Fmriprep: Derivatives & Session Filters Clash

Hey everyone! Let's dive into a common hiccup many of us encounter when pushing the boundaries with neuroimaging analysis, specifically with fmriprep. We're talking about those moments when you're trying to replicate complex analyses, especially when dealing with multiple sessions and pre-computed derivatives, and suddenly, your pipeline crashes. It's a frustrating experience, right? You've meticulously set up your data, followed the BIDS standard, and yet, bam! An error pops up, leaving you scratching your head. Today, we're going to unravel a specific knot: the conflict that arises when you try to use --derivatives alongside --session-label and BIDS filters in fmriprep. This isn't just a minor bug; it's a critical intersection point where different input mechanisms can clash, leading to unexpected failures. We'll break down what's happening under the hood, why these conflicts occur, and what you can do to navigate this tricky terrain. So, grab your favorite caffeinated beverage, and let's get this sorted!

Understanding the Core Issue: The --derivatives and --session-label Tug-of-War

Alright guys, let's get down to brass tacks. The core of the problem we're seeing here revolves around how fmriprep handles inputs, especially when you're trying to feed it pre-computed results using the --derivatives flag and simultaneously specify particular sessions with --session-label. Imagine you're building an intricate model, and you've already got some pieces pre-assembled (your derivatives). Now, you want fmriprep to use these pre-assembled pieces for a specific part of your analysis, but only for a particular session. This sounds straightforward, but the way fmriprep's internal logic connects these flags can lead to a bit of a showdown.

When you specify --derivatives, you're telling fmriprep to look for inputs like your anatomical segmentations or even previous processing steps in a designated directory. This is fantastic for speeding up your pipeline and ensuring consistency. However, the issue arises when --session-label comes into play. The fmriprep code, particularly around how it processes anatomical references and connects them to session-specific functional data, can get confused. It tries to apply the session specificity intended for functional MRI (fMRI) data to the anatomical derivatives, which, by their nature (especially from tools like FreeSurfer), often don't inherently have a session structure in the same way. Think of it like trying to find a specific chapter in a book that doesn't have chapters, but rather just a continuous narrative. The provided error message, IndexError: list index out of range originating from fmriprep/interfaces/bids.py, clearly points to this: the code is expecting a list of filenames related to a specific session within the derivatives, but it's finding none because the anatomical derivatives might not be organized or tagged with that session ID in the way fmriprep is expecting.

This is precisely what the user experienced: it passes the session-label intended for fMRI selection to the precomputed anat derivatives collection. The anatomical processing, often done once per subject, doesn't usually create session-specific outputs that fmriprep can directly link via a session label from the functional data context. The proposed solution, which is quite elegant, suggests conditionally passing the session_id only when using options like --subject-anatomical-reference sessionwise. This implies a more nuanced handling where the session specificity is only enforced when it's actually relevant and applicable to the derivatives being processed. It's a smart way to prevent the session label from incorrectly filtering the session-agnostic anatomical inputs.

Furthermore, the problem gets compounded when you don't use --session-label but rely solely on BIDS filters. In this scenario, another error surfaces, this time deep within niworkflows/utils/bids.py. The session_id variable, which is supposed to represent the sessions being processed, becomes a list of all sessions when it shouldn't be, even if --session-label wasn't explicitly set. This happens because fmriprep's configuration might be interpreting the overall processing group (config.execution.processing_groups) as containing all sessions, and the BIDS querying mechanism is then failing to handle this list correctly when it expects a singular or optional session identifier. It's like a floodgate opening when it should be a selective filter. The underlying issue seems to stem from a recent refactoring, and the lack of comprehensive tests for the precomputed derivatives input feature means these edge cases are slipping through the cracks. This is a classic example of how complex software, especially in active development, can exhibit unexpected behaviors when different features interact in less-tested ways. Understanding these interactions is key to robust data processing.

The Specific Scenario: Replicating Neuromod with fMRIPrep v25.2.3

So, what exactly was the user trying to achieve? They were aiming to replicate the analytical pipeline used for the 20LTS dataset, specifically for the neuromod use case, but leveraging the newer fmriprep version 25.2.3. The strategy was to process anatomical data (T1w, T2w) using smriprep (a variant or precursor often used for structural processing) and then run fmriprep on the functional MRI data. A crucial part of their strategy was to process each session separately to distribute the computational load more efficiently across a High-Performance Computing (HPC) cluster. This is a very common and practical approach for large-scale studies.

Here’s a breakdown of their intended workflow:

1. Anatomical Processing: Run smriprep on the T1w and T2w structural images. This step typically generates anatomical segmentations and, importantly, runs FreeSurfer, producing subject-specific structural derivatives. These anatomical derivatives are what they intended to feed into fmriprep using the --derivatives flag.
2. Functional Processing (Session-wise): Run fmriprep on the fMRI datasets. The key here is that they wanted to process each session independently. This is where the --session-label flag comes into play, allowing them to specify which session fmriprep should focus on for a given run. This is also where BIDS filters are used to ensure that the correct fMRI and fieldmap files are selected for that specific session.

