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- W2023372837 abstract "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." @default.
- W2023372837 created "2016-06-24" @default.
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- W2023372837 date "2012-07-01" @default.
- W2023372837 modified "2023-09-26" @default.
- W2023372837 title "Complex network structure influences processing in long-term and short-term memory" @default.
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- W2023372837 doi "https://doi.org/10.1016/j.jml.2012.02.008" @default.
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