(dist_plot_target)=

# QC-FC distribution

```{figure} ../pics/distribution_plot.png
:alt: Scatter plots of network connectivity measures against confound measures across scans

Each point is a scan. Measures of network connectivity — specificity and
amplitude — are contrasted with measures of confounds across the sample.
```

The QC-FC distribution plot visualises the joint distributions of network and 
confound data quality measures across the dataset, extending the per-scan qualitative
judgements from the [spatiotemporal diagnosis](diagnosis_target) into a quantitative
comparison between subjects.

Reading the plot:

- Points labelled in **grey** were removed using `--scan_QC_thresholds`. The
  grey dotted lines are the QC thresholds selected for network specificity
  (Dice overlap) and DR confound correlation.
- Among the remaining samples, and for each metric separately, scans presenting
  outlier values are labelled in **orange**. Outliers are detected with a
  modified Z-score threshold, set by `--outlier_threshold` and 3.5 by default.

The derivation of each quality metric is described in the
[metric definitions](dist_plot_metrics).

## What the report is for

**Identify systematic QC-FC associations at the dataset-level.** Visualise the association
between network (specificity and amplitude) and a set of scan-level summary confound measures (the columns
in the plot). This complements the [group statistical report](group_stats_target) by 
indicating whether a group-wise correlation in the report is
driven by a small number of outliers rather than by a dataset-wide effect.

**Setting scan inclusion criteria.** Inspect that network specificity is
sufficient and that the temporal correlation with confounds (DR confound corr.)
is minimal, then set thresholds for scan inclusion with `--scan_QC_thresholds`.
This is the top right subplot, discussed below.

```{seealso}
[How to assess data quality](../how_to/assess_data_quality.md) gives the
`--scan_QC_thresholds` syntax and the procedure for choosing values.
```


## Inclusion criteria exemplified

```{figure} ../pics/scan_QC_thresholds.png
:alt: Scan quality categories separated along network specificity and confound correlation axes

Reproduced from {cite}`Desrosiers-Gregoire2024-ou`: how the
[categories of scan quality outcome](quality_marker_target) separate along
these two measures.
```

The measures of network specificity (Dice overlap) and temporal correlation
with confounds — where confound timecourses are extracted using the confound
components specified with `--prior_confound_idx` and measured through dual
regression — were defined in {cite}`Desrosiers-Gregoire2024-ou` for conducting
scan-level QC.

They were selected as the measures best suited to quantifying network
detectability and spurious connectivity, and to applying inclusion thresholds
that select scans respecting the assumptions of network detectability and
minimal confound effects.