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Adaptive information processing during detection and discrimination of tactile sensory stimuli

Our sensory systems provide us with our ability to perceive and ultimately act upon the world around us. One of the challenges constantly placed on the nervous system is the task of detecting important stimuli among ongoing sensory inputs and then correctly discriminating between possible sources of the stimulus. This dissertation is focused on the study of tactile processing in the rodent vibrissa system to better understand how the nervous system moves between these two operating regimes. The work used a combination of behavioral tasks in trained rats and electrophysiological measurement of neural activity in both anesthetized and awake animals. Results demonstrate that persistent exposure to a sensory stimulus - sensory adaptation - improves spatial discrimination performance, but at the expense of the ability to detect weak stimuli. Parallel experiments involved cortical imaging of anesthetized animals demonstrated important processing changes that could explain these behavioral effects. In a final set of experiments, recordings were obtained from the thalamus, the input stage to the cortex, in awake, behaving animals during performance of a detection task including sensory adaptation. Important changes in the information processing characteristics of the thalamus helped to explain the subsequent cortical and behavioral effects of sensory adaptation. Taken together, results from this set of studies suggest a general principle of adaptive shaping of feature selectivity in sensory processing, resulting from both self-generated sensor motion and the properties of the ongoing stimulus.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/52933
Date12 January 2015
CreatorsOllerenshaw, Douglas R.
ContributorsStanley, Garrett B.
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Languageen_US
Detected LanguageEnglish
TypeDissertation
Formatapplication/pdf

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