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Updated: Jan 17, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Autonomous semantics and syntax on-demand in neurocomputational models of language
1Language Acquisition and Language Processing Lab, Department of Language and Literature, Norwegian University of Science and Technology, Trondheim, Norway.
Abstract:
ROSE is a rare example of a neurocomputational model of language that attempts, and partly manages, to align a formal theory of syntax and parsing with an oscillations-based 'neural code' that could implement the required operations. ROSE successfully reconciles hierarchical and predictive syntactic processing, but I argue that models of language in the brain should make room for the possibility that meaning may also be derived in the absence of any syntactic computation, be it hierarchical or predictive.
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