Download or read book Encoding of Touch written by Dhekra Al-Basha and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The encoding of touch starts at the periphery where the terminals of mechanosensitive neurons, called low threshold mechanoreceptors (LTMRs), convert mechanical forces into action potentials, or spikes. These spikes eventually propagate to the cortex where perception occurs. Here, I investigated how tactile stimuli are encoded in LTMRs and in somatosensory cortical neurons. LTMRs generate spikes in a two-step process: a transduction step where mechanical stimuli are converted into a local depolarization, or receptor potential, and a spike initiation step, where the local depolarization is transformed into spikes. While LTMR spike patterns in response to different tactile inputs have been investigated, the individual contributions of transduction and spike initiation have eluded investigation owing to the small size of LTMR terminals, which preclude direct recording. To overcome this limitation, I used a novel optogenetic approach to replace natural, hard-to-measure mechanopotentials with artificial, easy-to-control photopotentials. I discovered that slow-adapting type 2 (SA2) and rapid-adapting (RA) terminals have qualitatively different transduction and spike initiation properties, which is critical for spike-based coding of tactile input. In a subset of SA2 LTMRs, I also discovered integer-multiple-patterned spiking, comprising a fundamental interspike interval and multiples thereof. Using a combination of computational and experimental approaches, I showed that this pattern arises from intermittent failure of spike propagation. Because propagation failure was rare, I deduced that propagation in LTMRs is reliable while remaining energy efficient. Lastly, I investigated how cortical neurons encode tactile stimuli after inputs conveyed by functionally distinct LTMRs have converged. I showed that cortical neurons can simultaneously encode stimulus intensity in the rate of asynchronous spikes, and abrupt changes in stimulus intensity in the timing of synchronous spikes. The ability of neurons to simultaneously encode multiple stimulus features using different neural codes is an example of multiplexing. Similarly, I found that SA LTMRs are themselves capable of multiplexing. Deciphering the strategies by which neurons form multiplexed representations is needed to ultimately understand how information is decoded in downstream neural circuits. Taken together, these findings inform us how neurons generate and use spikes to represent tactile information.