Identification of functional neural networks of human brains with fMRI.

The highly evolved human brain comprises numerous functional systems, ranging from essential sensory, motor, attention and memory networks to higher-order cognitive functions like reasoning and language. These neural systems and cognitive functions are functionally integrated together to perform a task. BOLD-fMRI measures the neural activity across the entire brain at large-scale systems level. We define a functional neural network (FNN) as a network in which the temporal variation of the neural activity is the same across the entire network, i.e., all voxels in the network share the same BOLD time signal. We report a novel data-driven method to objectively and automatically identify FNNs across the entire brain for both brain states measured with resting-state and task-fMRI, respectively. The identified FNNs demonstrate dominating bilateral and symmetric characteristics for both brain states at both individual and group levels. These FNNs and the quantification of the interaction between them characterize the whole-brain activity holistically for each brain state and each individual subject.