ArticleFrontiers in psychology2026
Bridging the neuro-AI chasm: a framework for scalable, contextually adaptive training resources in large-scale brain data science.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- The neuroscience education readiness checklist for digital tools and methods.Frontiers in computational neuroscience · 2026Article
- Dissecting neuronal circuit function and dysfunction in Alzheimer's disease mouse models: from conventional calcium imaging analysis to machine learning-based approaches.Frontiers in aging neuroscience · 2026Review
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Authors and funding
6 authors.
Funding
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Abstract
Despite the increasing availability of large-scale brain data tools, many researchers struggle to use them effectively alongside AI. This is not due to a lack of access, but because existing training resources emphasize proficiency with these tools over critical reasoning. AI accelerates workflows but also risks deepening skill disparities: researchers with strong foundational knowledge can integrate AI-generated insights, while others become dependent on automated outputs without fully understanding their limitations, inducing risks to competency acquisition. Conventional training approaches assume that exposure to AI tools naturally translates to expertise, overlooking the need for structured cognitive engagement. We propose five cognitive science-based principles to rethink neuroscience training, ensuring AI serves as a scaffold for deeper scientific reasoning rather than a passive automation tool. We demonstrate the applicability of these principles in neuroscience education through a case study of EBRAINS training resources.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.