Association of Neural and Emotional Impacts of Reward Prediction Errors With Major Depression

Abstract

Importance: Major depressive disorder (MDD) is associated with deficits in representing reward prediction errors (RPEs), which are the difference between experienced and predicted reward. Reward prediction errors underlie learning of values in reinforcement learning models, are represented by phasic dopamine release, and are known to affect momentary mood.

Objective: To combine functional neuroimaging, computational modeling, and smartphone-based large-scale data collection to test, in the absence of learning-related concerns, the hypothesis that depression attenuates the impact of RPEs.

Design, setting, and participants: Functional magnetic resonance imaging (fMRI) data were collected on 32 individuals with moderate MDD and 20 control participants who performed a probabilistic reward task. A risky decision task with repeated happiness ratings as a measure of momentary mood was also tested in the laboratory in 74 participants and with a smartphone-based platform in 1833 participants. The study was conducted from November 20, 2012, to February 17, 2015.

Main outcomes and measures: Blood oxygen level-dependent activity was measured in ventral striatum, a dopamine target area known to represent RPEs. Momentary mood was measured during risky decision making.

Results: Of the 52 fMRI participants (mean [SD] age, 34.0 [9.1] years), 30 (58%) were women and 32 had MDD. Of the 74 participants in the laboratory risky decision task (mean age, 34.2 [10.3] years), 44 (59%) were women and 54 had MDD. Of the smartphone group, 543 (30%) had a depression history and 1290 (70%) had no depression history; 918 (50%) were women, and 593 (32%) were younger than 30 years. Contrary to previous results in reinforcement learning tasks, individuals with moderate depression showed intact RPE signals in ventral striatum (z = 3.16; P = .002) that did not differ significantly from controls (z = 0.91; P = .36). Symptom severity correlated with baseline mood parameters in laboratory (ρ = -0.54; P < 1 × 10-6) and smartphone (ρ = -0.30; P < 1 × 10-39) data. However, participants with depression showed an intact association between RPEs and happiness in a computational model of momentary mood dynamics (z = 4.55; P < .001) that was not attenuated compared with controls (z = -0.42; P = .67).

Conclusions and relevance: The neural and emotional impact of RPEs is intact in major depression. These results suggest that depression does not affect the expression of dopaminergic RPEs and that attenuated RPEs in previous reports may reflect downstream effects more closely related to aberrant behavior. The correlation between symptom severity and baseline mood parameters supports an association between depression and momentary mood fluctuations during cognitive tasks. These results demonstrate a potential for smartphones in large-scale computational phenotyping, which is a goal for computational psychiatry.

Figure 1.. Behavioral Measures for Neuroimaging Experiment

Participants played a probabilistic reward task during simultaneous functional magnetic resonance imaging for earnings. In each trial, participants had to select 1 of 2 lotteries and were then shown the outcome. A, Task earnings were similar in depressed and control groups. The task design was such that participants should always choose 1 of 4 observation lotteries with outcomes of gaining or losing £1 (US $1.29) and a probability of 0%, 25%, 75%, or 100% of receiving the better outcome. B, Reaction times were similar in depressed and control groups and faster for certain wins. C, Choice accuracy to the observation lotteries (D) was similar in depressed and control groups. Error bars indicate SEM.

Figure 2.. Main Effects of Reward-Related Neural Responses

A, Depressed participants (n = 32) showed intact expected value (EV) signals in ventral striatum and intact reward prediction error (RPE) signals in ventral striatum and medial prefrontal cortex. Images are displayed at uncorrected P < .001. B, EV and RPE signals in the ventral striatum region of interest were not significantly different in the depressed (n = 32) and control groups (n = 20). Scale indicates t statistics; Error bars, SEM; AU, arbitrary units.

Figure 3.. Computational Model of Momentary Mood in Laboratory and Smartphone Experiments

A, Participants (depressed, 54; control, 20) played a risky decision task in the laboratory and made a choice on every trial between safe and risky options; they then were shown the gamble expected values (EVs). After every 2 to 3 trials, participants were asked, “How happy are you at this moment?” Parameter weights for past certain rewards (CRs), gamble EVs, and reward prediction errors (RPEs) in the momentary mood computational model were significantly positive in both the depressed and control groups. B, Baseline mood parameters were negatively correlated with symptom severity (Patient Health Questionnaire [PHQ], ρ = −0.54, P < 1 × 10⁻⁶; Hamilton Scale for Depression [HAM-D], ρ = −0.50, P < 1 × 10⁻⁵). C, Participants (n = 1833) played a similar risky decision task on their smartphones and also completed the Beck Depression Inventory second edition (BDI-II) questionnaire. Parameter weights were not reduced for participants with high (≥15) compared with low (<15) BDI-II scores. The impact of RPEs was not reduced in depression and was greater in participants with worse symptom severity (ρ = 0.05, P = .01). D, Baseline mood parameters were negatively correlated with symptom severity (BDI-II, ρ = −0.30, P < 1 × 10⁻³⁹). Error bars indicate SEM.