Dynamo: An open-source Python application for quantifying neuronal structural plasticity over time
- 1University of British Columbia
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.
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BibTeX
@misc{hogg2026dynamo,
title = {{Dynamo: An open-source Python application for quantifying neuronal structural plasticity over time}},
author = {P. W. Hogg and P. Coleman and J. Fung and K. Podgorski and T. D. Toth and K. Haas},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.09.750485},
url = {https://www.biorxiv.org/content/10.64898/2026.09.09.750485v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Dynamo: An open-source Python application for quantifying neuronal structural plasticity over time
AU - P. W. Hogg
AU - P. Coleman
AU - J. Fung
AU - K. Podgorski
AU - T. D. Toth
AU - K. Haas
PY - 2026
DA - 2026/09/09
PB - bioRxiv
DO - 10.64898/2026.09.09.750485
UR - https://www.biorxiv.org/content/10.64898/2026.09.09.750485v1
AB - 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.
ER -