A Dynamical Cartography of the Epistemic Diffusion of Artificial Intelligence in Neuroscience
Sylvain Fontaine

TL;DR
This paper maps the evolution of AI in neuroscience, highlighting its growing focus on neurodegenerative diseases since the 1990s and analyzing how AI technologies remain confined within subfields without broad transfer.
Contribution
It provides a temporal and conceptual cartography of AI's integration into neuroscience, revealing limited cross-subfield transfer of AI technologies.
Findings
AI and neuroscience continue to grow together, especially in neurodegenerative research.
AI technologies tend to remain within specific subfields, showing limited transfer across disciplines.
The study offers a detailed dynamical mapping of the discipline since the 1970s.
Abstract
Neuroscience and AI have an intertwined history, largely relayed in the literature of both fields. In recent years, due to the engineering orientations of AI research and the monopoly of industry for its large-scale applications, the mutual expansion of neuroscience and AI in fundamental research seems challenged. In this paper, we bring some empirical evidences that, on the contrary, AI and neuroscience are continuing to grow together, but with a pronounced interest in the fields of study related to neurodegenerative diseases since the 1990s. With a temporal knowledge cartography of neuroscience drawn with advanced document embedding techniques, we draw the dynamical shaping of the discipline since the 1970s and identified the conceptual articulation of AI with this particular subfield mentioned before. However, a further analysis of the underlying citation network of the studied…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
