Epistemic integration and social segregation of AI in neuroscience
Sylvain Fontaine, Floriana Gargiulo, Michel Dubois, Paola Tubaro

TL;DR
This paper empirically analyzes how AI has integrated into neuroscience, forming a distinct community and publication ecosystem that maintains disciplinary boundaries rather than transforming them.
Contribution
It provides a scientometric analysis revealing AI's role in creating a specialized, socially confined subfield within neuroscience, highlighting its diffusion pattern and community structure.
Findings
AI forms a distinct disciplinary ecosystem in neuroscience.
The AI community in neuroscience is socially confined and publishes mainly in dedicated journals.
AI diffusion maintains disciplinary boundaries rather than causing fundamental changes.
Abstract
In recent years, Artificial Intelligence (AI) shows a spectacular ability of insertion inside a variety of disciplines which use it for scientific advancements and which sometimes improve it for their conceptual and methodological needs. According to the transverse science framework originally conceived by Shinn and Joerges, AI can be seen as an instrument which is progressively acquiring a universal character through its diffusion across science. In this paper we address empirically one aspect of this diffusion, namely the penetration of AI into a specific field of research. Taking neuroscience as a case study, we conduct a scientometric analysis of the development of AI in this field. We especially study the temporal egocentric citation network around the articles included in this literature, their represented journals and their authors linked together by a temporal collaboration…
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Taxonomy
TopicsMachine Learning in Materials Science · Bioinformatics and Genomic Networks · Scientific Computing and Data Management
