COGNITIVE SCIENCE PAPERS

https://arxiv.org/html/2603.15381v1

" Alison Gopnik

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Jitendra Malik

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A position paper with Emmanuel Dupoux and Yann LeCun https://arxiv.org/abs/2603.15381 on a cognitive science inspired AI. We analyse how autonomous learning works in living organisms, and propose a roadmap for reproducing it in artificial systems. The conceptual and technical challenges are large, and it will be years before they are solved. We hope this research will help increase our knowledge of learning in living organisms and help build safer and more robust AI systems."

Hierarchical Flows of Human Cortical Activity

Xiaobo Liu, Alex I. Wiesman, Sylvain Baillet

doi: https://doi.org/10.64898/2026.03.19.712872

This article is a preprint and has not been certified by peer review [what does this mean?].

Abstract

Ongoing brain activity unfolds as structured spatiotemporal patterns across the cortex, yet quantifying the direction and strength of this propagation on the folded cortical sheet is challenging within and across individuals. We introduce geodesic cortical flow, a surface-based optical-flow framework that estimates millisecond-resolved surface-tangent propagation fields from source-imaged magnetoencephalography (MEG) data. In resting-state MEG from 608 healthy adults, spontaneous propagation was anisotropic and bidirectionally aligned with the principal unimodal-to-transmodal functional gradient: slow activity (1-13 Hz) was biased toward upstream propagation from sensory to association cortex, whereas beta activity (13-30 Hz) was biased toward downstream propagation in the opposite direction. Across adulthood, this balance shifted toward weaker upstream slow propagation and stronger downstream beta propagation. Propagation strength, indexed by kinetic energy of the cortical flow, followed a robust posterior-to-anterior gradient and, within frontoparietal cortex, higher kinetic energy was associated with better fluid intelligence after adjustment for age. Kinetic-energy dynamics further identified stable-state dwell times that tracked regional neuronal timescales. Together, these findings establish geodesic cortical flow as a geometry-informed framework for quantifying frequency-resolved cortical propagation and its variation across aging and cognition.