Large-Scale Internetwork Functional Connectivity Mediates the Relationship between Serum Triglyceride and Working Memory in Young Adulthood

Abstract

Previous research has demonstrated that serum lipid profile is associated with cognitive function as well as brain structure and function in middle-aged, elderly, and clinical populations. However, the nature and extent of lipids-brain-cognition relationships in young adulthood are largely unknown. In this study, 157 healthy young adults underwent resting-state functional MRI scans. Functional connectivity between and within 14 functional networks were calculated using independent component analysis. Peripheral venous blood samples were collected to measure serum lipids. Working memory was assessed using a 3-back task. Linear regression, correlation, and mediation analyses were conducted to test for potential associations between serum lipids, inter- and intranetwork functional connectivity, and working memory performance. We found that higher serum triglyceride (TG) level was correlated with stronger connectivity between left frontoparietal and ventral attention networks, between right frontoparietal and dorsal attention networks, between right frontoparietal and dorsal sensorimotor networks, between right frontoparietal and lateral visual networks, and between salience (SN) and ventral sensorimotor (vSMN) networks, as well as lower connectivity between posterior default mode and left frontoparietal networks, between left frontoparietal and medial visual networks, and between ventral attention and dorsal sensorimotor networks. In addition, higher SN-vSMN connectivity was related to lower 3-back accuracy. More importantly, the relationship between serum TG and 3-back accuracy was mediated by SN-vSMN connectivity. Our findings not only may expand existing knowledge regarding serum lipids-brain-cognition relations from the perspective of large-scale functional network organization but also may inform a translational conceptualization of how to improve cognitive function through regulating serum lipids.

Abnormal Static and Dynamic Functional Network Connectivity in Patients With Presbycusis

“…Second, the InfoMax algorithm was used to run the appropriate ICA. Finally, the time courses and spatial maps of individual subjects were back-reconstructed by group ICA ( Wang et al, 2020 ), and the results were transformed to Z -scores for display. Ten significant components were identified as RSNs through visual observation of the ICA results based on previous studies.…”

“…Ten significant components were identified as RSNs through visual observation of the ICA results based on previous studies. These ICs were classified into eight RSNs, namely, AUN, DMN, attention network (AN), left frontoparietal network (LFPN), right frontoparietal network (RFPN), SMN, VN, and cerebellum network (CN), all of which have been widely reported in previous rs-fMRI research ( Jiang et al, 2020 ; Wang et al, 2020 ).…”

“…The temporal dFNC module, as implemented in the GIFT software package, was used to perform the dFNC analysis. Preprocessing included cubic detrending, despiking using 3D-despike, and low-pass filtering using a high-frequency cutoff of 0.15 Hz to decrease the impact of artifacts ( Wang et al, 2020 ). Then, a sliding time-window approach [window size set to 15 TRs of a rectangular window convolved with a Gaussian (= 3 TRs)] was employed to compute the dFNC between ICA time courses ( Du et al, 2016 ).…”

Networks Are Associated With Acupuncture Treatment in Patients With Diarrhea-Predominant Irritable Bowel Syndrome: A Resting-State Imaging Study

“…Independent component analysis is data-driven and provides information about functional connectivity on a whole-brain scale ( van den Heuvel and Hulshoff Pol, 2010 ). ICA was used to parcellate fMRI data using the GIFT toolbox 3 ( Wang et al, 2020 ). A total of 36 independent components were generated.…”

Metabolic and Neural Mechanisms Underlying the Associations Between Gut Bacteroides and Cognition: A Large-Scale Functional Network Connectivity Study

“…16S rRNA gene sequencing was conducted with abundances of Bacteroides and metabolic pathways quantified by species annotation and functional prediction analyses, respectively. Large-scale intra- and internetwork functional connectivity was measured using independent component analysis (ICA) ( Wang C. et al, 2020 ), as converging evidence has emphasized the pivotal role of functional network connectivity in cognition ( Park and Friston, 2013 ). By a combined analysis of these data, the objectives of this investigation were four-fold.…”