Relationships between multiple dimensions of executive functioning and resting-state networks in adults. (April 2020)

• Record Type: Journal Article
• Authors: Roye, Scott; Castagna, Peter J.; Calamia, Matthew; De Vito, Alyssa N.; Lee, Tae-Ho; Greening, Steven G.
• Is Part Of: Neuropsychologia. Volume 141(2020)
• Publication Date: 2020-04
• Subjects: Neuropsychology -- Periodicals; Neurology -- Periodicals; Psychophysiology -- Periodicals; Neuropsychologie -- Périodiques; Neuropsychology; Periodicals; Electronic journals; 616.8
• DOI: 10.1016/j.neuropsychologia.2020.107418
• Languages: English
• ISSNs: 0028-3932

Abstract

Abstract: The current study sought to examine the functional connectivity of resting state networks (RSNs) as they relate to the individual domains of executive functioning (EF). Based on the Unity and Diversity model (Miyake et al., 2000), EF performance was captured using a three-factor model proposed by Karr et al. (2018), which includes inhibition, shifting, and fluency. Publicly available data was used from the Nathan Kline Institute -Rockland project was used. Of the 722 participants who completed the Delis-Kaplan Executive Function System (D-KEFS), which was used to measure EF performance, 269 of these individuals completed resting state fMRI scans. First, a confirmatory factory analysis replicated Karr et al. (2018) revealing three components: inhibition, shifting and fluency. Next, RSNs were identified across the sample using an Independent Components Analysis (ICA) and was compared to previously established intrinsic connectivity networks (Laird et al., 2011). Finally, dual regression was used to analyze the relationships between the functional connectivity of RSNs and EF performance, which indicated that RSNs were differentially associated with inhibition and shifting. Better inhibition was related to increased connectivity between the left striatum and the attentional control network. Better shifting performance was related to increased connectivity between the pre- and postcentral gyri and the speech and sensorimotor network. These results highlight individual differences within these RSNs that are unique to the literature, as non-EF confounds are mitigated within the current measurements of EF performance. Highlights: Karr et al. (2018) model was replicated in a unique sample. EF performance demonstrated domain-specific relationships with unique resting state networks. Inhibition was related to the left striatum and attentional control network. Shifting was related to the pre- and postcentral gyri and speech and sensorimotor network.