This network includes the ventral attention network, which primarily includes the temporoparietal junction and the ventral frontal cortex of the right hemisphere.Specifically, it aids in directing attention by identifying important biological and cognitive events. It plays the key role of monitoring the salience of external inputs and internal brain events. The salience network consists of several structures, including the anterior (bilateral) insula, dorsal anterior cingulate cortex, and three subcortical structures which are the ventral striatum, substantia nigra/ventral tegmental region.ĭisruptions in activity in various networks have been implicated in neuropsychiatric disorders such as depression, Alzheimer's, autism spectrum disorder, schizophrenia, ADHD and bipolar disorder. The regions participating in a functional network may be dynamically reconfigured. The most common and stable networks are enumerated below. In one model, there is only the default mode network and the task-positive network, but most current analyses show several networks, from a small handful to 17. The number and composition of the coalitions will vary with the algorithm and parameters used to identify them. Large-scale brain networks are identified by their function and provide a coherent framework for understanding cognition by offering a neural model of how different cognitive functions emerge when different sets of brain regions join together as self-organized coalitions. In recent decades, the analysis of brain networks was made feasible by advances in imaging techniques as well as new tools from graph theory and dynamical systems. As a physical system with graph-like properties, a large-scale brain network has both nodes and edges and cannot be identified simply by the co-activation of brain areas. When the cognitive state is not explicit (i.e., the subject is at 'rest'), the large-scale brain network is a resting state network (RSN). The set of identified brain areas that are linked together in a large-scale network varies with cognitive function. Synchronized brain regions may also be identified using long-range synchronization of the EEG, MEG, or other dynamic brain signals. Functional connectivity networks may be found using algorithms such as cluster analysis, spatial independent component analysis (ICA), seed based, and others.

An emerging paradigm in neuroscience is that cognitive tasks are performed not by individual brain regions working in isolation but by networks consisting of several discrete brain regions that are said to be 'functionally connected'. Large-scale brain networks (also known as intrinsic brain networks) are collections of widespread brain regions showing functional connectivity by statistical analysis of the fMRI BOLD signal or other recording methods such as EEG, PET and MEG.

Functional network analysis definition