***** Overview *****
This is NIH1_Age_Gender, regression parameters obtained from a sample of healthy children whose data was acquired as part of the NIH study of normal brain development, objective 1 (Evans AC; Brain Development Cooperative Group: The NIH MRI study of normal brain development. Neuroimage 2006; 30: 184-202; further details on the study can be obtained at http://www.bic.mni.mcgill.ca/nihpd/info/). 


The rationale, approach, and many more details can be found in our accompanying manuscript (Wilke M, Holland SK, Altaye M, Gaser C: Template-O-Matic: A toolbox for creating customized pediatric templates, available online at http://dx.doi.org/10.1016/j.neuroimage.2008.02.056). This manuscript also contains more information on the processing stream applied to the data. This data is made available to the scientific community to explore the effects of using pediatric as opposed to adult brain data when doing neuroimaging studies in children. As laid out in the license agreement, the authors expect you to include a citation or acknowledgment if you present or publish results obtained using data from this distribution. Please also note our disclaimer!


Further information about the project as a whole can also be found on the website of the Imaging Research Center of Cincinnati Children's Hospital Medical Center at http://www.irc.cchmc.org (follow Software, Pediatric Brain Templates) and on the Structural Brain Mapping Group's website at http://dbm.neuro.uni-jena.de/software/tom/


***** Data *****
This set of regression parameters was obtained using the "estimate regression parameters" option within the Template-O-Matic (TOM8) toolbox, revision 9, on SPM8 (revision 3684, see http://www.fil.ion.ucl.ac.uk/spm/software/spm8/) running within Matlab 7.9 (http://www.mathworks.com/). It uses data from the 404 subjects listed below. Parameters were obtained for gray matter, white matter, cerebrospinal fluid, and T1 whole-brain datasets. Age was entered as years (with 2 decimal places) and was modelled as a combination of linear, quadratic, and cubic functions. Gender was coded as 1 (male) and 0 (female). No further covariates of interest were entered (see our manuscript, above, for the rationale for doing this). Note that, due to the contributing subjects, the age range of this dataset is confined to 4.75 - 18.58 years of age.


***** Getting Started *****
To create your own template, you should ...
- install and call up the Template-O-Matic toolbox (TOM8) in SPM8 (see Install.txt for this);
- click on "Create new template";
- select the TOM.mat file coming with this dataset;
- select the prior/template you want to save;
- select template creation method (we suggest "Average approach");
- enter the age of your desired template as a vector, e.g. reflecting your sample (e.g. "5.5 7.25 8.75 9.66");
- enter gender information of your sample as 1, male, or 0, female (optional - but may be a good idea);
- enter additional covariates of interest (optional and ONLY works if these have been used when creating the regression parameters, i.e. this will not work for this dataset as we only calculated the regression for age and gender);
- save animated gif image (optional - but nice to look at as it shows the structural change occurring within the age range you entered);
- output directory (optional - but a good idea to specify one as you may otherwise loose track of your data);
- Run

That's it. Matlab will now use the estimated parameters to generate a matched template based on your input data. 


***** Support *****
This collection of files is not officially supported or developed further since we do not have the ressources to provide this service on an acceptable and ongoing basis. Should there be the need for a public announcement, it will be posted to the SPM-mailing list (currently at www.jiscmail.ac.uk/lists/spm.html). Also, possible new versions or updates will be made available through our website.
We do, however, appreciate any comments and are open to suggestions. Please contact us via the Imaging Research Center's or the Structural Brain Mapping Group's website listed above.


***** Subjects details *****
NIH Subject_ID
1001 1002 1003 1004 1005 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1051 1052 1053 1054 1055 1056 1057 1058 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1118 1119 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1136 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1153 1154 1155 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1257 1258 1259 1260 1262 1263 1264 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1294 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1346 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398 1399 1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1413 1414 1415 1416 1417 1418 1419 1420 1422 1423 1424 1425 1426 1427 1428 1429 1430 1431 1432     

