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Human EEG Uncovers Latent Generalizable Rule Structure during Learning
被引:58
作者:
Collins, Anne G. E.
[1
]
Cavanagh, James F.
[1
,2
]
Frank, Michael J.
[1
]
机构:
[1] Brown Univ, Providence, RI 02912 USA
[2] Univ New Mexico, Dept Psychol, Albuquerque, NM 87131 USA
基金:
美国国家卫生研究院;
美国国家科学基金会;
关键词:
prefrontal cortex;
task-set;
reinforcement learning;
rules;
EEG;
COGNITIVE CONTROL;
PREFRONTAL CORTEX;
WORKING-MEMORY;
FRONTAL-CORTEX;
TASK;
MECHANISMS;
SWITCH;
RESOLUTION;
DYNAMICS;
ERP;
D O I:
10.1523/JNEUROSCI.3900-13.2014
中图分类号:
Q189 [神经科学];
学科分类号:
071006 ;
摘要:
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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页码:4677 / 4685
页数:9
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