Effects of spinal cord stimulation on WDR dorsal horn network (Zhang et al 2014)

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Accession:168414
" ... To study the mechanisms underlying SCS (Spinal cord stimulation), we constructed a biophysically-based network model of the dorsal horn circuit consisting of interconnected dorsal horn interneurons and a wide dynamic range (WDR) projection neuron and representations of both local and surround receptive field inhibition. We validated the network model by reproducing cellular and network responses relevant to pain processing including wind-up, A-fiber mediated inhibition, and surround receptive field inhibition. ..." See paper for more.
Reference:
1 . Zhang TC, Janik JJ, Grill WM (2014) Modeling effects of spinal cord stimulation on wide-dynamic range dorsal horn neurons: influence of stimulation frequency and GABAergic inhibition. J Neurophysiol 112:552-67 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Wide dynamic range neuron;
Channel(s):
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA; Glutamate; Glycine;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s):
Implementer(s): Zhang, Tianhe [tz5@duke.edu];
Search NeuronDB for information about:  GabaA; AMPA; NMDA; Glutamate; Glycine;
%MassPlotter_WoolfWall.m

%Program is designed to plot Woolf and Wall epicenters/time constants based
%on "Subdirectory" organization.

clear
%close all
%CHANGEBLOCK
%Load vital variables
filenameA = 'SG_Cell';
filenameB = 'T_Cell';
SourceID = {'A', 'C'};
%RunIndex =1:100;
%NumRuns = 100;
NumCells = 1;
DirType = {''}
Interval = 1000;
%[GuideNums GuideNames] = xlsread('RunRecordSheet.xls');
%GuideVector = [0.1 0.2 0.5 1 2 5 10 20 50 100];
%SpikeBasisMain = 'CEX_Parameterization_10Tau';
%Due to size of EP Files, only load times specified within TimeRange with a
%specified dt
%CHANGEBLOCK
PlotTitle = 'Woolf and Wall'
RunToPlot = 2; 

tend = 221000;

%Step 2: Load SG and T cell spike times.
for M = 1:length(DirType)
    filenameA = 'SG_Cell';
    filenameB = 'T_Cell';
for a = 1:NumCells 
    fid = fopen(['A Fiber Inhibition\' filenameA '_' num2str(a) '_Times.dat']);
    TempVar = fread(fid, 'double');
    eval([filenameA num2str(a) 'Times = TempVar;'])
    eval([filenameA num2str(a) 'IndexTracker = zeros(1, length(TempVar))+(2.*a-1);']);
    fclose(fid);
    fidB = fopen(['A Fiber Inhibition\' filenameB '_' num2str(a) '_Times.dat']);
    TempVar2 = fread(fidB, 'double');
    eval([filenameB num2str(a) 'Times = TempVar2;'])
    eval([filenameB num2str(a) 'IndexTracker = zeros(1, length(TempVar2))+(2.*a);']);
    fclose(fidB);
    disp('PRINT')
    
end

%Need to split Spike Times into vectors corresponding to "Interval" sized
%blocks.

NumRows = ceil(tend./Interval)
for m = 1:NumRows
    eval([filenameA num2str(a) 'TimesSeg' num2str(m) ' = [];']);
    eval([filenameA num2str(a) 'IndexSeg' num2str(m) ' = [];']);
    eval([filenameB num2str(a) 'TimesSeg' num2str(m) ' = [];']);
    eval([filenameB num2str(a) 'IndexSeg' num2str(m) ' = [];']);
end
    
if isempty(TempVar)==0
    for n = 1:length(TempVar)
        RowIndex = ceil(TempVar(n)./Interval);
        Placement = 221-ceil(TempVar(n)./Interval);
        eval([filenameA num2str(a) 'TimesSeg' num2str(RowIndex) ' = [' filenameA num2str(a) 'TimesSeg' num2str(RowIndex) ' TempVar(n)];']);
        eval([filenameA num2str(a) 'IndexSeg' num2str(RowIndex) ' = [' filenameA num2str(a) 'IndexSeg' num2str(RowIndex) ' ' num2str(Placement) '];']);
    end
end

if isempty(TempVar2)==0
    for n = 1:length(TempVar2)
        RowIndex = ceil(TempVar2(n)./Interval);
        Placement =221-ceil(TempVar2(n)./Interval);
        eval([filenameB num2str(a) 'TimesSeg' num2str(RowIndex) ' = [' filenameB num2str(a) 'TimesSeg' num2str(RowIndex) ' TempVar2(n)];']);
        eval([filenameB num2str(a) 'IndexSeg' num2str(RowIndex) ' = [' filenameB num2str(a) 'IndexSeg' num2str(RowIndex) ' ' num2str(Placement) '];']);
    end
end


%Raster Plots.  For now, use stem plots (idea from David Brocker) with no
%marker, solid lines spanning zone between index corresponding to 1 below
%cell and 1 at cell.  For single SG/T cell analyses, Cell 1 = SG cell, Cell
%2 = T Cell (Outputs)
%For inputs:
%Cell 1 = A Inputs
%Cell 2 = C Inputs 

figure(M+8)
clf
hold on
for a = 1:NumCells
    %If loops ensure that empty matrices (i.e. silent cells) don't stop the routine.
    for b = 1:NumRows
    if isempty(eval([filenameA num2str(a) 'TimesSeg' num2str(b)]))==0
    A = stem(eval([filenameA num2str(a) 'TimesSeg' num2str(b) './1000-(b-1)']), eval([filenameA num2str(a) 'IndexSeg' num2str(b)]), 'BaseValue', eval([filenameA num2str(a) 'IndexSeg' num2str(b) '(end)-0.75']), 'Marker', 'none')
    baseline_handle = get(A,'BaseLine');
    set(baseline_handle,'Color','w');
    set(A, 'Color', 'k')
    end
    end
end
xlim([0 0.18])
ylim([1 tend/1000])
ylabel([filenameA ' Spikes (' num2str(Interval/1000) 's Intervals)'])
title(['Output Activity: ' char(PlotTitle) ' SG'])

figure(M+9)
clf
hold on
for a = 1:NumCells
    for b = 1:NumRows
    if isempty(eval([filenameB num2str(a) 'TimesSeg' num2str(b)]))==0
    B = stem(eval([filenameB num2str(a) 'TimesSeg' num2str(b) './1000-(b-1)']), eval([filenameB num2str(a) 'IndexSeg' num2str(b)]), 'BaseValue', eval([filenameA num2str(a) 'IndexSeg' num2str(b) '(end)-0.75']), 'Marker', 'none', 'LineWidth', 2)
    baseline_handle = get(B,'BaseLine');
    set(baseline_handle,'Color','w');
    set(B, 'Color', 'k')
    end
    end
end
xlim([0 0.18])
ylim([1 tend/1000])
ylabel([filenameB ' Spikes (' num2str(Interval/1000) 's Intervals)'])
title(['Output Activity: ' char(PlotTitle) ' WDR'])

%saveas(gcf, [char(PlotTitle) '_Pair_' num2str(a) '_Output_Raster.png'], 'png')


%Analyze number of spikes per section.  NOTE: current assumption that each
%"section" is 1 second long.  In addition, "early" fiber response will be
%defined as the first 100 ms of each section, and "late' fiber response
%will be defined as everything past 100ms.  These time ranges are set
%according (roughly) to delay times between A fiber and C fiber signal
%arrival. (A fibers: mean 30ms, SD 10 ms; C fibers: mean 275 ms, SD 75ms).

%Reference values: total number of spikes (as expressed by lengths
%of total spike time vector for SG and T Cells). 

DidItWork = 1;
end

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