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BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation

Spiking neural networks (SNNs) serve as a promising computational framework for integrating insights from the brain into artificial intelligence (AI). Existing software infrastructures based on SNNs exclusively support brain simulation or brain-inspired AI, but not both simultaneously. To decode the...

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Detalles Bibliográficos
Autores principales: Zeng, Yi, Zhao, Dongcheng, Zhao, Feifei, Shen, Guobin, Dong, Yiting, Lu, Enmeng, Zhang, Qian, Sun, Yinqian, Liang, Qian, Zhao, Yuxuan, Zhao, Zhuoya, Fang, Hongjian, Wang, Yuwei, Li, Yang, Liu, Xin, Du, Chengcheng, Kong, Qingqun, Ruan, Zizhe, Bi, Weida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435966/
https://www.ncbi.nlm.nih.gov/pubmed/37602224
http://dx.doi.org/10.1016/j.patter.2023.100789
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author Zeng, Yi
Zhao, Dongcheng
Zhao, Feifei
Shen, Guobin
Dong, Yiting
Lu, Enmeng
Zhang, Qian
Sun, Yinqian
Liang, Qian
Zhao, Yuxuan
Zhao, Zhuoya
Fang, Hongjian
Wang, Yuwei
Li, Yang
Liu, Xin
Du, Chengcheng
Kong, Qingqun
Ruan, Zizhe
Bi, Weida
author_facet Zeng, Yi
Zhao, Dongcheng
Zhao, Feifei
Shen, Guobin
Dong, Yiting
Lu, Enmeng
Zhang, Qian
Sun, Yinqian
Liang, Qian
Zhao, Yuxuan
Zhao, Zhuoya
Fang, Hongjian
Wang, Yuwei
Li, Yang
Liu, Xin
Du, Chengcheng
Kong, Qingqun
Ruan, Zizhe
Bi, Weida
author_sort Zeng, Yi
collection PubMed
description Spiking neural networks (SNNs) serve as a promising computational framework for integrating insights from the brain into artificial intelligence (AI). Existing software infrastructures based on SNNs exclusively support brain simulation or brain-inspired AI, but not both simultaneously. To decode the nature of biological intelligence and create AI, we present the brain-inspired cognitive intelligence engine (BrainCog). This SNN-based platform provides essential infrastructure support for developing brain-inspired AI and brain simulation. BrainCog integrates different biological neurons, encoding strategies, learning rules, brain areas, and hardware-software co-design as essential components. Leveraging these user-friendly components, BrainCog incorporates various cognitive functions, including perception and learning, decision-making, knowledge representation and reasoning, motor control, social cognition, and brain structure and function simulations across multiple scales. BORN is an AI engine developed by BrainCog, showcasing seamless integration of BrainCog’s components and cognitive functions to build advanced AI models and applications.
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spelling pubmed-104359662023-08-19 BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation Zeng, Yi Zhao, Dongcheng Zhao, Feifei Shen, Guobin Dong, Yiting Lu, Enmeng Zhang, Qian Sun, Yinqian Liang, Qian Zhao, Yuxuan Zhao, Zhuoya Fang, Hongjian Wang, Yuwei Li, Yang Liu, Xin Du, Chengcheng Kong, Qingqun Ruan, Zizhe Bi, Weida Patterns (N Y) Article Spiking neural networks (SNNs) serve as a promising computational framework for integrating insights from the brain into artificial intelligence (AI). Existing software infrastructures based on SNNs exclusively support brain simulation or brain-inspired AI, but not both simultaneously. To decode the nature of biological intelligence and create AI, we present the brain-inspired cognitive intelligence engine (BrainCog). This SNN-based platform provides essential infrastructure support for developing brain-inspired AI and brain simulation. BrainCog integrates different biological neurons, encoding strategies, learning rules, brain areas, and hardware-software co-design as essential components. Leveraging these user-friendly components, BrainCog incorporates various cognitive functions, including perception and learning, decision-making, knowledge representation and reasoning, motor control, social cognition, and brain structure and function simulations across multiple scales. BORN is an AI engine developed by BrainCog, showcasing seamless integration of BrainCog’s components and cognitive functions to build advanced AI models and applications. Elsevier 2023-07-06 /pmc/articles/PMC10435966/ /pubmed/37602224 http://dx.doi.org/10.1016/j.patter.2023.100789 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Zeng, Yi
Zhao, Dongcheng
Zhao, Feifei
Shen, Guobin
Dong, Yiting
Lu, Enmeng
Zhang, Qian
Sun, Yinqian
Liang, Qian
Zhao, Yuxuan
Zhao, Zhuoya
Fang, Hongjian
Wang, Yuwei
Li, Yang
Liu, Xin
Du, Chengcheng
Kong, Qingqun
Ruan, Zizhe
Bi, Weida
BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation
title BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation
title_full BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation
title_fullStr BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation
title_full_unstemmed BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation
title_short BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation
title_sort braincog: a spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired ai and brain simulation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435966/
https://www.ncbi.nlm.nih.gov/pubmed/37602224
http://dx.doi.org/10.1016/j.patter.2023.100789
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