Resting-state functional connectivity in chronic pain and depression in the STRADL study

<h3>Background and Aims</h3> Chronic pain and depression often co-occur and individuals experiencing this comorbidity have been shown to have more severe symptoms and poorer prognoses than those with either condition in isolation. Despite previous work revealing aberrant connectivity signatures in both disorders, it remains unclear how functional connectivity (FC) is characterised in chronic pain and depression, as isolated disorders and in combination. Therefore, we aim to characterise static FC in each disorder separately and as a comorbidity. Furthermore, given the nature of large-scale brain networks to change over time, we aim to characterise dynamic FC in chronic pain and depression to account for functional coupling fluctuations between brain regions of interest. <h3>Methods</h3> STratifying Resilience and Depression Longitudinally (STRADL) is a depression- focused population-based study including detailed clinical and neuroimaging assessments. A total of 880 unrelated participants have resting-state functional magnetic resonance imaging (fMRI) data available. Preprocessing and first-level analysis of fMRI data was conducted using the HALFpipe pipeline developed by the ENIGMA consortium (https://github.com/HALFpipe/HALFpipe). Measures of static FC will be calculated using network-based statistic (NBS), from which between- group differences in FC networks will be derived. Dynamic FC will be measured using leading eigenvector dynamics analysis (LEiDA). Study preregistration: https://osf.io/dqpjr/. Statistical analysis is currently underway, results and discussion will be available by 20/05/24.