Modern neuroanatomical research is experiencing a transformation through the integration of advanced computer vision and deep learning technologies. This PhD project offers an exciting opportunity to explore the evolutionary development of neural cell populations across terrestrial and marine mammalian brains, examining how different cellular structures in functional brain areas have adapted to support species-specific behaviors and capabilities. By utilizing state-of-the-art artificial intelligence tools, this research makes the complex analysis of neural populations more accessible and efficient than ever before.

The research focuses on comparative studies of the mammalian encephalon across a fascinating range of species, from terrestrial mammals like horses, cats, and sheep, to wild species such as tigers, rhinos, and giraffes, and marine mammals including dolphins, Risso's dolphins, and Cuvier's beaked whales. By applying cutting-edge AI algorithms to analyze neural cell populations, you'll be able to examine intricate patterns of cellular organization with remarkable precision, uncovering evolutionary trends and adaptations that traditional methods might overlook. This modern, data-driven approach bridges the gap between classical comparative neuroanatomy and contemporary computational techniques, making the research both innovative and highly relevant to understanding brain evolution.

The successful candidate will have the unique opportunity to work with species that are rarely accessible for neuroanatomical research, offering invaluable insights into how neural cell populations within functional brain areas have evolved and specialized across terrestrial and marine environments. You will be involved in harvesting, preparing, and analyzing key functional regions including the somatomotor cortex, cerebellum, and hippocampus across various mammalian species. Using custom-developed deep learning algorithms, you'll conduct comparative analyses that characterize the structure and organization of neural cell populations, mapping these cellular architectures to different functional circuits and behavioral capabilities.

This evolutionary perspective provides a comprehensive understanding of how neural cell populations are organized within functional brain areas and how these structures have been shaped by different environmental pressures and ecological niches. Beyond advancing fundamental knowledge in comparative neuroanatomy and evolutionary neuroscience, the findings will have practical implications for veterinary medicine and wildlife conservation, making this an intellectually rewarding project with real-world impact.

Five publications related to the Research topic for the candidate interview:

• Amunts, K., Schleicher, A., Zilles, K.: Cytoarchitecture of the cerebral cortex—more than localization. NeuroImage 37(4), 1061–1065 (2007)
• Song, A.H., Jaume, G., Williamson, D.F., Lu, M.Y., Vaidya, A., Miller, T.R., Mahmood, F.: Artificial intelligence for digital and computational pathology. Nature Reviews Bioengineering 1(12), 930–949 (2023)
• Brenowitz, E. A., & Zakon, H. H. (2015). Emerging from the bottleneck: benefits of the comparative approach to modern neuroscience. Trends in neurosciences, 38(5), 273-278.
• Bolker, J. (2012). Model organisms: There’s more to life than rats and flies. Nature, 491(7422), 31–33. https://doi.org/10.1038/491031a
• Pluchot, C., Adriaensen, H., Parias, C., Dubreuil, D., Arnould, C., Chaillou, E., & Love, S. A. (2024). Sheep (Ovis aries) training protocol for voluntary awake and unrestrained structural brain MRI acquisitions. Behavior Research Methods, 56(7), 7761-7773.
• Glickstein, M., & Voogd, J. (2010). Cerebellum: Evolution and comparative anatomy. Encyclopedia of Neuroscience, 743–756. https://doi.org/10.1016/B978-008045046-9.00947-5

Tutor: Prof. Jean-Marie Graic
e-mail address: jeanmarie.graic@unipd.it