Neural network organization for courtship-song feature detection in Drosophila

Animals communicate using sounds in a wide range of contexts, and auditory systems must encode behaviorally relevant acoustic features to drive appropriate reactions. How feature detection emerges along auditory pathways has been difficult to solve due to both challenges in comprehensively mapping the underlying circuits, particularly in large brains, and in characterizing tuning for behaviorally relevant features. Here, we take advantage of the small size, genetic tools, and connectomic resources for the Drosophila melanogaster brain to investigate feature selectivity for the two main modes of fly courtship song, sinusoids and pulse trains. By building a large collection of genetic enhancer lines, we identify 24 new cell types of the intermediate layers of the auditory pathway. Using a new connectomic resource, FlyWire, we map connections among these cell types, in addition to connections to known early and higher-order auditory neurons. We characterize auditory responses throughout this pathway, and find that the newly discovered neurons show diverse preferences for courtship song modes. However, rather than being sorted into separate streams, neurons with different preferences are highly interconnected. Among this population, frequency tuning is centered on frequencies present in song, whereas rate tuning is biased towards rates below those present in song, suggesting that these neurons form a basis set for the generation of pulse feature tuning downstream. Our study provides new insights into the organization of auditory coding within the Drosophila brain.