Abstract
Geometric morphometric techniques are extensively used in paleontology and evolutionary biology to describe and quantify shape variation. These approaches, however, are rarely used in neuroscience. Approaches emphasizing qualitative anatomical description and volumetric measurements of brain structures dominate evolutionary neuroscience, whereas automated computing-intensive approaches are the norm in the field of human neuroimaging. Such approaches often are not compatible with formal quantitative assessments of brain evolution (anatomical descriptions), overlook fundamental aspects of shape variation (volumetric measurements), or involve intensive processing of neuroimaging scans, which can complicate straightforward neurobiological interpretation of results. Here we review how geometric morphometrics can provide a useful toolkit to analyze brain variation in a comparative and evolutionary context. We suggest different methodological alternatives within geometric morphometrics, highlighting their advantages and disadvantages. We also discuss how strengths of automated neuroimaging techniques can be combined with geometric morphometric analytical tools.
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We are grateful to Emiliano Bruner, Naomichi Ogihara, and Hiroki Tanabe for their invitation to contribute to this volume.
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Gómez-Robles, A., Reyes, L.D., Sherwood, C.C. (2018). Landmarking Brains. In: Bruner, E., Ogihara, N., Tanabe, H. (eds) Digital Endocasts. Replacement of Neanderthals by Modern Humans Series. Springer, Tokyo. https://doi.org/10.1007/978-4-431-56582-6_8
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