On the Electrodynamics of Neural Networks

Peter beim Graben and Serafim Rodrigues
Additional contact information
Peter beim Graben: Humboldt-Universität zu Berlin, Bernstein Center for Computational Neuroscience, Göttingen, Germany Department of German Studies and Linguistics
Serafim Rodrigues: University of Plymouth, School of Computing and Mathematics, Centre for Robotics and Neural Systems

Chapter Chapter 10 in Neural Fields, 2014, pp 269-296 from Springer

Abstract: Abstract We present a microscopic approach for the coupling of cortical activity, as resulting from proper dipole currents of pyramidal neurons, to the electromagnetic field in extracellular fluid in presence of diffusion Diffusion and Ohmic conduction. Starting from a full-fledged three-compartment model of a single pyramidal neuron, including shunting and dendritic propagation, we derive an observation model for dendritic dipole currents in extracellular space Extracellular space and thereby for the dendritic field potential that contributes to the local field potential of a neural population. Under reasonable simplifications, we then derive a leaky integrate-and-fire model for the dynamics of a neural network, which facilitates comparison with existing neural network and observation models. In particular, we compare our results with a related model by means of numerical simulations. Performing a continuum limit, neural activity becomes represented by a neural field equation, while an observation model for electric field potentials is obtained from the interaction of cortical dipole currents with charge density in non-resistive extracellular space as described by the Nernst-Planck equation. Our work consistently satisfies the widespread dipole assumption discussed in the neuroscientific literature.

Keywords: Pyramidal Neuron; Pyramidal Cell; Spike Train; Observation Model; Local Field Potential (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-54593-1_10

Ordering information: This item can be ordered from
http://www.springer.com/9783642545931

DOI: 10.1007/978-3-642-54593-1_10

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().