Their command line invocation looks like this:

fmriprep w ./workdir --participant-label 01 --session-label 001 --derivatives sourcedata/smriprep --fs-subjects-dir sourcedata/smriprep/sourcedata/*freesurfer* --bids-filter-file code/fmriprep_study-cneuromod.emotion-videos_sub-01_ses-001_bids_filters.json --output-layout bids --ignore slicetiming --use-syn-sdc warn --me-output-echos --output-spaces MNI152NLin2009cAsym T1w:res-iso2mm --cifti-output 91k --notrack --write-graph --skip_bids_validation --omp-nthreads 8 --nprocs 12 --mem_mb 45056 --fs-license-file code/freesurfer.license --track-carbon --stop-on-first-crash sourcedata/cneuromod.emotion-videos ./ participant

Notice a few critical arguments here:

• --participant-label 01: Specifies the subject to process.
• --session-label 001: Tells fmriprep to process only session '001'.
• --derivatives sourcedata/smriprep: Points fmriprep to the directory containing pre-computed anatomical derivatives (likely from smriprep).
• --fs-subjects-dir sourcedata/smriprep/sourcedata/*freesurfer*: Specifies the FreeSurfer output directory, which is essential for fmriprep's anatomical reference steps.
• --bids-filter-file ...: A custom BIDS filter file to precisely select the input files for this specific subject and session.

This setup is designed for efficiency and robustness. However, as we saw, combining --derivatives with --session-label (even indirectly via BIDS filters) caused the pipeline to choke. The initial crash, with the IndexError: list index out of range, occurred because fmriprep was attempting to find session-specific anatomical derivatives that simply don't exist in that format. The subsequent issue, when bypassing --session-label but still using BIDS filters, highlighted a problem with how session information was being propagated and interpreted within the BIDS querying system.

This scenario is described as an "edgy case," which is fair. It pushes the boundaries of how fmriprep is designed to be used, particularly regarding the interplay between session-specific functional inputs and potentially session-agnostic (or differently structured) anatomical derivatives. The fact that it broke during a "large fit/apply refactor" suggests that the underlying architecture for handling derivatives and session inputs might have been modified, and these specific interaction paths weren't fully covered by existing tests.

Deconstructing the Errors: What's Really Happening?

Let's zoom in on those error messages and trace them back to their sources. The first error, the dreaded IndexError: list index out of range, is a classic sign that the code is trying to access an element in a list that doesn't exist. In this context, it happens within the _create_multi_source_file function in fmriprep/interfaces/bids.py. This function is likely involved in constructing file paths or lists of files that fmriprep needs to process. The traceback points to line 148, where p = Path(filename_to_list(in_files)[0]). The issue here is that filename_to_list(in_files) is returning an empty list, and you can't get the [0] element from an empty list. This occurs because the session-label is being passed down to a part of the pipeline that's trying to collect anatomical derivatives. As the user correctly identified, smriprep outputs (or typical FreeSurfer outputs) for anatomical data are often structured per subject, not per session. So, when fmriprep queries for anatomical derivatives associated with session '001', it finds nothing, leading to the empty list and the subsequent crash.

The link provided, fmriprep/workflows/base.py#L281, shows where this session information might be incorrectly routed. The proposed fix is to only pass the session_id when it's relevant, such as when using --subject-anatomical-reference sessionwise. This suggests a conditional logic is needed: if you're using pre-computed derivatives that aren't session-wise, don't filter them by session. If you are using session-wise anatomical references, then by all means, pass the session ID.

The second error, observed when not using --session-label but relying on BIDS filters, is equally telling. This one surfaces in niworkflows/utils/bids.py around lines 279-281. Here, the problem is that the session_id variable is unexpectedly becoming a list containing all sessions from config.execution.processing_groups. This happens even when --session-label is not explicitly provided. The code expects session_id to be either a single session identifier or possibly Query.OPTIONAL (a placeholder indicating it might be optional or absent). When it receives a list of all sessions, the BIDS querying mechanism breaks because it's not designed to handle this broadened scope in that particular context. It seems like the internal representation of sessions being processed, perhaps derived from the BIDS filter file or general configuration, is being misinterpreted or over-generalized.

This specific issue, where session_id is a list of all sessions, is described as happening because Query.OPTIONAL is never returned even if --session-label is not specified. This implies that the BIDS query system, when faced with multiple sessions available, defaults to treating all of them as required or processed, rather than allowing for optional or selective processing based on other criteria (like the BIDS filter file). The interaction between the BIDS filter file, the overall processing group configuration, and the BIDS querying logic seems to be the culprit here. It's a complex interplay where the absence of one flag (--session-label) doesn't automatically reset the session handling mechanism as expected, especially when the BIDS filter file implicitly defines sessions or when the system infers multiple sessions.

It's crucial to remember that these tools are under active development. As the user noted, the "large fit/apply refactor" likely introduced changes that, while improving functionality elsewhere, inadvertently broke this specific, less-common usage pattern. The lack of comprehensive tests for the precomputed derivatives input is a significant factor here. Building out a robust test suite that specifically covers scenarios involving --derivatives with various configurations (session-wise vs. non-session-wise) and interacting with session selection mechanisms (like --session-label and BIDS filters) would be invaluable for preventing future regressions.

