Sequence Memory Constraints Give Rise to Language-Like Structure through Iterated Learning

PLoS One. 2017 Jan 24;12(1):e0168532. doi: 10.1371/journal.pone.0168532. eCollection 2017.

Abstract

Human language is composed of sequences of reusable elements. The origins of the sequential structure of language is a hotly debated topic in evolutionary linguistics. In this paper, we show that sets of sequences with language-like statistical properties can emerge from a process of cultural evolution under pressure from chunk-based memory constraints. We employ a novel experimental task that is non-linguistic and non-communicative in nature, in which participants are trained on and later asked to recall a set of sequences one-by-one. Recalled sequences from one participant become training data for the next participant. In this way, we simulate cultural evolution in the laboratory. Our results show a cumulative increase in structure, and by comparing this structure to data from existing linguistic corpora, we demonstrate a close parallel between the sets of sequences that emerge in our experiment and those seen in natural language.

MeSH terms

  • Cultural Evolution*
  • Female
  • Humans
  • Language*
  • Learning / physiology*
  • Male
  • Mental Recall / physiology*
  • Models, Psychological
  • Psycholinguistics
  • Retention, Psychology / physiology
  • Young Adult

Grants and funding

HC was supported by an Economic and Social Science Research Council (ESRC) studentship (grant number PTA-031-2005-00225). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.