The networked architecture of the brain promotes synchrony among neuronal populations
and the emergence of coherent dynamics. These communication patterns can be …

Introduction Computational models are often used to assess how functional connectivity
(FC) patterns emerge from neuronal population dynamics and anatomical connections in the …

Resting-state functional connectivity is typically modeled as the correlation structure of
whole-brain regional activity. It is studied widely, both to gain insight into the brain's intrinsic …

Mapping individual differences in brain function has been hampered by poor reliability as
well as limited interpretability. Leveraging patterns of brain‐wide functional connectivity (FC) …

Functional interactions between brain regions can be viewed as a network, empowering
neuroscientists to leverage network science to investigate distributed brain function …

This special issue attempts to identify novel methodology which bolsters the study of
dynamic Functional Connectivity (dFC). There is still much debate as to whether estimates of …

Functional connectivity (FC) refers to the statistical dependencies between activity of distinct
brain areas. To study temporal fluctuations in FC within the duration of a functional magnetic …

Resting-state functional connectivity is used throughout neuroscience to study brain
organization and to generate biomarkers of development, disease, and cognition. The …

Most previous work on dynamic functional connectivity (dFC) has focused on analyzing
temporal traits of functional connectivity (similar coupling patterns at different timepoints) …

Correlations are a basic object of analysis across neuroscience, but multivariate patterns of
correlations can be difficult to interpret. For example, correlations are fundamental to …