Joint probabilities and quantum cognition

TL;DR

This paper explores the conditions under which joint probability distributions can exist for quantum-like responses in the brain, using neural oscillator models to illustrate when such distributions are or are not possible.

Contribution

It demonstrates how neural oscillator models can produce contextual random variables lacking joint distributions, contrasting with quantum observable algebra.

Findings

Neural oscillator models can generate non-jointly distributable variables.

Certain quantum-like response patterns cannot be represented by quantum observables.

The study clarifies the relationship between neural models and quantum probability structures.

Abstract

In this paper we discuss the existence of joint probability distributions for quantum-like response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.