Comprehensive analysis of human dendritic spine morphology and density
Kerstin D Schünemann, Roxanne M Hattingh, Matthijs B Verhoog, Danqing Yang, Aniella Bak, Sabrina Peter, Karen M. J. van Loo, Stefan Wolking, Deborah Kronenberg‐Versteeg, Yvonne Weber, Niklas Schwarz, Joseph V. Raimondo, Roger Melvill, Sean Tromp, James Butler, Anke Hoellig, Daniel Delev, Thomas V. Wuttke, Björn M. Kampa, Henner Koch
Abstract
This study presents a dataset of nearly 4,000 morphologically reconstructed human dendritic spines across different ages, gender, and tissue conditions. The dataset was further used to evaluate a deep learning algorithm for three-dimensional spine reconstruction, offering a scalable method for semiautomated spine analysis across various tissues and microscopy setups. The findings enhance understanding of human neurology, indicating potential connections between spine morphology, brain function, and the mechanisms of neurological and psychiatric diseases.