Determinants of fast calcium dynamics in dendritic spines and dendrites (Cornelisse et al. 2007)

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"... Calcium influx time course and calcium extrusion rate were both in the same range for spines and dendrites when fitted with a dynamic multi-compartment model that included calcium binding kinetics and diffusion. In a subsequent analysis we used this model to investigate which parameters are critical determinants in spine calcium dynamics. The model confirmed the experimental findings: a higher SVR (surface-to-volume ratio) is not sufficient by itself to explain the faster rise time kinetics in spines, but only when paired with a lower buffer capacity in spines. Simulations at zero calcium-dye conditions show that calmodulin is more efficiently activated in spines, which indicates that spine morphology and buffering conditions in neocortical spines favor synaptic plasticity. ..."
1 . Cornelisse LN, van Elburg RA, Meredith RM, Yuste R, Mansvelder HD (2007) High speed two-photon imaging of calcium dynamics in dendritic spines: consequences for spine calcium kinetics and buffer capacity. PLoS One 2:e1073 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
Gap Junctions:
Simulation Environment: CalC Calcium Calculator;
Model Concept(s): Calcium dynamics;
Implementer(s): van Elburg, Ronald A.J. [R.van.Elburg at];
Search NeuronDB for information about:  Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
% Title:    Calcium Signals in Small Structures
% Filename: CaSignal_XDiffKOnSphere.par
% Author:   Ronald van Elburg 
% Associated Paper:
% Cornelisse LN, van Elburg RAJ, Meredith RM, Yuste R, Mansvelder HD (2007) 
% High Speed Two-Photon Imaging of Calcium Dynamics in Dendritic Spines: 
% Consequences for Spine Calcium Kinetics and Buffer Capacity. 
% PLoS ONE 2(10): e1073 doi:10.1371/journal.pone.0001073
Structure           = Sphere_Structure% Make it a sphere
Ca.D        =   D_Calcium*XDiff
Dye.D       =   D_Dye*XDiff         

path = ".\"         % If running under Windows, specify here the path to the
                                    % directory containing the script imported below
file = path "CaSignal_main.par"

include file                        % Import the simulation parameters from the main script

% Auxilary variables for monitoring concentrations at different distances from the membrane

    NoOfSteps = 6    % number of shells in the output (NOT IN THE SIMULATION, THERE THE GRIDSIZE DEFINES THE COMPARTMENTS)
    Ca1 := Ca[R1k] ; Dye1 := Dye[R1k] 
    Ca6 := Ca[R6k] ; Dye6 := Dye[R6k] 

    CaAverage:=Ca[] ; DyeAverage:=Dye[]

% Exporting the variables defined above to file
    %print stdout Ca.D ": " Dye.D
    plot point.mute  Ca1 "Output\Exp""Exp""\CSE""Exp""Geom""_Ca1_""LoopVar""_""LoopVar2"
    plot point.mute  Ca6 "Output\Exp""Exp""\CSE""Exp""Geom""_Ca6_""LoopVar""_""LoopVar2"
    plot point.mute  CaAverage "Output\Exp""Exp""\CSE""Exp""Geom""_CaAverage_""LoopVar""_""LoopVar2"
    plot point.mute  Dye1 "Output\Exp""Exp""\CSE""Exp""Geom""_Dye1_""LoopVar""_""LoopVar2"
    plot point.mute  Dye6 "Output\Exp""Exp""\CSE""Exp""Geom""_Dye6_""LoopVar""_""LoopVar2"
    plot point.mute  DyeAverage "Output\Exp""Exp""\CSE""Exp""Geom""_DyeAverage_""LoopVar""_""LoopVar2"

% Parameter variation
    for XDiff      = 0.05 to 2 step 0.05
    for KPlus_Dye  = 0.025  to  1   step 0.025

% The adaptive integration method fails for the fast calcium change
% to overcome this problem we run the first 20 ms with a fixed timestep 
% of 0.001 ms, then after the fast changes we switch to the adaptive method 
% for optimal performance.

Run  20.0  1.0e-3 ; current CalciumCurrent

Run  adaptive 480.0  1.0e-3 accuracy; current CalciumCurrent

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