School of Psychological Sciences, Tel Aviv Univeristy.
Sagol School of Neuroscience, Tel Aviv University.
J Exp Psychol Hum Percept Perform. 2024 Feb;50(2):139-151. doi: 10.1037/xhp0001173.
Considering working memory capacity limitations, representing all relevant data simultaneously is unlikely. What remains unclear is why some items are better remembered than others when all data are equally relevant. While trying to answer this question, the literature has identified a pattern named the mixed-category benefit in which performance is enhanced when presenting stimuli from different categories as compared to presenting a similar number of items that all belong to just one category. Moreover, previous studies revealed an asymmetry in performance while mixing certain categories, suggesting that not all categories benefit equally from being mixed. In a series of three change-detection experiments, the present study investigated the role of low-level perceptual similarities between categories in determining the mixed-category asymmetric advantages. Our primary conclusion is that items' similarity at the perceptual level has a significant role in the asymmetric performance in the mixed-category phenomenon. We measured sensitivity (d') to detect a change between sample and test displays and found that the mixed-category advantage dropped when the mixed categories shared basic features. Furthermore, we found that sensitivity to novel items was impaired when presented with another category sharing its basic features. Finally, increasing the encoding interval improved performance for the novel items, but novel items' performance was still impaired when these items were mixed with another category that shared their basic features. Our findings highlight the significant role low-level similarities play in the asymmetric mixed-category performances, for both novel and familiar categories. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
考虑到工作记忆容量的限制，同时呈现所有相关数据是不太可能的。目前尚不清楚的是，当所有数据都同等相关时，为什么有些项目比其他项目更容易被记住。在试图回答这个问题的过程中，文献中发现了一种名为“混合类别优势”的模式，即在呈现来自不同类别的刺激时，与呈现仅属于一个类别的相似数量的项目相比，表现会得到增强。此外，先前的研究揭示了在混合某些类别时表现的不对称性，表明并非所有类别都能从混合中同等受益。在一系列三项变化检测实验中，本研究探讨了类别之间低水平感知相似性在确定混合类别不对称优势中的作用。我们的主要结论是，项目在感知层面的相似性在混合类别现象中的不对称表现中起着重要作用。我们测量了检测样本和测试显示之间变化的敏感性（d'），发现当混合类别具有基本特征时，混合类别优势会下降。此外，我们发现当呈现与其具有基本特征的另一个类别时，对新类别的敏感性会受到损害。最后，增加编码间隔可以提高新类别的表现，但当这些新类别的项目与具有基本特征的另一个类别混合时，新类别的表现仍然会受到损害。我们的研究结果强调了低水平相似性在混合类别表现的不对称性中所起的重要作用，无论是对新类别还是熟悉的类别。（PsycInfo 数据库记录（c）2024 APA，保留所有权利）。
