Laminar analysis of excitatory circuits in vibrissal motor and sensory cortex (Hooks et al. 2011)

 Download zip file 
Help downloading and running models
Accession:137743
"... We mapped local excitatory pathways in each area (primary motor cortex (vM1), primary somatosensory cortex (vS1; barrel cortex), and secondary somatosensory cortex (S2)) across all cortical layers using glutamate uncaging and laser scanning photostimulation. We analyzed these maps to derive laminar connectivity matrices describing the average strengths of pathways between individual neurons in different layers and between entire cortical layers. ..."
Reference:
1 . Hooks BM, Hires SA, Zhang YX, Huber D, Petreanu L, Svoboda K, Shepherd GM (2011) Laminar analysis of excitatory local circuits in vibrissal motor and sensory cortical areas. PLoS Biol 9:e1000572 [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): Neocortex V1 L6 pyramidal corticothalamic GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Activity Patterns; Connectivity matrix; Laminar Connectivity; Touch; Whisking;
Implementer(s):
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
function mhconmatvalues20100928

%Based on Hooks B M, Hires S A, Zhang Y-X, Huber D, Petreanu L, Svoboda K,
%Shepherd G M G (2010 - submitted) "Laminar analysis of excitatory local 
%circuits in vibrissal motor and sensory cortical areas".
%
%Stores the values for connectivity matrices
%There are three cortical regions involved in vibrissal sensation and 
%movement (vM1, vS1, and S2) for which we computed connectivity
%matrices.  For each region there is a neuron-based and a layer-based
%connectivity matrix.
%
%Assigns the variables to the workspace
%Plots each connectivity matrix in a separate figure


connectivitymatrix.vM1.neuron=[NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN;
   -0.0304   -0.0934   -0.0308   -0.0387   -0.0279   -0.0042   -0.0077   -0.0042   -0.0039   -0.0028   -0.0060   -0.0034   -0.0121;
   -0.1727   -0.1112   -0.0970   -0.0416   -0.0326   -0.0103   -0.0073   -0.0055   -0.0054   -0.0013   -0.0020   -0.0031   -0.0031;
   -0.1981   -0.1989   -0.0937   -0.0477   -0.0352   -0.0181   -0.0115   -0.0061   -0.0094   -0.0037   -0.0021   -0.0031   -0.0123;
   -0.2879   -0.2171   -0.0961   -0.0433   -0.0307   -0.0244   -0.0250   -0.0142   -0.0206   -0.0031   -0.0044   -0.0043   -0.0047;
   -0.2666   -0.2893   -0.1143   -0.0481   -0.0507   -0.0407   -0.0569   -0.0381   -0.0258   -0.0059   -0.0030   -0.0046   -0.0034;
   -0.1527   -0.1608   -0.1037   -0.0530   -0.0747   -0.0679   -0.1015   -0.0742   -0.0559   -0.0074   -0.0080   -0.0031   -0.0020;
   -0.0705   -0.0586   -0.0443   -0.0358   -0.0403   -0.0567   -0.0705   -0.0564   -0.0642   -0.0257   -0.0114   -0.0056   -0.0054;
   -0.0889   -0.0416   -0.0219   -0.0218   -0.0235   -0.0255   -0.0334   -0.0382   -0.0447   -0.0248   -0.0301   -0.0186   -0.0173;
   -0.0080   -0.0131   -0.0155   -0.0140   -0.0204   -0.0175   -0.0210   -0.0316   -0.0359   -0.0223   -0.0193   -0.0115   -0.0054;
   -0.0039    0.0013   -0.0088   -0.0060   -0.0048   -0.0046   -0.0118   -0.0141   -0.0270   -0.0173   -0.0140   -0.0180   -0.0147;
    0.0002   -0.0030   -0.0003   -0.0043   -0.0018   -0.0036   -0.0040   -0.0087   -0.0226   -0.0230   -0.0152   -0.0168   -0.0164;
    0.0003   -0.0000   -0.0012   -0.0002   -0.0026   -0.0027   -0.0045   -0.0084   -0.0354   -0.0249   -0.0163   -0.0143   -0.0188;
   -0.0034   -0.0044   -0.0029    0.0013   -0.0020   -0.0017   -0.0054   -0.0049   -0.0171   -0.0148   -0.0122   -0.0117   -0.0138;];

connectivitymatrix.vM1.layer=1.0e+005*[-0.4861   -0.6708   -0.3636   -0.0331;
   -3.7225   -3.2168   -1.1721   -0.2561;
   -4.8596   -3.8855   -5.9974   -0.9269;
   -0.0685   -0.1716   -1.2409   -2.0142;];

