Reviewing the history of the development of artificial intelligence(AI)clearly reveals that brain science has resulted in breakthroughs in AI,such as deep learning.At present,although the developmental trend in AI and...Reviewing the history of the development of artificial intelligence(AI)clearly reveals that brain science has resulted in breakthroughs in AI,such as deep learning.At present,although the developmental trend in AI and its applications has surpassed expectations,an insurmountable gap remains between AI and human intelligence.It is urgent to establish a bridge between brain science and AI research,including a link from brain science to AI,and a connection from knowing the brain to simulating the brain.The first steps toward this goal are to explore the secrets of brain science by studying new brain-imaging technology;to establish a dynamic connection diagram of the brain;and to integrate neuroscience experiments with theory,models,and statistics.Based on these steps,a new generation of AI theory and methods can be studied,and a subversive model and working mode from machine perception and learning to machine thinking and decision-making can be established.This article discusses the opportunities and challenges of adapting brain science to AI.展开更多
Brain science accelerates the study of intelligence and behavior,contributes fundamental insights into human cognition,and offers prospective treatments for brain disease.Faced with the challenges posed by imaging tec...Brain science accelerates the study of intelligence and behavior,contributes fundamental insights into human cognition,and offers prospective treatments for brain disease.Faced with the challenges posed by imaging technologies and deep learning computational models,big data and high-performance computing(HPC)play essential roles in studying brain function,brain diseases,and large-scale brain models or connectomes.We review the driving forces behind big data and HPC methods applied to brain science,including deep learning,powerful data analysis capabilities,and computational performance solutions,each of which can be used to improve diagnostic accuracy and research output.This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible,by improving data standardization and sharing,and by providing new neuromorphic insights.展开更多
Military Brain Science is a cutting-edge innovative science that uses potential military application as the guidance. It was preliminarily divided into 9 aspects by authors： understanding the brain, protecting the br...Military Brain Science is a cutting-edge innovative science that uses potential military application as the guidance. It was preliminarily divided into 9 aspects by authors： understanding the brain, protecting the brain, monitoring the brain, injuring the brain, interfering with the brain, repairing the brain, enhancing the brain, simulating the brain and arming the brain. In this review, we attempt to propose the concept, content and meaning of the Military Brain Science, with the hope to provide some enlightenment and understandin~ of the research area.展开更多
The journal Genomics, Proteomics ＆ Bioinformatics （GPB） is now inviting submissions for a special issue （to be published in the summer of 2018） on the topic of＂Big data in brain science＂.
Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are d...Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.展开更多
The growing demand for advanced neural interfaces that enable precise brain monitoring and modulation has catalyzed significant research into flexible,biocompatible,and highly conductive materials.PEDOT:PSS-based bioe...The growing demand for advanced neural interfaces that enable precise brain monitoring and modulation has catalyzed significant research into flexible,biocompatible,and highly conductive materials.PEDOT:PSS-based bioelectronic materials exhibit high conductivity,mechanical flexibility,and biocompatibility,making them particularly suitable for integration into neural devices for brain science research.These materials facilitate high-resolution neural activity monitoring and provide precise electrical stimulation across diverse modalities.This review comprehensively examines recent advances in the development of PEDOT:PSS-based bioelectrodes for brain monitoring and modulation,with a focus on strategies to enhance their conductivity,biocompatibility,and long-term stability.Furthermore,it highlights the integration of multifunctional neural interfaces that enable synchronous stimulation-recording architectures,hybrid electro-optical stimulation modalities,and multimodal brain activity monitoring.These integrations enable fundamentally advancing the precision and clinical translatability of brain–computer interfaces.By addressing critical challenges related to efficacy,integration,safety,and clinical translation,this review identifies key opportunities for advancing next-generation neural devices.The insights presented are vital for guiding future research directions in the field and fostering the development of cutting-edge bioelectronic technologies for neuroscience and clinical applications.展开更多
基金the Consulting Research Project of the Chinese Academy of Engineering(2019-XZ-9)the National Natural Science Foundation of China(61327902)the Beijing Municipal Science&Technology Commission(Z181100003118014).
文摘Reviewing the history of the development of artificial intelligence(AI)clearly reveals that brain science has resulted in breakthroughs in AI,such as deep learning.At present,although the developmental trend in AI and its applications has surpassed expectations,an insurmountable gap remains between AI and human intelligence.It is urgent to establish a bridge between brain science and AI research,including a link from brain science to AI,and a connection from knowing the brain to simulating the brain.The first steps toward this goal are to explore the secrets of brain science by studying new brain-imaging technology;to establish a dynamic connection diagram of the brain;and to integrate neuroscience experiments with theory,models,and statistics.Based on these steps,a new generation of AI theory and methods can be studied,and a subversive model and working mode from machine perception and learning to machine thinking and decision-making can be established.This article discusses the opportunities and challenges of adapting brain science to AI.
