Small-world networks and disturbed functional connectivity in schizophrenia

2006 ◽  
Vol 87 (1-3) ◽  
pp. 60-66 ◽  
Author(s):  
Sifis Micheloyannis ◽  
Ellie Pachou ◽  
Cornelis Jan Stam ◽  
Michael Breakspear ◽  
Panagiotis Bitsios ◽  
...  
2006 ◽  
Vol 17 (1) ◽  
pp. 92-99 ◽  
Author(s):  
C. Stam ◽  
B. Jones ◽  
G Nolte ◽  
M Breakspear ◽  
P. Scheltens

2021 ◽  
Vol 15 ◽  
Author(s):  
Mohamed Khateb ◽  
Jackie Schiller ◽  
Yitzhak Schiller

Synchronized activity plays an important role in sensory coding and memory and is a hallmark of functional network connectivity. However, the effect of sensory activation on synchronization and cortical functional connectivity is largely unknown. In this study, we investigated the effect of whisker activation on synchronization and functional connectivity of the primary (wS1) and secondary (wS2) whisker somatosensory cortices at the single-cell level. The results showed that during the spontaneous pre-stimulus state, neurons tended to be functionally connected with nearby neurons which shared similar tuning characteristics. Whisker activation using either ramp-and-hold stimulation or artificial whisking against sandpaper has significantly reduced the average overall pairwise synchronization and functional connectivity within the wS1 barrel and wS2 cortices. Whisker stimulation disconnected approximately a third of neuronal pairs that were functionally connected during the unstimulated state. Nearby neurons with congruent tuning properties were more likely to remain functionally connected during whisker activation. The findings of this study indicated that cortical somatosensory networks are organized in non-random small world networks composed of neurons sharing relatively similar tuning properties. Sensory whisker activation intensifies these properties and further subdivides the cortical network into smaller more functionally uniform subnetworks, which possibly serve to increase the computational capacity of the network.


PLoS ONE ◽  
2010 ◽  
Vol 5 (11) ◽  
pp. e13788 ◽  
Author(s):  
Ernesto J. Sanz-Arigita ◽  
Menno M. Schoonheim ◽  
Jessica S. Damoiseaux ◽  
Serge A. R. B. Rombouts ◽  
Erik Maris ◽  
...  

2008 ◽  
Vol 29 (12) ◽  
pp. 1368-1378 ◽  
Author(s):  
Dirk J. A. Smit ◽  
Cornelis J. Stam ◽  
Danielle Posthuma ◽  
Dorret I. Boomsma ◽  
Eco J. C. de Geus

Author(s):  
Stefan Thurner ◽  
Rudolf Hanel ◽  
Peter Klimekl

Understanding the interactions between the components of a system is key to understanding it. In complex systems, interactions are usually not uniform, not isotropic and not homogeneous: each interaction can be specific between elements.Networks are a tool for keeping track of who is interacting with whom, at what strength, when, and in what way. Networks are essential for understanding of the co-evolution and phase diagrams of complex systems. Here we provide a self-contained introduction to the field of network science. We introduce ways of representing and handle networks mathematically and introduce the basic vocabulary and definitions. The notions of random- and complex networks are reviewed as well as the notions of small world networks, simple preferentially grown networks, community detection, and generalized multilayer networks.


2021 ◽  
Vol 144 ◽  
pp. 110745
Author(s):  
Ankit Mishra ◽  
Jayendra N. Bandyopadhyay ◽  
Sarika Jalan

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