scholarly journals Functional Connectivity in Brain Networks Underlying Cognitive Control in Chronic Cannabis Users

2012 ◽  
Vol 37 (8) ◽  
pp. 1923-1933 ◽  
Author(s):  
Ian H Harding ◽  
Nadia Solowij ◽  
Ben J Harrison ◽  
Michael Takagi ◽  
Valentina Lorenzetti ◽  
...  
2021 ◽  
Author(s):  
Xiang Xiao ◽  
Christopher Joseph Hammond ◽  
Betty Jo Salmeron ◽  
Hong Gu ◽  
Tianye Zhai ◽  
...  

The search for psychiatric biomarkers has remained elusive, in part, due to high comorbidity, low specificity, and poor concordance between neurobiological abnormalities and existing diagnostic categories. Developmental shifts in symptom expression and brain function across the lifespan further complicate biomarker identification. Recent studies suggest that focusing on cognition may be a pathway forward: Cognitive dysfunction is a common feature across psychiatric disorders. Individual differences in cognition may reflect variability in the connectivity of underlying neurocognitive brain networks, and predict psychopathology at different developmental periods. In the present study we identified brain-based dimensions of general cognitive capacity and psychopathology using sparse canonical correlation analysis (sCCA) in a sample of 7,383 preadolescents from the Adolescent Brian Cognitive Development (ABCD) study. This analysis revealed correlated patterns of functional connectivity with cognitive control capacity and psychopathology. Specifically, the results identified a single connectome-based latent brain variate that was positively correlated with performance on cognitive measures across domains and negatively correlated with parent-reported psychopathology across diagnoses and domains. Functional connectivity loadings for the brain variate were across distributed cortical and subcortical brain networks and a dose-dependent relationship with psychopathology based upon the cumulative number of psychiatric diagnoses was observed. These findings provide preliminary evidence for a connectome-based biomarker that indexes individual differences in cognitive control and predicts transdiagnostic psychopathology in a dose-dependent fashion.


2017 ◽  
Vol 39 (2) ◽  
pp. 811-821 ◽  
Author(s):  
Roger E. Beaty ◽  
Qunlin Chen ◽  
Alexander P. Christensen ◽  
Jiang Qiu ◽  
Paul J. Silvia ◽  
...  

2020 ◽  
Vol 109 (10) ◽  
pp. 2105-2111
Author(s):  
Dror Kraus ◽  
Jennifer Vannest ◽  
Ravindra Arya ◽  
John S. Hutton ◽  
James L. Leach ◽  
...  

2018 ◽  
Vol 29 (10) ◽  
pp. 4208-4222 ◽  
Author(s):  
Yuehua Xu ◽  
Miao Cao ◽  
Xuhong Liao ◽  
Mingrui Xia ◽  
Xindi Wang ◽  
...  

Abstract Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31–42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.


2015 ◽  
Vol 6 ◽  
Author(s):  
Roser Sala-Llonch ◽  
David Bartrés-Faz ◽  
Carme Junqué

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Nicola De Pisapia ◽  
Francesca Bacci ◽  
Danielle Parrott ◽  
David Melcher

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