Outputs of tedana¶
tedana derivatives¶
| Filename | Content |
|---|---|
| t2sv.nii | Limited estimated T2* 3D map. The difference between the limited and full maps is that, for voxels affected by dropout where only one echo contains good data, the full map uses the single echo’s value while the limited map has a NaN. |
| s0v.nii | Limited S0 3D map. The difference between the limited and full maps is that, for voxels affected by dropout where only one echo contains good data, the full map uses the single echo’s value while the limited map has a NaN. |
| ts_OC.nii | Optimally combined time series. |
| dn_ts_OC.nii | Denoised optimally combined time series. Recommended dataset for analysis. |
| lowk_ts_OC.nii | Combined time series from rejected components. |
| midk_ts_OC.nii | Combined time series from “mid-k” rejected components. |
| hik_ts_OC.nii | High-kappa time series. This dataset does not include thermal noise or low variance components. Not the recommended dataset for analysis. |
| comp_table_pca.txt | TEDPCA component table. A tab-delimited file with summary metrics and inclusion/exclusion information for each component from the PCA decomposition. |
| mepca_mix.1D | Mixing matrix (component time series) from PCA decomposition. |
| meica_mix.1D | Mixing matrix (component time series) from ICA decomposition. The only differences between this mixing matrix and the one above are that components may be sorted differently and signs of time series may be flipped. |
| betas_OC.nii | Full ICA coefficient feature set. |
| betas_hik_OC.nii | High-kappa ICA coefficient feature set |
| feats_OC2.nii | Z-normalized spatial component maps |
| comp_table_ica.txt | TEDICA component table. A tab-delimited file with summary metrics and inclusion/exclusion information for each component from the ICA decomposition. |
If verbose is set to True:
| Filename | Content |
|---|---|
| t2ss.nii | Voxel-wise T2* estimates using ascending numbers of echoes, starting with 2. |
| s0vs.nii | Voxel-wise S0 estimates using ascending numbers of echoes, starting with 2. |
| t2svG.nii | Full T2* map/time series. The difference between the limited and full maps is that, for voxels affected by dropout where only one echo contains good data, the full map uses the single echo’s value while the limited map has a NaN. Only used for optimal combination. |
| s0vG.nii | Full S0 map/time series. Only used for optimal combination. |
| __meica_mix.1D | Mixing matrix (component time series) from ICA decomposition. |
| hik_ts_e[echo].nii | High-Kappa time series for echo number echo |
| midk_ts_e[echo].nii | Mid-Kappa time series for echo number echo |
| lowk_ts_e[echo].nii | Low-Kappa time series for echo number echo |
| dn_ts_e[echo].nii | Denoised time series for echo number echo |
If gscontrol includes ‘gsr’:
| Filename | Content |
|---|---|
| T1gs.nii | Spatial global signal |
| glsig.1D | Time series of global signal from optimally combined data. |
| tsoc_orig.nii | Optimally combined time series with global signal retained. |
| tsoc_nogs.nii | Optimally combined time series with global signal removed. |
If gscontrol includes ‘t1c’:
| Filename | Content |
|---|---|
| sphis_hik.nii | T1-like effect |
| hik_ts_OC_T1c.nii | T1 corrected high-kappa time series by regression |
| dn_ts_OC_T1c.nii | T1 corrected denoised time series |
| betas_hik_OC_T1c.nii | T1-GS corrected high-kappa components |
| meica_mix_T1c.1D | T1-GS corrected mixing matrix |
Component tables¶
TEDPCA and TEDICA use tab-delimited tables to track relevant metrics, component classifications, and rationales behind classifications. TEDPCA rationale codes start with a “P”, while TEDICA codes start with an “I”.
| Classification | Description |
|---|---|
| accepted | BOLD-like components retained in denoised and high-Kappa data |
| rejected | Non-BOLD components removed from denoised and high-Kappa data |
| ignored | Low-variance components ignored in denoised, but not high-Kappa, data |
TEDPCA codes¶
| Code | Classification | Description |
|---|---|---|
| P001 | rejected | Low Rho, Kappa, and variance explained |
| P002 | rejected | Low variance explained |
| P003 | rejected | Kappa equals fmax |
| P004 | rejected | Rho equals fmax |
| P005 | rejected | Cumulative variance explained above 95% (only in stabilized PCA decision tree) |
| P006 | rejected | Kappa below fmin (only in stabilized PCA decision tree) |
| P007 | rejected | Rho below fmin (only in stabilized PCA decision tree) |
TEDICA codes¶
| Code | Classification | Description |
|---|---|---|
| I001 | rejected | Manual exclusion |
| I002 | rejected | Rho greater than Kappa or more significant voxels in S0 model than R2 model |
| I003 | rejected | S0 Dice is higher than R2 Dice and high variance explained |
| I004 | rejected | Noise F-value is higher than signal F-value and high variance explained |
| I005 | ignored | No good components found |
| I006 | rejected | Mid-Kappa component |
| I007 | ignored | Low variance explained |
| I008 | rejected | Artifact candidate type A |
| I009 | rejected | Artifact candidate type B |
| I010 | ignored | ign_add0 |
| I011 | ignored | ign_add1 |
Visual reports¶
We’re working on it.