Spectral Dynamic Causal Modelling of Resting-State fMRI: Relating Effective Brain Connectivity in the Default Mode Network to Genetics
Yunlong Nie, Eugene Opoku, Laila Yasmin, Yin Song, Jie Wang, Sidi Wu, Vanessa Scarapicchia, Jodie R. Gawryluk, Liangliang Wang, Jiguo Cao, Farouk S. Nathoo
arXiv Preprint Archive January 28, 2019 preprint
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort Longitudinal |
|---|---|
| Sample size | 111 |
| Population | Subjects with Alzheimer's disease or mild cognitive impairment from the ADNI database |
| Topics | Default mode network |
| Keywords | Q-bio.nc Q-bio.qm |
| Key findings | Exploratory patterns of associations between SNPs and effective brain connectivity in the DMN showed stability across linear mixed effect and function-on-scalar regression methods. |
Abstract
We conduct an imaging genetics study to explore how effective brain connectivity in the default mode network (DMN) may be related to genetics within the context of Alzheimer's disease and mild cognitive impairment. We develop an analysis of longitudinal resting-state functional magnetic resonance imaging (rs-fMRI) and genetic data obtained from a sample of 111 subjects with a total of 319 rs-fMRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. A Dynamic Causal Model (DCM) is fit to the rs-fMRI scans to estimate effective brain connectivity within the DMN and related to a set of single nucleotide polymorphisms (SNPs) contained in an empirical disease-constrained set which is obtained out-of-sample from 663 ADNI subjects having only genome-wide data. We examine longitudinal data in both a 4-region and an 6-region network and relate longitudinal effective brain connectivity networks estimated using spectral DCM to SNPs using both linear mixed effect (LME) models as well as function-on-scalar regression (FSR). In the former case we implement a parametric bootstrap for testing SNP coefficients and make comparisons with p-values obtained from the chi-squared null distribution. We also implement a parametric bootstrap approach for testing regression functions in FSR and we make comparisons between p-values obtained from the parametric bootstrap to p-values obtained using the F-distribution with degrees-of-freedom based on Satterthwaite's approximation. In both networks we report on exploratory patterns of associations with relatively high ranks that exhibit stability to the differing assumptions made by both FSR and LME.
Comparable studies
Other observational and cohort studies on default mode network, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| A default mode of brain function Normal adult human brain | 2001 | Observational study | |
| Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network Healthy subjects | 2008 | Observational cohort | |
| Meditation experience is associated with increased cortical thickness Participants with extensive Insight meditation experience and matched controls | 2005 | Observational cohort | n = 20 |
| Meditation experience is associated with differences in default mode network activity and connectivity Experienced meditators and matched meditation-naive controls | 2011 | Observational cohort | |
| The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis Healthy subjects | 2008 | Observational study |