专用的传感器运动电路可通过主动触摸实现精细的纹理识别

A dedicate sensorimotor circuit enables fine texture discrimination by active touch

Jie Yu^1,2, Xuan Guo^1,2, Shen Zheng^1,2, Wei ZhangID^1,2*
1 School of Life Sciences, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China,
² Tsinghua-Peking Center for Life Sciences, Beijing, China

Abstract
Active touch facilitates environments exploration by voluntary, self-generated movements. However, the neural mechanisms underlying sensorimotor control for active touch are poorly understood. During foraging and feeding, Drosophila gather information on the properties of food (texture, hardness, taste) by constant probing with their proboscis. Here we identify a group of neurons (sd-L neurons) on the fly labellum that are mechanosensitive to labellum displacement and synapse onto the sugar-sensing neurons via axo-axonal synapses to induce preference to harder food. These neurons also feed onto the motor circuits that control proboscis extension and labellum spreading to provide on-line sensory feedback critical for controlling the probing processes, thus facilitating ingestion of less liquified food. Intriguingly, this preference was eliminated in mated female flies, reflecting an elevated need for softer food. Our results propose a sensorimotor circuit composed of mechanosensory, gustatory and motor neurons that enables the flies to select ripe yet not over-rotten food by active touch.

主动触摸通过自发的、自发的动作促进环境探索。然而，对于主动触摸的感觉运动控制的神经机制却知之甚少。在觅食和进食期间，果蝇通过不断用鼻子探测来收集食物信息（质地、硬度、味道）。在这里，我们识别了飞行中的一组神经元（sd-L神经元），它们对标签移位和通过轴-轴突触与糖敏感神经元的突触具有机械敏感性，以诱导对较硬食物的偏好。这些神经元还向控制口鼻延伸和唇瓣扩展的运动回路提供反馈，以提供对控制探测过程至关重要的在线感觉反馈，从而促进摄入不太液化的食物。有趣的是，这种偏好在交配的雌性苍蝇中被消除了，这反映出对更软食物的需求增加。我们的研究结果提出了一种由机械感觉、味觉和运动神经元组成的感觉运动回路，使苍蝇能够通过主动触摸来选择成熟但尚未腐烂的食物。

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FlyPAD assay

FlyPAD (Fly Proboscis and Activity Detector) assay was carried out as previously described [59] with slight modifications. Flies were collected upon eclosion and aged for 3~6 days on standard cornmeal medium. For food deprivation, female flies were kept in an empty vial with filter paper soaked with water for 24 hours. Each fly was transferred to one feeding chamber on the FlyPAD board and recorded for 20 min. Sips were detected with Python codes (Cap2-Sip) translated from the MATLAB codes [59,60]. Cumulative sips duration and accumulation were calculated as the summation of all sips detected along the 20 min time window. The codes we used are available at GITHUB: https://github.com/EBGU/Cap2Sip.

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