connectivitymatrix.vS1.neuron=[NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN;
   -0.1270   -0.1306   -0.0827   -0.0422   -0.0318   -0.0490   -0.0446   -0.0319   -0.0063   -0.0028   -0.0011   -0.0016   -0.0009;
   -0.0566   -0.0702   -0.1222   -0.1200   -0.1202   -0.1591   -0.0764   -0.0307   -0.0218   -0.0089   -0.0026   -0.0023   -0.0042;
   -0.0676   -0.1042   -0.0891   -0.0884   -0.1184   -0.1304   -0.0431   -0.0389   -0.0213   -0.0051   -0.0020   -0.0033   -0.0024;
   -0.0051   -0.0311   -0.0174   -0.0435   -0.0226   -0.0505   -0.0131   -0.0120   -0.0075   -0.0061   -0.0018   -0.0025   -0.0012;
   -0.0083   -0.0146   -0.0232   -0.0170   -0.0197   -0.0143   -0.0142   -0.0187   -0.0179   -0.0078   -0.0048   -0.0020   -0.0015;
   -0.0196   -0.0220   -0.0159   -0.0164   -0.0134   -0.0270   -0.0165   -0.0159   -0.0106   -0.0046   -0.0053   -0.0046   -0.0013;
   -0.1436   -0.2153   -0.1286   -0.0467   -0.0276   -0.0451   -0.0385   -0.0454   -0.0180   -0.0107   -0.0112   -0.0107   -0.0058;
   -0.0308   -0.1210   -0.1165   -0.1472   -0.0629   -0.0469   -0.0428   -0.0376   -0.0241   -0.0118   -0.0105   -0.0067   -0.0035;
   -0.0212   -0.0488   -0.0714   -0.0498   -0.0442   -0.0384   -0.0281   -0.0271   -0.0351   -0.0197   -0.0203   -0.0143   -0.0123;
   -0.0051   -0.0040   -0.0086   -0.0203   -0.0116   -0.0125   -0.0168   -0.0226   -0.0154   -0.0138   -0.0212   -0.0155   -0.0133;
    0.0015   -0.0126    0.0011   -0.0057   -0.0087   -0.0332   -0.0149   -0.0160   -0.0211   -0.0193   -0.0133   -0.0255   -0.0122;
   -0.0036   -0.0081   -0.0096    0.0030    0.0015   -0.0011   -0.0078   -0.0162   -0.0052   -0.0092   -0.0094   -0.0250   -0.0149;
   -0.0030   -0.0033   -0.0035   -0.0030   -0.0038   -0.0015   -0.0022   -0.0042   -0.0033   -0.0019   -0.0035   -0.0078   -0.0152;];

connectivitymatrix.vS1.layer=1.0e+005*[-0.1803   -0.3532   -0.1350   -0.0794   -0.0701   -0.0154;
   -0.3444   -2.1938   -4.6320   -0.9099   -0.5106   -0.1237;
   -0.0436   -0.4269   -0.8707   -0.2070   -0.3143   -0.1608;
   -0.0468   -0.6434   -0.2865   -0.0959   -0.1290   -0.0904;
   -0.2455   -1.5502   -1.5988   -0.2029   -0.4798   -0.5012;
   -0.0296   -0.2624   -0.5109   -0.1061   -0.4726   -1.0880;];

