Structuring results and discussion, integrating figures, and managing co-author feed

[DavidL]

I'm a postdoc in neuroscience preparing my first major manuscript as lead author for a high-impact journal, and I'm struggling with structuring the results section to tell a compelling narrative without over-interpreting the data. My PI says my drafts are too descriptive and lack a clear through-line. For other early-career researchers or experienced manuscript reviewers, what is your process for outlining the logical flow of a paper before you start writing? How do you effectively integrate figures and statistical reporting to support your argument, and what strategies do you use for writing a discussion that acknowledges limitations while still confidently asserting the significance of your findings? I'm also unsure how to handle co-author contributions and feedback cycles efficiently.

[Dennis17]

Agree with starting from a high-level story arc. Draft a one-page 'through-line' mapping: what question you answer in each section, the key figure, and the core statistic. Then align each paragraph to that arc, cutting anything that doesn't advance the through-line. Also push back on the urge to describe every nuance; pick the strongest result per experiment that supports the main claim.

[RyanQJ]

I like constructing a results blueprint: list all experiments, their primary questions, the statistic, p-values or effect sizes, and the visual you plan. Then group them into 3-4 subsections that each tell a mini-story. The discussion should reference limitations and alternative explanations early, then frame significance with future work and broader impact. Use a 'significance ladder': what is the result, how robust is it, what would falsify it.

[SavannahDM]

From my experience, I outline by figure first, not by text. Create a figure list of 6-8 figures and supplements; each figure has a succinct caption that states the takeaway. Then write a paragraph that introduces the figure, followed by a short result sentence that supports the claim; tie across figures using connecting sentences. For stats, report exact tests, effect sizes, CIs, and justify multiple comparisons corrections. In the discussion, openly discuss limitations, alternative interpretations, and what would be needed to strengthen the claim (e.g., replication, power). Co-author feedback: set a strict comment window, use a shared doc with tracked changes, and schedule brief weekly 15-minute reviews focusing on content rather than line edits.

[EthanS]

I was in a similar spot last year. A trick is to write the discussion early but tempered: state the significance but add 'tentative' language for authorship concerns. Use a template: 1) big picture take-home, 2) robust results, 3) limitations, 4) next steps. Share a mini 'signals map' showing which results drive the main claim and which are supplementary.","Do you often work with co-authors across institutions? How do you handle authorship order and responsibility for certain claims? If you'd like, I can sketch a 2-3 page outline template you can adapt quickly and a 1-page checklist to keep authors aligned during revisions.