Vitevitch Michael S, Chan Kit Ying, Roodenrys Steven
Department of Psychology University of Kansas.
J Mem Lang. 2012 Jul 1;67(1):30-44. doi: 10.1016/j.jml.2012.02.008.
Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological word-forms influenced retrieval from the mental lexicon (that portion of long-term memory dedicated to language) during the on-line recognition and production of spoken words. In the present study we examined how network structure influences other retrieval processes in long- and short-term memory. In a false-memory task-examining long-term memory-participants falsely recognized more words with low- than high-C. In a recognition memory task-examining veridical memories in long-term memory-participants correctly recognized more words with low- than high-C. However, participants in a serial recall task-examining redintegration in short-term memory-recalled lists comprised of high-C words more accurately than lists comprised of low-C words. These results demonstrate that network structure influences cognitive processes associated with several forms of memory including lexical, long-term, and short-term.
复杂网络描述了系统中的实体如何相互作用；这种网络的结构被认为会影响信息处理。网络结构的一种度量指标，聚类系数C，衡量一个节点的邻居之间也是彼此邻居的程度。先前的心理语言学实验发现，语音词形的C值在口语单词的在线识别和生成过程中会影响从心理词库（长期记忆中专门用于语言的部分）的检索。在本研究中，我们考察了网络结构如何影响长期和短期记忆中的其他检索过程。在一项考察长期记忆的错误记忆任务中，参与者错误识别的低C值单词比高C值单词更多。在一项考察长期记忆中真实记忆的识别记忆任务中，参与者正确识别的低C值单词比高C值单词更多。然而，在一项考察短期记忆中重整作用的系列回忆任务中，参与者对由高C值单词组成的列表的回忆比对由低C值单词组成的列表更准确。这些结果表明，网络结构会影响与几种记忆形式相关的认知过程，包括词汇记忆、长期记忆和短期记忆。
