How people estimate the prevalence of aphantasia and hyperphantasia in the population

Consciousness and Cognition. 2025. Vol. 133. Article 103906.

Blazhenkova O., Kotov A. A., Kotova T.

This study examined how people estimate the prevalence of aphantasia (extreme lack of visual imagery) and hyperphantasia (extreme abundance of visual imagery) in the population and how their own imagery and verbal skills’ evaluations predict these estimations. Participants read the descriptions of extreme imagery and evaluated the percentage of individuals within a population to whom they apply. They also completed questionnaires assessing their cognitive skills and experiences related to imagery. We also assessed evaluations of sensory sensitivity as a related individual difference domain. The findings revealed significantly higher prevalence estimates for hyperphantasia than aphantasia in both population-level and self-rated measures. Consistently, these evaluations showed a shift toward positive values for object imagery skills, while no such pattern was observed for spatial imagery or verbal skills. Participants estimated the prevalence of hyperphantasia in the population at 37–53 % and aphantasia at 27–32 %, far exceeding the rates in the literature (approximately 3 % for hyperphantasia and 1 % for aphantasia) and their own vividness ratings. A similar trend was observed for sensitivity. Higher self-rated object imagery skills, but not spatial imagery or verbal skills, predicted higher population hyperphantasia estimates. Additionally, population-level measures from both the imagery and sensitivity domains predicted the estimated rates of both hyperphantasia and aphantasia in the population. Our work contributes to the understanding of public perceptions of visual-spatial cognitive diversity and suggests that self-observed traits may shape beliefs about the prevalence of these traits in the general population.

Keywords: imagination, aphantasia

Publication based on the results of: Cognitive processes in the information environment: phenomena and explanatory models (2025)