… Combining a whole-brain connectivity approach with directional effective connectivity analysis,
… Overall, the localizers served to constrain our analyses and interpretations by identifying …

… Using machine learning, we demonstrate that patterns of resting state fMRI connectivity (ie
the degree of synchronous BOLD activity across multiple cortical areas in the absence of …

… we are able to achieve successful results employing widely … translated into constraints in the
bundle dissection process which … These techniques of using anatomical constraints to define …

… While the configuration model is a good general null, is it an appropriate null generator for …
So far, each of these models preserve select features of a spatially constrained brain network …

… constrained Kalman filter (gKF) algorithm is proposed to construct dynamic effective connectivity
(… In the traditional connectivity modeling methods, brain connectivity is defined as the …

… develop over weeks, months, years, and even decades owing to environmental and
learning-induced plasticity mechanisms. A good example is literacy, which alters brain connections …

… that structural brain connectivity constrains the influence of functional connectivity on the …
is the measure of efficient information propagation across the whole network. It represents …

… domain metrics of effective connectivity based on vector autoregressive model and partial
directed … To demonstrate the effectiveness of specially designed CNN kernels for extracting …

… the scales at which a system can effectively be considered a network. At this scale, which …
geometrical and topological constraints on how brain function is projected onto brain anatomy (…

… BCI and NF by causal constraint. The proposed method based … connectivity can provide a
description of the brain network … effective connectivity. The interactions of spatially separated …