官方服务:
资源简介:
Figures from "Implicit value updating explains transitive inference performance: The betasort model"
应用场景:
提供机构:
Fabián Muñoz创建时间:
2015-04-02
相关数据集
Emergent neural dynamics and geometry for generalization in a transitive inference task
Relational cognition, the ability to infer relationships that generalize to novel combinations of objects, is fundamental to human and animal intelligence. Despite this importance, it remains unclear
DataONE2024-03-21 更新100
Multi-scale dynamics samples
Samples corresponding to Explaining multi-scale choice dynamics paper. See the corresponding OSF page (https://osf.io/fbu59/) for the corresponding code.
DataCite Commons2024-10-18 更新90
Forget-me-some: General versus special purpose models in a hierarchical probabilistic task
Humans build models of their environments and act according to what they have learnt. In simple experimental environments, such model-based behaviour is often well accounted for as if subjects are ide
NIAID Data Ecosystem70
Preprint Figures from "Implicit value updating explains transitive inference performance: The betasort model"
Figures from "Implicit value updating explains transitive inference performance: The betasort model" https://peerj.com/preprints/954/ Updated versions of these figure appear in Jensen et al. (2015) "I
DataCite Commons2020-09-04 更新90
Transitive Inference in Derived Lists (Order Maintained) Among Human Participants
Data from a TI experiment in which adjacent pairs were trained for five 5-item lists. At test, new "derived" lists were test, consisting of one item from each training list, each maintaining its origi
DataCite Commons2020-08-30 更新90



