Spike-timing in primary sensory neurons: a model of somatosensory transduction in the rat

A Triboelectric-Based Artificial Whisker for Reactive Obstacle Avoidance and Local Mapping

Since designing efficient tactile sensors for autonomous robots is still a challenge, this paper proposes a perceptual system based on a bioinspired triboelectric whisker sensor (TWS) that is aimed at reactive obstacle avoidance and local mapping in unknown environments. The proposed TWS is based on a triboelectric nanogenerator (TENG) and mimics the structure of rat whisker follicles. It operates to generate an output voltage via triboelectrification and electrostatic induction between the PTFE pellet and copper films (0.3 mm thickness), where a forced whisker shaft displaces a PTFE pellet (10 mm diameter). With the help of a biologically inspired structural design, the artificial whisker sensor can sense the contact position and approximate the external stimulation area, particularly in a dark environment. To highlight this sensor's applicability and scalability, we demonstrate different functions, such as controlling LED lights, reactive obstacle avoidance, and local mapping of autonomous surface vehicles. The results show that the proposed TWS can be used as a tactile sensor for reactive obstacle avoidance and local mapping in robotics.

Consequences of tuning network function by tonic and phasic locus coeruleus output and stress: Regulating detection and discrimination of peripheral stimuli

Flexible and adaptive behaviors have evolved with increasing complexity and numbers of neuromodulator systems. The neuromodulatory locus coeruleus-norepinephrine (LC-NE) system is central to regulating cognitive function in a behaviorally-relevant and arousal-dependent manner. Through its nearly ubiquitous efferent projections, the LC-NE system acts to modulate neuron function on a cell-by-cell basis and exert a spectrum of actions across different brain regions to optimize target circuit function. As LC neuron activity, NE signaling, and arousal level increases, cognitive performance improves over an inverted-U shaped curve. Additionally, LC neurons burst phasically in relation to novel or salient sensory stimuli and top-down decision- or response-related processes. Together, the variety of LC activity patterns and complex actions of the LC-NE system indicate that the LC-NE system may dynamically regulate the function of target neural circuits. The manner in which neural networks encode, represent, and perform neurocomputations continue to be revealed. This has improved our ability to understand the optimization of neural circuits by NE and generation of flexible and adaptive goal-directed behaviors. In this review, the rat vibrissa somatosensory system is explored as a model neural circuit to bridge known modulatory actions of NE and changes in cognitive function. It is argued that fluid transitions between neural computational states reflect the ability of this sensory system to shift between two principal functions: detection of novel or salient sensory information and detailed descriptions of sensory information. Such flexibility in circuit function is likely critical for producing context-appropriate sensory signal processing. Nonetheless, many challenges remain including providing a causal link between NE mediated changes in sensory neural coding and perceptual changes, as well as extending these principles to higher cognitive functions including behavioral flexibility and decision making.

The mathematical whisker: A review of numerical models of the rat׳s vibrissa biomechanics

The vibrissal system of the rat refers to specialized hairs the animal uses for tactile sensory perception. Rats actively move their whiskers in a characteristic way called "whisking". Interaction with the environment produces elastic deformation of the whiskers, generating mechanical signals in the whisker-follicle complex. Advances in our understanding of the vibrissal complex biomechanics is of interest not only for the biological research field, but also for biomimetic approaches. The recent development of whisker numerical models has contributed to comprehending its sophisticated movements and its interactions with the follicle. The great diversity of behavioral patterns and complexities of the whisker-follicle ensemble encouraged the creation of many different biomechanical models. This review analyzes most of the whisker biomechanical models that have been developed so far. This review was written so as to render it accessible to readers coming from different research areas.

Deflection of a vibrissa leads to a gradient of strain across mechanoreceptors in a mystacial follicle

Rodents use their vibrissae to detect and discriminate tactile features during active exploration. The site of mechanical transduction in the vibrissa sensorimotor system is the follicle sinus complex and its associated vibrissa. We study the mechanics within the ring sinus (RS) of the follicle in an ex vivo preparation of the mouse mystacial pad. The sinus region has a relatively dense representation of Merkel mechanoreceptors and longitudinal lanceolate endings. Two-photon laser-scanning microscopy was used to visualize labeled cell nuclei in an ∼ 100-nl vol before and after passive deflection of a vibrissa, which results in localized displacements of the mechanoreceptor cells, primarily in the radial and polar directions about the vibrissa. These displacements are used to compute the strain field across the follicle in response to the deflection. We observe compression in the lower region of the RS, whereas dilation, with lower magnitude, occurs in the upper region, with volumetric strain ΔV/V ∼ 0.01 for a 10° deflection. The extrapolated strain for a 0.1° deflection, the minimum angle that is reported to initiate a spike by primary neurons, corresponds to the minimum strain that activates Piezo2 mechanoreceptor channels.

