Abstract
A decline in cognitive functions due to aging has led to critical problems in modern society, and it is imperative to develop a method to predict the decline or related diseases, including dementia. Although it has been expected that language could be a sign of the cognitive decline, it remains less understood, especially in natural conditions. In this study, we recorded the large-scale data of one million words from group conversations among healthy elderly people and analysed the relationship between spoken language and cognitive functions based on scaling laws, namely, Zipf’s law and Heaps’ law. We found that word patterns followed these scaling laws irrespective of cognitive function, but the variations in scaling laws were associated with cognitive functions. Moreover, using generative models, we uncovered the relationship between the variations and cognitive functions. These results indicate that scaling laws in language can be a biomarker for the cognitive decline.
