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蜜蜂扇动翅膀时的行为控制和大脑活动变化。

Behavioral control and changes in brain activity of honeybee during flapping.

机构信息

Division of Intelligent and Biomechanical Systems, State Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing, China.

School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China.

出版信息

Brain Behav. 2021 Dec;11(12):e2426. doi: 10.1002/brb3.2426. Epub 2021 Nov 22.

Abstract

INTRODUCTION

Insect cyborg is a kind of novel robot based on insect-machine interface and principles of neurobiology. The key idea is to stimulate live insects by specific stimuli; thus, the flight trajectory of insects could be controlled as anticipated. However, the neuroregulatory mechanism of insect flight has not been elucidated completely at present.

METHODS

To explore the neuro-mechanism of insect flight behaviors, a series of electrical stimulation was applied on the optic lobes of semi-constrained honeybees. Times of flight initiation, flapping frequency, and duration were recorded by a high-speed camera. In addition, flapping and steering initiation experiments of the cyborg honeybee were verified. Moreover, series of local field potential signals of optic lobes during flapping were collected, pre-processed to remove baseline wander and DC components, then analyzed by power spectrum estimation.

RESULTS

A quantitative optimization method and optimal stimulation parameters of flight initiation were presented. Stimulation results showed that the flapping duration differed greatly while the flapping frequency varied with little difference among different individuals. Moreover, there was always a fluctuation peak around 20-30 Hz in power spectral density (PSD) curves during flapping, distinguishing from calm state, which indicated some brain activity changes during flapping.

CONCLUSIONS

Our study presented a range of relatively optimal electrical parameters to initiate honeybee flight behavior. Meanwhile, the regularity of flapping duration and flapping frequency under electrical stimulations with different parameters were given. The feasibility of controlling a honeybee's flight behavior by brain electrical stimulation was verified through the flapping and steering initiation experiment of honeybees under semi-constrained state. PSD fluctuations reflected changes in brain activity during flapping and that those fluctuation characteristics at the specific frequency band could be sensitive determinants to distinguish whether the honeybee was flying or not, which benefits our understanding of honeybee's flapping behavior and furthers the study of honeybee cyborgs.

摘要

简介

昆虫机器虫是一种基于昆虫-机器接口和神经生物学原理的新型机器人。其关键思想是通过特定刺激来刺激活体昆虫,从而可以按照预期控制昆虫的飞行轨迹。然而,目前昆虫飞行的神经调节机制尚未完全阐明。

方法

为了探索昆虫飞行行为的神经机制,对半约束状态下的蜜蜂的视叶施加了一系列电刺激。通过高速摄像机记录飞行起始时间、拍打频率和持续时间。此外,验证了机器蜜蜂的拍打和转向启动实验。此外,还收集了视叶在拍打过程中的一系列局部场电位信号,对其进行预处理以去除基线漂移和直流分量,然后通过功率谱估计进行分析。

结果

提出了一种定量优化方法和飞行起始的最佳刺激参数。刺激结果表明,不同个体的拍打持续时间差异很大,而拍打频率差异很小。此外,在拍打过程中,功率谱密度(PSD)曲线周围总是存在一个约 20-30 Hz 的波动峰,与平静状态不同,这表明在拍打过程中大脑活动发生了一些变化。

结论

我们的研究提出了一系列相对较优的电参数来启动蜜蜂的飞行行为。同时,给出了在不同参数下电刺激时拍打持续时间和拍打频率的规律。通过半约束状态下蜜蜂的拍打和转向启动实验,验证了通过脑电刺激控制蜜蜂飞行行为的可行性。PSD 波动反映了拍打过程中大脑活动的变化,而在特定频带的波动特征可以作为敏感的决定因素,用于区分蜜蜂是否在飞行,这有助于我们理解蜜蜂的拍打行为,并进一步研究蜜蜂机器虫。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c126/8671781/16d18846d507/BRB3-11-e2426-g005.jpg

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