Identification of Resting State Networks Involved in Executive Function

Abstract

The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function.

Exploring distinct default mode and semantic networks using a systematic ICA approach

“…This may be advantageous compared to assessing the activity of constituent regions (e.g., Laird et al., 2009 ) due to the involvement of regions in multiple networks. Whilst the combination of networks involved in an activity map can be estimated using spatial linear regression ( Connolly et al., 2016 ), this may lack precision compared to splitting the task data into distinct components and does not allow full assessment of the cognitive signature of each network involved. Comparison of the spatial extent of a network to activity maps is inadequate to determine its function.…”

Gait Speed and Gait Variability Are Associated with Different Functional Brain Networks

“…Executive function is an umbrella term for a series of cognitive processes that give rise to goal-oriented behavior such as response inhibition, shifting of attention and working memory ( Testa et al, 2012 ; Reineberg et al, 2015 ; Reineberg and Banich, 2016 ). Each of these subcomponents of executive function is governed by specific brain regions within and beyond the frontoparietal control network ( Miyake et al, 2000 ; Miller and Cohen, 2001 ; Alvarez and Emory, 2006 ; Reineberg et al, 2015 ; Connolly et al, 2016 ; Reineberg and Banich, 2016 ). Our observation that those with faster gait speed have stronger functional connectivity within the frontoparietal control network—and particularly the middle frontal gyri—suggests that this widely assessed characteristic of locomotor control depends upon the integrity of communication within a collection of brain regions linked to executive function.…”

“…The relationships between metrics of gait and brain function during walking have been challenging to establish primarily because current neuroimaging tools are sensitive to head and body movements ( Hamacher et al, 2015 ; Wittenberg et al, 2017 ). Alternatively, resting-state functional magnetic resonance imaging (rs-fMRI) is a powerful tool that enables estimation of functional organization within the brain ( Biswal et al, 1995 ; van den Heuvel and Pol, 2010 ) and subsequently, determination of how this organization is linked with function and behavior ( Lee et al, 2013 ; Cruz-Gómez et al, 2014 ; Connolly et al, 2016 ). Rs-fMRI can be used to identify highly replicable functional networks ( Fox and Raichle, 2007 ; Yeo et al, 2011 ) and to quantify the patterns of functional connectivity within and between networks ( Yeo et al, 2011 ), providing a reliable and measureable tool to assess cortico-cortical connectivity and its link with complicated human behaviors such as gait ( Yuan et al, 2015 ).…”

Disrupted Brain Intrinsic Networks and Executive Dysfunction in Cirrhotic Patients without Overt Hepatic Encephalopathy

“…Weissenborn et al ( 8 , 9 ) proposed that executive dysfunction in cirrhosis contributes to an alteration of energy metabolism in the medial and lateral frontal cortex, anterior cingulate gyrus, and parietal structures. In addition, neuroimaging studies using task-based functional magnetic resonance imaging (fMRI) have also revealed less activation in the brain network that involves the ACC, prefrontal cortex, parietal lobe, and temporal fusiform gyrus when cirrhotic patients without OHE performed the Stroop task ( 7 ) [a test assessing executive function that requires a number of cognitive abilities to occur in tandem, such as selective attention, dual processing, processing speed, and cognitive flexibility ( 10 )].…”