Exploiting point source approximation on detailed neuronal models to reconstruct single neuron electric field and population LFP
Contributo in Atti di convegno
Data di Pubblicazione:
2015
Citazione:
Exploiting point source approximation on detailed neuronal models to reconstruct single neuron electric field and population LFP / H. Parasuram, B. Nair, G. Naldi, E. D'Angelo, S. Diwakar (PROCEEDINGS OF ... INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS). - In: 2015 International Joint Conference on Neural Networks (IJCNN)Piscataway : Institute of Electrical and Electronics Engineers, 2015. - ISBN 9781479919604. - pp. 1-7 (( convegno International Joint Conference on Neural Networks (IJCNN) tenutosi a Killarney, Ireland nel 2015 [10.1109/IJCNN.2015.7280607].
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.
Tipologia IRIS:
03 - Contributo in volume
Keywords:
Cerebellar Granule neuron; Computational Neuroscience; L5 neuron; Local Field Potential; Plasticity; Point Source Approximation; Software; Artificial Intelligence
Elenco autori:
H. Parasuram, B. Nair, G. Naldi, E. D'Angelo, S. Diwakar
Link alla scheda completa:
Titolo del libro:
2015 International Joint Conference on Neural Networks (IJCNN)