Ambiguity in vocal expression perception: Evidence from voice morphing and its electrophysiological correlates

• Combined EEG, voice morphing, ERP, mTRF and MVPA to unravel neural mechanisms of ambiguous attitudinal vocal expression processing. • Pinpointed LSN (700–1600 ms) as the core neural signature distinguishing ambiguous from typical attitudinal voices. • Discovered early–late functional coupling, challenging serial models by linking acoustic encoding to late socio-cognitive inference. • Dissociated acoustic-driven (N1/P2) and valence-specific (LSN) effects via covariate-controlled LMM and mTRF analyses. • Extended multi-stage prosody models to attitudinal processing, integrating ambiguity in real-world social communication. Vocal attitudes (e.g., confidence, desire) convey rich acoustic cues that transmit speaker's intentions and beliefs, playing a pivotal role in natural speech communication. Neurocognitive research has largely centered on inferring attitudes from voices with unambiguous, clearly defined meanings (“typical voices”), while the neural mechanisms underlying ambiguous voices remain underexplored—particularly compared to vocal emotions, leaving a critical gap in understanding paralinguistic socio-cognitive processing. Here, we employed voice morphing to blended two typical attitudinal voices of opposing valences, recording participants’ valence ratings and electroencephalographic (EEG) responses. Data analysis combined conventional ERP analysis using linear mixed-effects modeling on single-trial data with multivariate approaches (multivariate temporal response function mTRF, multivariate pattern analysis MVPA). Behaviorally, ambiguous voices elicited longer reaction times and intermediate valence ratings. Neurally, ambiguous voices showed a P2 (274–324 ms) resembling positive voices, an N400-like negativity (400–450 ms) resembling negative voices, and a robust a Late Sustained Negativity (LSN; 700–1600 ms) distinct from typical voices. Controlling for acoustic parameters eliminated early effects (N1/P2/N4), confirming they reflect acoustic processing, while the LSN persisted—indexing neural responses to attitudinal ambiguity. mTRF validated stronger late-stage neural tracking of ambiguous voices after accounting for acoustics; MVPA revealed cross-temporal early-late functional coupling between acoustic encoding and pragmatic inference. Together, these findings demonstrate the brain treats ambiguous attitudinal prosody as a distinct category, engaging a specialized cascade: enhanced early acoustic discrimination, graded valence evaluation, refined semantic processing, and effortful pragmatic inference. This work extends multi-stage models from emotional to attitudinal prosody, challenging strictly serial accounts by highlighting interactive neural dynamics in ambiguity resolution.