The Female Songbird as a Novel Mechanistic Model for the Neural Basis of Social Evaluation

Project Summary In nearly every social interaction, we are constantly evaluating and making judgments about other people’s behaviors, such as their words, posture, or tone of voice. While neuroscience is making rapid progress on how the brain encodes one’s own behavior, little is known, in any model system, about how neural circuits evaluate another individual’s actions for proper social responses. Though an active area of research, neither has this problem been resolved by artificial intelligence algorithms. This lack of understanding presents a major obstacle to treating the large number of people with disorders of social evaluation, such as auditory processing disorders, aphasias, agnosias, autism spectrum disorder, and several neurodegenerative diseases. Here I propose the female songbird, which has evolved a specialized behavior and dedicated neural circuits to evaluate male song, as a novel mechanistic model for social evaluation. Mate choice is a prime example of social assessment, in which animals evaluate the quality of potential mates. Birdsong is one of the most quantifiable signals males use to court females, making the female songbird an ideal model for social evaluation. The male zebra finch is an excellent model in neuroscience because song is a highly stereotyped motor sequence and its brain contains a tractable song system dedicated to singing. While only males sing, females also possess a ‘song system’, required for perceiving song in several species of non-singing females. Thus, our overarching hypothesis is that the zebra finch song system has co-evolved for complementary sexually dimorphic traits: song production in males and song evaluation and preference in females. Female zebra finches prefer stereotyped over variable songs but evaluating stereotypy is not trivial; the brain must first form an internal representation of the suitor’s song, then rapidly compare features across renditions, before showing a preference for the most attractive songs. I propose studying the female songbird to address three fundamental questions: How does the brain encode an internal representation of others’ behavior? How does the brain evaluate the quality of others’ behavior? How does the brain show a preference for the most desirable behavior in others? Reflecting a larger bias toward males in neuroscience, songbird research has also primarily focused on song production in males, leaving the female brain, and the neural mechanisms of mate choice, largely neglected. For the New Innovator Award, I propose a unique melding of neurobiology, ethology, and evolution with state of the art behavioral (song preference assays, machine-learning based social behavior tracking), neural (photometry, optogenetics, multi-region electrophysiology), and computational methods to establish the female songbird as a mechanistic model for how we evaluate the actions of others. Such a cellular and circuit- level understanding will pave the way to decoding the neural circuits for mating, monogamy, and the pair bond, inform emerging artificial intelligence algorithms, and provide insights into disorders characterized by deficits in social interactions, such as aphasias, agnosias, and autism.