Birgit Elsner

Papers

Total Citations

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About

Birgit Elsner's research lies at the intersection of cognitive science, developmental psychology, and computational modeling, with a particular focus on how humans learn to predict and interact with their environment. Her work explores the fundamental mechanisms of event segmentation and hierarchical anticipation—how the brain breaks down continuous experience into meaningful events and uses those structures to make predictions across different timescales. A major contribution is her computational approach to modeling the development of these hierarchical predictions through neural networks that autonomously learn latent event codes, offering a mechanistic account of how infants and adults alike build predictive models of the world. Her 2022 paper on this topic has garnered 8 citations and represents a significant step toward unifying developmental and computational perspectives. Elsner also brings an interdisciplinary lens to the study of tool use, as evidenced by her 2023 work (5 citations) that synthesizes insights from archaeology, neuroscience, and psychology to understand the cognitive architecture underlying tool mastering—a capacity that has fundamentally shaped human evolution and culture. Her research bridges theory and modeling, offering testable frameworks for how hierarchical predictions emerge from experience.