Modeling Autonomous Shifts Between Focus State and Mind-Wandering Using a Predictive-Coding-Inspired Variational RNN Model

TL;DR

This study models neural mechanisms behind autonomous shifts between focus and mind-wandering using an extended variational RNN inspired by the free energy principle, revealing how parameter changes influence perception states.

Contribution

The paper introduces a meta-level adaptation mechanism in a variational RNN model to simulate autonomous focus and mind-wandering shifts based on the free energy principle.

Findings

Shifts occur when the meta-prior parameter switches between low and high values.

High meta-prior emphasizes top-down predictions, low emphasizes bottom-up sensations.

Simulation results align with existing neural and cognitive studies.

Abstract

The current study investigates possible neural mechanisms underling autonomous shifts between focus state and mind-wandering by conducting model simulation experiments. On this purpose, we modeled perception processes of continuous sensory sequences using our previous proposed variational RNN model which was developed based on the free energy principle. The current study extended this model by introducing an adaptation mechanism of a meta-level parameter, referred to as the meta-prior $\mathbf{w}$, which regulates the complexity term in the free energy. Our simulation experiments demonstrated that autonomous shifts between focused perception and mind-wandering take place when $\mathbf{w}$ switches between low and high values associated with decrease and increase of the average reconstruction error over the past window. In particular, high $\mathbf{w}$ prioritized top-down predictions while low $\mathbf{w}$ emphasized bottom-up sensations. This paper explores how our experiment results align with existing studies and highlights their potential for future research.