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Related Experiment Video

Updated: Sep 15, 2025

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

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Published on: July 5, 2015

Modeling autonomous shifts between focus state and mind-wandering using a predictive-coding-inspired variational

Henrique Oyama¹, Takazumi Matsumoto¹, Jun Tani¹

¹Cognitive Neurorobotics Research Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Onna, Japan.

Frontiers in Computational Neuroscience

|July 17, 2025

Summary

This summary is machine-generated.

This study models autonomous shifts between focused attention and mind-wandering (MW). A new meta-prior parameter regulates shifts by balancing top-down predictions and bottom-up sensations, offering insights into cognitive states.

Keywords:

brain-inspired modeling free energy principle mind-wandering predictive coding variational RNN

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Area of Science:

Cognitive Neuroscience
Computational Psychiatry

Background:

Mind-wandering (MW) involves dynamic shifts between focused attention and off-task states.
Understanding the neural mechanisms of autonomous shifts between focused states (FS) and MW is crucial for cognitive science.
Existing models lack a comprehensive account of these neural underpinnings.

Purpose of the Study:

To investigate the neural mechanisms driving autonomous shifts between FS and MW.
To propose a computational model based on predictive coding and free energy minimization.
To explore the role of a meta-prior parameter in regulating these cognitive state transitions.

Main Methods:

Utilized a variational recurrent neural network (RNN) model based on predictive coding principles.
Modeled perception of continuous sensory sequences under free energy minimization.
Introduced and manipulated an online adaptive meta-prior parameter (w) to regulate model complexity.

Main Results:

Demonstrated autonomous shifts between FS and MW driven by the meta-prior parameter (w).
Showed that low 'w' prioritizes bottom-up sensory input, while high 'w' emphasizes top-down predictions.
Observed that shifts correlate with changes in average reconstruction error over time.

Conclusions:

The proposed model provides a plausible neural mechanism for autonomous transitions between focused attention and mind-wandering.
The meta-prior parameter (w) acts as a critical regulator, influencing the balance between sensory evidence and internal predictions.
Speculated that accumulated prediction errors exceeding a threshold may underlie self-awareness of mind-wandering.