Infra-slow scale-free dynamics modulate the connection of neural and behavioral variability during attention

Area of Science:

• Neuroscience
• Cognitive Science
• Complexity Science

Background:

• Brain activity exhibits scale-free dynamics across various timescales.
• While Delta to Gamma bands are well-studied, infra-slow dynamics (e.g., power law exponent - PLE) and neural variability (e.g., standard deviation - SD, sample entropy - SE) roles in attention remain less explored.
• Understanding these infra-slow dynamics is crucial for deciphering brain-behavior connections during attention.

Purpose of the Study:

• To investigate how PLE, SD, and SE modulate behavioral performance dynamics during sustained attention.
• To explore the topographic distribution and rest-task modulation of these neurodynamical features.
• To examine the interrelationships between PLE, SD, and SE and their connection to behavioral variability.

Main Methods:

• Recruited 49 participants for functional magnetic resonance imaging (fMRI) data collection.
• Recorded resting-state and task-based fMRI data during a sustained attention task.
• Analyzed neurodynamical measures including PLE, SD, and SE in relation to behavioral variability.

Main Results:

• PLE, SD, and SE displayed distinct topographic distributions with hierarchical organization from sensory to associative networks during rest-task modulation.
• These measures showed varied topographic extensions from the visual cortex to the default-mode network concerning behavioral variability.
• The relationship between SD and SE was found to be mediated by PLE in both empirical data and simulations.

Conclusions:

• Distinct neurodynamical features (PLE, SD, SE) operate through topographically and dynamically layered mechanisms during attention.
• Scale-free dynamics play a significant role in modulating neural and behavioral variability.
• This research provides novel insights into the complex interplay of brain dynamics and attentional processes.