ArticleScientific reports2021
The measurement, evolution, and neural representation of action grammars of human behavior.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Isolating error-based and reward-based learning in a real-world task via gradual perturbations in embodied VR.iScience · 2026Article
- Measuring hierarchical structure across hominid percussive tool-use sequences.Communications biology · 2026Article
- Neural representation of action symbols in primate frontal cortex.bioRxiv : the preprint server for biology · 2025Article
- Motor learning mechanisms are not modified by feedback manipulations in a real-world task.NPJ science of learning · 2025Article
- Costs of Early Stone Toolmaking cannot Establish the Presence of Know-how Copying.Human nature (Hawthorne, N.Y.) · 2025Article
- Exploring the cognitive underpinnings of early hominin stone tool use through an experimental EEG approach.Scientific reports · 2024Article
- Expanding the causal menu: An interventionist perspective on explaining human behavioural evolution.Evolutionary human sciences · 2024Article
- Nonadjacent dependencies and sequential structure of chimpanzee action during a natural tool-use task.PeerJ · 2024Article
- Generative cultural learning in children and adults: the role of compositionality and generativity in cultural evolution.Proceedings. Biological sciences · 2023Article
- Neuroplasticity enables bio-cultural feedback in Paleolithic stone-tool making.Scientific reports · 2023Article
- Early knapping techniques do not necessitate cultural transmission.Science advances · 2022Article
- Efficiency fosters cumulative culture across species.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
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5 authors.
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Abstract
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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