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首页> 外文期刊>Journal of experimental psychology. Learning, memory, and cognition >Modeling Associative Recognition: A Comparison of Two-High-Threshold, Two-High-Threshold Signal Detection, and Mixture Distribution Models
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Modeling Associative Recognition: A Comparison of Two-High-Threshold, Two-High-Threshold Signal Detection, and Mixture Distribution Models

机译:建模关联识别:双高阈值,两高阈值信号检测和混合分布模型的比较

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摘要

A 2-high-threshold signal detection (HTSDT) model, a mixture distribution (SON) model, and 2-high-threshold (HT) models with responses distributed over 1 or several response categories were fit to results of 6 experiments from 2 studies on associative recognition: R. Kelley and J. T. Wixted (2001) and A. P. Yonelinas (1997). HTSDT assumes that associative recognition is based on conscious recollecLion and familiarity assessment, whereas according to SON and HT, associative information results in a shift of familiarity. The modeling results cast doubt on the prominent role of conscious recollection, and as far as models are valid, parameter estimation suggests 2 processes in associative recognition: a shift in familiarity that is due to associative information and the determination of the source of familiarity of pairs.
机译:具有分布在1或几个响应类别的响应的2高阈值信号检测(HTSDT)模型,混合分布(SON)模型和2高阈值(HT)模型适用于来自2项研究的6个实验的结果 关于联想识别:R. Kelley和JT Wixted(2001)和AP yonelinas(1997)。 HTSDT假设联想识别是基于有意识的回复和熟悉评估,而根据儿子和HT,联想信息导致熟悉的转变。 建模结果对有意识回忆的突出作用令人疑问,而且模型是有效的,参数估计表明联合识别的2个进程:熟悉的转变是由于联想信息和熟悉来源的熟悉来源 。

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