Inhibitory control explains locomotor statistics in walking Drosophila

• 成果类型: Article
• 署名作者: Gattuso, Hannah C.; van Hassel, Karin A.; Freed, Jacob D.; Nunez, Kavin M.; de la Rea, Beatriz; May, Christina E.; Ermentrout, Bard; Victor, Jonathan D.; Nagel, Katherine I.
• 署名单位: New York University; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Cornell University; Weill Cornell Medicine
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-10573
• DOI: 10.1073/pnas.2407626122
• 发表日期: 2025-04-22
• 关键词: descending neurons; BEHAVIOR; stimulation; distinct; motor

摘要

In order to forage for food, many animals regulate not only specific limb movements but the statistics of locomotor behavior, switching between long-range dispersal and local search depending on resource availability.How premotor circuits regulate locomotor statistics is not clear. Here, we analyze and model locomotor statistics and their modulation by attractive food odor in walking Drosophila. Food odor evokes three motor regimes in flies: baseline walking, upwind running during odor, and search behavior following odor loss. During search, we find that flies adopt higher angular velocities and slower ground speeds and turn for longer periods in the same direction. We further find that flies adopt periods of different mean ground speed and that these state changes influence the length of odor-evoked runs. We next developed a simple model of neural locomotor control that suggests that contralateral inhibition plays a key role in regulating the statistical features of locomotion. As the fly connectome predicts decussating inhibitory neurons in the pre-motor lateral accessory lobe (LAL), we gained genetic access to a subset of these neurons and tested their effects on behavior. We identified one population whose activation induces all three signature of local search and that regulates angular velocity at odor offset. We identified a second population, including a single LAL neuron pair, that bidirectionally regulates ground speed. Together, our work develops a biologically plausible computational architecture that captures the statistical features of fly locomotion across behavioral states and identifies neural substrates of these computations.