Predictive Processing Community Collaboration Policy

As our community transitions from a shared review of the literature to the collection and analysis of new data, we reaffirm our commitment to collaborative, open, and inclusive science. This policy outlines how we work together to design, execute, analyze, and share the results of our predictive processing experiments.

Collaborative Spirit

We are a community grounded in curiosity, openness, and mutual respect. By sharing data, code, and ideas freely—and by giving credit where credit is due—we accelerate discovery and improve reproducibility. Disputes are resolved transparently and fairly, ensuring every voice is heard and every contribution is valued.

How to Contribute

Everyone is welcome to contribute—whether through text, comments, code, or data analysis.

  • Engage Respectfully: All participants are expected to maintain a respectful tone to support productive debate.
  • Join Ongoing Projects: We encourage anyone to join ongoing data analysis efforts or start new ones that align with your expertise. Reach out directly to team members or comment on the relevant project page.
  • Embrace Open Science: All contributions should align with the principles of "Science in the Open."

Transparency and accountability:
All ongoing projects should be listed in the Project Tracking document.

1. Data: Open and Unrestricted

Data are the foundation of our collaboration. To drive scientific progress and ensure reproducibility, we commit to:

1.1 Immediate Public Release

All datasets are released without embargo via the Allen Institute or the DANDI/NWB archives.

1.2 Dataset Authorship Rights

  • Co‑authorship option: Dataset creators may opt in as co-authors on any manuscript using their data.
  • First publication claim: Dataset creators are entitled to authorship on the first paper that analyzes or validates their dataset.
  • Opt‑in process: Whenever a dataset is proposed for manuscript use, its creators will be invited to opt in as authors.

2. Code: Transparent and Collaborative

Code transforms raw data into insight. We treat code with the same openness and collaborative spirit as data:

2.1 Public Release

All analysis and processing code is hosted in public repositories (e.g., GitHub) under open-source licenses, with no embargo.

2.2 Contribution Workflow

  • Pull requests: Code changes typically go through pull requests, including documentation and tests where applicable.
  • Review: Core maintainers review changes before merging.
  • Community contributions: Anyone is welcome to propose improvements, fix bugs, or add new features. New write access to a repository is given freely upon request.

3. People: Authorship and Contribution

We prioritize transparency and fairness in recognizing contributions.

3.1 Project Tracking

We maintain a shared document that tracks all ongoing projects with:

  • Title & goal: A one-sentence project description
  • Contributors: Names and roles of active team members
  • Status & next steps: Current progress and upcoming milestones

All participants are encouraged to update this document regularly.

3.2 Opt‑in Authorship

  • Signup: Each project maintains a shared authorship list from the beginning.
  • Eligibility: Anyone making a substantive scientific contribution—through data, analysis, writing, or design—is eligible to opt in. Contributions should be documented.
  • Timing: Opt-in requests should be made before data release or manuscript drafting.

3.3 Paper Leadership & Author Order

  • Lead Author: A designated lead coordinates writing and revisions.
  • Ordering: The lead author proposes an order reflecting contributions. For large teams (>20 contributors), alphabetical listing is encouraged.
  • Author Contributions Statement: All papers include a CRediT-style contributions section detailing each author's role.

4. Governance: Steering Committee

A Steering Committee oversees policy adherence, authorship transparency, and dispute resolution.

4.1 Responsibilities

  • Maintain and update this collaboration policy
  • Keep a public record of contributions and authorship
  • Resolve disputes fairly and transparently

4.2 Composition

The committee includes one representative from each lab contributing data, along with representatives from major data analysis groups. To be determined. - Member 1 - Member 2 - …

4.3 Conflict Resolution

Disputes are resolved by a majority vote.