Classifying fMRI-derived resting-state connectivity patterns according to their daily rhythmicity

Area of Science:

• Neuroscience
• Chronobiology
• Brain Imaging

Background:

• Biological functions exhibit 24-hour rhythms.
• Understanding daily variations in brain activity is crucial for interpreting functional Magnetic Resonance Imaging (fMRI) data.

Purpose of the Study:

• To investigate the extent of daily modulation in resting-state fMRI connectivity patterns.
• To analyze the temporal dynamics of brain networks across the day, considering individual chronotypes.

Main Methods:

• Evaluated resting-state fMRI data from 15 subjects over 8 hours (4 sessions).
• Assessed 20 connectivity patterns, measuring connectivity strength and spatial extent.
• Determined individual chronotypes to control for internal time and staggered scan times.

Main Results:

• Significant daily modulation was observed across various fMRI connectivity patterns.
• Highly rhythmic patterns included Default-Mode Network (DMN) sub-systems and sensori-motor networks.
• A network associated with executive control demonstrated the most stability throughout the day.

Conclusions:

• The degree of daily modulation varies considerably among resting-state fMRI connectivity patterns.
• Findings highlight the importance of considering circadian influences when interpreting fMRI results.
• Brain network stability differs, with executive control networks being more consistent.