Low-dimensional sensory feature representation by trigeminal primary afferents

In any sensory system, the primary afferents constitute the first level of sensory representation and fundamentally constrain all subsequent information processing. Here, we show that the spike timing, reliability, and stimulus selectivity of primary afferents in the whisker system can be accurately described by a simple model consisting of linear stimulus filtering combined with spike feedback. We fitted the parameters of the model by recording the responses of primary afferents to filtered, white noise whisker motion in anesthetized rats. The model accurately predicted not only the response of primary afferents to white noise whisker motion (median correlation coefficient 0.92) but also to naturalistic, texture-induced whisker motion. The model accounted both for submillisecond spike-timing precision and for non-Poisson spike train structure. We found substantial diversity in the responses of the afferent population, but this diversity was accurately captured by the model: a 2D filter subspace, corresponding to different mixtures of position and velocity sensitivity, captured 94% of the variance in the stimulus selectivity. Our results suggest that the first stage of the whisker system can be well approximated as a bank of linear filters, forming an overcomplete representation of a low-dimensional feature space.

Whisker sensory system - from receptor to decision

One of the great challenges of systems neuroscience is to understand how the neocortex transforms neuronal representations of the physical characteristics of sensory stimuli into the percepts which can guide the animal's decisions. Here we present progress made in understanding behavioral and neurophysiological aspects of a highly efficient sensory apparatus, the rat whisker system. Beginning with the 1970s discovery of "barrels" in the rat and mouse brain, one line of research has focused on unraveling the circuits that transmit information from the whiskers to the sensory cortex, together with the cellular mechanisms that underlie sensory responses. A second, more recent line of research has focused on tactile psychophysics, that is, quantification of the behavioral capacities supported by whisker sensation. The opportunity to join these two lines of investigation makes whisker-mediated sensation an exciting platform for the study of the neuronal bases of perception and decision-making. Even more appealing is the beginning-to-end prospective offered by this system: the inquiry can start at the level of the sensory receptor and conclude with the animal's choice. We argue that rats can switch between two modes of operation of the whisker sensory system: (1) generative mode and (2) receptive mode. In the generative mode, the rat moves its whiskers forward and backward to actively seek contact with objects and to palpate the object after initial contact. In the receptive mode, the rat immobilizes its whiskers to optimize the collection of signals from an object that is moving by its own power. We describe behavioral tasks that rats perform in these different modes. Next, we explore which neuronal codes in sensory cortex account for the rats' discrimination capacities. Finally, we present hypotheses for mechanisms through which "downstream" brain regions may read out the activity of sensory cortex in order to extract the significance of sensory stimuli and, ultimately, to select the appropriate action.

Vibrissae motor cortex unit activity during whisking

Rats generate stereotyped exploratory (5-12 Hz) vibrissa movements when navigating through their environment. Like other rhythmic behaviors, the production of whisking relies on a subcortical pattern generator. However, the relatively large vibrissae representation in motor cortex (vMCx) suggests that cortex also contributes to the control of whisker movements. The goal of this study was to examine the relationship between neuronal activity in vMCx and the kinematics of vibrissae movements. We recorded multiunit activity (MUA) and single units in the rhythmic region of vMCx while measuring vibrissa position in awake, head-restrained rats. The rats were engaged in one of two behavioral tasks where they were rewarded for either 1) producing noncontact whisking epochs that met specified criteria (epochs ≥4 Hz, whisks >5 mm) or 2) whisking to contact an object. There was significant coherence between the frequency of MUA and vibrissae movements during free-air whisking but not when animals were using their vibrissae to contact an object. Spike rate in vMCx was most frequently correlated with the amplitude of vibrissa movements; correlations with movement frequency did not exceed chance levels. These findings suggest that the specific parameter under cortical control may be the amplitude of whisker movements.

