732. Individual Differences in the Healthy Population Helps Identify Schizophrenia-Specific Disruptions in Resting State Networks Related to Cognitive Control

2017 ◽  
Vol 81 (10) ◽  
pp. S296-S297
Author(s):  
Amanda Rodrigue ◽  
David J Schaeffer ◽  
Brett A Clementz ◽  
Jennifer E McDowell
NeuroImage ◽  
2015 ◽  
Vol 104 ◽  
pp. 69-78 ◽  
Author(s):  
Andrew E. Reineberg ◽  
Jessica R. Andrews-Hanna ◽  
Brendan E. Depue ◽  
Naomi P. Friedman ◽  
Marie T. Banich

2019 ◽  
Author(s):  
Thomas H. Alderson ◽  
Arun L.W. Bokde ◽  
J.A.Scott. Kelso ◽  
Liam Maguire ◽  
Damien Coyle

AbstractDespite resting state networks being associated with a variety of cognitive abilities, it remains unclear how these local areas act in concert to express particular cognitive operations. Theoretical and empirical accounts indicate that large-scale resting state networks reconcile dual tendencies toward integration and segregation by operating in a metastable regime of their coordination dynamics. One proposal is that metastability confers important behavioural qualities by dynamically binding distributed local areas into large-scale neurocognitive entities. We tested this hypothesis by analysing fMRI data in a large cohort of healthy individuals (N=566) and comparing the metastability of the brain’s large-scale resting network architecture at rest and during the performance of several tasks. Task-based reasoning was principally characterised by high metastability in cognitive control networks and low metastability in sensory processing areas. Although metastability between resting state networks increased during task performance, cognitive ability was more closely linked to spontaneous activity. High metastability in the intrinsic connectivity of cognitive control networks was linked to novel problem solving (or fluid intelligence) but was less important in tasks relying on prior experience (or crystallised intelligence). Crucially, subjects with resting architectures similar or ‘pre-configured’ to a task-general arrangement demonstrated superior cognitive performance. Taken together, our findings support a critical linkage between the spontaneous metastability of the large-scale networks of the cerebral cortex and cognition.


Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 2092-P
Author(s):  
LETICIA ESPOSITO SEWAYBRICKER ◽  
SUSAN J. MELHORN ◽  
MARY K. ASKREN ◽  
MARY WEBB ◽  
VIDHI TYAGI ◽  
...  

2020 ◽  
Vol 10 (9) ◽  
Author(s):  
Xiang‐Xin Xing ◽  
Xu‐Yun Hua ◽  
Mou‐Xiong Zheng ◽  
Zhen‐Zhen Ma ◽  
Bei‐Bei Huo ◽  
...  

2021 ◽  
pp. 1-15
Author(s):  
Bianca P. Acevedo ◽  
Tyler Santander ◽  
Robert Marhenke ◽  
Arthur Aron ◽  
Elaine Aron

<b><i>Background:</i></b> Sensory processing sensitivity (SPS) is a biologically based temperament trait associated with enhanced awareness and responsivity to environmental and social stimuli. Individuals with high SPS are more affected by their environments, which may result in overarousal, cognitive depletion, and fatigue. <b><i>Method:</i></b> We examined individual differences in resting-state (rs) brain connectivity (using functional MRI) as a function of SPS among a group of adults (<i>M</i> age = 66.13 ± 11.44 years) immediately after they completed a social affective “empathy” task. SPS was measured with the Highly Sensitive Person (HSP) Scale and correlated with rs brain connectivity. <b><i>Results:</i></b> Results showed enhanced rs brain connectivity within the ventral attention, dorsal attention, and limbic networks as a function of greater SPS. Region of interest analyses showed increased rs brain connectivity between the hippocampus and the precuneus (implicated in episodic memory); while weaker connectivity was shown between the amygdala and the periaqueductal gray (important for anxiety), and the hippocampus and insula (implicated in habitual cognitive processing). <b><i>Conclusions:</i></b> The present study showed that SPS is associated with rs brain connectivity implicated in attentional control, consolidation of memory, physiological homeostasis, and deliberative cognition. These results support theories proposing “depth of processing” as a central feature of SPS and highlight the neural processes underlying this cardinal feature of the trait.


2020 ◽  
Vol 27 ◽  
pp. 102336
Author(s):  
Margherita Carboni ◽  
Pia De Stefano ◽  
Bernd J. Vorderwülbecke ◽  
Sebastien Tourbier ◽  
Emeline Mullier ◽  
...  

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