These could produce conditions that resemble the rotating cylinder. Second, microvibrations may have some function unrelated to the perception of texture. For example, they may amplify contact signals to enhance edge detection, as suggested by Hartmann et al. [Hartmann et al. 2003]; or they may serve to maintain high-velocity input during prolonged contact, so that neuronal responsiveness in cortex does not diminish through adaptation [Arabzadeh et al. 2003; Maravall et al. 2007]. Third, they may have no perceptual significance whatsoever. Whiskers undergo high frequency vibrations because they are tapered elastic beams and their resonance follows from mechanical principles. It cannot be excluded that resonance is an unhelpful but unavoidable consequence of the physical properties of whiskers. Indeed, at moments when resonance would add noise to the afferent signal, rats may whisk in such a way as to suppress resonance – for example by increasing the damping (vibration absorption) in the follicle.

Kinetic signatures thus seem the most plausible texture encoding mechanism. But to specify in a definitive way which features of whisker kinetics are relevant to texture perception, more evidence is needed. Any candidate feature must occur in the short interval during which the animal forms its percept of texture; it must vary according to texture during this critical interval; it must evoke neuronal activity that carries information about texture; those neuronal response features must influence the animal’s percept.

Neuronal encoding of texture

Figure 5: Electrical stimulation of the facial nerve induced whisking in the air, on the smooth surface of a compact disk (CD) and on sandpapers of four different grades: P1200, P400, P280, P100 (from fine-grained to coarse-grained). Progressively coarser textures evoked kinetic signatures with higher Equivalent Noise Levels (green triangles). Higher ENLs led to higher firing rates in the trigeminal ganglion (blue squares) and barrel cortex (red diamonds). Adapted from [Arabzadeh et al. 2005].
How is the texture-specific motion signal transformed by the nervous system into spiking activity? In anesthetized animals, neurons at all stages of the sensory pathway, from the trigeminal ganglion to barrel cortex, are effectively driven by high-speed and high-acceleration kinetic events [Shoykhet et al. 2000; Arabzadeh et al. 2003; Jones et al. 2004; Arabzadeh et al. 2005]. Thus, texture-specific kinetic signatures obtained through electrical whisking are represented by differences in the overall rate of neuronal firing, which follow from the number and size of kinetic events. They are also represented by differences in the temporal pattern of neuronal firing, caused by the temporal pattern of kinetic events [Arabzadeh et al. 2005; 2006]. The firing-rate coding mechanism is illustrated in Figure 5, where spike count per trial, measured in the trigeminal ganglion and the barrel cortex (blue squares and red diamonds, respectively) are given for the corresponding set of textures [Arabzadeh et al. 2005]. It is evident that the value of ENL (Equivalent Noise Level is a measure of energy related to the number and size of kinetic events) for a given texture’s motion profile was accurately translated to firing rate. The temporal pattern coding mechanism is illustrated in Figure 5, where electrical whisking on textures P400, P280 and P100 evoked distinctive spike sequences in a ganglion cell. More studies are needed in order to quantify the relation between whisker kinetics and neuronal firing in alert, behaving animals.
Figure 6: Texture-specific spike patterns. Peristimulus time histogram (2 ms bins; 100 trials) of a ganglion cell for two whisks on textures P400 (left), P280 (middle) and P100 (right). Mean firing rate (dashed red lines) were similar, suggesting temporal firing pattern as a critical coding mechanism. Adapted from [Arabzadeh et al. 2005].

Decoding of the texture signal

A third problem in texture sensation is to understand how spike trains are "read out" to allow a behaving animal to discriminate between textures. The two coding mechanisms described above suggest two corresponding read out mechanisms, temporal integration and temporal pattern. According to the first hypothesis, the brain identifies texture by extracting a single integrated number of spikes (total number of spikes, or else spikes per unit of time) accumulated across a contact interval. In short, when the texture-specific kinetic signature causes high energy movements to reach the receptors in the follicle, high firing rates are evoked and the contacted texture is decoded as rough; lower energy movement and lower firing rate is decoded as smoother. According to the second hypothesis, the brain identifies texture by extracting from each contact interval the temporal sequence of high energy events within the kinetic signature. For example, one texture may evoke a kinetic signature with regularly timed stick-slip events, and a second texture may evoke a signature with alternating long and short intervals. The temporal pattern of kinetic events would be captured in the neuronal spiking sequence (e.g. Figure 6), and if the readout mechanism can decode firing patterns, then the animal would possess a much higher capacity for representing textures than if it used only the firing rate decoding mechanism [Arabzadeh et al. 2006].

Existing evidence supports temporal integration as a plausible readout mechanism. In a rough versus smooth texture discrimination task, contacts with the rough texture evoked significantly higher firing rates in barrel cortex than did contact with the smooth texture [von Heimendahl et al. 2007]. On trials when the rat correctly identified the stimulus, the firing rate of neurons in barrel cortex was higher for rough than for smooth during a temporal window immediately preceding the instant of choice. This firing-rate code was reversed on error trials (lower for rough than for smooth) suggesting that the rat made its decision based upon the magnitude of whisker-evoked activity in barrel cortex. But temporal firing patterns may provide supplementary information in other texture discrimination tasks; if a pair of textures evokes nearly the same firing rate, differences in spiking sequences could be crucial [Arabzadeh et al. 2006]. Just as rats shift their whisking strategy according to the textures they must discriminate [Carvell and Simons 1995], so might they adapt their strategy for decoding neuronal activity.

Sensorimotor Integration

In the sense of touch, it is the motion of the sensory receptors themselves that leads to an afferent signal – whether these receptors are in our fingertips sliding along a surface [Gamzu and Ahissar 2001] or a rat’s whiskers palpating an object. Thus, tactile exploration entails the interplay between motor output and sensory input (reviewed in [Kleinfeld et al. 2006; Diamond et al. 2008b]; also see [Kleinfeld 2006]. Just as we would not be able to estimate the weight of an object we are lifting without taking into account the motor signals that produce muscle contraction, nor can the afferent signal from a whisker be optimally decoded without information about the movement that generated the tactile signal to begin with. Anatomical and physiological evidence [Gioanni and Lamarche 1985; Kleinfeld et al. 2002] indicate that barrel cortex has access to motor signals as it is a direct participant in the motor network. The technical term for a signal in which motor areas inform sensory areas about outgoing motor signals – or, similarly, about their expected sensory consequences – is "corollary discharge" [Crapse and Sommer 2008]. While this has been studied in detail in many species, including song birds [Troyer and Doupe 2000] and bats [Ulanovsky and Moss 2008], in rats we know neither the signal's neuronal substrate, nor its coding properties nor how and where it is integrated during sensory processing. Understanding these aspects of sensorimotor integration will be the focus of future research in the field.

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Sponsored by: Prof. Tony J. Prescott, Dept Psychology, Univ of Sheffield, UK
Reviewed by: Anonymous
Reviewed by: Dr. Jason Wolfe, Berlin Center for Computational Neuroscience
Accepted on: 2009-04-19 09:39:17 GMT
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