UCSF

The ability to perceive and categorize spoken words is a remarkable capability of the human auditory system. Songbirds are one of the few animal orders that face auditory tasks of similar complexity. In this dissertation, I have analyzed auditory responses in the zebra finch at both behavioral (chapter one) and neuronal levels (chapter two). In chapter one, I use an operant condition paradigm to show that female songbirds are able to identify the social context in which a male's song was sung (alone, or directed towards a female). Females require only a short segment of recorded song (a single "motif") to perform this task. I also show that, given only simple temporal information about the stimuli, a machine-learning algorithm can classify most males' motifs according to social context. However, the model's behavior was not consistent with that of the females on individual stimuli, indicating that spectral and temporal cues beyond those tested by the model influence the birds' behavior. Finally, lesions of a nucleus required for social context-dependent differences in spectral variability caused most males to produce songs whose social context was still detectable to females performing the task. Chapter two describes the results of a series of acute electrophysiological recordings in anesthetized female zebra finches. I analyze the responses of single neurons in the songbird auditory forebrain to two types of stimuli: birdsong and an artificially generated stimulus. Using a relatively unbiased mutual-information-based technique, I show that the responses of these neurons change dramatically depending on the stimulus. Across different stages of the ascending auditory pathway, song stimuli gave rise to more complex receptive fields than the artificial stimulus. Receptive fields calculated in response to the song stimuli also had excellent predictive value, far surpassing that of the receptive fields calculated from the artificial stimuli. Our results indicate that for many neurons in the songbird auditory forebrain, receptive field structure is highly dependent on stimulus statistics, and that receptive fields constructed in response to different stimulus classes contain surprisingly little information regarding responses to other sounds.