Title
Exploiting Point Source Approximation On Detailed Neuronal Models To Reconstruct Single Neuron Electric Field And Population Lfp
Abstract
Extracellular electrodes record local field potential as an average response from the neurons within the vicinity of the electrode. Here, we used neuronal models and point source approximation techniques to study the compartmental contribution of single neuron LFP and the attenuation properties of extracellular medium. Cable compartmental contribution of single neuron LFP was estimated by computing electric potential generated by localized ion channels. We simulated the electric potential generated from axon-hillock region contributed significantly to the single neuron extracellular field. Models of cerebellar granule neuron and L5 pyramidal neuron were used to study single neuron extracellular field potentials. Attenuation properties of the extracellular medium were studied via the granule cell model. A computational model of a rat Crus-IIa cerebellar granular layer, built with detailed anatomical and physiological properties allowed reconstructing population LFP. As with single neurons, the same technique was able to reconstruct the T and C waves of evoked postsynaptic in vivo LFP trace. In addition to role of attenuation on the width of signals, plasticity was simulated via modifications of intrinsic properties of underlying neurons and population LFP validated experimental data correlating network function to underlying single neuron activity.
Year
Venue
Keywords
2015
2015 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
Computational Neuroscience, Local Field Potential, Point Source Approximation, Cerebellar Granule neuron, L5 neuron, Plasticity
Field
DocType
ISSN
Population,Computational neuroscience,Biological neuron model,Pattern recognition,Biological system,Computer science,Postsynaptic potential,Electric potential,Granule cell,Local field potential,Artificial intelligence,Neuron
Conference
2161-4393
Citations 
PageRank 
References 
1
0.37
4
Authors
5
Name
Order
Citations
PageRank
Harilal Parasuram131.08
Bipin Nair22614.21
Giovanni Naldi34513.96
Egidio D'Angelo45712.77
Shyam Diwakar54418.20