B - 93 The Role of ex-Gaussian Parameters and Apathy in Reward Sensitivity Using a Modified Probabilistic Learning Task

Objective The current study examined the associations of apathy with attentional processes, indicated by ex-Gaussian (Ex-G) parameters of sensorimotor response speed and reward learning. Methods One hundred college-aged participants (M age = 20.32; SD = 3.69; 69 female) completed self-report measures of depression, apathy, and attentional control. Laboratory tasks included a choice reaction time (RT) task and a modified probabilistic learning task to assess sensorimotor processing and reward sensitivity. In the probabilistic learning task, participants selected the symbol associated with a high probability of gaining a monetary reward. Choice RT data were fit with Ex-G models, from which the parameter τ (bootstrapped sampling, 1000 iterations) was derived and used as the index of attentional lapses. Results A non-linear relationship was found between apathy and reward learning. Hierarchical regression was used to examine linear and higher-order relationships between apathy and behavioral indices (Ex-G τ and reward sensitivity). Results show that apathy explained none of the variance in reward learning (β = −0.005, p = 0.792, [bootstrapCI = −0.037, 0.026]). Incorporating apathy2 into the model led to significant R2 change (0.086), F(2, 89) = 0.4.142, p = 0.019, suggesting that as apathy increases, reward learning increases (β =0.006, p = 0.002, bootstrapCI = 0.002, 0.010]). Moreover, when controlling for depression, τ significantly contributes to the model, F(3, 89) = 4.142, p = 0.019, R2 = 0.17. Interactive effects revealed that at higher levels of apathy, higher Ex-G τ significantly decreases reward sensitivity (β = −0.003, p = 0.037, 95% bootstrapCI = [−0.006, −002]). Conclusions Higher levels of apathy and attentional lapses jointly reduced reward sensitivity, highlighting the role of task disengagement in apathy.