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Bringing analytic rigor to agentic AI for science: The Brain Researcher platform for neuroimaging data analysis

arXiv cs.AI LLM Agents Zijiao Chen, Nicholas Lu, Xinhui Li, Jocelyn A. Ricard, Ce Ju, Huan H. Wang, Christian Kindermann, Jeanette A. Mumford, Steven Dillmann, James Kent, Alejandro de la Vega, Sanmi Koyejo, Vince D. Calhoun, Joshua W. Buckholtz, Juan Helen Zhou, Steffen Bollmann, Russell A. Poldrack 2026-08-20
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TL;DR - Brain Researcher is an agentic platform that embeds methodological constraints, evidence tracking, and scientific review into neuroimaging analysis workflows. It aims to make agent-generated findings more defensible by testing alternative analyses and limiting claims to what the evidence supports.

  • Improved first-choice tool-selection accuracy across seven models from 23.3% to 93.6%.
  • Increased verifiable grounding from 4.6% to 22.0%.
  • Uses multiverse analyses to reveal how findings vary with analytic choices.
  • Links decisions to evidence and provenance, while classifying claims as accepted, qualified, revised, blocked, rejected, or deferred.

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