Investigating intrinsic connectivity networks using simultaneous BOLD and CBF measurements

Area of Science:

• Neuroscience
• Functional Magnetic Resonance Imaging (fMRI)
• Systems Neuroscience

Background:

• Brain networks support task performance but can show subtle responses missed by standard analysis.
• The metabolic demands of these networks during stimulation are not fully understood.

Purpose of the Study:

• Compare general linear modelling (GLM) and independent component analysis (ICA) for analyzing brain responses to median nerve stimulation (MNS).
• Investigate the spatial, temporal, and metabolic properties of responses in the primary sensorimotor cortex (S1/M1), default mode network (DMN), and fronto-parietal network (FPN).

Main Methods:

• Concurrent BOLD and cerebral blood flow (CBF) measurements during MNS.
• Comparison of GLM and ICA for analyzing fMRI data.
• Calculation of changes in cerebral metabolic rate of oxygen consumption (Δ%CMRO2) and metabolism-flow coupling ratios.

Main Results:

• Excellent agreement between GLM and ICA for BOLD and CBF responses in S1/M1.
• ICA detected significant DMN and FPN activity not identified by GLM.
• Metabolism-flow coupling ratios (Δ%CMRO2/Δ%CBF) were comparable in S1/M1 and FPN but higher in the DMN.

Conclusions:

• ICA is a valid method for estimating CMRO2 changes and detecting subtle network responses.
• Metabolism-flow coupling may differ between task-positive (FPN) and task-negative (DMN) networks.
• These differences could stem from intrinsic network properties or task-related activity patterns.