Interindividual differences in cognitive flexibility: influence of gray matter volume, functional connectivity and trait impulsivity

Abstract

Cognitive flexibility, a core aspect of executive functioning, is required for the speeded shifting between different tasks and sets. Using an interindividual differences approach, we examined whether cognitive flexibility, as assessed by the Delis–Kaplan card-sorting test, is associated with gray matter volume (GMV) and functional connectivity (FC) of regions of a core network of multiple cognitive demands as well as with different facets of trait impulsivity. The core multiple-demand network was derived from three large-scale neuroimaging meta-analyses and only included regions that showed consistent associations with sustained attention, working memory as well as inhibitory control. We tested to what extent self-reported impulsivity as well as GMV and resting-state FC in this core network predicted cognitive flexibility independently and incrementally. Our analyses revealed that card-sorting performance correlated positively with GMV of the right anterior insula, FC between bilateral anterior insula and midcingulate cortex/supplementary motor area as well as the impulsivity dimension “Premeditation.” Importantly, GMV, FC and impulsivity together accounted for more variance of card-sorting performance than every parameter alone. Our results therefore indicate that various factors contribute individually to cognitive flexibility, underlining the need to search across multiple modalities when aiming to unveil the mechanisms behind executive functioning.

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

“…Such convergence arises from the fact that the frequency of observed activations in neuroimaging experiments and hence also BrainMap is not homogeneous across the brain. Some brain regions like the anterior insula (Kurth et al, 2010; Yarkoni et al, 2011) and the posterior-medial frontal cortex (Muller et al, 2015) are more often activated than, for instance, the lateral temporal cortex. By randomly sampling the noise foci from BrainMap, the current simulations thus reflect this bias, leading to incidental convergence outside the target location.…”

Three key regions for supervisory attentional control: Evidence from neuroimaging meta-analyses

“…As inhibition, working memory as well as sustained and selective attention are regarded as core component factors underlying executive functions (Alvarez and Emory, 2006), this network most likely represents a set of cortical regions that interact with each other during executive control processes across a wide variety of tasks (cf. Müller et al, in press). Along the same lines, a very similar set of regions has been shown to be engaged across a diversity of cognitively demanding tasks and hypothesized to respond in a domain- and process-general manner (Cole and Schneider, 2007; Duncan, 2010; Duncan and Owen, 2000; Fedorenko et al, 2013).…”

Psychosocial versus physiological stress — Meta-analyses on deactivations and activations of the neural correlates of stress reactions

“…In order to specifically determine functional networks for regions of interest derived from the current meta-analyses, we additionally conducted resting-state functional connectivity analyses as well as functional characterization (e.g., Müller et al, 2014). …”