P2-070: Increased randomness of functional brain networks in Alzheimer's disease: ‘small-world' network analysis of non-linear functional connectivity

2008 ◽  
Vol 4 ◽  
pp. T387-T388
Author(s):  
Ernesto J. Sanz-Arigita ◽  
Menno M. Schoonheim ◽  
Jeske S. Damoiseaux ◽  
Serge A.R.B. Rombouts ◽  
Frederik Barkhof ◽  
...  
2008 ◽  
Vol 4 ◽  
pp. T90-T91
Author(s):  
Ernesto J. Sanz-Arigita ◽  
Menno M. Schoonheim ◽  
Jeske S. Damoiseaux ◽  
Serge A.R.B. Rombouts ◽  
Frederik Barkhof ◽  
...  

2019 ◽  
Author(s):  
Aya Kabbara ◽  
Veronique Paban ◽  
Arnaud Weill ◽  
Julien Modolo ◽  
Mahmoud Hassan

AbstractIntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks.ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits.MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated.ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks.ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.


2008 ◽  
Vol 102 (1-3) ◽  
pp. 9 ◽  
Author(s):  
Kelvin Lim ◽  
Bryon Mueller ◽  
Jazmin Camchong ◽  
Chris Bell

2015 ◽  
Vol 2 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Zhijun Yao ◽  
Bin Hu ◽  
Yuanwei Xie ◽  
Philip Moore ◽  
Jiaxiang Zheng

NeuroImage ◽  
2009 ◽  
Vol 47 ◽  
pp. S168 ◽  
Author(s):  
E.J. Sanz-Arigita ◽  
M.M. Schoonheim ◽  
J.S. Damoiseaux ◽  
S.A. Rombouts ◽  
F. Barkhof ◽  
...  

2021 ◽  
Author(s):  
Alireza Fathian ◽  
Yousef Jamali ◽  
Mohammad Reza Raoufy

Abstract Alzheimer’s disease (AD) is a progressive disorder associated with cognitive dysfunction that alters the brain’s functional connectivity. Assessing these alterations has become a topic of increasing interest. However, a few studies have examined different stages of AD from a complex network perspective that cover different topological scales. This study analyzed the trend of functional connectivity alterations from a cognitively normal (CN) state through early and late mild cognitive impairment (EMCI and LMCI) and to Alzheimer’s disease. The analyses had been done at the local (hubs and activated links and areas), meso (clustering, assortativity, and rich-club), and global (small-world, small-worldness, and efficiency) topological scales. The results showed that the trends of changes in the topological architecture of the functional brain network were not entirely proportional to the AD progression, and these trends behaved differently at the earliest stage of the disease, i.e., EMCI. Further, it has been indicated that the diseased groups engaged somatomotor, frontoparietal, and default mode modules compared to the CN group. The diseased groups also shifted the functional network towards more random architecture. In the end, The methods introduced in this paper enable us to gain an extensive understanding of the pathological changes of the AD process.


2021 ◽  
Vol 11 (11) ◽  
pp. 1535
Author(s):  
Hui Zhang ◽  
Edward S. Hui ◽  
Peng Cao ◽  
Henry K. F. Mak

Previous studies have demonstrated that the accumulation of amyloid-β (Aβ) pathologies has distinctive stage-specific effects on the structural and functional brain networks along the Alzheimer’s disease (AD) continuum. A more comprehensive account of both types of brain network may provide a better characterization of the stage-specific effects of Aβ pathologies. A potential candidate for this joint characterization is the coupling between the structural and functional brain networks (SC-FC coupling). We therefore investigated the effect of Aβ accumulation on global SC-FC coupling in patients with mild cognitive impairment (MCI), AD, and healthy controls. Patients with MCI were dichotomized according to their level of Aβ pathology seen in 18F-flutemetamol PET-CT scans—namely, Aβ-negative and Aβ-positive. Our results show that there was no difference in global SC-FC coupling between different cohorts. During the prodromal AD stage, there was a significant negative correlation between the level of Aβ pathology and the global SC-FC coupling of MCI patients with positive Aβ, but no significant correlation for MCI patients with negative Aβ. During the AD dementia stage, the correlation between Aβ pathology and global SC-FC coupling in patients with AD was positive. Our results suggest that Aβ pathology has distinctive stage-specific effects on global coupling between the structural and functional brain networks along the AD continuum.


2017 ◽  
Author(s):  
Annika C. Linke ◽  
Conor Wild ◽  
Leire Zubiaurre-Elorza ◽  
Charlotte Herzmann ◽  
Hester Duffy ◽  
...  

AbstractObjectiveFunctional connectivity magnetic resonance imaging (fcMRI) of neonates with perinatal brain injury could improve prediction of motor impairment before symptoms manifest, and establish how early brain organization relates to subsequent development. Methods: This cohort study is the first to describe and quantitatively assess functional brain networks and their relation to later motor skills in neonates with a diverse range of perinatal brain injuries. Infants (n=65, included in final analyses: n=53) were recruited from the neonatal intensive care unit (NICU) and were stratified based on their age at birth (premature vs. term), and on whether neuropathology was diagnosed from structural MRI. Functional brain networks and a measure of disruption to functional connectivity were obtained from 14 minutes of fcMRI acquired during natural sleep at term-equivalent age.ResultsDisruption to connectivity of the somatomotor and frontoparietal executive networks predicted motor impairment at 4 and 8 months. This disruption in functional connectivity was not found to be driven by differences between clinical groups, or by any of the specific measures we captured to describe the clinical course.ConclusionfcMRI was predictive over and above other clinical measures available at discharge from the NICU, including structural MRI. Motor learning was affected by disruption to somatomotor networks, but also frontoparietal executive networks, which supports the functional importance of these networks in early development. Disruption to these two networks might be best addressed by distinct intervention strategies.


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