The complex workings of the human brain were once thought to be dictated by specific, isolated regions, each performing a distinct function. Modern neuroscience has shifted this understanding, revealing that thought and behavior arise from integrated brain networks. These networks are vast systems of interconnected brain regions that work in concert, distributing processing across multiple areas simultaneously. Studying these integrated systems helps researchers understand how the brain coordinates its computational power to generate complex cognition.
The Architecture of Brain Networks
The structural foundation of a brain network is often described using graph theory, which defines the system by two primary components: nodes and edges. Nodes represent the functional centers, typically macroscopic brain regions like the hippocampus or prefrontal cortex, where information processing occurs. Edges are the connections or pathways linking these nodes, serving as the communication lines of the network.
These connections are categorized into two main types: structural and functional. Structural connectivity refers to the physical wiring of the brain, consisting of white matter tracts—bundles of myelinated axons that physically link distant brain regions. Functional connectivity describes a statistical relationship, specifically the temporal correlation of activity between two or more spatially distinct brain areas. Functional connections reflect synchronized activity when regions work together, even if they are not directly wired.
Within this architecture, certain brain regions act as specialized “hubs,” which are nodes with a disproportionately high number of connections. These hubs are analogous to major airport terminals, serving as relay stations for integrating information from diverse parts of the brain. The presence of these highly connected hubs is thought to be responsible for the brain’s high efficiency and capacity for rapid information transfer. Damage to a single hub can therefore have widespread effects, disrupting communication across multiple functional systems.
Mapping and Measuring Network Activity
To observe these complex systems in living humans, scientists rely on non-invasive neuroimaging techniques that capture the brain’s activity patterns. Functional Magnetic Resonance Imaging (fMRI) is a primary tool, measuring brain activity indirectly by detecting changes in blood flow and oxygenation, known as the blood-oxygen-level-dependent (BOLD) signal. Resting-state fMRI (rs-fMRI) is useful for network analysis, measuring synchronized BOLD fluctuations when a person is awake but not performing a specific task.
The synchronized patterns observed through rs-fMRI reveal which brain regions are functionally connected, providing a map of the large-scale networks. While fMRI offers excellent spatial resolution, its temporal resolution is slow because the hemodynamic response to neural activity is delayed. To capture the rapid temporal dynamics of brain communication, researchers employ Electroencephalography (EEG) and Magnetoencephalography (MEG).
These two methods directly measure the electrical signals generated by neuronal activity, offering millisecond-level resolution. EEG records electrical potentials from electrodes placed on the scalp, while MEG detects the tiny magnetic fields produced by the same electrical currents. Combining the high spatial detail of fMRI with the high temporal precision of EEG and MEG provides a more complete picture of how information flows and is processed within brain networks.
Core Functional Networks and Their Roles
Modern research has identified several large-scale functional networks, with three forming a triple-network model that governs much of human cognition. These three—the Default Mode Network (DMN), the Central Executive Network (CEN), and the Salience Network (SN)—must maintain a dynamic, balanced interplay for healthy thought and behavior.
The Default Mode Network (DMN) is most active when the brain is at rest, engaged in internally focused tasks, such as:
- Self-referential thought
- Future planning
- Remembering past events
- Mind-wandering
Key components of the DMN include the posterior cingulate cortex, the medial prefrontal cortex, and the angular gyrus. Activity in the DMN is suppressed when a person focuses on the external world or a demanding task, representing the brain’s “idle state” for internal processing.
In contrast to the DMN, the Central Executive Network (CEN), also known as the frontoparietal network, becomes highly active during demanding, goal-directed tasks. This network is centered around the dorsolateral prefrontal cortex and the posterior parietal cortex, regions associated with working memory, decision-making, and sustained attention. When the CEN is engaged, it enables a person to focus on external stimuli, manipulate information, and execute problem-solving strategies.
The third network, the Salience Network (SN), acts as a dynamic moderator that controls the switching between the DMN and the CEN. Anchored by the anterior insula and the anterior cingulate cortex, the SN constantly monitors the internal and external environment for relevant stimuli. If the SN detects an important external change, it rapidly inhibits the DMN and activates the CEN, shifting the brain from internal contemplation to external, goal-directed action. This ability to switch between networks is fundamental to flexible behavior.
Network Disruption and Cognitive Health
When the balance and connectivity within and between these large-scale networks are impaired, the result is often cognitive and behavioral dysfunction. Alterations in network connectivity are recognized as a neurobiological signature for many psychiatric and neurological disorders.
In major depressive disorder, a common finding is hyper-connectivity within the Default Mode Network, particularly involving regions like the subgenual cingulate cortex. This excessive connectivity is thought to provide a neural basis for persistent, negative self-referential thought, or rumination, a hallmark symptom of depression. The necessary anti-correlation between the DMN and the CEN is often weakened, hindering the ability to shift attention away from internal distress to engage with the external world.
Neurodegenerative diseases, such as Alzheimer’s disease, are characterized by a progressive breakdown of network integrity. Early stages of cognitive decline often involve a disruption of the Salience Network’s control over the other two, leading to a failure in the dynamic switching mechanism. As the disease advances, structural and functional connections fragment, resulting in widespread network disconnection and a loss of communication efficiency across the brain.
In schizophrenia, the pathology is often described as widespread dysconnectivity, affecting multiple networks, including those involved in executive function and self-processing. Studies consistently show abnormal connectivity within the frontoparietal network and the Salience Network, which contributes to the impaired reality monitoring, attention deficits, and disorganized thought patterns. These findings suggest that many cognitive health conditions result from a failure of the integrated communication system, rather than a single damaged brain region.