I have a set of multi-echo data which have been motion-corrected and slice timing corrected using fMRIprep. For some of the data, tedana fails at the spatial clustering of components, giving the following errors message. I’m wondering what I can do to fix this issue? Thank you.
INFO:tedana.decomposition.pca:Computing PCA of optimally combined multi-echo data
INFO:tedana.decomposition.ma_pca:Performing SVD on original OC data…
INFO:tedana.decomposition.ma_pca:SVD done on original OC data
INFO:tedana.decomposition.ma_pca:Estimating the subsampling depth for effective i.i.d samples…
INFO:tedana.decomposition.ma_pca:Generating subsampled i.i.d. OC data…
INFO:tedana.decomposition.ma_pca:Performing SVD on subsampled i.i.d. OC data…
INFO:tedana.decomposition.ma_pca:SVD done on subsampled i.i.d. OC data
INFO:tedana.decomposition.ma_pca:Effective number of i.i.d. samples 5272
INFO:tedana.decomposition.ma_pca:Perform eigen spectrum adjustment …
INFO:tedana.decomposition.ma_pca:Estimating the dimension …
INFO:tedana.decomposition.ma_pca:Estimated components is found out to be 45
INFO:tedana.metrics.kundu_fit:Fitting TE- and S0-dependent models to components
INFO:tedana.decomposition.pca:Selected 45 components with mdl dimensionality detection
INFO:tedana.decomposition.ica:ICA attempt 1 converged in 84 iterations
INFO:tedana.workflows.tedana:Making second component selection guess from ICA results
INFO:tedana.metrics.kundu_fit:Fitting TE- and S0-dependent models to components
INFO:tedana.metrics.kundu_fit:Performing spatial clustering of components
INFO:tedana.selection.tedica:Performing ICA component selection with Kundu decision tree v2.5
WARNING:tedana.selection.tedica:Too few BOLD-like components detected. Ignoring all remaining.
WARNING:tedana.workflows.tedana:No BOLD components detected! Please check data and results!
INFO:tedana.io:Writing optimally combined time series: C:\test\out\ts_OC.nii.gz
INFO:tedana.io:Variance explained by ICA decomposition: 97.34%
INFO:tedana.io:Writing low-Kappa time series: C:\test\out\lowk_ts_OC.nii.gz
INFO:tedana.io:Writing denoised time series: C:\test\out\dn_ts_OC.nii.gz
INFO:tedana.io:Writing full ICA coefficient feature set: C:\test\out\betas_OC.nii.gz
INFO:tedana.workflows.tedana:Making figures folder with static component maps and timecourse plots.