Validating a population model of tactile mechanotransduction of slowly adapting type I afferents at levels of skin mechanics, single-unit response and psychophysics.

Previous models of touch have linked skin mechanics to neural firing rate, neural dynamics to action potential elicitation, and mechanoreceptor populations to psychophysical discrimination. However, no one model spans all levels. The objective of work herein is to build a multi-level, computational model of tactile neurons embedded in cutaneous skin, and then validate its predictions of skin surface deflection, single-afferent firing to indenter shift, and population response for sphere discrimination. The model includes a 3D finite element representation of the distal phalange with hyper- and visco-elastic mechanics. Distributed over its surface, a population of receptor models is comprised of bi-phasic functions to represent Merkel cells' transformation of stress/strain to membrane current and a leaky integrate-and-fire neuronal models to generate the timing of action potentials. After including neuronal noise, the predictions of two population encoding strategies (gradient sum and euclidean distance) are compared to psychophysical discrimination of spheres. Results indicate that predicted skin surface deflection matches Srinivasan's observations for 50 micron and 3.17 mm diameter cylinders and single-afferent responses achieve R(2) = 0.81 when compared to Johnson's recordings. Discrimination results correlate with Goodwin's experiments, whereby 287 and 365 m(-1) spheres are more discriminable than 287 and 296 m(-1).

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.

Mimicking the End Organ Architecture of Slowly Adapting Type I Afferents May Increase the Durability of Artificial Touch Sensors.

In effort to mimic the sensitivity and efficient information transfer of natural tactile afferents, recent work has combined force transducers and computational models of mechanosensitive afferents. Sensor durability, another feature important to sensor design, might similarly capitalize upon biological rules. In particular, gains in sensor durability might leverage insight from the compound end organ of the slowly adapting type I afferent, especially its multiple sites of spike initiation that reset each other. This work develops models of compound spiking sensors using a computational network of transduction functions and leaky integrate and fire models (together a spike encoder, the software element of a compound spiking sensor), informed by the output of an existing force transducer (hardware sensing elements of a compound spiking sensor). Individual force transducer failures are simulated with and without resetting between spike encoders to test the importance of both resetting and configuration on system durability. The results indicate that the resetting of adjacent spike encoders, upon the firing of a spike by any one, is an essential mechanism to maintain a stable overall response in the midst of transducer failure. Furthermore, results suggest that when resetting is enabled, the durability of a compound sensor is maximized when individual transducers are paired with spike encoders and multiple, paired units are employed. To explore these ideas more fully, use cases examine the design of a compound sensor to either reach a target lifetime with a set probability or determine how often to schedule maintenance to control the probability of failure.

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.

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.

Predicting SA-I mechanoreceptor spike times with a skin-neuron model.

Slowly adapting type I (SA-I) mechanoreceptors encode the edges and curvature of touched objects by generating neural spikes in response to indentation of the skin. Beneath this general input-output relationship, models are of great utility for understanding the sub-processes, as SA-I transduction sites are inaccessible to whole-cell recording. This work develops and validates a SA-I skin-receptor model that combines a finite element model of skin mechanics, a sigmoidal function of transduction, and a leaky integrate-and-fire model of neural dynamics. The model produced a R(2)=0.80 goodness of fit between predicted and observed firing rates for 3 and 5mm grating stimuli. In addition, modulation indices of predicted firing rates for 3 and 5mm gratings are 0.46 and 0.59, respectively, compared to the 0.71 and 0.72 found in vivo. An analysis of predicted first spikes indicates their latency may also be enhanced by edges, as edge proximity shortened first spike latencies by 26.2 and 41.8 ms for the 3 and 5mm gratings, respectively. The model described here bridges the gap between those models that transform sustained indentation to firing rates and those that transform vibration to spike times.

Modeling the data transformations underlying touch sensation to further tactile feedback in neural prosthesis.

The sense of touch is vital to everyday life, yet touch feedback in upper limb prosthesis is limited to vibrating motors on the skin. While touch may one day be recreated with artificial feedback presented through nerves, the transformations that underlie touch sensation must first be better understood. The skin-receptor model described here seeks to understand how skin indentation is transformed into neural pulses bound for the brain.