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Mechanisms for gain control and temporal processing in the auditory brainstem of the big brown bat, Eptesicus fuscus

Posted on:2000-11-17Degree:Ph.DType:Dissertation
University:University of WashingtonCandidate:Boatright, Rebecca DoreenFull Text:PDF
GTID:1464390014961257Subject:Health Sciences
Abstract/Summary:
The inferior colliculus (IC) receives convergent input from a number of brainstem auditory structures, including the monaural nuclei of the lateral lemniscus (NLL). The cell groups of the NLL receive input from the contralateral cochlear nucleus and send dense projections throughout most of the IC. The NLL are especially large and highly differentiated in echolocating animals such as the bat, suggesting that they are specialized for processing biologically relevant information. Because it is highly likely that the response properties of IC neurons are shaped in part by inputs from the NLL, the effects of selectively removing input from each subdivision of the bat's NLL on responses of IC neurons were examined. With one micropipette, the glutamate antagonist, kynurenic acid, was injected in a physiologically characterized region of the NLL. With a second micropipette, the responses of tonotopically matched IC neurons to sound were recorded. The effects of inactivating groups of neurons in the NLL depended in part on the subdivision of the NLL that was inactivated and in part on the response characteristics of the IC neuron as measured before NLL inactivation. Response properties that were altered by reversibly inactivating the NLL included rate-level functions, response latency, discharge patterns, selectivity for frequency-modulated stimuli, and duration tuning.; Inactivation had less of an effect on amplitude-modulated stimuli and virtually no effect on frequency tuning. The results of these studies indicate that virtually every neuron in the IC is affected by input from the NLL and that the NLL play a key role in modulating gain control and temporal responses of IC neurons.
Keywords/Search Tags:NLL, IC neurons, Input, Response
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