DYNAMICS OF INTRINSIC CONNECTIVITY NETWORKS IN SCHIZOPHRENIA

2014 ◽  
Vol 153 ◽  
pp. S12-S13
Author(s):  
Vince Calhoun ◽  
Dan Mathalon ◽  
Theo van Erp ◽  
Sarah J. McEwen ◽  
Adrian Preda ◽  
...  
2021 ◽  
Author(s):  
Jonathan S Jones ◽  
Duncan Astle ◽  

Functional connectivity within and between Intrinsic Connectivity Networks (ICNs) transforms over development and supports high order cognitive functions. But how variable is this process, and does it diverge with altered cognitive developmental trajectories? We investigated age-related changes in integration and segregation within and between ICNs in neurodevelopmentally at-risk children, identified by practitioners as experiencing cognitive difficulties in attention, learning, language, or memory. In our analysis we used performance on a battery of 10 cognitive tasks, alongside resting-state functional Magnetic Resonance Imaging in 175 at-risk children and 62 comparison children aged 5-16. We observed significant age-by-group interactions in functional connectivity between two network pairs. Integration between the ventral attention and visual networks and segregation of the limbic and fronto-parietal networks increased with age in our comparison sample, relative to at-risk children. Furthermore, functional connectivity between the ventral attention and visual networks in comparison children significantly mediated age-related improvements in executive function, compared to at-risk children. We conclude that integration between ICNs show divergent neurodevelopmental trends in the broad population of children experiencing cognitive difficulties, and that these differences in functional brain organisation may partly explain the pervasive cognitive difficulties within this group over childhood and adolescence.


NeuroImage ◽  
2009 ◽  
Vol 47 ◽  
pp. S152 ◽  
Author(s):  
C Habas ◽  
N Kamdar ◽  
D Nguyen ◽  
C Keller ◽  
CF Beckmann ◽  
...  

2018 ◽  
Vol 44 (6) ◽  
pp. 1332-1340 ◽  
Author(s):  
Simon Anhøj ◽  
Mette Ødegaard Nielsen ◽  
Maria Høj Jensen ◽  
Kristin Ford ◽  
Birgitte Fagerlund ◽  
...  

2011 ◽  
Vol 23 (12) ◽  
pp. 4022-4037 ◽  
Author(s):  
Angela R. Laird ◽  
P. Mickle Fox ◽  
Simon B. Eickhoff ◽  
Jessica A. Turner ◽  
Kimberly L. Ray ◽  
...  

An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific mental functions. However, it was recently demonstrated that similar brain networks can be extracted from resting state data and data extracted from thousands of task-based neuroimaging experiments archived in the BrainMap database. Here, we present a full functional explication of these intrinsic connectivity networks at a standard low order decomposition using a neuroinformatics approach based on the BrainMap behavioral taxonomy as well as a stratified, data-driven ordering of cognitive processes. Our results serve as a resource for functional interpretations of brain networks in resting state studies and future investigations into mental operations and the tasks that drive them.


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