Predictive Biases in Emotional Perception: Differential Influence of Mood and Affective Primes in Individuals with and without Mood Disorders

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Introduction Predictive processing models perception as an interplay between top-down predictions and bottom-up sensory inputs. When signals are ambiguous, perception increasingly relies on prior expectations. In emotional contexts, mood and affective primes may act as endogenous and exogenous predictions, biasing emotional perception, particularly in mood disorders, where predictions may become overly strong or unstable.Methods Eighty-four participants (53 healthy controls, HC; 31 with self-reported mood disorders) completed an online affective priming task on unambiguous and ambiguous (morphs) facial expressions, preceded by masked or unmasked faces. Participants rated target emotions and completed mood questionnaires. Principal Component Analysis extracted latent mood dimensions. Drift Diffusion Modeling (DDM) estimated cognitive processes underlying ambiguous face perception. Results In HC and bipolar disorder (BD), happy primes increased positive morph categorization, while in depression (DEP), masked sad primes increased negative categorizations more than in HC and BD. Masked primes accelerated responses to morphs in HC, while BD showed faster responses regardless of priming type, with stronger facilitation than HC and DEP. No reaction time priming effects were observed in DEP. DDM revealed pre-decisional biases induced by primes, while mood only subtly influenced evidence accumulation. Conclusions Findings suggest group-specific predictive biases: HC used masked primes to resolve emotional ambiguity, BD showed stronger reliance on external cues regardless of priming type, and DEP showed reduced sensitivity to primes alongside a selective negativity categorization bias. These biases may underlie core clinical features of mood disorders and may point to new targets for interventions aiming to restore adaptive emotional inference.

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