As the size of brain imaging data such as fMRI grows explosively, it provides us with
unprecedented and abundant information about the brain. How to reduce the size of fMRI …

High spatial resolution in functional magnetic resonance imaging improves its sensitivity to
brain activation signals by reducing partial volume effects. However, the long acquisition …

Introduction Independent component analysis (ICA) has been extensively used for reducing
task‐free BOLD fMRI recordings into spatial maps and their associated time‐courses. The …

There is a growing conviction that the understanding of the brain function can come through
a deeper knowledge of the network connectivity between different brain areas. Resting state …

Functional magnetic resonance imaging (fMRI) has recently proved its utility in studying
brain large-scale networks through fluctuations in resting-state data. To process such rest …

Ongoing fluctuations of brain activity measured by functional magnetic resonance imaging
(fMRI) provide a novel window onto the organizational principles of brain function. Advances …

Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-
linear-model-based analyses (GLM). Their findings are often inconsistent across different …

There is increasing use of functional imaging data to understand the macro-connectome of
the human brain. Of particular interest is the structure and function of intrinsic networks …

Functional magnetic resonance imaging (fMRI) has become the most popular method for
imaging brain function. Handbook of Functional MRI Data Analysis provides a …

Numerous neuroimaging studies have identified various brain networks using task-free
analyses. While these networks undoubtedly support higher cognition, their precise …