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Image Analysis of Pre-Historic Artifacts Containing Abstract Geometric Patterns in the Context of the Emergence of Human Language




24: Linguistics and Philosophy

Faculty Supervisor:

Shigeru Miyagawa

Faculty email:


Apply by:

February 11, 2021


Shigeru Miyagawa (miyagawa@mit.edu), Christine Ortiz (cortiz@mit.edu)

Project Description

Students majoring in materials science, mechanical engineering, or computer science are encouraged to apply for this research project. Experience with image analysis software and quantitative computational methods will be beneficial. In this project, combinatorial sequences of images of prehistoric material engravings and cave art containing abstract geometric patterns will be analyzed using a variety of cross-disciplinary image analysis and computational methods. Such methods will include dimensional analysis, orientation distribution analysis, deformation morphology characterization, morphometric (shape) analysis, and pattern recognition. These data will be used to elucidate aspects of the emergence of human language. There is a broad consensus across a broad array of disciplines that symbolic behavior and language are intimately connected, and the production of symbolic artifacts is consequently viewed as evidence for the availability of linguistic competence. However, the conceptual link between symbolic behavior and language is still nascent. This project addresses this hypothesized connection between symbolic behavior and language by utilizing cross-disciplinary methodologies for comparing these apparently heterogeneous human symbolic expressions and to identify evidence supporting whether the abstract geometric patterns of prehistoric non-figurative engravings and cave art reflect the availability of a formal grammar parallel to that observed in present-day human language. Quantitative data will be interpreted in partnership with colleagues bringing expertise in linguistic frameworks for formal syntax, history of human visual narratives, and material culture and archeology.


Background in computational analysis of materials would be helpful.