Back close

Reconstructing Local Field Potential from realistic computational models for spontaneous and evoked stimuli

Reconstructing Local Field Potential from realistic computational models for spontaneous and evoked stimuli

Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. LFPsim was developed to be used on existing cable compartmental neuron and network models. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. Simulations with ataxia model suggest that the dysfunction at a single neuron can lead to population code malformations in circuit computations. Further progress in the computational reconstruction of such disease models will also assist in developing animal models of similar disorders.

References

  • Parasuram H, Nair B, D’Angelo E, Hines M, Naldi G, Diwakar S. Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim. Front Comput Neurosci. 2016 Jun 28;10:65. doi: 10.3389/fncom.2016.00065. PMID: 27445781; PMCID: PMC4923190.

Related Projects

Cloud based hybrid pattern recognition approach for fault diagnosis of motor driven rotating machines using motor current signature analysis
Cloud based hybrid pattern recognition approach for fault diagnosis of motor driven rotating machines using motor current signature analysis
Modelling the cerebellar information code in large-scale realistic circuits – Towards pharmacological predictions and robotic abstractions
Modelling the cerebellar information code in large-scale realistic circuits – Towards pharmacological predictions and robotic abstractions
Role of Staphylococcal Pathogen Associated Molecular Patterns in Septic Arthritis
Role of Staphylococcal Pathogen Associated Molecular Patterns in Septic Arthritis
A Machine Learning Approach for Early Prediction of Blood Culture Positivity in Neutropenia Patients Using Medical History and Hematological Parameters
A Machine Learning Approach for Early Prediction of Blood Culture Positivity in Neutropenia Patients Using Medical History and Hematological Parameters
Hybrid Composite for Aviation, Space and Defence Applications
Hybrid Composite for Aviation, Space and Defence Applications
Admissions Apply Now