P180 DendroTweaks: An interactive approach for unraveling dendritic dynamics
Roman Makarov*1,2, Spyridon Chavlis1, Panayiota Poirazi1
1Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology-Hellas (FORTH), Heraklion, Greece
2Department of Biology, University of Crete, Heraklion, Greece
*Email: roman_makarov@imbb.forth.gr
Introduction
Neurons rely on the interplay between dendritic morphology and ion channels to transform synaptic inputs into somatic spikes. Detailed biophysical models with active dendrites have been instrumental in exploring this interaction but challenging to understand and validate due to numerous free parameters. We introduceDendroTweaks, a comprehensive toolbox for creating and validating single-cell neuronal models with active dendrites, bridging computational implementation with conceptual understanding.
Methods
DendroTweaksis implemented in Python and provides a high-level interface to NEURON [1] with extended functionality for single-cell modeling and data processing. The core components include: (1) algorithms for representing and refining neuronal morphologies; (2) a NMODL-to-Python converter, along with a framework for standardizing ion channel models through parameter fitting based on equations from [2]; (3) an extended implementation of the impedance-based morphology reduction approach [3] enabling continuous reduction levels; and (4) automated validation protocols for testing somatic and dendritic activity.
Results
The toolbox provides researchers with capabilities to: (1) clean and manipulate SWC morphology files; (2) convert MOD files to Python and standardize kinetics of voltage-gated ion channel models; (3) interactively distribute membrane parameters and synapses across neuronal compartments; (4) reduce detailed morphological models to simplified versions while preserving key electrophysiological properties; and (5) record activity from multiple somatic and dendritic locations to validate neuronal responses to external stimuli. The GUI provides interactive widgets and plots for parameter adjustment with real-time visual feedback (Fig. 1).
Discussion
DendroTweaksaddresses critical challenges in computational neuroscience through data cleaning and model standardization. Its interactive interface enables intuitive exploration of models, illuminating how morpho-electric properties shape dendritic computations and neuronal output. Future work will focus on multi-platform integration with other simulators to further enhance the standardization and accessibility of detailed biophysical models.
Figure 1. Figure 1. A screenshot of the web-based GUI accessed through the Chrome browser. The interface consists of a main workspace and side menus with widgets. The workspace displays interactive plots showing neural morphology, ion channel distributions and kinetics, and simulated activity.
Acknowledgements
Funded by the Horizon 2020 programme of the European Union under grant agreement No 860949. The research project was co-funded by the Stavros Niarchos Foundation (SNF) and the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the 5th Call of “Science and Society” Action Always strive for excellence – Theodoros Papazoglou” (Project Number: DENDROLEAP 28056).
References
1. Hines, M., Davison, A. P., & Muller, E. (2009). NEURON and Python. Frontiers in neuroinformatics, 3, 391. https://doi.org/10.3389/neuro.11.001.2009
2. Sterratt, D., Graham, B., Gillies, A., Einevoll, G., & Willshaw, D. (2023). Principles of computational modelling in neuroscience. Cambridge university press.
3. Amsalem, O., Eyal, G., Rogozinski, N., Gevaert, M., Kumbhar, P., Schürmann, F., & Segev, I. (2020). An efficient analytical reduction of detailed nonlinear neuron models. Nature communications, 11(1), 288. https://doi.org/10.1038/s41467-019-13932-6
