Sentence examples for global brain network from inspiring English sources

In a very recent report applying graph analysis (a whole-brain network analysis technique; see below), Supekar et al. describe disruptions in local network connectivity in AD but no change in the connectedness of the global brain network [17].

Global brain network segregation was assessed using normalized clustering coefficient and modularity.

Furthermore, it has been proposed that the structure of the global brain network enhances the interaction between the segregation and integration of functionally specialized areas in the brain [ 83].

It has been demonstrated that global brain network connectivity presents a small-world organization that is far from random, characterized by a high level of local connections between nodes and a very short path length which configure the so-called "hub" and a low presence of long connections between hubs; this network organization elevates efficiency and reduces substantially redundancy [ 44].

This approach aims to reduce pathologically enhanced neural synchrony within the primary auditory cortices which, in turn, results in a net decrease in effective connectivity across the global brain network involved in tinnitus perception [ 9, 14] along with a decrease of tinnitus-related abnormal cross-frequency coupling [ 31].

The analysis of the global brain networks exhibited a small-world-like topology (Table S3, S4) as expected.

Here, we combined optogenetics, fMRI, electrophysiology, and video-EEG monitoring to characterize the central thalamus-driven global brain networks responsible for switching brain state.

To overcome such obstacles and dissect the dynamic influence of central thalamus on global brain networks, we combined targeted optogenetic control of excitatory relay neurons within central thalamus with whole-brain fMRI readouts, EEG, and single-unit recordings.

These findings strongly implicate that the average properties of the global brain functional networks can not be representative of individual module-specific properties because each module in the network contains a specific topological structure.

Three of them are about what Mr. Arthur has dubbed the second economy: the rise of what Mr. Milner calls "the Internet of things," or the machine-to-machine economy; the growing power of artificial intelligence; and the emergence of a "global brain," which is the network of all of the people and the machines in the world and their connections to one another.

However, targeted attack on high degree nodes caused the global efficiency of the brain network to deteriorate more rapidly than the efficiency of a random graph (Fig. 2A).