A Brain-Inspired Decision-Making Spiking Neural Network and Its Application in Unmanned Aerial Vehicle
- 1Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- 2University of Chinese Academy of Sciences, Beijing, China
- 3National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- 4Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
A corrigendum on
A brain-inspired decision-making spiking neural network and its application in unmanned aerial vehicle
by Zhao, F., Zeng, Y., and Xu, B. (2018). Front. Neurorobot. 12:56. doi: 10.3389/fnbot.2018.00056
In the published article, there was an error. “Variable writing error in the algorithm 1.”
A correction has been made to Materials and methods, “Experimental procedure,” Algorithm 1. This sentence previously stated:
“DLPFC-DtrD1”
The corrected sentence appears below:
“DLPFC-StrD1”
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
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Keywords: spiking neural network, brain-inspired decision-making, dopamine regulation, multiple brain areas coordination, reinforcement learning, UAV autonomous learning
Citation: Zhao F, Zeng Y and Xu B (2022) Corrigendum: A brain-inspired decision-making spiking neural network and its application in unmanned aerial vehicle. Front. Neurorobot. 16:1092428. doi: 10.3389/fnbot.2022.1092428
Received: 08 November 2022; Accepted: 17 November 2022;
Published: 29 November 2022.
Edited and reviewed by: Yongping Pan, National University of Singapore, Singapore
Copyright © 2022 Zhao, Zeng and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yi Zeng, eWkuemVuZyYjeDAwMDQwO2lhLmFjLmNu
†These authors have contributed equally to this work