Predictive Methods and Probabilistic Mapping of Subcortical Brain Components in Fossil Carnivora

Paleoneurology reconstructs the evolutionary history of nervous systems through direct observations from the fossil record and comparative data from extant species. Although this approach can provide direct evidence of phylogenetic links among species, it is constrained by the availability and quality of data that can be gleaned from the fossil record. Here, we sought to translate brain component relationships in a sample of extant Carnivora to make inferences about brain structure in fossil species. Using high resolution magnetic resonance imaging on extant canids and felids and 3D laser scanning on fossil Carnivora, spanning some 40 million years of evolution, we derived measurements for select brain components. From these primary data, predictive equations of cortical (gray matter mass, cortical thickness, and gyrification index) and subcortical structures (caudate nucleus, putamen, and external globus pallidus mass) were used to derive estimates for select fossil Carnivora. We found that regression equations based on both extant and simulation samples provided moderate to high predictability of subcortical masses for fossil Carnivora. We also found that using exploratory probabilistic mapping of subcortical structures in extant Carnivora, a reasonable prediction could be made of the 3D subcortical morphospace of fossil endocasts. These results identify allometric departures and establish adult species ranges in brain component size for fossil species. The integrative approach taken in this study may serve as a model to promote further dialog between neurobiologists working on extant Carnivora models and paleoneurologists describing the nervous system of fossils from this understudied group of mammals.

Authors

Institutions

Publication Details

Journal
The Journal of Comparative Neurology
Published
2025-01-01
DOI
https://doi.org/10.1002/cne.70014
Citations
1
Primary Topic
Evolution and Paleontology Studies
Type
article
Field-Weighted Citation Impact
4.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive Methods and Probabilistic Mapping of Subcortical Brain Components in Fossil Carnivora

P. Mahesh, Cheuk Y. Tang, Paul Linh Nguyen, David Hall et al.
1 citations
The Journal of Comparative Neurology
Evolution and Paleontology Studies
4.33
article

Predictive Methods and Probabilistic Mapping of Subcortical Brain Components in Fossil Carnivora

P. Mahesh, Cheuk Y. Tang, Paul Linh Nguyen, David Hall, Olivia C. Matz, Jie Song, Kathleen Bitterman, Chet C. Sherwood, Peter F. Cook, Paul R. Manger, Patrick R. Hof, Rogier B. Mars, Rachna Sahasrabudhe, Mads F. Bertelsen, Muhammad A. Spocter, Demi Oddes, Rachel Dunn, Mathew Yee, Emily Baer, Brandon J. Merritt, Christelle Eliacin, Stefan Lilly, Susan La
article en
1 citations

Abstract

Paleoneurology reconstructs the evolutionary history of nervous systems through direct observations from the fossil record and comparative data from extant species. Although this approach can provide direct evidence of phylogenetic links among species, it is constrained by the availability and quality of data that can be gleaned from the fossil record. Here, we sought to translate brain component relationships in a sample of extant Carnivora to make inferences about brain structure in fossil species. Using high resolution magnetic resonance imaging on extant canids and felids and 3D laser scanning on fossil Carnivora, spanning some 40 million years of evolution, we derived measurements for select brain components. From these primary data, predictive equations of cortical (gray matter mass, cortical thickness, and gyrification index) and subcortical structures (caudate nucleus, putamen, and external globus pallidus mass) were used to derive estimates for select fossil Carnivora. We found that regression equations based on both extant and simulation samples provided moderate to high predictability of subcortical masses for fossil Carnivora. We also found that using exploratory probabilistic mapping of subcortical structures in extant Carnivora, a reasonable prediction could be made of the 3D subcortical morphospace of fossil endocasts. These results identify allometric departures and establish adult species ranges in brain component size for fossil species. The integrative approach taken in this study may serve as a model to promote further dialog between neurobiologists working on extant Carnivora models and paleoneurologists describing the nervous system of fossils from this understudied group of mammals.

The Journal of Comparative NeurologyVol. 533(1)
Allen Institute for Brain Science (US), Radboud University Nijmegen (NL), Iowa State University (US), University of the Witwatersrand (ZA), George Washington University (US), Copenhagen Zoo (DK), University of Oxford (GB), New College of Florida (US), Wellcome Centre for Integrative Neuroimaging (GB), New York Consortium in Evolutionary Primatology (US), Center for Discovery (US), Des Moines University (US), Icahn School of Medicine at Mount Sinai (US)
Carnegie Corporation of New York, Carnegie Foundation for the Advancement of Teaching, Wellcome Trust, Directorate for Biological Sciences, Biotechnology and Biological Sciences Research Council
Life in Land
Openalex Percentile: Top 10%
Evolution and Paleontology Studies
4.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.