Source Code
Reduced Error-Related Default Mode Network Deactivations Linked with HIV and Poor Medication Management

Flannery JS, Riedel MC, Salo T, Poudel R, Laird AR, Gonzalez R, Sutherland MT, HBM (2021).



Brain function supporting error-monitoring has rarely been examined among persons living with HIV (PLWH) despite its importance for recognizing and preventing maladaptive behavior (e.g., medication non-adherence) that could lead to worsened health outcomes among this vulnerable population. As medicinal and recreational cannabis use is prevalent among PLWH [1], we aimed to assess interactive impacts of HIV infection and chronic cannabis (CB) use on error-processing brain activity and investigate implications for clinically relevant disease management behaviors.


Our sample of 103 participants (68.0% male, mean age=35.610.9 years) was stratified into four groups based on HIV serostatus and CB use history (HIV+/CB+, n=30; HIV+/CB-, n=25; HIV-/CB+, n=26; HIV-/CB-, n=22). To probe error-processing mechanisms, participants underwent fMRI scanning while completing a Go/NoGo, motor inhibition paradigm called the Error Awareness Task (EAT). Participants also completed a battery of well-validated instruments including the Revised Medication Management Test (MMT-R), an objective behavioral measure of medication management abilities [2], and self-reports of cannabis use history. Following preprocessing (FMRIPREP v1.1.1 [3]), six EAT runs were entered into a subject-level general linear model (GLM) including nuisance regressors and three task-related regressors. To characterize brain activity linked with cognitive control/failures, NoGo-correct minus NoGo-error [C-E] contrast values were assessed with a whole-brain, one-sample t-test (3dTtest++: two-tailed, pvoxel-wise=1.0e-10, cluster extent: 20 voxels). To assess HIV and CB main and interaction effects on these [C-E] contrast values, a whole-brain, 2(HIV) x 2(CB) ANOVA (3dMVM), including sex, age, and IQ as covariates, was performed. To assess brain-behavior relationships, we conducted Pearson’s correlations between averaged error-related  coefficients, extracted from identified clusters/regions of interest (ROIs), and error frequency in the EAT (ERROR COUNT). To probe clinically-relevant implications of HIV-associated alterations, we examined relationships between error-related brain activity and behavioral performance on the MMT-R (MMT SCORE) by conducting HIV-status x MMT SCORE ANCOVAs. Additionally, we tested a meditation model in which error-related brain activity (M) mediated the effect of HIV-status (X) on MMT SCORE (Y) [4, 5]. Finally, to evaluate the impact of lifetime cannabis use amount (AMOUNT), we assessed HIV-status x AMOUNT interactions on error-related brain activity and MMT SCORE among cannabis using participants (n=55).


We observed error-related brain activity in the anterior insula that was associated with better EAT performance across the full sample. Regarding group effects, PLWH displayed a lack of error-related deactivation in two default mode network (DMN) hub regions (the posterior cingulate cortex [PCC] and medial prefrontal cortex [mPFC]) that was contrarily observed among HIV- controls (Fig.1A). Additionally, degree of PCC suppression was associated with improved EAT performance among HIV- controls but not among PLWH (Fig.1B). CB main and interaction effects were not detected. Across all groups, reduced error-related PCC deactivation was associated with poorer medication management performance (Fig.2A) and mediated the effect of HIV-status on medication management abilities (Fig.2B). Finally, amount of CB used over the lifetime was associated with reduced mPFC deactivation to errors among CB using, HIV- controls, and poorer medication management abilities across all CB users.


Our results demonstrate diminished error-related DMN suppression among PLWH linked to poor medication management. Identifying this HIV-associated, neurobiological alteration, which may contribute to high rates of medication nonadherence among this population [6, 7], could inform treatment planning and tailor self-care education.