The present study aimed to explore the characteristics and dynamics of reward sensitivity in a sample of young people with MDD ranging from early adolescence to young adulthood. Our findings revealed reduced reward sensitivity in young patients with MDD, with this effect being particularly pronounced in adolescents. Additional analysis employing drift diffusion modeling corroborated a reduced rate of evidence accumulation in response to rewarding stimuli, as evidenced by lower drift rates and larger decision thresholds among depressed adolescents. Interestingly, the starting point of evidence accumulation was closer to the more frequently rewarded option in healthy adolescents than adolescents with MDD. Furthermore, these differences were found to correlate with the severity of depression and diminished hedonic capacity.
Our study discovered distinctive deficits in reward sensitivity that distinguish adolescents with MDD from young adult counterparts. Notably, adolescents with MDD displayed diminished reward bias, contrasting with young adults with MDD who exhibited reward responses more closely resemble to those observed in healthy individuals. This observation aligned with existing research indicating a decline in reward sensitivity, as evidenced in studies utilizing the PRT among both adolescents with MDD [28] and those at high risk for depression [29]. The pronounced deficiency in bias towards high-frequency rewarding stimuli among adolescents with MDD implied an impaired ability to modulate behaviors in response to reinforcing rewards over time [9, 10, 30]. The disparities in reward bias further suggested a heightened blunting of reward sensitivity in adolescent MDD patients, potentially serving as a vulnerability marker for depression during adolescence. Such discrepancy might be explained by the susceptibility of reward sensitivity to disturbances or instability in reward function and related neural systems undergoing maturation changes during adolescence [31]. Prior studies have suggested that heightened dopamine activity, which mediates reward-related brain function, contributes to enhanced reward responsiveness and reward-seeking behaviors during adolescence [32]. Additionally, it's important to consider that the development of reward-related brain regions follows a distinct trajectory. For instance, the mesolimbic systems, responsible for reward processing, mature earlier than the prefrontal regions, which govern more complex cognitive functions like decision-making [33]. This developmental discordance may result in neural hyperactivation within the mesolimbic system, particularly the ventral striatum, during typical adolescence [34]. Consequently, deviations from this neurodevelopmental pattern could lead to a significant reduction in reward sensitivity and heightened susceptibility to depression.
Combining the modeling findings, distinct patterns of reward sensitivity were reconfirmed in depressed adolescents and young adults when compared to healthy individuals. Specifically, depressed adolescents exhibited lower drift rates and elevated decision threshold, suggesting a reduced ability to accumulate evidence in response to rewarding information. This aligned with previous researches by Lawlor et al. [17] and Pitliya et al. [18], which identified lower drift rates and larger threshold as indicative of deficits in reward processing among individuals with depression. In contrast to previous research suggesting diminished reward bias in adults with MDD compared to HC [9–11, 30], our findings among young adults with MDD presented a divergent pattern. Nonetheless, similarities in drift rate and starting point bias within decision dynamics offer insights into their comparable reward sensitivity relative to HC. Specifically, our observation of higher drift rate with faster information processing and evidence accumulation in reward decision-making [26], and the starting point of evidence accumulation leaned towards the more frequent rewards in young adults with MDD might suggest a shared decision processing with the healthy group. These alignments could elucidate the discernible response bias in individuals with MDD in our study. Moreover, it is noteworthy that we found that young adults with MDD also demonstrated elevated decision threshold, which indicating a heightened amount of evidence to make decisions despite having a similar information processing speed as the HC. This observation suggested potential delays or uncertainty in the decision processes, positing that young adults with MDD might employ more cautious strategies (e.g., reduce decisional risks or enhance decisional accuracy) when deciding how to approach rewards [17, 18]. Together, these findings suggested the distinct impairments in reward sensitivity and decision-making processes among young depressed individuals, with variations across different age groups and need to be determined in future investigations.
Our findings, derived from both subjective and objective measures of anhedonia and depression, support the idea that self-reported assessments indicating reduced hedonic capacity and higher levels of depression correlate with slower evidence accumulation of reward. Consistent with the hypothesis that impaired behavioral modulation in response to rewards may underlie the diminished hedonic capacity in MDD [9, 10, 35], the current findings shed light on elucidating the psychopathology of anhedonia during adolescence was linked to aberrant reward processing in depression, suggesting that decreased sensitivity to rewards could contribute to a diminished experience of pleasure and an increased risk for MDD.
The present study also has some limitations that need to be acknowledged. Firstly, as this was a cross-sectional study, we were unable to investigate the long-term impact of reduced reward sensitivity on the developmental psychopathology of depression. Future research should conduct longitudinal follow-up studies to address this issue. Secondly, while our study examined the behavioral aspects of reward sensitivity in depressed young people, there is a need to investigate the underlying neural mechanisms of abnormal reward sensitivity during adolescence using neuroimaging techniques. This will help shed light on how atypical brain development interacts with dysfunctional reward processing to contribute to the development of depressive symptoms. Thirdly, our study used only monetary reinforcement as a reward stimulus. However, it is possible that there are differences in reward processing in MDD patients that depend on the type of reward stimuli used [36]. Investigating social motivation in MDD using paradigms with greater ecological validity will be an important direction for future research to understand the full scope of dysfunctional reward processing in depression.