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Teeth

Teeth

The formation of teeth, also known as odontogenesis, is a complex process that begins in utero, around the sixth week of embryonic development. There are three stages to this process: the bud stage, the cap stage, and the bell stage.
In the bud stage, the tooth germ (an aggregation of cells) starts to form in the developing jawbone. During the cap stage, the tooth germ differentiates into enamel organ, dental papilla, and dental sac, which will later develop into the tooth's enamel, dentin...

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Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology

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Artificial neural networks reconstruct missing perikymata in worn teeth.

Mario Modesto-Mata^1,2, Luis de la Fuente Valentín², Leslea J Hlusko¹

¹Centro Nacional de Investigación sobre la Evolución Humana (CENIEH), Burgos, Spain.

Anatomical Record (Hoboken, N.J. : 2007)

|March 12, 2024

Summary

Researchers developed a new artificial neural network (ANN) method to reconstruct missing perikymata (dental growth lines) in fossil hominin teeth. This method improves the accuracy of dental development studies by including worn teeth in analyses.

Keywords:

enamel neural network perikymata reconstruction tooth

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Area of Science:

Paleoanthropology
Developmental Biology
Bioarchaeology

Background:

Dental evolutionary studies are crucial for understanding hominin growth and development.
Tooth enamel's incremental growth records chronological information via perikymata, but early lines are lost to wear.
Previous methods relied on polynomial regressions, with limitations in accuracy and applicability to worn teeth.

Purpose of the Study:

To develop a novel method for reconstructing early, wear-lost perikymata in hominin teeth.
To improve the accuracy of dental developmental timing and growth rate estimations.
To enable the inclusion of worn teeth in dental evolutionary research.

Main Methods:

Utilized an artificial neural network (ANN) approach on a modern human dataset.
Reconstructed earliest perikymata from visible, later-developed perikymata.
Applied the method to all tooth types (incisors, canines, premolars, molars).

Main Results:

The ANN method accurately predicts perikymata counts within 2 units in the initial crown height deciles.
This method enhances the reliability of estimating dental growth periodicity.
Worn teeth, previously excluded, can now be incorporated into research.

Conclusions:

The ANN method offers a significant advancement for reconstructing dental growth lines in fossil hominins.
This tool expands the dataset potential for studies on dental development and evolutionary biology.
The open-source R package 'teethR' facilitates broader application by researchers worldwide.