Brain networks and their relevance for stroke rehabilitation.

TL;DR: This state-of-the-art review makes clear the value of networks and brain models for understanding symptoms and signs of disease and can serve as a foundation for further work.

TL;DR: This review describes the results achieved by existing neurotechnologies and highlights their current limitations, and proposes new approaches for the effective use of neuroTechnologies in stroke survivors, as well as in people with other neurological disorders.

TL;DR: Preliminary evidence suggests that the lesioned brain flexibly (re-)distributes its computational capacities to functionally reorganize impaired brain functions, using a similar set of mechanisms to achieve adaptive network plasticity compared to short-term reorganization observed in the healthy brain after rTMS.

TL;DR: It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.

TL;DR: It is suggested that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain, featuring the presence of anticorrelated networks in the absence of overt task performance.

TL;DR: The results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements.

TL;DR: This study constitutes, to the knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network.