Age (years)
10.00 10.67 13.75 10.83 9.67 4.92 15.08 5.75 12.75 6.92 13.42 10.50 7.92 6.75 6.50 8.92 7.17 7.25 13.50 10.17 5.08 11.92 9.50 7.08 11.00 14.00 17.67 18.42 8.50 7.92 8.42 8.50 16.08 10.92 11.25 15.42 8.17 17.58 10.00 8.50 9.17 11.00 6.92 10.50 17.00 17.08 14.58 12.33 5.92 13.50 10.92 17.50 9.83 9.42 6.00 16.17 6.17 7.25 10.58 16.08 8.75 9.58 6.92 9.67 6.75 6.00 13.67 8.92 6.92 8.67 6.33 11.33 6.42 8.50 6.50 9.25 7.50 12.33 15.67 6.75 17.25 9.17 8.25 6.33 15.42 8.50 6.67 6.17 16.42 12.92 7.67 17.75 12.58 5.83 7.25 15.00 6.17 9.58 7.33 8.75 9.00 14.75 7.33 5.67 6.17 5.17 5.67 5.25 7.50 15.75 6.58 17.92 5.00 9.33 16.08 16.67 5.83 11.92 13.75 15.67 7.83 10.58 12.58 6.67 8.58 17.75 5.92 15.83 6.42 10.92 11.33 17.00 15.17 14.08 7.25 7.25 5.83 15.50 7.25 9.17 7.92 12.17 7.17 5.42 15.75 10.83 9.58 13.33 10.92 11.75 8.33 15.67 12.67 13.58 6.92 10.42 17.67 9.25 13.67 12.67 7.75 12.25 14.83 17.33 14.25 9.33 14.58 6.08 18.00 7.25 6.50 15.17 11.08 5.50 7.17 5.83 7.08 9.50 11.67 14.33 15.00 17.00 18.33 10.33 6.92 4.75 7.50 7.17 10.92 13.08 17.92 6.67 12.50 11.67 8.42 8.92 12.17 10.17 6.17 12.00 12.50 10.17 7.67 18.50 10.92 13.58 17.75 7.42 12.42 6.42 16.67 10.50 11.50 15.75 7.00 6.08 10.33 13.00 11.08 9.58 10.25 11.50 10.83 8.00 6.83 4.83 13.17 7.58 10.67 16.67 8.75 6.58 5.25 11.67 9.67 6.08 11.75 8.25 14.25 17.25 6.83 17.17 16.17 6.58 17.92 6.25 10.00 6.67 10.92 5.92 13.00 8.67 11.33 15.25 6.58 17.17 7.92 7.75 5.58 18.33 8.00 14.42 5.58 14.67 10.08 4.83 16.17 9.83 6.33 13.17 14.92 9.33 6.58 14.33 6.00 17.17 8.00 12.00 5.50 12.17 12.33 11.67 17.92 10.17 11.92 5.08 16.25 10.50 6.75 6.00 15.33 10.58 13.25 5.83 12.67 12.83 6.58 6.58 12.50 18.42 15.25 17.33 10.08 13.33 16.83 17.75 8.67 13.67 8.00 16.50 6.17 8.83 7.17 8.67 7.75 11.17 18.58 13.67 12.00 14.17 16.25 10.25 13.08 9.92 13.83 6.83 5.33 6.92 5.58 15.00 5.33 6.50 11.25 8.25 8.92 17.92 10.58 5.08 5.67 16.17 14.33 11.83 11.58 14.17 8.33 6.50 13.25 6.08 4.83 6.33 9.83 6.67 10.33 14.67 5.00 8.00 11.17 6.42 5.75 16.92 10.08 18.00 12.08 17.25 13.75 8.58 9.08 5.75 11.75 7.67 8.42 13.25 9.17 7.92 17.17 8.83 15.33 7.08 8.17 16.83 13.17 11.00 16.92 16.00 9.00 14.25 6.58 13.42 12.50 5.58 5.33 17.58 9.33 16.00 14.33 12.08 5.83 14.17 6.67 10.17 15.75 12.50 13.25 6.42 

Gender (male = 1, female = 0)
1 0 1 0 1 0 1 1 1 1 1 1 1 1 0 0 0 0 1 0 0 0 1 1 0 0 1 1 1 0 1 0 1 1 0 0 1 1 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 1 0 1 1 1 1 1 0 1 1 0 0 0 0 1 1 0 0 1 1 0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 0 1 1 1 1 1 0 0 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 0 1 0 1 1 1 0 1 0 0 0 1 0 0 0 1 1 1 0 0 0 1 0 1 1 1 0 0 0 1 1 1 1 0 1 0 0 0 1 0 1 1 0 1 0 1 0 0 1 1 0 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 1 0 1 1 0 0 0 0 1 1 1 0 1 0 0 0 0 1 1 1 1 1 0 1 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 1 1 0 1 0 1 1 1 1 0 1 0 1 1 1 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 1 0 1 1 1 0 1 0 1 1 1 1 1 1 0 1 0 1 1 1 1 1 0 0 1 1 1 0 0 0 1 0 0 1 0 1 1 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 1 1 0 1 1 1 1 0 1 0 0 1 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 1 0 1 1 1 0 1 0 1 1 1 1 0 0 0 0 0 1 
