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.

Synthesizing coverage of sensation and reward into a comprehensive systems overview, Neurobiology of Sensation and Reward presents a cutting-edge and multidisciplinary approach to the interplay of sensory and reward processing in the brain. While over the past 70 years these areas have drifted apart, this book makes a case for reuniting sensation a

The world within reach is characterised to a large extent by our ability to sense objects through touch. Research into the sensation of touch has a long history. However, it is only relatively recently that significant advances have been made in understanding how information about objects we touch is represented in both the peripheral and central divisions of the nervous systems. This volume draws together the increasing body of knowledge regarding the mechanisms underlying tactile sensation and how they relate to tactile perception.Individual chapters address; the response of mechanoreceptors to stimuli (including movement and shape), the role of the somatosensory cortex in processing tactile information, the psychophysics and neurophysiology of the detection and categorisation of somesthetic stimuli, perceptual constancy, recent findings in regard to short term and long term plasticity in the somatosensory cortex and the psychophysical correlates of this plasticity, and parallel versus serial information processing in the cortex.The authors look at past and current research, and comment on the direction of future investigation, relating findings from psychophysical studies of tactile behavior to our growing understanding of the underlying neural mechanisms.

The developing brain is shaped by both genetic and activity-dependent mechanisms. Despite genetic constraints, the neocortex has the capacity to be constructed based on the particular sensory milieu experienced by an animal over the course of development. The ratios of incoming inputs from different sensory systems to the developing neocortex can be altered either by changes in the external environment of the animal or by modifications to its sensory receptor arrays. The large majority of studies that examine the role of sensory inputs in the development of the neocortex have focused on changes that occur within the sensory system in which inputs have been altered, removed or enhanced. Far less is known about the effects of such manipulations on the cortical function of the remaining, intact sensory systems. The overarching goal of the studies presented here is to investigate the effects of complete loss of vision early in life on the neural coding of stimuli in a spared sensory modality, specifically, touch. The short-tailed opossum (Monodelphis domestica) was used as the animal model in these studies because the highly immature state of its nervous system at birth allows for targeted extrauterine manipulations at specific time points relative to early developmental milestones. First, we characterized the responses of single neurons in primary somatosensory cortex (S1) of sighted opossums to simple tactile stimuli in the form of individual whisker deflections. We found that S1 neurons were selectively responsive to a small fraction of whiskers on the mystacial pad and receptive fields tended to have a horizontally elongated shape, similar to barrel cortex neurons in mice and rats. Next, we tested for differences in the representation of tactile stimuli in S1 of early blind opossums. Single neurons in early blind opossums were less sensitive, but more selective to whisker stimuli, in comparison to sighted opossums. As a result of this improved spatial resolution for whisker touch, the location of whisker stimuli could be decoded with better accuracy from the responses of neurons in early blind versus sighted animals, particularly along the horizontal axis, the primary axis of natural whisker movements. Finally, by rearing sighted and early blind opossums in a three-dimensionally enriched environment, we found evidence that alterations in receptive fields of S1 neurons following early blindness could be shaped by tactile experience, leading to an even greater enhancement of neuronal tuning along the horizontal axis.

This Handbook serves as an authoritative reference book in the field of Neuroengineering. Neuroengineering is a very exciting field that is rapidly getting established as core subject matter for research and education. The Neuroengineering field has also produced an impressive array of industry products and clinical applications. It also serves as a reference book for graduate students, research scholars and teachers. Selected sections or a compendium of chapters may be used as “reference book” for a one or two semester graduate course in Biomedical Engineering. Some academicians will construct a “textbook” out of selected sections or chapters. The Handbook is also meant as a state-of-the-art volume for researchers. Due to its comprehensive coverage, researchers in one field covered by a certain section of the Handbook would find other sections valuable sources of cross-reference for information and fertilization of interdisciplinary ideas. Industry researchers as well as clinicians using neurotechnologies will find the Handbook a single source for foundation and state-of-the-art applications in the field of Neuroengineering. Regulatory agencies, entrepreneurs, investors and legal experts can use the Handbook as a reference for their professional work as well.​

Information-Processing Channels in the Tactile Sensory System addresses the fundamental question of whether sensory channels, similar to those known to operate in vision and audition, also operate in the sense of touch. Based on the results of psychophysical and neurophysiological experimentation the authors make a powerful case that channels operate in the processing of mechanical stimulation of the highly sensitive glabrous skin of the hand. According to the multichannel model presented in this monograph, each channel, with its specific type of mechanoreceptor and afferent nerve fiber, responds optiimally to particular aspects of the tactile stimulus. It is further proposed that the tactile perception of objects results from the combined activity of the individual tactile channels. This work is important because it provides researchers and students in the field of sensory neuroscience with a comprehensive model that enhances our understanding of tactile perception.

Adaptation or the attenuation of neural responses due to the recent history of sensory input has been observed across all sensory modalities. However, computational role of adaptation in conveying sensory information is not completely clear, especially when one considers neural coding problems including discrimination of stimulus location in which adaptation increases the ambiguity of the neural responses about the stimulus's identity. To disentangle this ambiguity, in order to further our understanding of the functional role of adaptation during tactile exploration when an object repeatedly contacts neighboring locations along the tactile organ, we recorded responses from neurons in the rat thalamus while delivering paired stimuli to the whiskers, and quantified the impact of adaption on the representation of information about the stimuli. At the level of single neuron, we found that although adaptation reduces the information about the location of the present stimulus, the adapted response is capable of conveying significant amounts of information about whether, when and where a previous stimulus occurred. Further analysis showed that adaption increases variability of the response across stimuli and this variability conveys increasing amounts of information as the information conveyed by the magnitude of the response decreases. At the level of population neurons, ambiguity of the adapted responses about the present stimulus could be compensated for by large neuronal population size, with more information per spike in the adapted compared to the non-adapted state especially if the identities of each neuron are recognized by the downstream decoder. These results suggest the efficient coding of adaptive population response so that adaptation does not cost the ability to discriminate stimulus location and, more importantly, it gains the capacity to provide information about the spatiotemporal history of the stimulus. However, since the adapted response carries information about the current stimulus as well as the past, it is likely that there is some redundancy (or synergy) in the information about the two stimuli (past and present), potentially ambiguity to completely separate the information about the past stimulus from that of the present from the adapted response. To understand this ambiguity in temporal dimension, we updated our analysis model to include the external and internal source of synergy/redundancy information, and developed expressions for redundancy to explicitly analysis the information contents in the adapted response in the formalism of entropy measurement. The results supported the ability of adapted thalamic neuron to provide information about the stimulus in the past and present simultaneously, in a way that the integrated information about the stimulus pair is not decreased. With the information breakdown. We found that this efficiency in conveying information about the stimulus pair is probably attributed to the adapted response that allowed to encoding the posterior information about the dynamic contexts of the paired stimuli.