Variation in high-amplitude events across the human lifespan

Area of Science:

• Neuroscience
• Cognitive Science
• Developmental Neuroscience

Background:

• Edge time series analysis reveals fine-scale functional connectivity.
• High-amplitude events in edge time series form distinct, reproducible patterns.
• Lifespan changes in these event patterns remain largely unexplored.

Purpose of the Study:

• Investigate how event patterns in edge time series change across the human lifespan.
• Examine the relationship between age-related event patterns and structural connectivity.
• Determine if event clusters predict cognitive phenotypes.

Main Methods:

• Clustering of event frames from edge time series data.
• Analysis of a lifespan-spanning dataset (Nathan Kline Institute-Rockland sample).
• Correlation analysis with structural connectivity measures and phenotype prediction.

Main Results:

• Identified two main event clusters present across ages, varying in magnitude and frequency with age.
• Demonstrated distinct, age-dependent relationships between event clusters and structural connectivity.
• Showcased superior predictive power of event clusters over non-events for intelligence and achievement phenotypes.

Conclusions:

• Edge time series event patterns exhibit systematic changes throughout the human lifespan.
• These age-related changes in functional connectivity dynamics are linked to structural properties and cognitive outcomes.
• Findings provide a foundation for understanding the origins of lifespan changes in brain functional connectivity.