DocumentCode
3661295
Title
Exploiting point source approximation on detailed neuronal models to reconstruct single neuron electric field and population LFP
Author
Harilal Parasuram;Bipin Nair;Giovanni Naldi;Egidio D´Angelo;Shyam Diwakar
Author_Institution
Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham (Amrita University), Amritapuri, Kerala, India, 690 525
fYear
2015
fDate
7/1/2015 12:00:00 AM
Firstpage
1
Lastpage
7
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.
Keywords
"Biological system modeling","Attenuation","Physiology","Conductivity","Convergence"
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2015 International Joint Conference on
Electronic_ISBN
2161-4407
Type
conf
DOI
10.1109/IJCNN.2015.7280607
Filename
7280607
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