Development of Effective Connectome from Infancy to Adolescence

Area of Science:

• Neuroscience
• Developmental Neuroscience
• Brain Imaging

Background:

• Understanding brain development is crucial for assessing growth and detecting diseases.
• Functional connectivity (FC) using resting-state fMRI (rs-fMRI) has limitations in capturing directed influences.
• Effective connectivity (EC) offers a more nuanced view of directed causal interactions in neural networks.

Purpose of the Study:

• To delineate the developmental trajectories of effective connectivity (EC) in whole-brain networks from infancy to adolescence.
• To investigate age-related changes in directed causal influences using regression dynamic causal modeling (rDCM).
• To identify specific brain regions and networks exhibiting significant developmental changes in EC.

Main Methods:

• Applied regression dynamic causal modeling (rDCM) to rs-fMRI data from the Baby Connectome Project (BCP) and Human Connectome Project Development (HCP-D).
• Analyzed data from individuals aged 0-22 years to map developmental trajectories of EC.
• Utilized linear mixed models to assess the effect of age on nodal EC and identify significant developmental patterns.

Main Results:

• A significant age effect on mean nodal EC was observed, best described by a quadratic "U"-shaped curve with a minimum around 2 years of age.
• The left and right cuneus, left precuneus, left supramarginal gyrus, and right inferior temporal gyrus showed the most significant age-related changes in nodal EC.
• The frontoparietal control (FPC) network exhibited the fastest increase in EC from early childhood to adolescence, followed by visual and salience networks.

Conclusions:

• Brain's effective connectivity displays a complex, nonlinear developmental profile from infancy through adolescence.
• These findings suggest dynamic structural and functional maturation processes occurring during this critical developmental period.
• The study provides a normative developmental map of EC, valuable for understanding typical brain maturation and identifying deviations.