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ELFENN: A Generalized Platform for Modeling Ephaptic Coupling in Spiking Neuron Models.

Aaron R Shifman1,2,3, John E Lewis1,2,3

  • 1Department of Biology, University of Ottawa, Ottawa, ON, Canada.

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|June 20, 2019
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Summary

Computational modeling of brain electric fields is crucial. A new toolbox, ELFENN, simulates ephaptic coupling by solving electric fields and neuronal dynamics simultaneously, enabling closed-loop analysis.

Keywords:
LFPbioelectric fieldselectric field effectsmodeling toolboxphase locking

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Area of Science:

  • Computational neuroscience
  • Biophysics
  • Neuroimaging

Background:

  • Extracellular electric fields generated by transmembrane ionic currents form the basis of brain signals like EEG.
  • Traditional computational models often treat electric fields and neuronal dynamics separately (post-hoc).
  • This approach is insufficient when extracellular conductivity is low, leading to ephaptic coupling where fields influence neuronal dynamics.

Purpose of the Study:

  • To develop a computational modeling toolbox, ELFENN (Electric Field Effects in Neural Networks), capable of simulating ephaptic coupling.
  • To enable simultaneous solving of neuronal dynamics and extracellular electric fields for closed-loop analysis.
  • To investigate the influence of electric fields on neuronal activity, particularly in low-conductivity brain regions.

Main Methods:

  • Developed ELFENN, a generalized toolbox for compartmental neuron models.
  • Validated ELFENN's open-loop components against established tools (NEURON, LFPy) for membrane dynamics and field potentials.
  • Implemented and utilized ELFENN's closed-loop capability to model feedback of electric fields on neuronal dynamics.

Main Results:

  • ELFENN accurately models membrane dynamics and field potentials in open-loop conditions.
  • ELFENN successfully simulates closed-loop scenarios, demonstrating feedback effects of electric fields on neuronal activity.
  • Used ELFENN to study phase-locking of action potentials in parallel axon bundles as an example of closed-loop ephaptic coupling.

Conclusions:

  • ELFENN provides a novel computational approach to study ephaptic coupling.
  • The toolbox enables simultaneous modeling of neuronal dynamics and electric fields, crucial for understanding closed-loop interactions.
  • ELFENN facilitates research into the physical basis of brain electric fields and their influence on neural dynamics.