Machine learning classification reveals robust morphometric biomarker of glial and neuronal arbors.

ABSTRACT: Neurons and glia are the two main cell classes in the nervous systems of most animals. Although functionally distinct, neurons and glia are both characterized by multiple branching arbors stemming from the cell bodies. Glial processes are generally known to form smaller trees than neuronal dendrites. However, the full extent of morphological differences between neurons and glia in multiple species and brain regions has not yet been characterized, nor is it known whether these cells can be reliably distinguished based on geometric features alone. Here, we show that multiple supervised learning algorithms deployed on a large database of morphological reconstructions can systematically classify neuronal and glial arbors with nearly perfect accuracy and precision. Moreover, we report multiple

SUBMITTER: Akram MA 

PROVIDER: S-EPMC9828050 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature