Gattuso Hannah C, van Hassel Karin A, Freed Jacob D, Nuñez Kavin M, de la Rea Beatriz, May Christina E, Ermentrout Bard, Victor Jonathan D, Nagel Katherine I
Department of Neuroscience, Neuroscience Institute, New York University School of Medicine, New York, NY 10016.
Department of Mathematics, University of Pittsburgh, Pittsburgh, PA 15213.
Proc Natl Acad Sci U S A. 2025 Apr 22;122(16):e2407626122. doi: 10.1073/pnas.2407626122. Epub 2025 Apr 17.
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 . 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 premotor 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.
为了觅食，许多动物不仅会调节特定的肢体运动，还会调节运动行为的统计特征，根据资源可用性在长距离扩散和局部搜索之间切换。运动前回路如何调节运动统计尚不清楚。在这里，我们分析并模拟了运动统计及其在行走过程中被诱人食物气味调制的情况。食物气味在果蝇中引发三种运动状态：基线行走、气味存在时的逆风奔跑以及气味消失后的搜索行为。在搜索过程中，我们发现果蝇采用更高的角速度和更慢的地面速度，并且在同一方向上转向的时间更长。我们进一步发现果蝇采用不同平均地面速度的时间段，并且这些状态变化会影响气味诱发奔跑的长度。接下来，我们开发了一个简单的神经运动控制模型，该模型表明对侧抑制在调节运动的统计特征中起关键作用。由于果蝇连接体预测在前运动外侧副叶（LAL）中存在交叉抑制神经元，我们通过遗传学方法研究了这些神经元的一个子集，并测试了它们对行为的影响。我们确定了一群神经元，其激活会诱发局部搜索的所有三个特征，并在气味消失时调节角速度。我们还确定了第二群神经元，包括一对单一的LAL神经元，它们双向调节地面速度。总之，我们的工作开发了一种生物学上合理的计算架构，该架构捕捉了果蝇在不同行为状态下运动的统计特征，并确定了这些计算的神经基础。