A unifying framework underlying mechanotransduction in the somatosensory system

Rodents use their whiskers to sense their surroundings. As most of the information available to the somatosensory system originates in whiskers' primary afferents, it is essential to understand the transformation of whisker motion into neuronal activity. Here, we combined in vivo recordings in anesthetized rats with mathematical modeling to ascertain the mechanical and electrical characteristics of mechanotransduction. We found that only two synergistic processes, which reflect the dynamic interactions between (1) receptor and whisker and (2) receptor and surrounding tissue, are needed to describe mechanotransduction during passive whiskers deflection. Interactions between these processes may account for stimulus-dependent changes in the magnitude and temporal pattern of tactile responses on multiple scales. Thus, we are able to explain complex electromechanical processes underlying sensory transduction using a simple model, which captures the responses of a wide range of mechanoreceptor types to diverse sensory stimuli. This compact and precise model allows for a ubiquitous description of how mechanoreceptors encode tactile stimulus.

Muscle architecture in the mystacial pad of the rat

The vibrissal system of the rat is an example of active tactile sensing, and has recently been used as a prototype in construction of touch-oriented robots. Active vibrissal exploration and touch are enabled and controlled by musculature of the mystacial pad. So far, knowledge about motor control of the rat vibrissal system has been extracted from what is known about the vibrissal systems of other species, mainly mice and hamsters, since a detailed description of the musculature of the rat mystacial pad was lacking. In the present work, the musculature of the rat mystacial pad was revealed by slicing the mystacial pad in four different planes, staining of mystacial pad slices for cytochrome oxidase, and tracking spatial organization of mystacial pad muscles in consecutive slices. We found that the rat mystacial pad contains four superficial extrinsic muscles and five parts of the M. nasolabialis profundus. The connection scheme of the three parts of the M. nasolabialis profundus is described here for the first time. These muscles are inserted into the plate of the mystacial pad, and thus, their contraction causes whisker retraction. All the muscles of the rat mystacial pad contained three types of skeletal striated fibers (red, white, and intermediate). Although the entire rat mystacial pad usually functions as unity, our data revealed its structural segmentation into nasal and maxillary subdivisions. The mechanisms of whisking in the rat, and hypotheses concerning biomechanical interactions during whisking, are discussed with respect to the muscle architecture of the rat mystacial pad.

Predicting the timing of spikes evoked by tactile stimulation of the hand

What does the hand tell the brain? Tactile stimulation of the hand evokes remarkably precise patterns of neural activity, suggesting that the timing of individual spikes may convey information. However, many aspects of the transformation of mechanical deformations of the skin into spike trains remain unknown. Here we describe an integrate-and-fire model that accurately predicts the timing of individual spikes evoked by arbitrary mechanical vibrations in three types of mechanoreceptive afferent fibers that innervate the hand. The model accounts for most known properties of the three fiber types, including rectification, frequency-sensitivity, and patterns of spike entrainment as a function of stimulus frequency. These results not only shed light on the mechanisms of mechanotransduction but can be used to provide realistic tactile feedback in upper-limb neuroprostheses.

Modeling the emergence of whisker direction maps in rat barrel cortex

Based on measuring responses to rat whiskers as they are mechanically stimulated, one recent study suggests that barrel-related areas in layer 2/3 rat primary somatosensory cortex (S1) contain a pinwheel map of whisker motion directions. Because this map is reminiscent of topographic organization for visual direction in primary visual cortex (V1) of higher mammals, we asked whether the S1 pinwheels could be explained by an input-driven developmental process as is often suggested for V1. We developed a computational model to capture how whisker stimuli are conveyed to supragranular S1, and simulate lateral cortical interactions using an established self-organizing algorithm. Inputs to the model each represent the deflection of a subset of 25 whiskers as they are contacted by a moving stimulus object. The subset of deflected whiskers corresponds with the shape of the stimulus, and the deflection direction corresponds with the movement direction of the stimulus. If these two features of the inputs are correlated during the training of the model, a somatotopically aligned map of direction emerges for each whisker in S1. Predictions of the model that are immediately testable include (1) that somatotopic pinwheel maps of whisker direction exist in adult layer 2/3 barrel cortex for every large whisker on the rat's face, even peripheral whiskers; and (2) in the adult, neurons with similar directional tuning are interconnected by a network of horizontal connections, spanning distances of many whisker representations. We also propose specific experiments for testing the predictions of the model by manipulating patterns of whisker inputs experienced during early development. The results suggest that similar intracortical mechanisms guide the development of primate V1 and rat S1.