The effects of noise exposure and genetic background on auditory-evoked behaviors in larval zebrafish

Auditory sensitivity and perception can be influenced by extrinsic factors, such as environmental noise, and intrinsic factors, such as genes and arousal. How do these factors interact and influence auditory-related behaviors? I addressed this question in the larval zebrafish (Danio rerio). Zebrafish have been a powerful genetic model species used in the study of development of auditory structures and exhibit a well-studied and robust escape response when presented with a loud acoustic stimulus. I used psychophysical methods to measure auditory sensitivity and perception by observing changes in this behavioral response. In chapter 2, I describe a novel paradigm using prepulse inhibition as a tool to measure auditory sensitivity in larval zebrafish. I show that this paradigm is more sensitive than other behavioral measures used in zebrafish research. Next, in chapter 3, I demonstrate that loud noise exposure leads to a temporary hypersensitivity toward startle-inducing stimuli, whereas auditory sensitivity, as measured using the prepulse inhibition paradigm, is unchanged. I use pharmacological and physiological measures to explore potential mechanisms of this hypersensitization effect. Finally, in chapter 4, I investigate effects of genetic background on auditory sensitivity and susceptibility to noise exposure between closely related individuals and across multiple zebrafish lines. The results of these experiments show large-scale differences in startle sensitivity between wild-type zebrafish lines. I discuss the implications of this data, summarize these findings in a larger context, and discuss future studies in chapter 5.

Author dc:creator

• Bhandiwad, Ashwin

Advisor dc:contributor.advisor

• Sisneros, Joseph A

• auditory behavior
• noise exposure
• prepulse inhibition
• zebrafish

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/1773/36819

OAI identifier oai:identifier

oai:digital.lib.washington.edu:1773/36819