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Writing study: BrainWorld: A Structural-Prior-Conditioned Generative Model for Whole-Brain 4D fMRI Dynamics

← NeurIPS 2026 oral writing corpus

Junfeng Xia, Wenhao Ye, Junxiang Zhang, Xuanye Pan, Mo WANG, Quanying Liu · Official NeurIPS 2026 oral record

Figure, table and section ledger

Editorial contribution type: Domain-grounded methods & physical systems (primary).

Layout extraction, not a required paper template. Counts are distinct caption labels; a multi-panel figure counts once. Section spans are estimated from heading positions, including floats and whitespace. Method and limitations.

Canonical PDF
33 physical pages
Before references / appendix
≈ 9.09 page-equivalents
Main figures / tables
4 / 2
Attached appendix figures / tables
8 / 6
Attached appendix span
≈ 18.91 page-equivalents
Before references / appendix: ≈ 27.55%References / intervening material: ≈ 15.15%Attached appendix: ≈ 57.3%Estimated layout envelopes, not text/artwork area. Unresolved appendix boundaries remain within the undivided post-body material.

Source-bound correction: Top-level heading and reference/appendix boundaries checked against source PDF text. Bibliography titles/author initials, numbered contribution/property bullets, diagram steps, equations and TOC entries are not substantive headings. Section spans are page-coordinate estimates, not ink area or prose-only length. This is an author manuscript mirror, not a verified accepted-version template. Source layout uses physical single-column y/page-height, including equation-heavy pages.

Section-by-section lengths and source pages

The title/abstract/front matter precede the first numbered heading. A span ends at the next detected top-level heading, not at the last sentence; end-page whitespace is included. References and statements are listed separately. These are not measurements of text-only or artwork area.

Top-level headingStarts on PDF pageEstimated spanShare of entire PDF
1 Introduction1≈ 1.24 pp.3.76%
2 Related Work2≈ 1.44 pp.4.36%
3 Method4≈ 2.56 pp.7.76%
4 Experiments6≈ 1.94 pp.5.88%
5 Discussion8≈ 1.33 pp.4.03%
References10≈ 5 pp.15.15%
Supplementary Material15≈ 0.03 pp.0.09%
A. ROI baseline for comparison: BrainMAE15≈ 3.48 pp.10.55%
B. Supplementary Results18≈ 4.89 pp.14.82%
C. Details of Materials23≈ 10.51 pp.31.85%
All detected figure and table locations

Argument and organization

  1. Problem and contribution

    Separates conditional future fMRI generation from representation-only foundation models, with anatomy serving as subject-level context.

  2. Argument sequence

    Explains a spatial VAE, conditioned diffusion, rollout and representation extraction before generation, augmentation and transfer experiments.

  3. Evidence and verification

    Full-finetuning and frozen-backbone tables are separate; modalities, metric directions and the effect-size marker are defined in captions.

Problem, claim and contribution

Separates conditional future fMRI generation from representation-only foundation models, with anatomy serving as subject-level context.

Introduction · Main paper

Argument and section order

Explains a spatial VAE, conditioned diffusion, rollout and representation extraction before generation, augmentation and transfer experiments.

Sections 3–4 · Main paper

Figures, captions and visual explanation

The overview combines motivation, dataset roles, preprocessing and architecture as labeled panels, with frozen components and optional inputs distinguished.

Figure 2, p. 3 · Main paper

Tables, comparisons and evidence

Full-finetuning and frozen-backbone tables are separate; modalities, metric directions and the effect-size marker are defined in captions.

Tables 1–2, p. 9 · Main paper

Appendix and reproducibility

Additional horizon results, median-performing qualitative cases and detailed cohort/preprocessing conditions support the main summaries.

Appendices B–C · Main paper

Clarity and writing conventions

The paper defines 'structural prior' as conditioning rather than an explicit Bayesian prior and disclaims biological causality.

Section 3; limitations, p. 9 · Main paper

What to reuse—and what not to infer

Transferable lesson: For a domain application, state data roles and information access, and separate reconstruction, augmentation and transfer as different claims.

Boundary: Effect size is not a significance test; generated examples are not independent biological measurements. This fMRI paper is writing evidence, not WSI-specific guidance.

Apply this lesson using the argument and evidence worksheet.

Inspection record and sources

Checked
2026-10-02
Reading status
Writing-focused manuscript scan + selected visuals inspected
Main text
Writing-oriented distributed manuscript scan of Sections 1–5, pp. 1–9; references pp. 10–14: abstract/framing, section sequence, substantive text windows, captions, evidence organization and conclusion; not exhaustive technical verification.
Appendix / supplement
Writing-oriented scan of Supplementary baseline, results, data, preprocessing and configuration sections, pp. 15–33; code and experiments were not executed.
Visually inspected PDF pages
3, 9

This is a writing-focused scan of the manuscript and the stated supplementary scope: framing, organization, visual explanation, evidence presentation and wording. It is not a line-by-line proof audit, reproduction of results or exhaustive scientific review.