Dynamo: An open-source Python application for quantifying neuronal structural plasticity over time

Authors

Hogg, P. W., Coleman, P., Fung, J., Podgorski, K., Toth, T. D., Haas, K.

Abstract

Neurons exhibit tremendous structural plasticity during the growth of dendritic and axonal arbors in early brain circuit formation, followed by experience-driven structural plasticity throughout life. Advances in labeling and in vivo time-lapse imaging allow capture of dynamic structural changes within intact and awake animals, and fluorescent biosensors of neural activity offer opportunities to link structural and functional plasticity. However, the resulting large multi-dimensional data sets are challenging to quantify due to time-consuming tracking of minute structural changes throughout complex neuronal morphologies across time. Here, we present Dynamo: an open-source Python application that enables dynamic morphometrics, the quantitative analysis of morphological changes over time, by streamlining arbor reconstruction, registration of structures across time, and quantitative analyses of growth behavior. Dynamo yields rich characterization of neural structural changes necessary for determining how rapid growth events culminate into long-term patterning, linking structural and functional plasticity, and for identifying underlying molecular mechanisms.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 16 Sep 2026.

Stats

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.