Mapping mental representations of fear-relevant stimuli through similarity modeling

Anxiety disorders involve maladaptive responses to fear, yet the underlying mental representations remain poorly understood. Traditional approaches have typically relied on predetermined psychological dimensions, limiting the characterization of underlying representations. Focusing on arachnophobia as a model condition, we used a similarity-based approach to reveal mental representations of spider-related images. From 705 individuals, we analyzed 49,141 pairwise similarity judgments among 314 spider-related images, constituting the largest dataset of its kind. Multidimensional Scaling identified a 5-dimensional representational space, with four dimensions strongly predicting fear ratings, and capturing a substantial amount of variance relevant to spider-related fear. These findings indicate that fear-related representations are structured along specific dimensions with complex information that cannot be reduced to conventional predetermined dimensions, such as fear and disgust. Our approach provides a scalable and flexible framework for studying fear-related representations, offering potential applications for refining exposure therapy and anxiety treatment strategies.