Best practices for digitally constructing endocranial casts: examples from birds and their dinosaurian relatives

Amy M. Balanoff, G. S. Bever, Matthew W. Colbert, Julia A. Clarke, Daniel J. Field, Paul M. Gignac, Daniel T. Ksepka, Ryan C. Ridgely, N. Adam Smith, Christopher R. Torres, Stig Walsh, Lawrence M. Witmer

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


The rapidly expanding interest in, and availability of, digital tomography data to visualize casts of the vertebrate endocranial cavity housing the brain (endocasts) presents new opportunities and challenges to the field of comparative neuroanatomy. The opportunities are many, ranging from the relatively rapid acquisition of data to the unprecedented ability to integrate critically important fossil taxa. The challenges consist of navigating the logistical barriers that often separate a researcher from high-quality data and minimizing the amount of non-biological variation expressed in endocasts – variation that may confound meaningful and synthetic results. Our purpose here is to outline preferred approaches for acquiring digital tomographic data, converting those data to an endocast, and making those endocasts as meaningful as possible when considered in a comparative context. This review is intended to benefit those just getting started in the field but also serves to initiate further discussion between active endocast researchers regarding the best practices for advancing the discipline. Congruent with the theme of this volume, we draw our examples from birds and the highly encephalized non-avian dinosaurs that comprise closely related outgroups along their phylogenetic stem lineage.

Original languageEnglish
Pages (from-to)173-190
Number of pages18
JournalJournal of Anatomy
Issue number2
StatePublished - 1 Aug 2016


  • Aves
  • brain
  • comparative neuroanatomy
  • computed tomography
  • endocast


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