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Author Notes:

Correspondence to: dwstout@emory.edu

We thank Francois Belletti for software development support, and James Steele and Daniel Wolpert for support and encouragement that made this project possible.

DS conceived the study and conducted the replication experiments. TC analyzed brain imaging data. AF and AT developed and applied pattern recognition methods. JA contributed to ethogram development and coded videos. DS, AF and TC wrote the paper.

The authors declare no competing financial interests.

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Research Funding:

This work was supported by the Commission of the European Communities Research Directorate-General Specific Targeted Project number 029065, “Hand to Mouth: A framework for understanding the archaeological and fossil records of human cognitive evolution.”

Keywords:

  • human behavior
  • tool-making
  • language
  • hierarchical action sequencing
  • action grammars
  • basic ethograms

Grammars of action in human behavior and evolution

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Journal Title:

bioRxiv

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Type of Work:

Article | Preprint: Prior to Peer Review

Abstract:

Distinctive human behaviors from tool-making to language are thought to rely on a uniquely evolved capacity for hierarchical action sequencing. Unfortunately, testing of this idea has been hampered by a lack of objective, generalizable methods for measuring the structural complexity of real-world behaviors. Here we present a data-driven approach for quantifying hierarchical structure by extracting action grammars from basic ethograms. We apply this method to the evolutionarily-relevant behavior of stone tool-making by comparing sequences from the experimental replication of ˜2.5 Mya Oldowan vs. more recent ˜0.5 Mya Achuelean tools. Results show that, while using the same “alphabet” of elementary actions, Acheulean sequences are structurally more complex. Beyond its specific evolutionary implications, this finding illustrates the broader applicability of our method to investigate the structure of naturalistic human behaviors and cognition. We demonstrate one application by using our complexity measures to re-analyze data from an fMRI study of tool-making action observation.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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