scholarly journals Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain

2009 ◽  
Vol 30 (10) ◽  
pp. 3127-3141 ◽  
Author(s):  
Martijn P. van den Heuvel ◽  
René C.W. Mandl ◽  
René S. Kahn ◽  
Hilleke E. Hulshoff Pol
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Structural Connectivity ◽  
Resting State Networks

scholarly journals Neuronal dynamics enable the functional differentiation of resting state networks in the human brain

2018 ◽  
Vol 40 (5) ◽  
pp. 1445-1457 ◽  
Author(s):  
Marco Marino ◽  
Quanying Liu ◽  
Jessica Samogin ◽  
Franca Tecchio ◽  
Carlo Cottone ◽  
...  
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Functional Differentiation ◽  
Resting State Networks ◽  
Neuronal Dynamics

scholarly journals Psilocybin exerts distinct effects on resting state networks associated with serotonin and dopamine in mice

2019 ◽  
Author(s):  
Joanes Grandjean ◽  
David Buehlmann ◽  
Michaela Buerge ◽  
Hannes Sigrist ◽  
Erich Seifritz ◽  
...  
Keyword(s):  
Resting State ◽  
Depressive Disorders ◽  
Human Subjects ◽  
Expression Patterns ◽  
Structural Connectivity ◽  
Resting State Fmri ◽  
Resting State Networks ◽  
Dual Regression ◽  
Underlying Mechanisms ◽  
Molecular Expression

AbstractHallucinogenic agents have been proposed as potent antidepressants; this includes the serotonin (5-HT) receptor 2A agonist psilocybin. In human subjects, psilocybin alters functional connectivity (FC) within the default-mode network (DMN), a constellation of inter-connected regions that is involved in self-reference and displays altered FC in depressive disorders. In this study we investigated the effects of psilocybin on FC in the analogue of the DMN in mouse, with a view to establishing an experimental animal model to investigate underlying mechanisms. Psilocybin effects were investigated in lightly-anaesthetized mice using resting-state fMRI. Dual-regression analysis identified reduced FC within the ventral striatum in psilocybin-relative to vehicle-treated mice. Refinement of the analysis using spatial references derived from both gene expression maps and viral tracer projection fields revealed two distinct effects of psilocybin: it increased FC between 5-HT-associated networks and elements of the murine DMN, thalamus, and midbrain; it decreased FC within dopamine (DA)-associated striatal networks. These results suggest that interaction between 5-HT- and DA-regulated neural networks contributes to the neural and therefore psychological effects of psilocybin. Furthermore, they highlight how information on molecular expression patterns and structural connectivity can assist in the interpretation of pharmaco-fMRI findings.

scholarly journals Emergence of resting state networks in the preterm human brain

2010 ◽  
Vol 107 (46) ◽  
pp. 20015-20020 ◽  
Author(s):  
V. Doria ◽  
C. F. Beckmann ◽  
T. Arichi ◽  
N. Merchant ◽  
M. Groppo ◽  
...  
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Resting State Networks

scholarly journals Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation

NeuroImage ◽  
2018 ◽  
Vol 179 ◽  
pp. 570-581 ◽  
Author(s):  
Silvia Tommasin ◽  
Daniele Mascali ◽  
Marta Moraschi ◽  
Tommaso Gili ◽  
Ibrahim Eid Hassan ◽  
...  
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Resting State Networks ◽  
Scale Invariant

Alterations of resting state networks and structural connectivity in relation to the prefrontal and anterior cingulate cortices in late prematurity

Neuroreport ◽  
2015 ◽  
Vol 26 (1) ◽  
pp. 22-26 ◽  
Author(s):  
Andrew J. Degnan ◽  
Jessica L. Wisnowski ◽  
SoYoung Choi ◽  
Rafael Ceschin ◽  
Chitresh Bhushan ◽  
...  
Keyword(s):  
Resting State ◽  
Structural Connectivity ◽  
Anterior Cingulate ◽  
Resting State Networks

scholarly journals The dynamic modular fingerprints of the human brain at rest

2020 ◽  
Author(s):  
Aya Kabbara ◽  
Veronique Paban ◽  
Mahmoud Hassan
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Brain Networks ◽  
Brain Network ◽  
Strongly Correlated ◽  
Resting State Networks ◽  
Modular Network ◽  
Track Dynamics ◽  
Network Pattern ◽  
Over Time

AbstractThe human brain is a dynamic modular network that can be decomposed into a set of modules and its activity changes permanently over time. At rest, several brain networks, known as Resting-State Networks (RSNs), emerge and cross-communicate even at sub-second temporal scale. Here, we seek to decipher the fast reshaping in spontaneous brain modularity and its relationship to RSNs. We use Electro/Magneto-Encephalography (EEG/MEG) to track dynamics of modular brain networks, in three independent datasets (N= 568) of healthy subjects at rest. We show the presence of striking spatiotemporal network pattern consistent over participants. We also show that some RSNs, such as default mode network and temporal network, are not necessary ‘unified units’ but rather can be divided into multiple sub-networks over time. Using the resting state questionnaire, our results revealed also that brain network dynamics are strongly correlated to mental imagery at rest. These findings add new perspectives to brain dynamic analysis and highlight the importance of tracking fast reconfiguration of electrophysiological networks at rest.

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