Schema theory revisited: A spectrum of abstraction in AI and neuroscience
By
Mandana Samiei1,2 Send email to [email protected]
Summary
This article examines schema theory—a foundational concept in psychology, cognitive science, and neuroscience—and its relevance to both biological brains and artificial intelligence. The authors challenge classical models that treat schemas as distinct, fixed memory structures. Instead, drawing inspiration from generative AI, they propose that schemas exist along a "spectrum of abstraction," where declarative knowledge is organized hierarchically from concrete episodic memories to abstract semantic knowledge. The paper explores how memory schematization, replay, and consolidation processes in the brain relate to distributed representations and emergent structures in modern AI systems, bridging neuroscience and machine learning perspectives on knowledge abstraction.
Source
bskySchema theory revisited: A spectrum of abstraction in AI and neurosciencecell.comKey quotes
· 3 pulledSchema theory has a long and influential history across psychology, cognitive science, and neuroscience.
Samiei et al. argue against classical models that treat schemas as distinct memory structures.
They propose that schemas are merely a conceptual tool describing how declarative knowledge exists along a spectrum of abstraction.
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