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Add a BIDS stats model for U26C (#21)
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| { | ||
| "Name": "NARPS U26C", | ||
| "Description": "NARPS Analysis model for team U26C", | ||
| "BIDSModelVersion": "1.0.0", | ||
| "Input": { | ||
| "task": [ | ||
| "MGT" | ||
| ] | ||
| }, | ||
| "Nodes": [ | ||
| { | ||
| "Level": "Run", | ||
| "Description": "Note: derivatives for motion correction are not implemented in pybids (added as '_der' in X below)", | ||
| "Name": "run", | ||
| "GroupBy": [ | ||
| "run", | ||
| "subject" | ||
| ], | ||
| "Transformations": { | ||
| "Transformer": "pybids-transforms-v1", | ||
| "Instructions": [ | ||
| { | ||
| "Description": "Turn the 'gain' column into a column 'trials' with only values of 1, to make sure all events are included.", | ||
| "Name": "Threshold", | ||
| "Input": [ | ||
| "gain" | ||
| ], | ||
| "Binarize": true, | ||
| "Output": [ | ||
| "trials" | ||
| ] | ||
| }, | ||
| { | ||
| "Description": "Create derivatives of motion correction parameters.", | ||
| "Name": "Derivative", | ||
| "Input": [ | ||
| "RotX", | ||
| "RotY", | ||
| "RotZ", | ||
| "X", | ||
| "Y", | ||
| "Z" | ||
| ], | ||
| "Order": 1, | ||
| "Initial": "NaN", | ||
| "Output": [ | ||
| "RotX_der", | ||
| "RotY_der", | ||
| "RotZ_der", | ||
| "X_der", | ||
| "Y_der", | ||
| "Z_der" | ||
| ] | ||
| } | ||
| ] | ||
| }, | ||
| "Model": { | ||
| "X": [ | ||
| "trials", | ||
| "gain", | ||
| "loss", | ||
| "RotX", | ||
| "RotY", | ||
| "RotZ", | ||
| "X", | ||
| "Y", | ||
| "Z", | ||
| "RotX_der", | ||
| "RotY_der", | ||
| "RotZ_der", | ||
| "X_der", | ||
| "Y_der", | ||
| "Z_der", | ||
| "CSF", | ||
| "WhiteMatter", | ||
| 1 | ||
| ], | ||
| "HRF": { | ||
| "Description": "Only events in the 'trials' are included as convolved. All other variables are confounds EXCEPT those listed below in Software.SPM.ParametricModulation.Values", | ||
| "Variables": [ | ||
| "trials" | ||
| ], | ||
| "Model": "spm" | ||
| }, | ||
| "Type": "glm", | ||
| "Software": { | ||
| "SPM": { | ||
| "SerialCorrelations": "AR(1)", | ||
| "Description": "list what conditions we must apply the modulation to and what values are used for the modulation.", | ||
| "ParametricModulations": [ | ||
| { | ||
| "Name": "pmod_loss", | ||
| "Conditions": [ | ||
| "trials" | ||
| ], | ||
| "Values": [ | ||
| "loss" | ||
| ] | ||
| }, | ||
| { | ||
| "Name": "pmod_gain", | ||
| "Conditions": [ | ||
| "trials" | ||
| ], | ||
| "Values": [ | ||
| "gain" | ||
| ] | ||
| } | ||
| ], | ||
| "PolynomialExpansion": 1 | ||
| } | ||
| } | ||
| }, | ||
| "DummyContrasts": { | ||
| "Conditions": [ | ||
| "trials", | ||
| "gain", | ||
| "loss" | ||
| ], | ||
| "Test": "t" | ||
| }, | ||
| "Options": { | ||
| "HighPassFilterCutoffHz": 0.08 | ||
| } | ||
| }, | ||
| { | ||
| "Level": "Subject", | ||
| "Name": "subject", | ||
| "GroupBy": [ | ||
| "subject", | ||
| "contrast" | ||
| ], | ||
| "Model": { | ||
| "X": [ | ||
| 1 | ||
| ], | ||
| "Type": "meta" | ||
| }, | ||
| "DummyContrasts": { | ||
| "Test": "t" | ||
| } | ||
| }, | ||
| { | ||
| "Level": "Dataset", | ||
| "Name": "between-groups", | ||
| "GroupBy": [ | ||
| "contrast" | ||
| ], | ||
| "Model": { | ||
| "Type": "glm", | ||
| "X": [ | ||
| 1, | ||
| "group" | ||
| ], | ||
| "Formula": "0 + C(group)" | ||
| }, | ||
| "Contrasts": [ | ||
| { | ||
| "Name": "range_vs_indiference", | ||
| "ConditionList": [ | ||
| "C(group)[T.equalRange]", | ||
| "C(group)[T.equalIndifference]" | ||
| ], | ||
| "Weights": [ | ||
| 1, | ||
| -1 | ||
| ], | ||
| "Test": "t" | ||
| } | ||
| ] | ||
| }, | ||
| { | ||
| "Level": "Dataset", | ||
| "Name": "positive", | ||
| "GroupBy": [ | ||
| "contrast", | ||
| "group" | ||
| ], | ||
| "Model": { | ||
| "Type": "glm", | ||
| "X": [ | ||
| 1 | ||
| ] | ||
| }, | ||
| "DummyContrasts": { | ||
| "Test": "t" | ||
| } | ||
| }, | ||
| { | ||
| "Level": "Dataset", | ||
| "Name": "negative-loss", | ||
| "GroupBy": [ | ||
| "contrast", | ||
| "group" | ||
| ], | ||
| "Model": { | ||
| "Type": "glm", | ||
| "X": [ | ||
| 1 | ||
| ] | ||
| }, | ||
| "Contrasts": [ | ||
| { | ||
| "Name": "negative", | ||
| "ConditionList": [ | ||
| 1 | ||
| ], | ||
| "Weights": [ | ||
| -1 | ||
| ], | ||
| "Test": "t" | ||
| } | ||
| ] | ||
| } | ||
| ], | ||
| "Edges": [ | ||
| { | ||
| "Source": "run", | ||
| "Destination": "subject" | ||
| }, | ||
| { | ||
| "Source": "subject", | ||
| "Destination": "positive" | ||
| }, | ||
| { | ||
| "Source": "subject", | ||
| "Destination": "negative-loss", | ||
| "Filter": { | ||
| "contrast": [ | ||
| "loss" | ||
| ] | ||
| } | ||
| }, | ||
| { | ||
| "Source": "subject", | ||
| "Destination": "between-groups", | ||
| "Filter": { | ||
| "contrast": [ | ||
| "loss" | ||
| ] | ||
| } | ||
| } | ||
| ] | ||
| } |