@@ -18,7 +18,7 @@ contains `"Phenotype"` in the `dataset_description.json`.
1818
1919Aggregate participant information across all sessions into one tabular TSV file per
2020measurement or phenotypic assessment and store this file in the ` /phenotype ` directory.
21- Demographic information is a special case and MUST be aggregated
21+ Demographic information is a special case and SHOULD be aggregated
2222in the ` participants.tsv ` file at the root level of the dataset.
2323It is RECOMMENDED to use the ` age ` column in the ` participants.tsv ` file
2424to record participant age at every session in longitudinal or multi-session data sets.
@@ -51,8 +51,8 @@ the smallest unit of acquisition). In other words:
5151 in the data set regardless of whether those sessions are in
5252 the ` phenotype/ ` data, ` sub-<label>/ ` data, or a combination of the two.
5353
54- - If more than one of the same measurement tool is acquired within
55- the same ` session_id ` , a ` run_id ` column MUST be added.
54+ - If a measurement tool is acquired multiple times within a single session,
55+ a ` run_id ` column MUST be added to disambiguate the separate acquisitions .
5656
5757- A measurement tool’s acquisition time SHOULD be stored in the ` sessions.tsv `
5858 file at the root-level of the dataset in the ` acq_time ` column.
@@ -74,8 +74,6 @@ all imaging data and tabular phenotypic data MUST have sessions.
7474
7575This produces a file in which same-participant entries can take up as many rows as needed
7676according to the smallest unit of acquisition.
77- The combination of values in the ` participant_id ` , ` session_id ` , and ` run_id ` (if present)
78- columns MUST be unique for the entire tabular file.
7977
8078### 5. Store demographic data in the participants file and instrument data in the phenotype directory
8179
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