Nonretinal vision is a term for visual experience in the absence of visual stimulation (e.g., visual imagery, visual working memory). Many previous studies have found that humans can use nonretinal vision to influence perceptual task performance (e.g., holding the identity of an upcoming target in mind prior to visual search), but different studies have made vastly different conclusions about the extent of this influence. One issue is that individual differences in nonretinal vision are rarely taken into account, but they may greatly impact perception. For example, there is a wide spectrum of visual imagery vividness: on one end, there are people who cannot visualize even concrete objects (aphantasia). On the other end, some people have such strong imagery that it can interfere with visual perception (hyperphantasia). The main goal of this project is to investigate the extent to which individual differences in sensory mental representations influence (and are influenced by) visual perception.


Anomalous perception

Previous studies have proposed a link between modal imagery vividness and hallucination proneness in pathology (Aleman et al., 2000; Aleman & de Haan, 2004). Exploring the relationship between visual imagery and anomalous perception in normative samples (in the absence of pathology) will provide much-needed insight about top-down factors that contribute to hallucinatory experience. My research therefore focuses on inducing pseudo-hallucinatory experiences using visual noise (pareidolia) and visual flicker (Ganzflicker) paradigms. Currently, I am interested in categorical differences in the likelihood to experience vivid and complex pseudo-hallucinations in people with different visual imagery abilities, such as aphantasia.

A breakdown of the likelihood to experience pseudo-hallucinations (PH) across different imagery vividness ratings from 0 (complete aphantasia) to 10 (extremely vivid imagery). PH-Y (salmon color) refers to the number of individuals who saw PH at some point while observing the Ganzflicker, whereas PH-N (gray color) displays the number of individuals who did not see PH. A logistic regression line in blue indicates the probability of seeing PH: about 60% probability for aphants and about 95% probability for people with vivid imagery. Blue shading around the line shows the 95% confidence intervals. Individual data points (blue dots, jittered) are shown above and below the bars.