Brain connectivity research investigates how different regions of the brain interact to support perception, thought and behavior. It is usually divided into structural connectivity, which maps the physical wiring of neural pathways, and functional connectivity, which measures how activity in distant regions becomes correlated over time. More recently, effective connectivity aims to uncover the direction and causal influence that one region exerts on another.

Structural connections are mapped with techniques such as diffusion MRI, which estimates the orientation of white matter fibers. Functional connectivity is often studied with functional MRI, electroencephalography or magnetoencephalography by examining synchronized fluctuations in neural signals. Graph theory provides a common mathematical framework, treating brain regions as nodes and their interactions as edges. This approach reveals global properties such as hubs, modular communities and small world organization that balance efficient communication with specialized processing.

Connectivity patterns change across development, aging and disease. Typical maturation involves strengthening long range connections and refining network efficiency, while many neurological and psychiatric conditions show disrupted hubs, altered modular structure or abnormal synchronization. Individual differences in connectivity are increasingly linked to cognitive abilities and behavioral traits.

Researchers also study how connectivity reorganizes dynamically over seconds to minutes, rather than assuming a fixed network. Methods that track time varying patterns reveal that the brain shifts among recurring connectivity states during rest and tasks. Future work aims to integrate structural, functional and effective connectivity into multiscale models, combine them with genetic and behavioral data, and apply them to personalized diagnosis and interventions.