scholarly journals Intrinsic Functional Connectivity Networks in Healthy Elderly Subjects: A Multiparametric Approach with Structural Connectivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Martin Gorges ◽  
Hans-Peter Müller ◽  
Albert C. Ludolph ◽  
Volker Rasche ◽  
Jan Kassubek

Intrinsic functional connectivity magnetic resonance imaging (iFCMRI) provides an encouraging approach for mapping large-scale intrinsic connectivity networks (ICNs) in the “resting” brain. Structural connections as measured by diffusion tensor imaging (DTI) are a major constraint on the identified ICNs. This study aimed at the combined investigation of ten well-defined ICNs in healthy elderly subjects at single subject level as well as at the group level, together with the underlying structural connectivity. IFCMRI and DTI data were acquired in twelve subjects (68 ± 7 years) at a 3T scanner and were studied using thetensor imaging and fiber trackingsoftware package. The seed-based iFCMRI analysis approach was comprehensively performed with DTI analysis, following standardized procedures including an 8-step processing of iFCMRI data. Our findings demonstrated robust ICNs at the single subject level and conclusive brain maps at the group level in the healthy elderly sample, supported by the complementary fiber tractography. The findings demonstrated here provide a methodological framework for future comparisons of pathological (e.g., neurodegenerative) conditions with healthy controls on the basis of multiparametric functional connectivity mapping.

2021 ◽  
Vol 15 ◽  
Author(s):  
Xinchun Zhou ◽  
Ningning Ma ◽  
Benseng Song ◽  
Zhixi Wu ◽  
Guangyao Liu ◽  
...  

The optimal organization for functional segregation and integration in brain is made evident by the “small-world” feature of functional connectivity (FC) networks and is further supported by the loss of this feature that has been described in many types of brain disease. However, it remains unknown how such optimally organized FC networks arise from the brain's structural constrains. On the other hand, an emerging literature suggests that brain function may be supported by critical neural dynamics, which is believed to facilitate information processing in brain. Though previous investigations have shown that the critical dynamics plays an important role in understanding the relation between whole brain structural connectivity and functional connectivity, it is not clear if the critical dynamics could be responsible for the optimal FC network configuration in human brains. Here, we show that the long-range temporal correlations (LRTCs) in the resting state fMRI blood-oxygen-level-dependent (BOLD) signals are significantly correlated with the topological matrices of the FC brain network. Using structure-dynamics-function modeling approach that incorporates diffusion tensor imaging (DTI) data and simple cellular automata dynamics, we showed that the critical dynamics could optimize the whole brain FC network organization by, e.g., maximizing the clustering coefficient while minimizing the characteristic path length. We also demonstrated with a more detailed excitation-inhibition neuronal network model that loss of local excitation-inhibition (E/I) balance causes failure of critical dynamics, therefore disrupting the optimal FC network organization. The results highlighted the crucial role of the critical dynamics in forming an optimal organization of FC networks in the brain and have potential application to the understanding and modeling of abnormal FC configurations in neuropsychiatric disorders.


NeuroImage ◽  
2014 ◽  
Vol 101 ◽  
pp. 390-403 ◽  
Author(s):  
Jorge Jovicich ◽  
Moira Marizzoni ◽  
Beatriz Bosch ◽  
David Bartrés-Faz ◽  
Jennifer Arnold ◽  
...  

Author(s):  
Miriam Punzi ◽  
Tommaso Gili ◽  
Laura Petrosini ◽  
Carlo Caltagirone ◽  
Gianfranco Spalletta ◽  
...  

Diabetes ◽  
1982 ◽  
Vol 31 (3) ◽  
pp. 203-211 ◽  
Author(s):  
J. J. Robert ◽  
J. C. Cummins ◽  
R. R. Wolfe ◽  
M. Durkot ◽  
D. E. Matthews ◽  
...  

2020 ◽  
Vol 11 ◽  
Author(s):  
Giulia Fusi ◽  
Elena Ferrari ◽  
Marina Zanetti ◽  
Maura Crepaldi ◽  
Carol Bersanini ◽  
...  

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