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2 - Culture, Mind, and Brain in Human Evolution

An Extended Evolutionary Perspective on Paleolithic Toolmaking as Embodied Practice

from Section 1 - The Co-emergence of Culture, Mind, and Brain

Published online by Cambridge University Press:  18 September 2020

By
Dietrich Stout
Edited by
Laurence J. Kirmayer ,
Carol M. Worthman ,
Shinobu Kitayama ,
Robert Lemelson  and
Constance A. Cummings
Laurence J. Kirmayer
Affiliation:
McGill University, Montréal
Carol M. Worthman
Affiliation:
Emory University, Atlanta
Shinobu Kitayama
Affiliation:
University of Michigan, Ann Arbor
Robert Lemelson
Affiliation:
University of California, Los Angeles
Constance A. Cummings
Affiliation:
The Foundation for Psychocultural Research
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Summary

Ancient stone tools provide a unique source of empirical evidence for reconstructing the evolutionary origins of human culture, mind, and brain. As a key component of hominid adaptations throughout the Paleolithic, stone tools not only document human evolution but likely helped to shape it. Properly interpreting this evidence requires both “middle-range” theory linking archaeologically observable material remains to the behaviors that created them and high-level theory appropriate for placing these reconstructed behaviors in a broader evolutionary framework. An extended evolutionary perspective on Paleolithic toolmaking as embodied practice integrates levels of analysis by emphasizing the interaction of evolutionary and behavioral processes unfolding on multiple spatiotemporal scales. Although much work remains to be done, initial efforts toward an integrated evolutionary neuroscience of toolmaking are beginning to trace the evolution of a uniquely human technological niche rooted in a shared primate heritage of visuomotor coordination and dexterous manipulation.

Keywords

paleolithic archaeologyhuman evolutioncognitionstone toolsneurosciencecultural evolutionexperimental archaeology4E cognitionextended evolutionary synthesis
Type
Chapter
Information
Culture, Mind, and Brain
Emerging Concepts, Models, and Applications
 , pp. 55 - 87
Publisher: Cambridge University Press
Print publication year: 2020

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