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Updated: Feb 3, 2026

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning
Published on: June 2, 2014
[Comparison of decoding performance between spike and local field potential signals during goal-directed
Xinyu Liu1, Yanna Ping2, Dongyun Wang2
1School of Information Engineering, Huanghuai University, Zhumadian, Henan 463000, P.R.China;School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, P.R.China;Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou University, Zhengzhou 450001, P.R.China.liuxinyu@huanghuai.edu.cn.
Abstract:
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 k-nearest neighbor (LOO- kNN). And the influence of the parameters, include the number of channels, the position and size of decoding window, and the nearest neighbor k 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- kNN algorithm, the accuracy is inversely proportional to the k value. The smaller the k 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.
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