Azusa Kamikouchi

This study shows that the fruitless gene in male Aedes aegypti mosquitoes is essential for swarming and attraction to female flight sounds, with its disruption causing loss of these behaviors.

This study identifies a male-specific role for SP-SPR signaling in regulating mating-induced Sex peptide replenishment in Drosophila, suggesting an ancestral function before its known role in female post-mating responses.

This study shows that the doublesex gene is essential for female-specific flight and hearing traits in Aedes aegypti mosquitoes by regulating gene expression in thoraces and ears.

This study shows that dopaminergic signaling via Dop1R2 modulates auditory sensory neuron responses in Drosophila females based on their mating status, affecting song response behavior.

The paper investigates how octopamine and its receptors modulate hearing function in Aedes aegypti mosquitoes, identifying cAMP as a mediator and showing no link between hair erection and frequency tuning.

This study investigates the role of the Shal potassium channel in Drosophila hearing, finding it contributes to mechanotransduction and active antennal tuning.

YORU uses deep learning to detect social behaviors in animals by analyzing their appearance, enabling real-time optogenetic feedback during interactions.

The paper identifies sexual dimorphisms in auditory processing in Aedes aegypti by combining neurotracing, calcium imaging, and molecular analyses, finding enriched motile ciliary-related terms in males.

This study identifies reciprocal neural circuits between pC1 and pCd-2 neurons in Drosophila that mediate song preference learning through GABAergic and dopaminergic inputs.

This study shows fruit flies have an innate preference for conspecific courtship songs, which requires auditory input and can be reacquired during aging.

The paper identifies distinct mechanosensory neuron subpopulations in Drosophila that converge onto a shared neural circuit to elicit grooming behavior.

This paper introduces a hybrid machine learning method to estimate behavioral states and extract features from low-content animal trajectory data, validated across diverse species and environments.