Document Type thesis Author Name Bradshaw, Sam URN etd-0430101-131542 Title Characterization of the Mechanosensitivity of Tactile Receptors using Multivariate Logistical Regression Degree MS Department Electrical & Computer Engineering Advisors Fred Looft, Advisor Sean Kohles, Committee Member Peter Grigg, Committee Member Edward Clancy, Committee Member Len Polizzotto, Committee Member Keywords cutaneous mechanoreceptors logistical regression Date of Presentation/Defense 2001-04-18 Availability unrestricted
Tactile sensation is a complex manifestation of mechanical stimuli applied to the skin. At the most fundamental level of the somatosensory system is the cutaneous mechanoreceptor, making it the logical starting point in the bottom-up approach to understanding the somatosensory system and sensation, in general. Unfortunately, a consensus has not been reached in terms of the afferent behavior of mechanoreceptors subjected to compressive stimulation.
In this study, several afferent mechanoreceptors were isolated, mechanically stimulated with controlled compressive loads. Their responses were recorded and the sensitivities of the individual receptors to compressive stimulation were statistically evaluated by correlating the compressive state of the skin to the observed “all-or-nothing” responses. A host of linear techniques have been employed previously to describe this multiple-input, binary-output system; however, each of these techniques has associated shortcomings when employed in this context. In particular, two shortcomings are the assumption of linear system input-output and the inability of the model to assess individual input-output associations relative to concurrent input in a multivariate context with interacting input. Therefore, a non-linear regression technique called logistical regression was selected for characterizing the mechanoreceptor system. From this model, the relative contributions that each component of the stimulus has upon the neural response of the receptor can be quantitatively assessed and extrapolated to the greater population of cutaneous mechanoreceptors.
Since this study represents a novel approach to receptor characterization, a framework for the application of logistical regression to the time-series representation of the multiple-input, binary-output mechanoreceptor system was established and validated. Subsequently, in-vitro experiments were performed in which the afferent behavior of tactile receptors in rat hairy skin were recorded and the relative association between a number of biologically meaningful stimulus metrics and the observed neural response was evaluated for each receptor. Through the application of logistical regression, it was determined that cutaneous mechanoreceptors are preferentially sensitive to the rate of change of compressive stress when force-control stimulated and both stress and its rate of change when position-control stimulated.
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