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json_ex.json
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{
"nidm_NeuroimagingAnalysisSoftware/prov:type": "SPM",
"nidm_NeuroimagingAnalysisSoftware/nidm_softwareVersion": "8.6325",
"nidm_NIDMResultsExporter/prov:type": "nidmfsl",
"nidm_NIDMResultsExporter/nidm_softwareVersion": "0.2.0",
"nidm_NIDMResults/nidm_version": "1.1.0",
"nidm_DesignMatrix/nidm_hasDriftModel": "spm_DiscreteCosineTransformbasisDriftModel",
"nidm_DriftModel/spm_SPMsDriftCutoffPeriod": "128",
"nidm_Data/nidm_hasMRIProtocol": "nlx_FunctionalMRIprotocol",
// *** Need to ask the user
"nidm_Data/nidm_hasMRIProtocol": "nlx_FunctionalMRIprotocol",
// not needed since we can deduce from protocol:
//"nlx_Imaginginstrument/prov:type" : "nlx_Magneticresonanceimagingscanner'",
// Groups is optional > no "Groups" means single-subject analysis
"Groups" :
{
"Control": 23,
"Patient": 21
},
// *** Usually Retreived automatically
"nidm_Data/nidm_grandMeanScaling": true,
// If nidm_grandMeanScaling is false then target intensity should not be specified
"nidm_Data/nidm_targetIntensity": "10000",
// Need to rething the design matrix, would it be easier to path a json matrix and then create
// the csv in the exporter
// So either nidm_DesignMatrix/prov:value or nidm_DesignMatrix/prov:atLocation
"nidm_DesignMatrix/prov:atLocation": "./DesignMatrix.csv",
"nidm_DesignMatrix/prov:value": [ [50,10,5,50],
[51,9,6.5,58.5],
[52,8,7,56],
[53,7,8.5,59.5]
],
// Only for first-level models
"nidm_DesignMatrix/nidm_hasHRFBasis": ["fsl_FSLsGammaHRF"],
"nidm_DesignMatrix/nidm_hasDriftModel/prov:type": "fsl_GaussianRunningLineDriftModel",
"nidm_DesignMatrix/nidm_regressorNames":
"nidm_ErrorModel/nidm_hasErrorDistribution": "obo_normaldistribution",
"nidm_ErrorModel/nidm_errorVarianceHomogeneous": true,
"nidm_ErrorModel/nidm_varianceMapWiseDependence" : "nidm_IndependentParameter",
"nidm_ErrorModel/nidm_hasErrorDependence": "obo_Toeplitzcovariancestructure",
// nidm_ErrorModel/nidm_dependenceMapWiseDependence should not be filled if nidm_hasErrorDependence
//"nidm_ErrorModel/nidm_dependenceMapWiseDependence" : 'nidm_IndependentParameter',
"nidm_ModelParameterEstimation/nidm_withEstimationMethod": "obo_generalizedleastsquaresestimation",
// Name for contrasts
// ------
"ParameterEstimateMaps" :
{
"tone_counting": "/Users/pe1.nii.gz",
"tone_counting_probe": "/Users/pe2.nii.gz",
},
"nidm_ResidualMeanSquaresMap/prov:atLocation": "/Users/rms.nii.gz",
// avg all input data?
