Multimodal brain network analysis reveals divergent dysconnectivity patterns during mental fatigue: A concurrent...

Area of Science:

• Neuroscience
• Cognitive Science
• Neuroergonomics

Background:

• Mental fatigue is crucial in neuroergonomics, necessitating research into its neural underpinnings.
• Understanding brain network reorganization during fatigue is essential for optimizing human performance and well-being.

Purpose of the Study:

• To investigate fatigue-related brain network reorganization using concurrent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI).
• To compare brain network architectures during vigilant and fatigued states induced by a sustained attention task.

Main Methods:

• Acquired multimodal neuroimaging data (EEG-fMRI) from 35 healthy participants performing a 15-minute psychomotor vigilance task.
• Quantitatively compared brain network architectures between the most vigilant (first 3 minutes) and most fatigued (last 3 minutes) states.
• Analyzed network properties including information transmission efficiency and nodal efficiency.

Main Results:

• EEG and fMRI networks showed distinct but interconnected reorganizations during mental fatigue.
• EEG revealed decreased parallel information transmission across frequency bands, while fMRI showed altered local efficiency.
• Both EEG and fMRI networks exhibited decreased nodal efficiency in the default mode network, indicating reduced cognitive control.

Conclusions:

• Multimodal EEG-fMRI network analysis provides novel insights into dynamic neural adaptations to mental fatigue.
• Mental fatigue leads to specific network reorganizations impacting information processing and cognitive control capacity.
• This research enhances the understanding of the neural mechanisms underlying mental fatigue.