Chekaf Mustapha, Gauvrit Nicolas, Guida Alessandro, Mathy Fabien
Bases Corpus Langage UMR 7320 CNRS, Université Côte d'Azur.
Human and Artificial Cognition Lab, EPHE.
Cogn Sci. 2018 Jun;42 Suppl 3:904-922. doi: 10.1111/cogs.12601. Epub 2018 Mar 10.
Working memory has been shown to be strongly related to fluid intelligence; however, our goal is to shed further light on the process of information compression in working memory as a determining factor of fluid intelligence. Our main hypothesis was that compression in working memory is an excellent indicator for studying the relationship between working-memory capacity and fluid intelligence because both depend on the optimization of storage capacity. Compressibility of memoranda was estimated using an algorithmic complexity metric. The results showed that compressibility can be used to predict working-memory performance and that fluid intelligence is well predicted by the ability to compress information. We conclude that the ability to compress information in working memory is the reason why both manipulation and retention of information are linked to intelligence. This result offers a new concept of intelligence based on the idea that compression and intelligence are equivalent problems.
工作记忆已被证明与流体智力密切相关；然而，我们的目标是进一步阐明工作记忆中的信息压缩过程，将其作为流体智力的一个决定性因素。我们的主要假设是，工作记忆中的压缩是研究工作记忆容量与流体智力之间关系的一个极佳指标，因为二者都依赖于存储容量的优化。使用算法复杂性度量来估计记忆内容的可压缩性。结果表明，可压缩性可用于预测工作记忆表现，并且信息压缩能力能很好地预测流体智力。我们得出结论，在工作记忆中压缩信息的能力是信息的操纵和保留都与智力相关联的原因。这一结果基于压缩与智力是等效问题的观点，提出了一种新的智力概念。
