A Baseline for the Multivariate Comparison of Resting-State Networks

Abstract

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.

Brain activity and connectivity during poetry composition: Toward a multidimensional model of the creative process

“…A novel method of functional network connectivity (FNC) analysis has previously been applied to resting‐state data [Allen et al, 2011; Doucet et al, 2011; Jafri et al, 2008]. Here, this FNC method was used in a task‐based study.…”

“…The time courses of remaining 53 components for each subject and condition, which were computed from the group ICA time courses by a PCA‐based back‐reconstruction method [Erhardt et al, 2011], were used for the following FNC analyses [Allen et al, 2011; Doucet et al, 2011; Jafri et al, 2008]. …”

Dynamic interactions of the cortical networks during thought suppression

“…Then, we calculated low‐frequency power ratio (LFPR) as the ratio of the sum of spectral power between 0.003 and 0.10 Hz to the sum between 0.15 and 0.25 Hz (Allen et al. 2011; Yu et al. 2013).…”

“…In line with a previous report (Allen et al. 2011), LFPR values <3 were only observed in clearly artifactual components, and values <3.5 were considered indicative of artifactual origin. We kept this procedure conservative by leaving some of these suspicious ICs in the subsequent analysis.…”

Male‐to‐female gender dysphoria: Gender‐specific differences in resting‐state networks

“…Concerning the influence of gender on the RSN, a few studies have been conducted with mixed results: there is evidence for gender differences in resting‐state FC (rs‐FC) in specific brain regions such as the amygdala (Dai et al., 2012; Kogler et al., 2016), insula (Li, Qin, Jiang, Zhang, & Yu, 2012) and within the sensorimotor network (Allen et al., 2011). In addition, men showed stronger connectivity in parieto‐temporal regions, and within cognitive and sensory networks.…”