Connectivity Patterns in the Core Resting-State Networks and Their Influence on Cognition

Brain Connect. 2022 May;12(4):334-347. doi: 10.1089/brain.2020.0943. Epub 2021 Aug 23.

Abstract

Introduction: Three prominent resting-state networks (rsNW) (default mode network [DMN], salience network [SN], and central executive network [CEN]) are recognized for their important role in several neuropsychiatric conditions. However, our understanding of their relevance in terms of cognition remains insufficient. Materials and Methods: In response, this study aims at investigating the patterns of different network properties (resting-state activity [RSA] and short- and long-range functional connectivity [FC]) in these three core rsNWs, as well as the dynamics of age-associated changes and their relation to cognitive performance in a sample of healthy controls (N = 74) covering a large age span (20-79 years). Using a whole-network based approach, three measures were calculated from the functional magnetic resonance imaging (fMRI) data: amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and degree of network centrality (DC). The cognitive test battery covered the following domains: memory, executive functioning, processing speed, attention, and visual perception. Results: For all three fMRI measures (ALFF, ReHo, and DC), the highest values of spontaneous brain activity (ALFF), short- and long-range connectivity (ReHo, DC) were observed in the DMN and the lowest in the SN. Significant age-associated decrease was observed in the DMN for ALFF and DC, and in the SN for ALFF and ReHo. Significant negative partial correlations were observed for working memory and ALFF in all three networks, as well as for additional cognitive parameters and ALFF in CEN. Discussion: Our results show that higher RSA in the three core rsNWs may have an unfavorable effect on cognition. Conversely, the pattern of network properties in healthy subjects included low RSA and FC in the SN. This complements previous research related to the three core rsNW and shows that the chosen approach can provide additional insight into their function. Impact statement Using a whole network-based approach, our study characterizes the normal patterns (including resting-state activity [RSA], short- and long-range functional connectivity [FC]) of three prominent resting-state networks (rsNW) within the context of age-dependent changes and explores their relevance for different cognitive domains. Our results revealed a pattern with low RSA and FC in the salience network in healthy volunteers, whereas higher RSA, particularly in the central executive network, seemed to have a negative effect on cognition. These results increase the knowledge about the three core rsNWs and the understanding about their relevance for cognition.

Keywords: ALFF; cognition; degree of network centrality; regional connectivity.

MeSH terms

  • Adult
  • Aged
  • Brain Mapping / methods
  • Brain* / diagnostic imaging
  • Cognition*
  • Executive Function / physiology
  • Humans
  • Magnetic Resonance Imaging / methods
  • Memory, Short-Term
  • Middle Aged
  • Young Adult