The sense of touch enables numerous behaviors fundamental to human existence, allowing individuals to eat, communicate and survive. With this sense, people can discern a surface's roughness, stickiness and vibration, among other attributes. A particularly critical dimension is object compliance. Interactions with compliant objects are pervasive in the world, whether with muscle and tissue, the hands of others, fruits and vegetables, or manufactured elastics. Despite prior psychophysical efforts to identify salient cues between the skin and complaint objects, very little is understood about the underlying neural codes. In particular, how can a diverse population of mechanosensory neurons encode perceptible differences in compliance ? given a rich diversity of stimulus-response transformations, conduction velocities, receptive field characteristics, densities and arrangements? This application's central hypothesis is that cues signaling compliance are reflected in the population response of different types of cutaneous mechanoreceptors, in time-dependent output based on spatial positioning. The hypothesis will be addressed by: i) establishing a new computational paradigm for the in silica generation and validation of population codes empowered by calcium imaging of populations of neurons combined with single-unit neurophysiology and ii) using this novel, intermediate observation point to understand how distinct, naturalistic properties of compliant stimuli are encoded in the periphery. This effort focuses on mouse somatosensory afferents innervating glabrous skin as a tractable mammalian system for computational, experimental and genetic studies.
Distinguishing whether an object is 'soft' or 'hard' is crucial to our ability to handle items that enable independent living (for example, a glass of water or a nutritious piece of fruit). This project combines computational and experimental tools to understand the neural encoding of softness, which is the perception of object compliance. This basic knowledge has the potential to aid in the design of upper-limb prosthetics that interface with the nervous system.
| Gerling, Gregory J; Hauser, Steven C; Soltis, Bryan R et al. (2018) A Standard Methodology to Characterize the Intrinsic Material Properties of Compliant Test Stimuli. IEEE Trans Haptics 11:498-508 |
| Gerling, Gregory J; Wan, Lingtian; Hoffman, Benjamin U et al. (2018) Computation predicts rapidly adapting mechanotransduction currents cannot account for tactile encoding in Merkel cell-neurite complexes. PLoS Comput Biol 14:e1006264 |
| Moayedi, Yalda; Duenas-Bianchi, Lucia F; Lumpkin, Ellen A (2018) Somatosensory innervation of the oral mucosa of adult and aging mice. Sci Rep 8:9975 |