"nidm_GrandMeanMap/prov:atLocation": "/Users/grand_mean_map.nii.gz",
// for SnPM deduce from resm
"nidm_MaskMap/prov:atLocation": "/Users/mask.nii.gz",
// Rename according to spec
"nidm_CustomMap/prov:atLocation": "/Users/mask.nii.gz",
// optional
"nidm_ReselsPerVoxelMap/prov:atLocation": "/Users/rpv.nii.gz",
// Everything in same coord space
"nidm_CoordinateSpace/nidm_inWorldCoordinateSystem": "nidm_Ixi549CoordinateSystem",
"Contrasts" :
{
// having the contrast name as the key restrict the characters that can be used so we use a dummy numbering scheme instead
"tone counting vs baseline": {
"obo_contrastweightmatrix/prov:value" : [1, 0],
"nidm_StatisticMap/nidm_statisticType": "obo_tstatistic",
"nidm_StatisticMap/nidm_errorDegreesOfFreedom": "72.999",
"nidm_StatisticMap/prov:atLocation": "/Users/tstat1.nii.gz",
"nidm_ContrastMap/prov:atLocation": "/Users/con1.nii.gz",
"nidm_ContrastStandardErrorMap/prov:atLocation": "/Users/cstd1.nii.gz",
// optional
"nidm_StatisticMap-Z/prov:atLocation": "/Users/zstat1.nii.gz",
// optional (replace the field name for this contrast)
"nidm_ContrastMap/nidm_contrastName": "tone counting vs baseline",
},
"Contrast_2": {
"obo_contrastweightmatrix/prov:value" : [1, 0],
"nidm_ContrastMap/prov:atLocation": "/Users/con1.nii.gz",
"nidm_ContrastStandardErrorMap/prov:atLocation": "/Users/cstd1.nii.gz",
"nidm_StatisticMap/nidm_statisticType": "obo_Fstatistic",
"nidm_StatisticMap/nidm_errorDegreesOfFreedom": "72.999",
// only for F-stat
"nidm_StatisticMap/nidm_effectDegreesOfFreedom": "2",
"nidm_StatisticMap/prov:atLocation": "/Users/fstat1.nii.gz",
// optional
"nidm_StatisticMap-Z/prov:atLocation": "/Users/zfstat1.nii.gz",
// optional (replace the field name for this contrast)
"nidm_ContrastMap/nidm_contrastName": "tone counting vs baseline",
},
},
"nidm_ClusterDefinitionCriteria/nidm_hasConnectivityCriterion": "nidm_voxel26connected",
"nidm_PeakDefinitionCriteria/nidm_minDistanceBetweenPeaks": "8.0",
// optional
"nidm_PeakDefinitionCriteria/nidm_maxNumberOfPeaksPerCluster": "3",
"ConjunctionInferences":
{
"ConjunctionInference-1": {
"nidm_contrastName": ["Contrast_1", "Contrast_2"],
"nidm_Inference/prov:type": "nidm_ConjunctionInference",
}
},
"Inferences":
{
// we assume we will only have one thresholding procedure for a given contrast
"Contrast_1": {
"nidm_HeightThreshold/prov:type": "PValueUncorrected",
"nidm_HeightThreshold/prov:value": "0.001",
"nidm_ExtentThreshold/prov:type": "obo_statistic",
"nidm_ExtentThreshold/nidm_clusterSizeInVoxels": "0",
// optional
"nidm_ExtentThreshold/nidm_clusterSizeInResels": "0",
// optional
"nidm_HeightThreshold/nidm_equivalentThreshold": {
"p<0.0545 unc": {
"nidm_HeightThreshold/prov:type": "PValueUncorrected",
"nidm_HeightThreshold/prov:value": "0.001",
}
"p<0.0545 unc": {
"nidm_HeightThreshold/prov:type": "PValueUncorrected",
"nidm_HeightThreshold/prov:value": "0.001",
}
}
// optional
"nidm_ExtentThreshold/nidm_equivalentThreshold": {
"p<0.0545 unc": {
"nidm_ExtentThreshold/prov:type": "obo_statistic",
"nidm_ExtentThreshold/prov:value": "0",