Potential Solutions and Best Practices

Dealing with these kinds of conflicts can be a real headache, but there are definitely strategies you can employ to work around them or resolve them. The user's insight into conditionally applying the session_id is a great starting point for developers, but for us end-users, we need practical advice.

1. Separate Anatomical and Functional Runs

The most robust approach, and often the simplest to manage, is to run your anatomical preprocessing and functional preprocessing as completely separate jobs. This means:

• Job 1: Anatomical Preprocessing: Run smriprep (or fmriprep with only anatomical flags) for all subjects. Collect the FreeSurfer outputs and any other anatomical derivatives you need. Ensure these outputs are organized clearly, typically by subject.
• Job 2: Functional Preprocessing: Run fmriprep for all subjects and sessions. In this job, you won't typically need to specify --derivatives for the anatomical inputs unless you're using them for specific steps like anatomical reference alignment. If you are, be mindful of how you specify the --fs-subjects-dir and ensure it points to the subject-level FreeSurfer outputs.

By treating these as distinct steps, you avoid the direct conflict of passing session labels intended for functional data into the anatomical derivative pipeline. If you are using anatomical derivatives for alignment, ensure the command for functional processing targets the subject's derivatives, not a session-specific derivative.

2. Leverage BIDS Filters Wisely (and Test Them)

BIDS filters are incredibly powerful for specifying exactly which files fmriprep should consider. If you're processing session by session, your BIDS filter file should be meticulously crafted to only include the fMRI and fieldmap data for that specific session. When using BIDS filters, the goal is to let the filter define the session, rather than relying solely on --session-label.

If you find yourself encountering the second type of error (where session_id becomes a list of all sessions), it might be that your BIDS filter file, while intended for a specific session, isn't being interpreted correctly in conjunction with the overall processing configuration. Experiment with simplifying the BIDS filter file to see if it isolates the issue. Also, consider not using --session-label and relying entirely on the BIDS filter file to specify the session. Sometimes, having redundant session specifications can confuse the parser.

3. Explore fmriprep Configuration Options

fmriprep has a vast array of configuration options. For instance, the user mentioned --subject-anatomical-reference sessionwise. This is a key flag. If your anatomical derivatives are session-wise (perhaps from a custom preprocessing pipeline), then using this flag might align better with fmriprep's expectations. However, if your anatomical derivatives are standard FreeSurfer outputs (which are usually subject-level), then you'd typically not use --subject-anatomical-reference sessionwise. Instead, you'd point --fs-subjects-dir to the subject's FreeSurfer directory. The strategy here is to ensure your command-line arguments accurately reflect the structure of your input data, especially your derivatives.

4. Consider --skip_bids_validation (with Caution)

The user included --skip_bids_validation. While this flag is useful for dealing with minor BIDS non-compliance that doesn't affect processing, it's generally not the solution for fundamental conflicts in how flags are interpreted. In fact, relying on it might mask deeper issues. It's better to fix the underlying flag interaction problem than to bypass validation.

5. Report and Contribute (If You Can)

As the user rightly pointed out, this is an "edgy case" that broke during a refactor and might not be well-tested. If you encounter such issues, especially when using recent versions of fmriprep (like 25.2.3), reporting them on the nipreps GitHub issues page is incredibly valuable. Providing the exact command, the error logs, and a description of your data structure helps the developers identify and fix these bugs. If you have the technical expertise, contributing a test case or even a potential fix is the best way to ensure the software remains robust for everyone.

6. Process Sequentially (Less Efficient, More Stable)

If all else fails and you need to get the job done, a less efficient but often more stable approach is to process each subject-session combination entirely from scratch, without using --derivatives for the anatomical inputs. This means fmriprep will re-run the anatomical processing for every session it needs it for. This is computationally expensive but sidesteps the derivative input conflict entirely. Once you have confirmed your pipeline works with this method, you can then investigate reintroducing derivative usage if performance becomes a bottleneck.

Conclusion: Navigating the Nuances

Encountering conflicts between --derivatives, --session-label, and BIDS filters in fmriprep can be a perplexing part of advanced neuroimaging analysis. The errors we've discussed highlight the complex interactions between different input mechanisms and the importance of how session information is managed internally. The key takeaway is that the way fmriprep interprets and routes session information can clash with the structure of pre-computed anatomical derivatives, which are often subject-level rather than session-level.

By understanding the specific points of failure – the misapplication of session labels to anatomical derivatives and the incorrect expansion of session IDs in BIDS queries – we can adopt more effective strategies. Separating anatomical and functional preprocessing jobs, meticulously crafting BIDS filters, and carefully aligning command-line arguments with data structure are crucial best practices. While these edge cases can be challenging, they also offer opportunities to deepen our understanding of the tools we use and contribute to their improvement. Keep experimenting, keep reporting, and happy analyzing, guys!