Adaptive Gain Control in the Electrosensory System of Apternotus Leptorhynchus, and Supporting Informatics
Payne, Jeremy Roy
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https://hdl.handle.net/2142/82544
Description
Title
Adaptive Gain Control in the Electrosensory System of Apternotus Leptorhynchus, and Supporting Informatics
Author(s)
Payne, Jeremy Roy
Issue Date
2000
Doctoral Committee Chair(s)
Nelson, Mark E.
Department of Study
Neuroscience
Discipline
Neuroscience
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
"Sensory systems generally exhibit a common class of signal processing features employed to filter primary sensory data before it is interpreted by higher brain structures, removing unwanted noise, suppressing reafferent signals, and compensating for a changing environment. Weakly electric fish possess a unique ""sixth sense,"" which encodes modulations in a self-generated electric field, and is used for navigation, communication, and hunting their prey. The electric sense provides a rich system in which to understand how descending feedback mediates signal processing in active sensory acquisition. It has been previously established that apteronotid weakly electric fish adaptively regulate the gain of pyramidal neurons in the electrosensory lateral line lobe, the first-order nucleus of the gymnotiform electric sense. This work demonstrates that electrosensory afferents are sensitive to changes in the magnitude of the electric organ discharge, whereas the response of pyramidal neurons appears in part to compensate for such changes. Compartmental and simplified cellular models suggest that balanced excitatory and inhibitory descending synapses on pyramidal neurons may mediate such a mechanism at the cellular level, although this effect was noted to be dependent upon the form of action potential generation modeled. Informatics developed to support ongoing investigations are described, including a database system for the management of time-series data (ISNPA), a new platform-independent protocol for storage and analysis of such data (TSDP), and an extensive UNIX-based data acquisition platform (JUDAS)."
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