标题： 人工智能在神经科学中的认识扩散的动力学制图 显示英文标题

标题： A Dynamical Cartography of the Epistemic Diffusion of Artificial Intelligence in Neuroscience

摘要： 神经科学和人工智能有着交织的历史，这在两个领域的文献中都有所体现。 近年来，由于人工智能研究的工程导向以及产业界在其大规模应用中的垄断，神经科学和人工智能在基础研究中的相互扩展似乎面临挑战。 在本文中，我们提供了一些实证证据，表明相反的情况是，人工智能和神经科学仍在继续共同发展，但自20世纪90年代以来，对与神经退行性疾病相关的研究领域表现出明显的兴趣。 通过使用先进的文档嵌入技术绘制神经科学的时间知识图谱，我们描绘了该学科自20世纪70年代以来的动态演变，并确定了人工智能与前述特定子领域的概念结合。 然而，对所研究语料库的潜在引用网络的进一步分析显示，生成的人工智能技术仍局限于不同的子领域，并未从一个子领域转移到另一个子领域。 这促使我们讨论人工智能在学科内发展背景下的通用性能力，尤其是在其相关度量标准的传播方面。 显示英文摘要

摘要： 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 corpus shows that the produced AI technologies remain confined in the different subfields and are not transferred from one subfield to another. This invites us to discuss the genericity capability of AI in the context of an intradisciplinary development, especially in the diffusion of its associated metrology.