Advancing neuroscience through real-time processing of big data:Transition from open-loop to closed-loop paradigms  

作　　者：Yu-Fan Wang Jiu-Lin Du 

机构地区：[1]Institute of Neuroscience,State Key Laboratory of Neuroscience,Center for Excellence in Brain Science and Intelligence Technology,Chinese Academy of Sciences,Shanghai 200031,China [2]University of Chinese Academy of Sciences,Beijing 100049,China [3]School of Life Science and Technology,ShanghaiTech University,Shanghai 200031,China

出　　处：《Zoological Research》2024年第3期518-519,共2页动物学研究（英文）

摘　　要：The brain functions as a closed-loop system that continuously generates behavior in response to the external environment and adjusts actions based on the outcomes.Traditional research methodologies in neuroscience,especially those employed in brain imaging experiments,have mainly adopted an open-loop paradigm(Grosenick et al.,2015).Functional neural circuits are analyzed offline and subsequently tested through manipulation of neuronal activities within specific regions or with genetic markers.By establishing a closed-loop research paradigm,functional ensembles can be detected and tested in real time with temporal sequences.These functional ensembles,rather than brain regions or genetically labeled neural populations,serve as fundamental units of neural networks,offering valuable insights into the dissection of neural circuits.The closed-loop research paradigm also enables the capture of high-dimensional activities of internal brain dynamics and precise elucidation of physiological processes such as learning,decision-making,and sleep.

关 键 词：NEURAL LOOP TRANSITION 

分 类 号：Q189[生物学—神经生物学]