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Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim

Overview of attention for article published in Frontiers in Computational Neuroscience, June 2016
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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Title
Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim
Published in
Frontiers in Computational Neuroscience, June 2016
DOI 10.3389/fncom.2016.00065
Pubmed ID
Authors

Harilal Parasuram, Bipin Nair, Egidio D'Angelo, Michael Hines, Giovanni Naldi, Shyam Diwakar

Abstract

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. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. 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. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals.

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
Unknown 119 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 20%
Researcher 19 16%
Student > Master 19 16%
Student > Bachelor 11 9%
Student > Doctoral Student 8 7%
Other 14 12%
Unknown 25 21%
Readers by discipline Count As %
Engineering 31 26%
Neuroscience 29 24%
Agricultural and Biological Sciences 8 7%
Computer Science 8 7%
Medicine and Dentistry 5 4%
Other 10 8%
Unknown 29 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 July 2016.
All research outputs
#7,733,197
of 24,226,848 outputs
Outputs from Frontiers in Computational Neuroscience
#416
of 1,406 outputs
Outputs of similar age
#122,047
of 358,177 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#11
of 37 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,406 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 358,177 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.