LLM predictions of brain activity during naturalistic listening show cross-lingual spatial stability in cortical and subcortical networks that is not driven by surprisal or intrinsic dimensionality.
Burns, Cindee Madison, Dav Clark, Yaroslav O
3 Pith papers cite this work, alongside 2,456 external citations. Polarity classification is still indexing.
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NeuroAgent uses a hierarchical LLM agent framework with Generate-Execute-Validate loops to automate neuroimaging preprocessing, reaching 84.8% end-to-end correctness and 0.9518 AUC for Alzheimer's classification on 1470 ADNI subjects using four modalities.
BCER agent improves end-to-end reliability of long-horizon MRI workflows via compilation, artifact binding, and bounded local recovery, outperforming reactive baselines especially on long-chain tasks across brain, prostate, and cardiac benchmarks.
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Cross-lingual robustness of LLM-brain alignment and its computational roots
LLM predictions of brain activity during naturalistic listening show cross-lingual spatial stability in cortical and subcortical networks that is not driven by surprisal or intrinsic dimensionality.
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NeuroAgent: LLM Agents for Multimodal Neuroimaging Analysis and Research
NeuroAgent uses a hierarchical LLM agent framework with Generate-Execute-Validate loops to automate neuroimaging preprocessing, reaching 84.8% end-to-end correctness and 0.9518 AUC for Alzheimer's classification on 1470 ADNI subjects using four modalities.
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BCER Agent: Reliable Long-Horizon MRI Workflow Execution via Compilation, Artifact Binding, and Bounded Local Recovery
BCER agent improves end-to-end reliability of long-horizon MRI workflows via compilation, artifact binding, and bounded local recovery, outperforming reactive baselines especially on long-chain tasks across brain, prostate, and cardiac benchmarks.