基金supported by the National Natural Science Foundation of China(Grant No.31771466)the National Key R&D Program of China(Grant Nos.2018YFB0203903,2016YFC0503607,and 2016YFB0200300)+3 种基金the Transformation Project in Scientific and Technological Achievements of Qinghai,China(Grant No.2016-SF-127)the Special Project of Informatization of Chinese Academy of Sciences,China(Grant No.XXH13504-08)the Strategic Pilot Science and Technology Project of Chinese Academy of Sciences,China(Grant No.XDA12010000)the 100-Talents Program of Chinese Academy of Sciences,China(awarded to BN)
文摘Brain science accelerates the study of intelligence and behavior,contributes fundamental insights into human cognition,and offers prospective treatments for brain disease.Faced with the challenges posed by imaging technologies and deep learning computational models,big data and high-performance computing(HPC)play essential roles in studying brain function,brain diseases,and large-scale brain models or connectomes.We review the driving forces behind big data and HPC methods applied to brain science,including deep learning,powerful data analysis capabilities,and computational performance solutions,each of which can be used to improve diagnostic accuracy and research output.This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible,by improving data standardization and sharing,and by providing new neuromorphic insights.
基金Chinese National Natural Science Foundation （Grant No. 81701227） the Doctoral Scientific Research Foundation of Liaoning Province （Grant No. 20170520307）.
文摘Military Brain Science is a cutting-edge innovative science that uses potential military application as the guidance. It was preliminarily divided into 9 aspects by authors： understanding the brain, protecting the brain, monitoring the brain, injuring the brain, interfering with the brain, repairing the brain, enhancing the brain, simulating the brain and arming the brain. In this review, we attempt to propose the concept, content and meaning of the Military Brain Science, with the hope to provide some enlightenment and understandin~ of the research area.
文摘The journal Genomics, Proteomics ＆ Bioinformatics （GPB） is now inviting submissions for a special issue （to be published in the summer of 2018） on the topic of＂Big data in brain science＂.
基金supported by the National Natural Science Foundation of China (Grant Nos. 62221005, 61936001, and 62376045)the Natural Science Foundation of Chongqing, China (Grant Nos. cstc2021ycjhbgzxm0013)the Project of Chongqing Municipal Education Commission, China (Grant No. HZ2021008)。
文摘Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.
基金supported by the Hospital-level scientific research fund of Yunfu People’s Hospital(A20231006)the Start-Up Fund for Introduced Talents and Scientific Research at Beijing Normal University(28709-312200502501)+11 种基金Overseas Expert Project of Guangdong Province(30802-110690303)National major project of brain science and brain-like research(2021ZD0204300)National major scientific research instrument development project(61827811)National Natural Science Foundation of China(22407015)Natural Science Foundation of Guangdong Province(2024A1515012271)Guangdong Provincial Pearl River Talents Program(2023QN10Y223)the start-up funding from Beijing Normal University(312200502504)Macao Science and Technology Development Fund(FDCT 0020/2019/AMJ and FDCT 0048/2021/AGJ)University of Macao(MYRGGRG2023-00038-FHS and MYRG2022-00054-FHS)Higher Education Fund of Macao SAR Government Natural Science Foundation of Guangdong Province(EF017/FHS-YZ/2021/GDST)the Macao Science and Technology Development Fund(FDCT 0014/2024/RIB1)Science Foundation of High-Level Talents of Wuyi University(2021AL002).
文摘The growing demand for advanced neural interfaces that enable precise brain monitoring and modulation has catalyzed significant research into flexible,biocompatible,and highly conductive materials.PEDOT:PSS-based bioelectronic materials exhibit high conductivity,mechanical flexibility,and biocompatibility,making them particularly suitable for integration into neural devices for brain science research.These materials facilitate high-resolution neural activity monitoring and provide precise electrical stimulation across diverse modalities.This review comprehensively examines recent advances in the development of PEDOT:PSS-based bioelectrodes for brain monitoring and modulation,with a focus on strategies to enhance their conductivity,biocompatibility,and long-term stability.Furthermore,it highlights the integration of multifunctional neural interfaces that enable synchronous stimulation-recording architectures,hybrid electro-optical stimulation modalities,and multimodal brain activity monitoring.These integrations enable fundamentally advancing the precision and clinical translatability of brain–computer interfaces.By addressing critical challenges related to efficacy,integration,safety,and clinical translation,this review identifies key opportunities for advancing next-generation neural devices.The insights presented are vital for guiding future research directions in the field and fostering the development of cutting-edge bioelectronic technologies for neuroscience and clinical applications.
