Human EEG uncovers latent generalizable rule structure during learning

人类脑电图揭示了学习过程中潜在的可泛化规则结构

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Abstract

Human cognition is flexible and adaptive, affording the ability to detect and leverage complex structure inherent in the environment and generalize this structure to novel situations. Behavioral studies show that humans impute structure into simple learning problems, even when this tendency affords no behavioral advantage. Here we used electroencephalography to investigate the neural dynamics indicative of such incidental latent structure. Event-related potentials over lateral prefrontal cortex, typically observed for instructed task rules, were stratified according to individual participants' constructed rule sets. Moreover, this individualized latent rule structure could be independently decoded from multielectrode pattern classification. Both neural markers were predictive of participants' ability to subsequently generalize rule structure to new contexts. These EEG dynamics reveal that the human brain spontaneously constructs hierarchically structured representations during learning of simple task rules.

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