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.
Many kinds of locomotion abilities of insects-including flight control, spatial orientation memory, position memory, angle information integration, and polarized light guidance are considered to be related to the central complex. However, evidence was still not sufficient to support those conclusions from the aspect of neural basis. For the locomotion form of wing flapping, little is known about the patterns of changes in brain activity of the central complex during movement. Here, we analyze the changes in honeybees’ neuronal population firing activity of central complex and optic lobes with the perspectives of energy and nonlinear changes. Although the specific function of the central complex remains unknown, evidence suggests that its neural activities change remarkably during wing flapping and its delta rhythm is dominative. Together, our data reveal that the firing activity of some of the neuronal populations of the optic lobe shows reduction in complexity during wing flapping. Elucidating the brain activity changes during a flapping period of insects promotes our understanding of the neuro-mechanisms of insect locomotor control, thus can inspire the fine control of insect cyborgs.
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