Prioritized neural computations of socially-relevant signals during perceptual decision-making

Abstract

AbstractSocially-relevant signals benefit from prioritized processing, from initial orientation to behavioral choice elaboration. Yet it remains unclear whether such prioritized processing engages specific or similar neural computations as the processing of non-social cues during decision-making. Here, we developed a novel behavioral paradigm in which participants performed two different detection tasks on the same, two-dimensional visual stimuli. We presented morphed facial displays of emotion (from neutral to angry) on top of a morphed colored background (from grey to violet). Participants reported the presence or absence of either emotion (anger) or color (violet) in the stimulus, while ignoring the other task-irrelevant dimension. Importantly, we equalized detection sensitivity across dimensions using an adaptive titration procedure. Computational modeling of electroencephalographic (EEG) activity first revealed that premotor EEG activity scales with the amount of perceptual evidence earlier, around 150ms, when the decision concerns emotion rather than color. Second, participant choice was decoded earlier during emotion (260ms) than color decisions in band-limited EEG power in the same premotor regions. Third, these two effects varied across participants as a function of their social anxiety. Together, these findings indicate that emotion cues benefit from a prioritized neural coding in action-selective brain regions, further supporting their motivational value.