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Interindividual aperiodic resting-state EEG activity predicts cognitive-control styles.

Yu Pi¹, Jimin Yan¹, Charlotte Pscherer²

¹Department of Psychology, Shandong Normal University, Jinan, China.

Psychophysiology

|March 31, 2024

Summary

Individual differences in resting-state neural noise, measured by aperiodic electroencephalography (EEG) activity, predict distinct cognitive control styles. This suggests inherent brain biases influence task performance, adaptable under demanding conditions.

Keywords:

EEG aperiodic neural activity cognitive control metacontrol neural noise

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Area of Science:

Neuroscience
Cognitive Psychology
Electrophysiology

Background:

Metacontrol involves balancing cognitive flexibility and persistence.
Aperiodic electroencephalography (EEG) activity and task demands may influence metacontrol styles.
Individual differences in resting-state neural activity could predict task-related cognitive control.

Purpose of the Study:

To investigate if off-task aperiodic EEG activity predicts individual cognitive control styles.
To examine how resting-state neural noise relates to metacontrol under varying task demands.

Main Methods:

Analysis of resting-state EEG, task-EEG, and behavioral data from 65 healthy participants performing a Go/Nogo task.
Quantification of aperiodic EEG activity as an indicator of neural noise.
Group assignment (high-noise vs. low-noise) based on resting-state aperiodic exponents.

Main Results:

Off-task aperiodic exponents predicted different cognitive control styles in Go and Nogo conditions.
Low-noise individuals showed consistent control, while high-noise individuals reduced noise in the more demanding Nogo condition.
Resting-state neural noise levels influenced task-specific cognitive control strategies.

Conclusions:

Trait-like neural biases influence default cognitive control styles.
Cognitive control can adapt and be compensated for under challenging task demands.
Aperiodic EEG activity reflects dynamic metacontrol and the brain's adaptive capacity.