Decomposing alpha and 1/f brain activities reveals their differential associations with cognitive processing speed

Area of Science:

• Cognitive Neuroscience
• Neuroscience
• Computational Neuroscience

Background:

• Temporal dynamics of brain activity are linked to cognitive functioning.
• Brain activity comprises coexisting oscillatory and 1/f noise-like components.
• Conventional analysis may confound 1/f activity with oscillations, impacting functional associations.

Purpose of the Study:

• Investigate the relationship between resting-state EEG and cognitive functioning efficiency.
• Determine the role of 1/f brain activity versus oscillations in cognitive speed.
• Clarify the functional relevance of the 1/f power law pattern in neural activity.

Main Methods:

• Analyzed resting-state electroencephalography (EEG) data from 180 individuals.
• Employed methods to dissociate 1/f brain activity from oscillatory components (e.g., alpha oscillations).
• Correlated isolated 1/f and oscillatory activity with measures of cognitive speed.

Main Results:

• 1/f brain activity was a significant predictor of between-person variability in cognitive speed.
• Alpha oscillation power initially appeared predictive but lost significance upon dissociation from 1/f activity.
• Only the isolated 1/f component, not alpha oscillations, reliably predicted cognitive speed.

Conclusions:

• 1/f brain activity is crucial for explaining cognitive speed variations.
• Conventional power spectrum analysis can misattribute effects of 1/f activity to oscillations.
• Isolating the 1/f component is necessary for accurate functional analysis of spontaneous brain activity.