Constructing a bridge between functioning of oscillatory neuronal networks and quantum-like cognition along with quantum-inspired computation and AI
Andrei Khrennikov, Atsushi Iriki, and Irina Basieva

TL;DR
This paper proposes a quantum-theoretical framework linking neuronal oscillations to quantum-like cognitive behaviors, suggesting that AI systems should incorporate quantum principles for more human-like information processing.
Contribution
It introduces the concept of QL oscillatory cognition, connecting neural oscillations with quantum-inspired models, and formulates testable conjectures on cognition and neural entanglement.
Findings
Neuronal oscillations may generate quantum-like states in cognition.
Fundamental cognitive processes could follow quantum principles.
Quantum-like AI can be implemented via oscillatory neural networks.
Abstract
Quantum-like (QL) modeling, one of the outcomes of the quantum information revolution, extends quantum theory methods beyond physics to decision theory and cognitive psychology. While effective in explaining paradoxes in decision making and effects in cognitive psychology, such as conjunction, disjunction, order, and response replicability, it lacks a direct link to neural information processing in the brain. This study bridges neurophysiology, neuropsychology, and cognitive psychology, exploring how oscillatory neuronal networks give rise to QL behaviors. Inspired by the computational power of neuronal oscillations and quantum-inspired computation (QIC), we propose a quantum-theoretical framework for coupling of cognition/decision making and neural oscillations - {\it QL oscillatory cognition.} This is a step, may be very small, towards clarification of the relation between mind and…
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Taxonomy
TopicsNeural Networks and Reservoir Computing
MethodsALIGN
