Neural correlates of evidence accumulation in social-affective decision-making under perceptual ambiguity

Evidence accumulation models have been successfully applied to decision-making in sensory and cognitive domains; however, it remains unclear how this process is regulated when perceptual ambiguity arises from social-affective content. Here, we integrate computational modeling with multimodal neuroscience to characterize how perceptual ambiguity in emotion judgment shapes decision dynamics. Participants viewed perceptually ambiguous stimuli – morphed images of two categories, such as happy and fearful facial expression – and made binary categorization decisions. Using drift diffusion modeling (DDM), we first demonstrate that drift rate, a key index of evidence accumulation, decreases as perceptual ambiguity increases. Scalp electroencephalography (EEG) data reveal that the magnitude of the late positive potential (LPP) tracks the speed of evidence accumulation in both emotional and non-emotional stimulus categories, but only when the ambiguous dimension is relevant to the categorization decision. Similar to LPP magnitude, single-unit recordings from the dorsomedial prefrontal cortex (dmPFC) and amygdala show that neuronal firing rates in both regions also encode drift rate during the emotion categorization task. Moreover, fMRI-based functional connectivity reveals that the strength of connectivity between the amygdala and dmPFC correlates with individual differences in drift rate. To establish the causal role of the dmPFC, we applied anodal transcranial direct current stimulation (tDCS) targeting the dmPFC in patients with schizophrenia and found that stimulation enhanced evidence accumulation speed in emotion categorization under perceptual ambiguity. These findings identify a distributed corticolimbic circuit that dynamically modulates evidence accumulation during social-affective decision-making under perceptual ambiguity. Our results bridge social-affective and perceptual neuroscience, offering a translational framework for understanding emotion recognition and decision-making impairments.