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A flexible, interactive software tool for fitting the parameters of neuronal models.

Péter Friedrich¹, Michael Vella², Attila I Gulyás³

¹Laboratory of Cerebral Cortex Research, Institute of Experimental Medicine, Hungarian Academy of Sciences Budapest, Hungary ; Faculty of Information Technology, Péter Pázmány Catholic University Budapest, Hungary.

Frontiers in Neuroinformatics

|July 30, 2014

Summary

Optimizer is a new Python software tool that simplifies fitting neuronal models to experimental data. It offers a user-friendly interface and advanced methods for accurate parameter optimization, outperforming existing tools.

Keywords:

graphical user interface model fitting neuronal modeling parameter optimization python simulation software

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Area of Science:

Computational Neuroscience
Systems Neuroscience
Biophysics

Background:

Accurate neuronal models are crucial for understanding neural function and analyzing experimental data.
Simultaneous fitting of multiple model parameters is computationally challenging and requires specialized tools.

Purpose of the Study:

To develop a user-friendly and extensible software framework, Optimizer, for optimizing neuronal models.
To provide access to advanced fitting methods and guide users through complex optimization scenarios.

Main Methods:

Developed Optimizer in Python, utilizing open-source nonlinear optimization modules.
Integrated Optimizer with the NEURON simulator and supported other simulators via an external interface.
Tested Optimizer on diverse problems, including fitting compartmental and integrate-and-fire models to simulated and experimental data.

Main Results:

Optimizer successfully determined passive parameters and conductance densities in compartmental models.
The software effectively fitted simple neuronal models to complex biological data.
Optimizer demonstrated comparable or superior performance to existing neuronal model fitting tools across various complexities.

Conclusions:

Optimizer provides a powerful, accessible, and flexible solution for neuronal model optimization.
The software facilitates both novice and expert users in fitting complex neuronal models.
Optimizer enhances the analysis of experimental data and the construction of biologically relevant neuronal models.