Bringing analytic rigor to agentic AI for science: The Brain Researcher platform for neuroimaging data analysis
AI agents can execute scientific analyses, but an analytic output becomes a defensible claim only after alternatives are weighed and the claim is limited to what the evidence supports. Agents may reproduce failures including selective analysis, premature declarations of success and optimization of imperfect criteria. We present Brain Researcher, an agentic research harness operating in a neuroimaging researcher's computational environment under rules for admissible analyses, required checks and claim scope. In benchmarks, Brain Researcher increased first-choice tool-selection accuracy across seven models by 70.2 percentage points (23.3% without it versus 93.6% with it) and verifiable grou...
| Authors | Zijiao Chen, Nicholas Lu, Xinhui Li et al. |
|---|---|
| Primary category | cs.AI |
| Published | 20 August 2026 |
| Last updated at source | 20 August 2026 |
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