connectivitymatrix.S2.neuron=[NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN;
   -0.0591   -0.1308   -0.1832   -0.0557   -0.0650   -0.0477   -0.0544   -0.0248   -0.0092   -0.0057   -0.0058   -0.0039   -0.0136;
   -0.1604   -0.1631   -0.1704   -0.1391   -0.1210   -0.0944   -0.0793   -0.0399   -0.0163   -0.0059   -0.0042   -0.0030   -0.0045;
   -0.0781   -0.1021   -0.1465   -0.1358   -0.1634   -0.1264   -0.1001   -0.0916   -0.0343   -0.0134   -0.0137   -0.0125   -0.0074;
   -0.1078   -0.1754   -0.2208   -0.1234   -0.2358   -0.1397   -0.1476   -0.1118   -0.0525   -0.0202   -0.0125   -0.0068   -0.0062;
   -0.0334   -0.0347   -0.0651   -0.0685   -0.0614   -0.0814   -0.0490   -0.0600   -0.0489   -0.0232   -0.0160   -0.0102   -0.0047;
   -0.1553   -0.1627   -0.0973   -0.0516   -0.0871   -0.1659   -0.1604   -0.0853   -0.0585   -0.0415   -0.0332   -0.0294   -0.0157;
   -0.1920   -0.3733   -0.2269   -0.1106   -0.0683   -0.1014   -0.2215   -0.1143   -0.0643   -0.0251   -0.0272   -0.0240   -0.0073;
   -0.0774   -0.3233   -0.4035   -0.1430   -0.0730   -0.0619   -0.1745   -0.1421   -0.0618   -0.0424   -0.0451   -0.0238   -0.0061;
   -0.0364   -0.1039   -0.1911   -0.0969   -0.0637   -0.0518   -0.1674   -0.1168   -0.0499   -0.0439   -0.0653   -0.0415   -0.0140;
   -0.0225   -0.1137   -0.0527   -0.0238   -0.0378   -0.0594   -0.0298   -0.0779   -0.0778   -0.0387   -0.0505   -0.0436   -0.0228;
   -0.0109   -0.0018   -0.0086   -0.0151   -0.0167   -0.0321   -0.0384   -0.0747   -0.1022   -0.0605   -0.0283   -0.0223   -0.0279;
   -0.0112   -0.0113   -0.0148   -0.0091   -0.0137   -0.0240   -0.0641   -0.0736   -0.0705   -0.0430   -0.0318   -0.0383   -0.0258;
   -0.0087   -0.0112   -0.0094   -0.0062   -0.0119   -0.0137   -0.0252   -0.0217   -0.0256   -0.0318   -0.0212   -0.0149   -0.0219;];

connectivitymatrix.S2.layer=1.0e+005*[-1.3149   -0.9112   -1.1729   -0.4420   -0.2175   -0.2535;
   -0.9569   -1.1056   -2.1124   -0.6964   -0.6252   -0.4760;
   -0.7033   -0.9021   -1.9951   -0.7609   -0.9807   -0.8880;
   -0.7991   -0.2735   -0.5836   -0.7011   -0.7227   -0.8317;
   -3.7910   -4.6571   -2.8148   -2.0091   -3.3479   -4.4772;
   -0.2924   -0.2949   -0.8099   -1.0271   -4.0796   -7.1397;];

figure, imagesc([0 1],[0 1],connectivitymatrix.vM1.neuron),colormap(flipud(jet(256))),colorbar,title('connectivitymatrix.vM1.neuron');
daspect([1 1 1]);
hold on;
set(gca,'XTick',[0 0.5 1],'YTick',[0 0.5 1]);
xlabel('Presynaptic distance (normalized)');
ylabel('Postsynaptic distance (normalized)');
figure, imagesc([0 1],[0 1],connectivitymatrix.vM1.layer),colormap(flipud(jet(256))),colorbar,title('connectivitymatrix.vM1.layer');
daspect([1 1 1]);
hold on;
set(gca,'XTick',[0 0.5 1],'YTick',[0 0.5 1]);
xlabel('Presynaptic distance (normalized)');
ylabel('Postsynaptic distance (normalized)');

figure, imagesc([0 1],[0 1],connectivitymatrix.vS1.neuron),colormap(flipud(jet(256))),colorbar,title('connectivitymatrix.vS1.neuron');
daspect([1 1 1]);
hold on;
set(gca,'XTick',[0 0.5 1],'YTick',[0 0.5 1]);
xlabel('Presynaptic distance (normalized)');
ylabel('Postsynaptic distance (normalized)');
figure, imagesc([0 1],[0 1],connectivitymatrix.vS1.layer),colormap(flipud(jet(256))),colorbar,title('connectivitymatrix.vS1.layer');
daspect([1 1 1]);
hold on;
set(gca,'XTick',[0 0.5 1],'YTick',[0 0.5 1]);
xlabel('Presynaptic distance (normalized)');
ylabel('Postsynaptic distance (normalized)');

figure, imagesc([0 1],[0 1],connectivitymatrix.S2.neuron),colormap(flipud(jet(256))),colorbar,title('connectivitymatrix.S2.neuron');
daspect([1 1 1]);
hold on;
set(gca,'XTick',[0 0.5 1],'YTick',[0 0.5 1]);
xlabel('Presynaptic distance (normalized)');
ylabel('Postsynaptic distance (normalized)');
figure, imagesc([0 1],[0 1],connectivitymatrix.S2.layer),colormap(flipud(jet(256))),colorbar,title('connectivitymatrix.S2.layer');
daspect([1 1 1]);
hold on;
set(gca,'XTick',[0 0.5 1],'YTick',[0 0.5 1]);
xlabel('Presynaptic distance (normalized)');
ylabel('Postsynaptic distance (normalized)');

assignin('base', 'connectivitymatrix', connectivitymatrix);

Loading data, please wait...