State-dependent differences between functional and effective connectivity of the human cortical motor system

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Brain Imaging

Background:

• Neural processing relies on interactions between specialized brain areas, assessed via functional or effective connectivity.
• Functional connectivity is typically measured using resting-state fMRI, while effective connectivity uses task-based fMRI.
• Understanding how these connectivity measures relate is crucial for interpreting brain network dynamics.

Purpose of the Study:

• To investigate whether resting-state and task-based fMRI yield similar network topologies.
• To compare functional connectivity and effective connectivity estimates within the same subjects.
• To determine the relationship between different connectivity approaches in motor network assessment.

Main Methods:

• 36 healthy volunteers underwent resting-state fMRI followed by task-based fMRI (hand movement task).
• Time-series data were extracted from motor task activation maxima.
• Functional connectivity (correlation) and effective connectivity (Dynamic Causal Modeling - DCM) were computed for both states.

Main Results:

• All analyses revealed strong interactions within motor areas.
• Resting-state functional connectivity showed weak correlations with task-based functional and effective connectivity.
• Task-based functional connectivity strongly correlated with DCM effective connectivity parameters.

Conclusions:

• Resting-state and task-based connectivity capture distinct aspects of functional integration.
• The functional state during scanning significantly influences connectivity estimates.
• Resting-state fMRI and DCM are complementary tools for comprehensive brain network assessment.