Epidermal Merkel cells are mechanosensory cells that tune mammalian touch receptors.

Touch submodalities, such as flutter and pressure, are mediated by somatosensory afferents whose terminal specializations extract tactile features and encode them as action potential trains with unique activity patterns. Whether non-neuronal cells tune touch receptors through active or passive mechanisms is debated. Terminal specializations are thought to function as passive mechanical filters analogous to the cochlea's basilar membrane, which deconstructs complex sounds into tones that are transduced by mechanosensory hair cells. The model that cutaneous specializations are merely passive has been recently challenged because epidermal cells express sensory ion channels and neurotransmitters; however, direct evidence that epidermal cells excite tactile afferents is lacking. Epidermal Merkel cells display features of sensory receptor cells and make 'synapse-like' contacts with slowly adapting type I (SAI) afferents. These complexes, which encode spatial features such as edges and texture, localize to skin regions with high tactile acuity, including whisker follicles, fingertips and touch domes. Here we show that Merkel cells actively participate in touch reception in mice. Merkel cells display fast, touch-evoked mechanotransduction currents. Optogenetic approaches in intact skin show that Merkel cells are both necessary and sufficient for sustained action-potential firing in tactile afferents. Recordings from touch-dome afferents lacking Merkel cells demonstrate that Merkel cells confer high-frequency responses to dynamic stimuli and enable sustained firing. These data are the first, to our knowledge, to directly demonstrate a functional, excitatory connection between epidermal cells and sensory neurons. Together, these findings indicate that Merkel cells actively tune mechanosensory responses to facilitate high spatio-temporal acuity. Moreover, our results indicate a division of labour in the Merkel cell-neurite complex: Merkel cells signal static stimuli, such as pressure, whereas sensory afferents transduce dynamic stimuli, such as moving gratings. Thus, the Merkel cell-neurite complex is an unique sensory structure composed of two different receptor cell types specialized for distinct elements of discriminative touch.

Computation identifies structural features that govern neuronal firing properties in slowly adapting touch receptors.

Touch is encoded by cutaneous sensory neurons with diverse morphologies and physiological outputs. How neuronal architecture influences response properties is unknown. To elucidate the origin of firing patterns in branched mechanoreceptors, we combined neuroanatomy, electrophysiology and computation to analyze mouse slowly adapting type I (SAI) afferents. These vertebrate touch receptors, which innervate Merkel cells, encode shape and texture. SAI afferents displayed a high degree of variability in touch-evoked firing and peripheral anatomy. The functional consequence of differences in anatomical architecture was tested by constructing network models representing sequential steps of mechanosensory encoding: skin displacement at touch receptors, mechanotransduction and action-potential initiation. A systematic survey of arbor configurations predicted that the arrangement of mechanotransduction sites at heminodes is a key structural feature that accounts in part for an afferent's firing properties. These findings identify an anatomical correlate and plausible mechanism to explain the driver effect first described by Adrian and Zotterman. DOI: http://dx.doi.org/10.7554/eLife.01488.001.

Force sensor in simulated skin and neural model mimic tactile SAI afferent spiking response to ramp and hold stimuli.

BACKGROUND: The next generation of prosthetic limbs will restore sensory feedback to the nervous system by mimicking how skin mechanoreceptors, innervated by afferents, produce trains of action potentials in response to compressive stimuli. Prior work has addressed building sensors within skin substitutes for robotics, modeling skin mechanics and neural dynamics of mechanotransduction, and predicting response timing of action potentials for vibration. The effort here is unique because it accounts for skin elasticity by measuring force within simulated skin, utilizes few free model parameters for parsimony, and separates parameter fitting and model validation. Additionally, the ramp-and-hold, sustained stimuli used in this work capture the essential features of the everyday task of contacting and holding an object. METHODS: This systems integration effort computationally replicates the neural firing behavior for a slowly adapting type I (SAI) afferent in its temporally varying response to both intensity and rate of indentation force by combining a physical force sensor, housed in a skin-like substrate, with a mathematical model of neuronal spiking, the leaky integrate-and-fire. Comparison experiments were then conducted using ramp-and-hold stimuli on both the spiking-sensor model and mouse SAI afferents. The model parameters were iteratively fit against recorded SAI interspike intervals (ISI) before validating the model to assess its performance. RESULTS: Model-predicted spike firing compares favorably with that observed for single SAI afferents. As indentation magnitude increases (1.2, 1.3, to 1.4 mm), mean ISI decreases from 98.81 ± 24.73, 54.52 ± 6.94, to 41.11 ± 6.11 ms. Moreover, as rate of ramp-up increases, ISI during ramp-up decreases from 21.85 ± 5.33, 19.98 ± 3.10, to 15.42 ± 2.41 ms. Considering first spikes, the predicted latencies exhibited a decreasing trend as stimulus rate increased, as is observed in afferent recordings. Finally, the SAI afferent's characteristic response of producing irregular ISIs is shown to be controllable via manipulating the output filtering from the sensor or adding stochastic noise. CONCLUSIONS: This integrated engineering approach extends prior works focused upon neural dynamics and vibration. Future efforts will perfect measures of performance, such as first spike latency and irregular ISIs, and link the generation of characteristic features within trains of action potentials with current pulse waveforms that stimulate single action potentials at the peripheral afferent.

Skin relaxation predicts neural firing rate adaptation in SAI touch receptors.

