Neuroscience and artificial intelligence (AI) share a long history. Many of the founding ideas of AI attempted to borrow the brain’s tricks and reverse-engineer its mechanisms. In the ensuing decades, however, engineering intelligent machines became its own discipline, with its own drives and achievements. Though the dominant paradigm of modern AI is still the neural network (renamed “deep learning” in the mid-2000s), the resemblance to the brain is now mostly conceptual. The astonishing recent achievements in AI owe neuroscience surprisingly little in their actual machinery and operating principles.
Still, the brain—particularly the human brain—remains the only known intelligent system in the full, “general” sense, with an efficiency and flexibility that artificial systems have yet to achieve.
Over the past decade, a growing coalition of prominent institutions and intellectuals in the fields of AI, brain and cognitive sciences (includingGeoffrey Hinton,John HopfieldandDemis Hassabis, who won Nobel Prizes in 2024 for AI-related work) has argued that thetwo fields canand shouldfuel each other, with the potential for compound gains neither can reach alone. Under the umbrella termNeuroAI, the idea is thatneuroscience can offer AI principles, architectures and algorithms it cannot obtain elsewhere, and AI can contribute rigorous foundations and tools that help neuroscientists theorize about neural computation, cognition and intelligence, creating a “virtuous circle.”
The promise is appealing—obvious, even, to anyone who has worked in this space—but its real impact is hard to verify. The past few years have seen a growing number of dedicated institutes, endowments, manifestos and events, highlighting real enthusiasm. But is there a genuine intellectual merger taking place? Has anything shifted in how these fields interact? Instead of asking whether neuroscience and AI should fuel each other, I asked whether they actually do, examining how knowledge moves between them. I analyzed roughly 458 million works from OpenAlex, an open database of publications, and the 2.9 billion links among them, tracing patterns in how the two fields have cited each other over time.
