MEG offers dynamic and spectral resolution for resting-state connectivity which is
unavailable in fMRI. However, there are a wide range of available network estimation …

The human brain can be divided into multiple areas, each responsible for different aspects
of behaviour. Healthy brain function relies upon efficient connectivity between these areas …

Fluctuations in functional interactions between brain regions typically occur at the
millisecond time scale. Conventional connectivity metrics are not adequately time-resolved …

Connectivity studies using resting-state functional magnetic resonance imaging are
increasingly pooling data acquired at multiple sites. While this may allow investigators to …

Functional connectivity (FC) between brain regions is thought to be central to the way in
which the brain processes information. Abnormal connectivity is thought to be implicated in a …

Determining the dynamics of functional connectivity is critical for understanding the brain.
Recent functional magnetic resonance imaging (fMRI) studies demonstrate that measuring …

A number of recent studies have begun to show the promise of magnetoencephalography
(MEG) as a means to non-invasively measure functional connectivity within distributed …

Source-space coherence analysis has become a popular method to estimate functional
connectivity based on MEG/EEG. Source-space analysis involves solving the inverse …

Network properties can be estimated using functional connectivity MRI (fcMRI). However,
regional variation of the fMRI signal causes systematic biases in network estimates including …

Introduction Studies using functional connectivity and network analyses based on
magnetoencephalography (MEG) with source localization are rapidly emerging in …