Spike Regression connection fix

[sgiavasis]

Fixes

Fixes #2137 by @sgiavasis

Description

• Removes an erroneous connection which would send a censor file with a binary spike regressor into the -cenmode KILL flag of AFNI 3dTproject as part of nuisance denoising.
• This would sometimes cause TRs to be dropped from the timeseries unnecessarily, as if scrubbing was being performed.

Technical details

• The binary spike regressor vector is already calculated earlier in the pipeline and is correctly incorporated into the nuisance model GLM matrix.
• The connection being removed is unnecessary.

Tests

• No TRs dropped when using spike regression as part of the nuisance denoising strategy.
• Spike regressor is present in the desc-confounds_timeseries matrix.
• No censor file is submitted to AFNI 3dTproject as an input.

Screenshots

Checklist

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[sgiavasis]

This was fun! Here's what changed:

• Functionality identifying the offending timepoints - which TRs/timepoints have a motion measure (FD_J, FD_P, DVARS) higher than the user-set threshold, and producing a censors.tsv binary vector - has been abstracted out into its own function because we realized it needed to be used in different places - thanks @birajstha for that one.
• When spike regression is enabled, offending timepoints are identified before nuisance regressor creation, and SpikeRegression columns are created and included in the regressors matrix. Thus spike regression is facilitated through the -ort pathway of AFNI 3dTproject and is modeled into the confounds.
• The rest of the censoring methods continue to operate as they always have, with the offending timepoints going into a binary vector (censors.tsv) and being submitted to 3dTproject via the -censor parameter, along with the censoring mode setting (like KILL - scrubbing, NTRP - interpolate, etc.).

[sgiavasis]

@shnizzedy I incorporated your suggestions - hows it look?