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);