Draft slice banding metrics - #1461
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This reverts commit 958498e.
Add two TE-dependence-independent artifact metrics that flag acquisition/motion signatures which can mimic mixed TE-dependence: - compute_slice_banding: detects multiband/slice-leakage structure in a component's spatial weight map (per-axis bandR2 * bandMB). - compute_spike: Fisher temporal kurtosis of each component time series, flagging isolated transients after linear detrending. Both are registered in metrics.json and computed in collect.generate_metrics when requested. Includes unit tests for behavior and registration. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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I ran tedana on the first 20 runs of ds006185 (PAFIN fMRIPrep derivatives), then found the run with the component with the highest value for each component and the component with the lowest value in that same run (so we're comparing apples to apples), then plotted the relevant data. Hopefully this helps give an idea of what these metrics are capturing. Spike: the component time series
Slice banding: the squared beta map (cropped to 2nd - 98th percentile)
Slice leakage: the squared beta map (cropped to 2nd - 98th percentile)
Slice leakage, aliasing component: the squared beta map (cropped to 2nd - 98th percentile)
Slice leakage, periodicity component: the squared beta map (cropped to 2nd - 98th percentile)
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Closes #1415. This drafts a couple of metrics that might be useful for flagging multiband slice leakage artifacts.
Changes proposed in this pull request:
spikemetric, which looks at kurtosis in a time series to flag components dominated by single large signal spikes.slice_bandingandslice_leakagemetrics, which might help with multiband acceleration artifacts.