The longitudinal stability of fMRI activation during reward processing in adolescents and young adults

Abstract

BackgroundThe use of functional neuroimaging has been an extremely fruitful avenue for investigating the neural basis of human reward function. This approach has included identification of potential neurobiological mechanisms of psychiatric disease and examination of environmental, experiential, and biological factors that may contribute to disease risk via effects on the reward system. However, a central and largely unexamined assumption of much of this research is that neural reward function is an individual difference characteristic that is relatively stable over time.MethodsIn two independent samples of adolescents and young adults studied longitudinally (Ns = 145 & 153, 100% female & 100% male, ages 15-21 & 20-22, 2-4 scans & 2 scans respectively), we tested within-person stability of reward-task BOLD activation, with a median of 1 and 2 years between scans. We examined multiple commonly used contrasts of active states and baseline in both the anticipation and feedback phases of a card-guessing reward task. We examined the effects of cortical parcellation resolution, contrast, network (reward regions and resting-state networks), region-size, and activation strength and variability on the stability of reward-related activation.ResultsOverall, stability (ICC; intra-class correlation) across 1-2 years was modest. In both samples, contrasts of an active state relative to a baseline were more stable (e.g., Win>Baseline; mean ICC = 0.13 – 0.33) than contrasts of two active states (e.g., Win>Loss; mean ICC = 0.048 – 0.05). Additionally, activation in reward regions was less stable than in many non-task networks (e.g., dorsal attention), and activation in regions with greater between-subject variability showed higher stability in both samples.ConclusionsThese results show that functional neuroimaging activation to reward has modest stability over 1-2 years. Notably, results suggest that contrasts intended to map cognitive function and show robust group-level effects (i.e. Win > Loss) may be less effective in studies of individual differences and disease risk. The robustness of group-level activation should be weighed against other factors when selecting regions of interest in individual difference fMRI studies.

Reliability and Stability Challenges in ABCD Task fMRI Data

“…For example, an activation elicited by emotional faces relative to baseline shows higher ICCs than activation of emotional faces relative to neutral faces (which is totally unreliable in the ABCD data). Similarly, Baranger et al (2021) recently demonstrated using a number-guessing reward task that reward activation contrasted with baseline had greater reliability than reward contrasted directly with loss. However, contrasts with baseline lack specificity because they may include activation elicited by emotional content as well as nonspecific activation that can be attributed to any outcome regardless of semantic content, and even activation that is common to visual stimuli in general, resulting in poor discriminant validity.…”

“…For example, an activation elicited by emotional faces relative to baseline shows higher ICCs than activation of emotional faces relative to neutral faces (which is totally unreliable in the ABCD data). Similarly, Baranger et al (2021) recently demonstrated using a number-guessing reward task that reward activation contrasted with baseline had greater reliability than reward contrasted directly with loss.…”

From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research

“…Beyond behavioral measures, the Reliability Paradox is also apparent in neuroscience-a recent meta-analysis of 90 fMRI experiments showed an average task-based BOLD response 𝜌 ≈ .4 across different brain regions and tasks (16). Resting state, task-based, and regional activation/connectivity measures show comparably low reliability (24)(25)(26), suggesting that-like behavioral tasks-many neural measures cannot be used for clinical decision-making.…”

Peer Connectedness and Pre‐Existing Social Reward Processing Predicts U.S. Adolescent Girls’ Suicidal Ideation During COVID‐19

“…The following a priori reward‐related regions were selected: caudate, putamen, AI, NAcc, and vmPFC. Reward‐related neural activation has adequate stability over a 1‐ to 2‐year period (Baranger et al., 2021), supporting the use of neural activation to reward as a trait‐level predictor in short‐term longitudinal analysis. Finally, we explored the association between peer connectedness during the pandemic and pre‐existing neural activation to positive peer feedback, based on work showing a link between neural activation to social feedback and daily peer connectedness (Silk et al., under review).…”