等级制度
集合(抽象数据类型)
计算机科学
人工智能
生成语法
过程(计算)
符号(正式)
计算
理论计算机科学
人工神经网络
任务(项目管理)
序列(生物学)
生成模型
模式识别(心理学)
算法
机器学习
编码(内存)
作者
Bingjiang Lyu,Lang Qin,Xiongfei Wang,Jianxin Ou,Matthew M. Nour,Nai Ding,Jia‐Hong Gao,Yunzhe Liu
标识
DOI:10.1073/pnas.2507417122
摘要
Hierarchically nested structures are fundamental to human cognition, enabling complex behaviors across domains including language, planning, and mathematics. However, the neural mechanisms that enable the flexible construction of these hierarchical structures are poorly understood. Here, we designed a task where participants mentally built sequences with nested, multidepth structures by recursively applying a fixed set of rules. Using magnetoencephalography, we find that the brain constructs nested hierarchies through rapid neural sequences that perform two recurring generative operations. The first operation identifies the hierarchy depth of a symbol and is associated with increased ripple-band power; while the second arranges the symbol into its correct order at that level, a process that scales with the number of depths, also positively correlated with planning time. These results reveal a fundamental neural computation for transforming sensory information into structured representations, which is essential for higher-order cognition.
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