ABSTRACT
The neural stimulator is a core component of animal robots. While the control effect of animal robots is influenced by various factors, the performance of the neural stimulator plays a decisive role in regulating animal robots. In order to optimize animal robots, embedded neural stimulators had been developed using flexible printed circuit board technology. This innovation not only enabled the stimulator to generate parameter-adjustable biphasic current pulses through control signals, but also optimized its carrying mode, material, and size, overcoming the disadvantages of traditional backpack or head-inserted stimulators, which have poor concealment and are prone to infection. Static, in vitro, and in vivo performance tests of the stimulator demonstrated that it not only had precise pulse waveform output capability, but also was lightweight and small in size. It had excellent in vivo performance in both laboratory and outdoor environments. Our study has high practical significance for the application of animal robots.
Subject(s)
Animals , RoboticsABSTRACT
As an interface between external electronic devices and internal neural nuclei, microelectrodes play an important role in many fields, such as animal robots, deep brain stimulation and neural prostheses. Aiming at the problem of high price and complicated fabrication process of microelectrode, a microelectrode twisting machine based on open source electronic prototyping platform (Arduino) and three-dimensional printing technology was proposed, and its microelectrode fabrication performance and neural stimulation performance were verified. The results show that during the fabrication of microelectrodes, the number of positive twisting turns of the electrode wire should generally be set to about 1.8 times of its length, and the number of reverse twisting rings is independent of the length, generally about 5. Moreover, compared with the traditional instrument, the device is not only inexpensive and simple to manufacture, but also has good expandability. It has a positive significance for both the personalization and popularization of microelectrode fabrication and the reduction of experimental cost.
Subject(s)
Equipment Design , Microelectrodes , Printing, Three-DimensionalABSTRACT
Both spike and local field potential (LFP) signals are two of the most important candidate signals for neural decoding. At present there are numerous studies on their decoding performance in mammals, but the decoding performance in birds is still not clear. We analyzed the decoding performance of both signals recorded from nidopallium caudolaterale area in six pigeons during the goal-directed decision-making task using the decoding algorithm combining leave-one-out and -nearest neighbor (LOO- NN). And the influence of the parameters, include the number of channels, the position and size of decoding window, and the nearest neighbor value, on the decoding performance was also studied. The results in this study have shown that the two signals can effectively decode the movement intention of pigeons during the this task, but in contrast, the decoding performance of LFP signal is higher than that of spike signal and it is less affected by the number of channels. The best decoding window is in the second half of the goal-directed decision-making process, and the optimal decoding window size of LFP signal (0.3 s) is shorter than that of spike signal (1 s). For the LOO- NN algorithm, the accuracy is inversely proportional to the value. The smaller the value is, the larger the accuracy of decoding is. The results in this study will help to parse the neural information processing mechanism of brain and also have reference value for brain-computer interface.