The measurement, evolution, and neural representation of action grammars of human behavior
Human behaviors from toolmaking to language are thought to rely on a uniquely evolved capacity for hierarchical action sequencing. Testing this idea will require objective, generalizable methods for measuring the structural complexity of real-world behavior. Here we present a data-driven approach fo...
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| Published in | Scientific reports Vol. 11; no. 1; pp. 13720 - 13 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
02.07.2021
Nature Publishing Group Nature Portfolio |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2045-2322 2045-2322 |
| DOI | 10.1038/s41598-021-92992-5 |
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| Summary: | Human behaviors from toolmaking to language are thought to rely on a uniquely evolved capacity for hierarchical action sequencing. Testing this idea will require objective, generalizable methods for measuring the structural complexity of real-world behavior. Here we present a data-driven approach for extracting action grammars from basic ethograms, exemplified with respect to the evolutionarily relevant behavior of stone toolmaking. We analyzed sequences from the experimental replication of ~ 2.5 Mya Oldowan vs. ~ 0.5 Mya Acheulean tools, finding that, while using the same “alphabet” of elementary actions, Acheulean sequences are quantifiably more complex and Oldowan grammars are a subset of Acheulean grammars. We illustrate the utility of our complexity measures by re-analyzing data from an fMRI study of stone toolmaking to identify brain responses to structural complexity. Beyond specific implications regarding the co-evolution of language and technology, this exercise illustrates the general applicability of our method to investigate naturalistic human behavior and cognition. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Undefined-1 ObjectType-Feature-3 content type line 23 |
| ISSN: | 2045-2322 2045-2322 |
| DOI: | 10.1038/s41598-021-92992-5 |