tpl-dhcpAsym_cohort-43_hemi-L_den-32k_roi.shape.gii 17 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263
  1. <?xml version="1.0" encoding="UTF-8"?>
  2. <GIFTI xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  3. xsi:noNamespaceSchemaLocation="http://brainvis.wustl.edu/caret6/xml_schemas/GIFTI_Caret.xsd"
  4. Version="1"
  5. NumberOfDataArrays="1">
  6. <MetaData>
  7. <MD>
  8. <Name><![CDATA[AnatomicalStructurePrimary]]></Name>
  9. <Value><![CDATA[CortexLeft]]></Value>
  10. </MD>
  11. <MD>
  12. <Name><![CDATA[ParentProvenance]]></Name>
  13. <Value><![CDATA[/Users/jelena/Downloads/jbozek_account_Imperial/MSMtemplate/adaptive_subjectsToDataConteALL/roi/43.L.roi.shape.gii:
  14. /Users/jelena/Downloads/workbench-mac64-dev_latest/bin_macosx64/../macosx64_apps/wb_command.app/Contents/MacOS/wb_command -metric-math ' Sum + Map' /Users/jelena/Downloads/jbozek_account_Imperial/MSMtemplate/adaptive_subjectsToDataConteALL/roi/43.L.roi.shape.gii -var Sum /Users/jelena/Downloads/jbozek_account_Imperial/MSMtemplate/adaptive_subjectsToDataConteALL/roi/43.L.roi.shape.gii -var Map /Users/jelena/Downloads/jbozek_account_Imperial/MSMtemplate/adaptive_subjectsToDataConteALL/labels/43.L.prob_map30.shape.gii
  15. ]]></Value>
  16. </MD>
  17. <MD>
  18. <Name><![CDATA[ProgramProvenance]]></Name>
  19. <Value><![CDATA[Connectome Workbench
  20. Type: Command Line Application
  21. Version: 1.2.3
  22. Qt Compiled Version: 5.7.0
  23. Qt Runtime Version: 5.7.0
  24. Commit: 8951f7eccbad8cfed5bbd65323cd1c70fa536d0b
  25. Commit Date: 2017-05-30 10:34:41 -0500
  26. Compiled with OpenMP: YES
  27. Compiler: clang++ (/usr/local/clang/4.0.0/bin)
  28. Compiler Version: 4.0.0
  29. Compiled Debug: NO
  30. Operating System: Apple OSX
  31. ]]></Value>
  32. </MD>
  33. <MD>
  34. <Name><![CDATA[Provenance]]></Name>
  35. <Value><![CDATA[/Users/jelena/Downloads/workbench-mac64-dev_latest/bin_macosx64/../macosx64_apps/wb_command.app/Contents/MacOS/wb_command -metric-math ' Sum + Map' /Users/jelena/Downloads/jbozek_account_Imperial/MSMtemplate/adaptive_subjectsToDataConteALL/roi/43.L.roi.shape.gii -var Sum /Users/jelena/Downloads/jbozek_account_Imperial/MSMtemplate/adaptive_subjectsToDataConteALL/roi/43.L.roi.shape.gii -var Map /Users/jelena/Downloads/jbozek_account_Imperial/MSMtemplate/adaptive_subjectsToDataConteALL/labels/43.L.prob_map32.shape.gii]]></Value>
  36. </MD>
  37. <MD>
  38. <Name><![CDATA[WorkingDirectory]]></Name>
  39. <Value><![CDATA[/Users/jelena/Downloads/jbozek_account_Imperial/HCP_standard_mesh_atlases/Conte69/MNINonLinear/fsaverage_LR32k]]></Value>
  40. </MD>
  41. </MetaData>
  42. <LabelTable>
  43. <Label Key="0" Red="1" Green="1" Blue="1" Alpha="0"><![CDATA[???]]></Label>
  44. </LabelTable>
  45. <DataArray Intent="NIFTI_INTENT_NORMAL"
  46. DataType="NIFTI_TYPE_FLOAT32"
  47. ArrayIndexingOrder="RowMajorOrder"
  48. Dimensionality="1"
  49. Dim0="32492"
  50. Encoding="GZipBase64Binary"
  51. Endian="LittleEndian"
  52. ExternalFileName=""
  53. ExternalFileOffset="0">
  54. <MetaData>
  55. <MD>
  56. <Name><![CDATA[Name]]></Name>
  57. <Value><![CDATA[L_prob_map1]]></Value>
  58. </MD>
  59. </MetaData>
  60. <Data>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</Data>
  61. </DataArray>
  62. </GIFTI>