False-alarm rate and inter-trial priming predict hallucination proneness in the Signal Detection Pareidolia Test

Pareidolia, the phenomenon of seeing faces in clouds, is a form of perceptual false alarm. The recently developed Noise Pareidolia Test (NPT) is used diagnostically to assess hallucination proneness in Parkinsonian psychosis patients (Yokoi et al., 2014). It utilizes images with salient (i.e., high signal) faces embedded in visual noise and pure-noise images. In the NPT, patient populations produce false alarms, but the general population does not. This suggests that hallucinations and pareidolia may share a common neural basis. Normal pareidolic processes in the general population may be amplified in patients. However, the NPT is not suited to test this hypothesis because it does not systematically illicit false alarms in the general population. To address this, we evaluated the Signal Detection Pareidolia Test (SDPT), designed to measure hallucination proneness across populations. In the SDPT, half of the images consist of gaussian-filtered 1/f noise. The rest of the images consist of noise with embedded faces. Four face signal-to-noise ratios are produced by mixing percentages of noise pixels (0.2, 0.35, 0.5, 0.65) with face pixels, and then applying a gaussian filter. In an online study, participants (N=57) viewed each image for 3 seconds before reporting yes-face or no-face. They then rated their confidence on a scale of 1-4. To measure hallucination proneness, participants completed the Cardiff Anomalous Perception Scale (CAPS). Results: two measures of the SDPT significantly correlated with hallucination proneness: 1) false-alarm rate (r=0.33, p=0.012) and 2) inter-trial priming (r=0.28, p=0.037), quantified by the conditional probability of reporting yes-face on trial N given a yes-face response on trial N-1. The first result validates that the SDPT can index hallucination proneness in the general population. The second result suggests that perceptual expectation plays a role in hallucination proneness. The latter finding supports a leading theory of hallucinogenesis (Sheldon et al., 2022).