Working Group 2: 2010 Initiatives

Jim Bassingtwaighte (March 7, 2010):

We are brainstorming with the overall goal of determining community/group efforts we can focus on to forward research in muscle physiology.

I have a variant on your last suggestion. Given that we all need a big model of intermediary metabolism (Mito energetics, TCA, NAD/NADH/ phosphoenergetics, ion cycling, pentose shunt, insulin recpetor regulation, and such) we might take individual pieces of these and plan to put them together as a group.

Hippocampal Large-Scale Model

What is being modeled?
Rat Hippocampus
Description & purpose of resource

The project is to develop a full-scale model of rat hippocampus using compartmental models of individual neurons. The code available can be used to construct the connectivity for an entorhinal-dentate network with lateral and medial entorhinal cortical cells as spike generators and compartmental models of dentate granule cells and basket cells. The code can then be used to run simulations using the network.

Spatial scales
cellular
Temporal scales
10-6 - 10-3 s
10-3 - 1 s
1 - 103 s
This resource is currently
a demonstration or a framework to be built upon (perhaps with a sample implementation)
Has this resource been validated?
No
Key publications (e.g. describing or using resource)
  1. Yu, G.J., Bouteiller, J.-M.C., Song, D., and Berger, T.W.  Axonal anatomy optimizes spatial encoding in the rat entorhinal-dentate system: A computational study.  IEEE Transactions on Biomedical Engineering, 2019, 1-1, DOI: 10.1109/TBME.2019.2894410.
  2. Bingham, C.S., Loizos, K., Yu, G.J., Gilbert, A., Bouteiller, J.-M.C., Song, D., Lazzi, G., and Berger, T.W.  Model-based analysis of electrode placement and pulse amplitude for hippocampal stimulation.  IEEE Transactions on Biomedical Engineering, 2018, 99, 1-1, DOI: 10.1109/TBME.2018.2791860.
  3. Hendrickson, P.J., Yu, G.J., Song, D., and Berger, T. W. A million­plus neuron model of the hippocampal dentate gyrus: Critical role for topography in determining spatiotemporal network dynamics. IEEE Transactions on Biomedical Engineering, 2015, 63(1), DOI: 10.1109/TBME.2015.2445771.
DOI link to publication describing this resource
  1. 10.1109/TBME.2019.2894410
  2. 10.1109/TBME.2018.2791860
  3. 10.1109/TBME.2015.2445771
Link to resource
Git Repository for Model
Collaborators
Theodore W. Berger
PI contact information
berger@usc.edu
Keywords
MSM U01
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SHAPED Dendritic Morphology Generation

What is being modeled?
Dendritic morphology
Description & purpose of resource

This project measures statistical properties from sets of digital reconstructions of dendritic morphologies. It then stochastically generates new morphologies based on the measured statistical distributions. The key innovation of this tool's approach is to estimate the change in branching rate as a function of distance from soma by modeling branching rate as a heterogeneous Poisson process. A point process filter is used to estimate the branching rate. The uploaded example includes a data set for measuring the the morphology of dentate granule cells and generating new granule cells.

Spatial scales
cellular
This resource is currently
a demonstration or a framework to be built upon (perhaps with a sample implementation)
Has this resource been validated?
No
Key publications (e.g. describing or using resource)

Chou, Z. Z., Yu, G. J., & Berger, T. W. (2020). Generation of Granule Cell Dendritic Morphologies by Estimating the Spatial Heterogeneity of Dendritic Branching. Frontiers in Computational Neuroscience, 14. https://doi.org/10.3389/fncom.2020.00023

DOI link to publication describing this resource

https://doi.org/10.3389/fncom.2020.00023

Link to resource
Git Repository for Tool
Collaborators
Theodore W. Berger
PI contact information
berger@usc.edu
Keywords
MSM U01
Table sorting checkbox
Off
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