}
"p<0.0545 unc": {
"nidm_ExtentThreshold/prov:type": "obo_statistic",
"nidm_ExtentThreshold/prov:value": "0",
}
}
"nidm_Inference/nidm_hasAlternativeHypothesis": "nidm_OneTailedTest",
// todo conjunctions
// optional
"nidm_DisplayMaskMap/prov:atLocation": ["/Users/my_mask.nii.gz"],
// optional
"nidm:SubVolumeMap/prov:atLocation": "/Users/my_mask.nii.gz",
// todo searchspacemap
"nidm_SearchSpaceMaskMap/prov:atLocation": "uri(spm_file(files.searchspace,'cpath'))",
"nidm_SearchSpaceMaskMap/nidm_searchVolumeInVoxels": 5452552,
"nidm_SearchSpaceMaskMap/nidm_searchVolumeInUnits": 546545,
"nidm_SearchSpaceMaskMap/nidm_reselSizeInVoxels": 64565,
// optional
"nidm_SearchSpaceMaskMap/nidm_searchVolumeInResels": 64565,
// SPM only
"nidm_SearchSpaceMaskMap/spm_searchVolumeReselsGeometry": [45 45 7 5],
"nidm_SearchSpaceMaskMap/nidm_noiseFWHMInVoxels": [6 6 6],
"nidm_SearchSpaceMaskMap/nidm_noiseFWHMInUnits": [5.5 5.5 5.5],
"nidm_SearchSpaceMaskMap/nidm_randomFieldStationarity": true,
// optional
"nidm_SearchSpaceMaskMap/nidm_expectedNumberOfVoxelsPerCluster": 65456,
"nidm_SearchSpaceMaskMap/nidm_expectedNumberOfClusters": 56554,
"nidm_SearchSpaceMaskMap/nidm_heightCriticalThresholdFWE05": 52.55,
"nidm_SearchSpaceMaskMap/nidm_heightCriticalThresholdFDR05": 54.25,
// optional
"nidm_SearchSpaceMaskMap/spm_smallestSignificantClusterSizeInVoxelsFWE05": 56454.25,
// optional
"nidm_SearchSpaceMaskMap/spm_smallestSignificantClusterSizeInVoxelsFDR05": 56457.25,
"nidm_ExcursionSetMap/prov:atLocation": "/Users/thresh.nii.gz",
"nidm_ExcursionSetMap/nidm_hasMaximumIntensityProjection": "/Users/MIP.png",
// and also nidm_numberOfSupraThresholdClusters
// optional
"nidm_ClusterLabelsMap/prov:atLocation": "/Users/thresh.nii.gz",
"Clusters": {
"1": {
"nidm_SupraThresholdCluster/nidm_clusterSizeInVoxels": "12",
"nidm_SupraThresholdCluster/nidm_clusterSizeInResels": "1",
// optional
"nidm_SupraThresholdCluster/nidm_pValueUncorrected": "9.56276736481136e-52",
"nidm_SupraThresholdCluster/nidm_pValueFWER": "0.00073267843",
"nidm_SupraThresholdCluster/nidm_qValueFDR": "0.00018638",
"Peaks": {
"1": {
"nidm_Peak/prov:value": "13.93461",
"nidm_Coordinate/nidm_coordinateVector": "[ -60, -28, 13 ]",
// optional
"nidm_Coordinate/nidm_coordinateVectorInVoxels": "[ -60, -28, 13 ]",
"nidm_Peak/nidm_pValueUncorrected": "",
"nidm_Peak/nidm_equivalentZStatistic": "12",
"nidm_Peak/nidm_pValueFWER": "0.00073267843",
"nidm_Peak/nidm_qValueFDR": "0.00018638",
},
},
},
},
// Extension for non-parametric statistics - true for all contrasts ??
"nidm_NonParametricNullDistribution/nidm_numberOfPermutations": "5000",
"nidm_NonParametricNullDistribution/nidm_hasResamplingScheme": "nidm_Permutation",
"nidm_NonParametricNullDistribution/nidm_hasApproximationMethod": "nidm_MonteCarlo",
"nidm_NonParametricNullDistribution/nidm_maximumNumberOfPermutations": "12345",
// first-level only
"nidm_NonParametricNullDistribution/nidm_exchangeabilityBlocks": [1 1 1 2 2 2 3 3 3],
"nidm_NonParametricNullDistribution/nidm_exchangeabilityWithin": true,
},
"Contrast_2": {
},
},
}