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在诗歌中,如果韵律有助于记忆,那它会慢慢来。

In poetry, if meter has to help memory, it takes its time.

作者信息

Andreetta Sara, Soldatkina Oleksandra, Boboeva Vezha, Treves Alessandro

机构信息

Cognitive Neuroscience, SISSA, Trieste, 34136, Italy.

Bioengineering, Imperial College London, London, SW7 2AZ, UK.

出版信息

Open Res Eur. 2023 Feb 23;1:59. doi: 10.12688/openreseurope.13663.2. eCollection 2021.

DOI:10.12688/openreseurope.13663.2
PMID:37645121
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10445917/
Abstract

To test the idea that poetic meter emerged as a cognitive schema to aid verbal memory, we focused on classical Italian poetry and on three components of meter: rhyme, accent, and verse length. Meaningless poems were generated by introducing prosody-invariant non-words into passages from Dante's Divina Commedia and Ariosto's Orlando Furioso. We then ablated rhymes, modified accent patterns, or altered the number of syllables. The resulting versions of each non-poem were presented to Italian native speakers, who were then asked to retrieve three target non-words. Surprisingly, we found that the integrity of Dante's meter has no significant effect on memory performance. With Ariosto, instead, removing each component downgrades memory proportionally to its contribution to perceived metric plausibility. Counterintuitively, the fully metric versions required longer reaction times, implying that activating metric schemata involves a cognitive cost. Within schema theories, this finding provides evidence for high-level interactions between procedural and episodic memory.

摘要

为了验证诗歌韵律作为一种认知模式有助于言语记忆这一观点,我们聚焦于古典意大利诗歌以及韵律的三个组成部分:押韵、重音和诗行长度。通过将韵律不变的非单词引入但丁的《神曲》和阿里奥斯托的《疯狂的奥兰多》的段落中,生成了无意义的诗歌。然后我们去除押韵、修改重音模式或改变音节数量。将每首非诗歌的最终版本呈现给以意大利语为母语的人,然后要求他们检索三个目标非单词。令人惊讶的是,我们发现但丁韵律的完整性对记忆表现没有显著影响。相反,对于阿里奥斯托的作品,去除每个组成部分都会根据其对感知韵律合理性的贡献按比例降低记忆效果。与直觉相反的是,完全符合韵律的版本需要更长的反应时间,这意味着激活韵律模式涉及认知成本。在模式理论中,这一发现为程序性记忆和情景记忆之间的高级相互作用提供了证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/2f82fac4c0c4/openreseurope-1-15845-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/032206a030ae/openreseurope-1-15845-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/b142d4d041c5/openreseurope-1-15845-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/692f42a4c40e/openreseurope-1-15845-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/24da9231ffb6/openreseurope-1-15845-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/bc97748f4174/openreseurope-1-15845-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/febbd7818ae6/openreseurope-1-15845-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/2f82fac4c0c4/openreseurope-1-15845-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/032206a030ae/openreseurope-1-15845-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/b142d4d041c5/openreseurope-1-15845-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/692f42a4c40e/openreseurope-1-15845-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/24da9231ffb6/openreseurope-1-15845-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/bc97748f4174/openreseurope-1-15845-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/febbd7818ae6/openreseurope-1-15845-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79a7/10446344/2f82fac4c0c4/openreseurope-1-15845-g0006.jpg

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