What do we really know about the interplay between brain, behavior, and cognition from childhood to early adulthood? An international group effort to generate and share simulated datasets.
Bibliographic record
Abstract
Background: Neuroimaging has contributed considerably to our understanding of brain development and its relationship to cognition and behavior. However, despite advancements in neuroimaging, replicability in research remains a key issue and there are no gold standard models that quantify neuroanatomical correlates of cognition, behavior and their interplay. Methods: Research groups across the globe have each independently created simulated datasets containing the interplay between brain development, behavior, and cognition. Each group has worked independently and unaware of the approaches and assumptions made by the other groups. Each group was provided the same number of variables and were instructed to create three datasets with each embedding how they envision the interplay between brain development, behavior, and cognition emerges throughout development. Results: We are releasing these simulated datasets to challenge/invite the research community to determine the underlying patterns and assumptions within the simulated datasets. Each dataset contains 10,000 participants over 7 longitudinal waves, ranging from age 7 to 20. The data can be found at https://socoden.github.io/Simulation/. The code and descriptions of the models that were used to create these datasets will be released mid 2025. The research community is invited to explore underlying models and data patterns in simulated datasets and submit their findings. Discussion: Findings from those in the community analyzing data will be evaluated by the groups that generated the simulated datasets. Evaluations will be qualitative and will be used to identify common themes across patterns in simulated datasets and models applied by the community, to learn which proposed neurodevelopment patterns were picked up, which ones were missed and what were common assumptions made. Lessons learned will be disseminated to the research community and may also be beneficial to test with real data as large developmental datasets, such as the ABCD Study and the China Child Brain Development (CCBD) Study, come to fruition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.059 | 0.174 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".