Predictive biases in emotional perception: differential influence of mood and affective primes in individuals with and without mood disorders
Abstract
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. 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. 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. 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.
Related
- Dynamic Semantic–Prosodic Integration in Emotional Speech Perception: From Channel Dominance to Precision-Weighted Predictive Coding
- Enhanced Pitch Perception in Early Blind Individuals and Musicians Is due to Reduced Internal Noise
- The dynamic influence of exercise on emotional state among people with a history of mood disorder
- Predictive perception via simultaneous learning and inference
- Towards an analytical framework for investigating the neurophysiological influence of social context in speech perception
BibTeX
@article{leclerc2026predictive,
title = {{Predictive biases in emotional perception: differential influence of mood and affective primes in individuals with and without mood disorders}},
author = {Alexane Leclerc and Ladislas Nalborczyk and Louise Kauffmann and Yann Leprince and Josselin Houenou and Lucie Berkovitch and Pauline Favre},
journal = {Neuroscience of Consciousness},
year = {2026},
month = oct,
doi = {10.1093/nc/niag072},
url = {https://doi.org/10.1093/nc/niag072},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Predictive biases in emotional perception: differential influence of mood and affective primes in individuals with and without mood disorders
AU - Alexane Leclerc
AU - Ladislas Nalborczyk
AU - Louise Kauffmann
AU - Yann Leprince
AU - Josselin Houenou
AU - Lucie Berkovitch
AU - Pauline Favre
PY - 2026
DA - 2026/10/31
JO - Neuroscience of Consciousness
DO - 10.1093/nc/niag072
UR - https://doi.org/10.1093/nc/niag072
AB - 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. 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. 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. 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.
SN - 2057-2107
ER -