BrainPharm: Computational model - Channel density variability among CA1 neurons (Migliore et al. 2018)

Computational model

Data

Name

Channel density variability among CA1 neurons (Migliore et al. 2018)

Submitter name

Michele Migliore

Pipeline ID

Model File

MiglioreEtAl2018PLOSCompBiol2018_r1 [5226322]

Notes

The peak conductance of many ion channel types measured in any given animal is highly variable across neurons, both within and between neuronal populations. The current view is that this occurs because a neuron needs to adapt its intrinsic electrophysiological properties either to maintain the same operative range in the presence of abnormal inputs or to compensate for the effects of pathological conditions. Limited experimental and modeling evidence suggests this might be implemented via the correlation and/or degeneracy in the function of multiple types of conductances. To study this mechanism in hippocampal CA1 neurons and interneurons, we systematically generated a set of morphologically and biophysically accurate models. We then analyzed the ensembles of peak conductance obtained for each model neuron. The results suggest that the set of conductances expressed in the various neuron types may be divided into two groups: one group is responsible for the major characteristics of the firing behavior in each population and the other more involved with degeneracy. These models provide experimentally testable predictions on the combination and relative proportion of the different conductance types that should be present in hippocampal CA1 pyramidal cells and interneurons.

Model Neurons

Hippocampus CA1 pyramidal GLU cell Show Other

More Cells

Model Currents

I h Show Other
Ca pump Show Other
I K Show Other
I K,Ca Show Other
I Calcium Show Other
I CAN Show Other
I M Show Other
I Na,t Show Other
I A Show Other
I_KD Show Other
I T low threshold Show Other
I L high threshold Show Other

Model Receptors

Model Type

Neuron or other electrically excitable cell Show Other

Model Concept

Activity Patterns Show Other
Action Potentials Show Other
Detailed Neuronal Models Show Other
Methods Show Other
Parameter Fitting Show Other

Simulator software

NEURON Show Other
BluePyOpt Show Other

Model papers

Migliore R, Lupascu CA, Bologna LL, Romani A, Courcol JD, Antonel S, Van Geit WAH, Thomson AM, Mercer A, Lange S, Falck J, Roessert CA, Shi Y, Hagens O, Pezzoli M, Freund TF, Kali S, Muller EB, Schuermann F, Markram H, Migliore M (2018) Show Other

Gene

hg folder name (applicable when in ModelDB hg)

MiglioreEtAl2018PLOSCompBiol

Region Organism

Hippocampus Show Other

Model ID Number

Gap Junctions

Implemented by

Migliore, Rosanna [rosanna.migliore at cnr.it] Show Other
Migliore, Michele [Michele.Migliore at Yale.edu] Show Other

Public Submitter Email Address

michele.migliore@pa.ibf.cnr.it

Other Neuron

Hippocampus CA1 interneurons

Model Neurotransmitters

Other Receptor

Other Current

I CAT, I CAL

Other Neurotransmitter

Other Model Type

Other Concept

Parameter Optimizations

Other Simulator

BluePyOPt

Other Implementer

Alternative Version

Citation

Default File Notes

Other Gene

Simulation Platform ID

Has Model View

False

Component

RAM

Hide Auto-launch button

False

Run Protocols

ICG Channel Details

Species

Other categories referring to Channel density variability among CA1 neurons (Migliore et al. 2018)

Revisions:	12
Last Time:	9/24/2018 9:55:03 AM
Reviewer:	Tom Morse - MoldelDB admin
Owner:	Michele Migliore