Open AccessBehavioral control and changes in brain activity of honeybee during flapping
Author(s) -
Ding Haojia,
Zhao Jieliang,
Yan Shaoze
Publication year - 2021
Publication title -
brain and behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.915
H-Index - 41
ISSN - 2162-3279
DOI - 10.1002/brb3.2426
Subject(s) - flapping , insect flight , trajectory , stimulation , duration (music) , simulation , computer science , control theory (sociology) , physics , aerodynamics , neuroscience , acoustics , aerospace engineering , biology , engineering , artificial intelligence , wing , control (management) , astronomy
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.