期刊
STAR PROTOCOLS
卷 2, 期 2, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.xpro.2021.100423
关键词
-
资金
- NSF CAREER Award [1846578]
- NIH [R56 MH119116]
- UC Davis
Humans can learn the relationship structure between abstract concepts, but internal representations of cognitive maps are challenging to observe. A behavioral training protocol and analytic tools were introduced to measure the internal representation of two-dimensional social hierarchies.
Humans are adept at learning the latent structure of the relationship between ab-stract concepts and can build a cognitive map from limited experiences. Howev-er, examining internal representations of the cognitive map is challenging because they are unobservable and differ across individuals. Here, we introduce a behavioral training protocol designed for human participants to implicitly build a map of two-dimensional social hierarchies while making a series of binary choices and analytic tools for measuring the internal representation of this struc-tural knowledge. For complete details on the use and execution of this protocol, please refer to Park et al. (2020a, 2020b).
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