Neural correlates of evidence accumulation in social-affective decision-making under perceptual ambiguity
Evidence accumulation models have been widely used to explain decision-making in sensory and cognitive domains, but how this process explains social-affective decision-making under perceptual ambiguity remains unclear. Here, we integrate computational modeling with multimodal neuroscience to investigate how perceptual ambiguity in emotion judgment influences decision dynamics. Participants viewed ambiguous stimuli--morphed images blending emotional expressions--and made binary categorizations. Using drift diffusion modeling (DDM), we show that drift rate, a core index of evidence accumulation, decreases as ambiguity increases. Scalp EEG data reveal that the late positive potential (LPP) tracks drift rate in both emotional and non-emotional decisions, but only when perceptual ambiguity is relevant to the task. Likewise, single-unite recordings from the dorsomedial prefrontal cortex (dmPFC) and amygdala neurons show that trial-by-trial firing rates in both regions encode drift rate, with opposite encoding patterns. fMRI-based connectivity analyses further reveal that the strength of amygdala-dmPFC coupling correlates with individual differences in the modulator effect of perceptual ambiguity on drift rate. Together, these findings identify a corticolimbic network that dynamically modulates evidence accumulation during social-affective decision-making under perceptual ambiguity. By linking computational parameters to neural activity across multiple modalities, this work advances our understanding of how the brain resolves emotionally ambiguous perceptual information. It provides a translational framework for studying emotion recognition and decision-making impairments in clinical populations.