In response to ramp-and-hold indentation, the slowly-adapting type I (SAI) afferent exhibits an exponential decrease in its firing frequency during the hold phase. Such adaptation may be tied to skin relaxation but is neither well understood nor has it been quantitatively modeled. The specific hypothesis of this work is that skin relaxation is a primary contributor to observed changes in firing rate. Double exponential functions were fit to 21 responses from a mouse SAI afferent for both instantaneous firing rate and indenter tip force over time. The model was then generalized by using a linear transformation between fit parameters for force and firing rate data, allowing prediction of firing rates from force. The results show that the generalized model matches the recorded firing rate (R(2) = 0.65) equally well as fitting a doubleexponential function directly to firing rate (R(2) = 0.67) for a second dataset. When the procedure was repeated with two D-hair fibers, the generalized model matched the recorded firing rate (R(2) = 0.47) much more poorly compared to the fitted double-exponential function (R(2) = 0.89). Thus, firing rate adaptation in SAI responses can be predicted by skin relaxation, whereas this factor alone did not adequately describe adaptation in the D-hair.

The regularity of sustained firing reveals two populations of slowly adapting touch receptors in mouse hairy skin.

Touch is initiated by diverse somatosensory afferents that innervate the skin. The ability to manipulate and classify receptor subtypes is prerequisite for elucidating sensory mechanisms. Merkel cell-neurite complexes, which distinguish shapes and textures, are experimentally tractable mammalian touch receptors that mediate slowly adapting type I (SAI) responses. The assessment of SAI function in mutant mice has been hindered because previous studies did not distinguish SAI responses from slowly adapting type II (SAII) responses, which are thought to arise from different end organs, such as Ruffini endings. Thus we sought methods to discriminate these afferent types. We developed an epidermis-up ex vivo skin-nerve chamber to record action potentials from afferents while imaging Merkel cells in intact receptive fields. Using model-based cluster analysis, we found that two types of slowly adapting receptors were readily distinguished based on the regularity of touch-evoked firing patterns. We identified these clusters as SAI (coefficient of variation = 0.78 +/- 0.09) and SAII responses (0.21 +/- 0.09). The identity of SAI afferents was confirmed by recording from transgenic mice with green fluorescent protein-expressing Merkel cells. SAI receptive fields always contained fluorescent Merkel cells (n = 10), whereas SAII receptive fields lacked these cells (n = 5). Consistent with reports from other vertebrates, mouse SAI and SAII responses arise from afferents exhibiting similar conduction velocities, receptive field sizes, mechanical thresholds, and firing rates. These results demonstrate that mice, like other vertebrates, have two classes of slowly adapting light-touch receptors, identify a simple method to distinguish these populations, and extend the utility of skin-nerve recordings for genetic dissection of touch receptor mechanisms.

Using Force Sensors and Neural Models to Encode Tactile Stimuli as Spike-based Responses.

Tactile sensors will augment the next generation of prosthetic limbs. However, currently available sensors do not produce biologically-compatible output. This work seeks to illustrate that a force sensor combined with a bi-phasic, neural spiking algorithm, or spiking-sensor, can produce spiking patterns similar to that of the slowly adapting type I (SAI) mechanoreceptor. Experiments were conducted where first spike latency and inter-spike interval, in response to a rapidly delivered (100 ms) sustained displacement (1.1, 1.3, 1.5 mm for 5 s), were compared between the spiking-sensor and SAI recording. The results indicated that the predicted spike times were similar, in magnitude and increasing linear trend, to those observed with the SAI. Over the three displacements, average dynamic ISIs were 7.3, 4.2, 3.8 ms for the spiking-sensor and 6.2, 6.9, 4.1 ms for the SAI, while average static ISIs were 69.0, 45.2, 35.1 ms and 159.9, 69.6, 38.8 ms. The predicted first spike latencies (74.3, 73.9, 96.3 ms) lagged in comparison to those observed for the SAI (26.8, 31.7, 28.8 ms), which may be due to both the different applied force ramp-ups and the SAI's exquisite dynamic sensitivity range and rapid response time.

Statistical analysis and modeling of variance in the SA-I mechanoreceptor response to sustained indentation.

The slowly-adapting type I mechanoreceptor (SA-I) exhibits variability in its steady-state firing rate both within an afferent upon repeated stimulation and between afferents. Additionally, inter-spike intervals of the SA-I are extremely variable during this steady-state firing. While variability of the SA-I response has been noted previously, the work presented herein provides a finer analysis of the impact of force and fiber on the SA-I response. Specifically, we test two hypotheses, that 1) fiber-to-fiber variation will significantly impact firing rate over the range of applied forces, and that 2) fiber-to-fiber variation will significantly impact the coefficient of variation (CV) of inter-spike intervals over the range of applied forces. Utilizing an ex vivo skin nerve preparation in the mouse, experiments were conducted with six SA-I fibers from five mice, and with compressive stimuli with force magnitudes up to 9.59 mN. We found fiber to significantly impact both firing rate and CV. These findings motivated the construction of a generalized input (force)-output (firing rate) model composed of a baseline response profile and a multiplicative fiber sensitivity factor. This work will inform future efforts to attribute variability to differences in skin, neuron, and receptor properties, and will contribute to the understanding of how much variability is acceptable in systems designed to provide tactile feedback to the nervous system.

Merkel cells are essential for light-touch responses.

The peripheral nervous system detects different somatosensory stimuli, including pain, temperature, and touch. Merkel cell-neurite complexes are touch receptors composed of sensory afferents and Merkel cells. The role that Merkel cells play in light-touch responses has been the center of controversy for over 100 years. We used Cre-loxP technology to conditionally delete the transcription factor Atoh1 from the body skin and foot pads of mice. Merkel cells are absent from these areas in Atoh1(CKO) animals. Ex vivo skin/nerve preparations from Atoh1(CKO) animals demonstrate complete loss of the characteristic neurophysiologic responses normally mediated by Merkel cell-neurite complexes. Merkel cells are, therefore, required for the proper encoding of Merkel receptor responses, suggesting that these cells form an indispensible part of the somatosensory system.