Curiosity shapes brain-like architectures and functions
- 1University of Cambridge
Abstract
How does complex cognition emerge from simpler underlying processes? We show that two components are sufficient: infant-like curiosity and brain-like biophysical constraints jointly drive the emergence of complex neuronal architectures and cognitive abilities. We first tested curiosity-driven exploration in 275 8- to 15-month-old infants. We then implemented these mechanisms in artificial recurrent neural networks, letting them actively sample 20 cognitive tasks during training, while forcing the networks to operate under brain-like biophysical constraints. These two components were sufficient for a range of biological and cognitive phenomena to emerge: The resulting networks captured human synaptic development, the adult brain's architecture, and displayed compositional generalisation, a hallmark of human cognition. Curiosity, long viewed as a downstream consequence of complex brains, is also a driver of their complexity.
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BibTeX
@misc{poli2026curiosity,
title = {{Curiosity shapes brain-like architectures and functions}},
author = {F. Poli and K. Fakhar and A. Mousley and C. Klein and C. Grosse Wiesmann and D. Astle},
howpublished = {bioRxiv},
year = {2026},
month = jul,
doi = {10.64898/2026.07.02.735826},
url = {https://www.biorxiv.org/content/10.64898/2026.07.02.735826v2},
note = {CC BY},
}
RIS
TY - UNPB
TI - Curiosity shapes brain-like architectures and functions
AU - F. Poli
AU - K. Fakhar
AU - A. Mousley
AU - C. Klein
AU - C. Grosse Wiesmann
AU - D. Astle
PY - 2026
DA - 2026/07/02
PB - bioRxiv
DO - 10.64898/2026.07.02.735826
UR - https://www.biorxiv.org/content/10.64898/2026.07.02.735826v2
AB - How does complex cognition emerge from simpler underlying processes? We show that two components are sufficient: infant-like curiosity and brain-like biophysical constraints jointly drive the emergence of complex neuronal architectures and cognitive abilities. We first tested curiosity-driven exploration in 275 8- to 15-month-old infants. We then implemented these mechanisms in artificial recurrent neural networks, letting them actively sample 20 cognitive tasks during training, while forcing the networks to operate under brain-like biophysical constraints. These two components were sufficient for a range of biological and cognitive phenomena to emerge: The resulting networks captured human synaptic development, the adult brain's architecture, and displayed compositional generalisation, a hallmark of human cognition. Curiosity, long viewed as a downstream consequence of complex brains, is also a driver of their complexity.
ER -