Moral decisions are multifaceted with two essential aspects, flexibility and consistency. However, the interaction between these two and the underlying mechanisms is rarely studied. Here, we combined mouse-tracking and functional magnetic resonance imaging (fMRI) together in a value-based moral decision task, which allows us to quantify accumulative history responses as self-consistency. Using a multi-attribute time-dependent drift-diffusion model (tDDM), we disentangled the role of consistency and self-interest, highlighting the dominant role of cognitive-control-related regions. The drift rate of self-consistency was directly associated with the brain activity responsible for cognitive control, while the relationship between the reward and the activity of the related brain regions was mediated by the mouse-tracking index area under the curve(AUC). Dorsolateral prefrontal cortex was revealed as a hub connecting prACC and ventral striatum, whose functional connectivity was correlated with consistency drift rate and reward drift rate respectively. Furthermore, decision flexibility was quantified by choice entropy, which links to mouse tracking indices and the activity of cognitive - control related regions. Together, our study uncovers the interplay between self-consistency and reward in behavior, and highlights the key role of cognitive control in modulating these two attributes, thereby deepening our understanding of consistency and flexibility in moral decisions.

This study assesses the validity of a newly integrated memory detection method, MT-aIAT, which is a combination of the autobiographical Implicit Association Test (aIAT) and the mouse-tracking method. Participants were assigned to steal a credit card and then performed the aIAT while mouse tracker was recording their motor trajectories. Replicating previous work, we found a RT congruency effect. Critically, the mouse trajectories indicate a congruency effect and a block order effect, suggesting the validity of mouse-tracking technique in unraveling real-time measurement of the IAT congruency effect. Lastly, to test the computational modeling in MT-aIAT, we posited a connectionist model combined with the drift-discussion model to simulate participants’ behavioral performance. Our model captures the ubiquitous implicit bias towards the autobiographical event. Implications of the MT-aIAT in identifying autobiographical memories, the combination of MT-aIAT with computational modeling approach were discussed.