Negative mood invites psychotic false perception in dementia

Pareidolia in a Built Environment as a Complex Phenomenological Ambiguous Stimuli

Pareidolia is a kind of misperception caused by meaningless, ambiguous stimuli perceived with meaning. Pareidolia in a built environment may trigger the emotions of residents, and the most frequently observed pareidolian images are human faces. Through a pilot experiment and an in-depth questionnaire survey, this research aims to compare built environmental pareidolian phenomena at different time points (6 a.m., 12 p.m., 2 a.m.) and to determine people’s sensitivity and reactions towards pareidolia in the built environment. Our findings indicate that the differences in stress level do not influence the sensitivity and reactions towards pareidolia in the built environment; however, age does, and the age of 40 seems to be a watershed. Females are more likely to identify pareidolian faces than males. Smokers, topers, and long-term medicine users are more sensitive to pareidolian images in the built environment. An unexpected finding is that most pareidolian images in built environments are much more easily detected in the early morning and at midnight but remain much less able to be perceived at midday. The results help architects better understand people’s reactions to pareidolia in the built environment, thus allowing them to decide whether to incorporate it appropriately or avoid it consciously in building design.

Pareidolia in Parkinson's Disease and Multiple System Atrophy

Pareidolia is a visual illusion of meaningful objects that arise from ambiguous forms embedded in visual scenes. Previous studies showed that pareidolias are frequently observed in patients with Parkinson's disease (PD) as well as dementia with Lewy bodies. However, whether pareidolias are useful for differentiating PD from other neurodegenerative parkinsonism disorders including multiple system atrophy (MSA) is unclear. The noise pareidolia test (NPT) was performed in 40 and 48 patients with PD and MSA, respectively. A receiver operating characteristic (ROC) curve analysis was used to evaluate sensitivity and specificity. Results of neuropsychological tests were also compared between patients with PD with and without pareidolias. Visual hallucinations were present in none of the subjects. Pareidolic response in the NPT was observed in 47.5% and 18.8% of patients with PD and MSA, respectively. The number of pareidolic responses in patients with PD was significantly larger compared with patients with MSA (P=0.001). ROC curve analyses showed the sensitivity and specificity at 33% and 98%, respectively. Among patients with PD, those with pareidolias demonstrated higher State-Trait Anxiety Inventory-state (P=0.044) and State-Trait Anxiety Inventory-trait (P=0.044) than those without pareidolias. Pareidolias can be found in patients with PD without visual hallucinations, and the pareidolia test may be a highly specific test for differentiating PD from MSA. Thus, anxiety may be associated with pareidolias in patients with PD.

Prestimulus Low-Alpha Frontal Networks Are Associated with Pareidolias in Parkinson's Disease

Background: Pareidolias are visual phenomena wherein ambiguous, abstract forms or shapes appear meaningful due to incorrect perception. In Parkinson's disease (PD), patients susceptible to visual hallucinations experience visuo-perceptual deficits in the form of pareidolias. Although pareidolias necessitate top-down modulation of visual processing, the cortical dynamics of internally generated perceptual priors on these visual misperceptions is unknown. Objectives: To study prestimulus-related electroencephalography (EEG) spectral and network abnormalities in PD patients experiencing pareidolias. Methods: Twenty-one PD in-patients and 10 age-matched controls were evaluated. Neuropsychological assessments included tests for cognition, attention, and executive functions. Pareidolias were quantified by using the "noise pareidolia test" with simultaneous EEG recording. The PD patients were subdivided into two groups-those with high pareidolia counts (n = 10) and those without (n = 11). The EEG was analyzed 1000 msec before stimulus presentation in the spectral domain (theta, low-alpha, and high-alpha frequencies) with corresponding graph networks to evaluate network properties. Statistical analysis included analysis of variance and multiple regression to evaluate the differences. Results: The PD patients with high pareidolia counts were older with lower scores on neuropsychological tests. Their prestimulus EEG low-alpha band showed a tendency toward higher frontal activity (p = 0.07). Graph networks showed increased normalized clustering coefficient (p = 0.05) and lower frontal degree centrality (p = 0.005). These network indices correlated positively to patients' pareidolia scores. Discussion: We suggest that pareidolias in PD are a consequence of an abnormal top-down modulation of visual processing; they are defined by their frontal low-alpha spectral and network alterations in the prestimulus phase due to a dissonance between patients' internally generated mental processing with external stimuli. Impact statement Pareidolias in Parkinson's disease (PD) are considered to be promising early markers of visual hallucinations and an indicator of PD prognosis. In certain susceptible PD patients, pareidolias can be evoked and studied. Here, via electroencephalography, we aimed at understanding this visual phenomenon by studying how neural information is processed before stimulus presentation in such patients. Using spectral and graph network measures, we revealed how top-down modulated internally generated processes affect visual perception in patients with pareidolias. Our findings highlight how prestimulus network alterations in the frontal cortex shape poststimulus pareidolic manifestations in PD.

Pareidolia in Schizophrenia and Bipolar Disorder

While there are many studies on pareidolia in healthy individuals and patients with schizophrenia, to our knowledge, there are no prior studies on pareidolia in patients with bipolar disorder. Accordingly, in this study, we, for the first time, measured pareidolia in patients with bipolar disorder (N = 50), and compared that to patients with schizophrenia (N = 50) and healthy controls (N = 50). We have used (a) the scene test, which consists of 10 blurred images of natural scenes that was previously found to produce illusory face responses and (b) the noise test which had 32 black and white images consisting of visual noise and 8 images depicting human faces; participants indicated whether a face was present on these images and to point to the location where they saw the face. Illusory responses were defined as answers when observers falsely identified objects that were not on the images in the scene task (maximum illusory score: 10), and the number of noise images in which they reported the presence of a face (maximum illusory score: 32). Further, we also calculated the total pareidolia score for each task (the sum number of images with illusory responses in the scene and noise tests). The responses were scored by two independent raters with an excellent congruence (kappa > 0.9). Our results show that schizophrenia patients scored higher on pareidolia measures than both healthy controls and patients with bipolar disorder. Our findings are agreement with prior findings on more impaired cognitive processes in schizophrenia than in bipolar patients.

Illusions, hallucinations, and visual snow

Illusions and hallucinations are commonly encountered in both daily life and clinical practice. In this chapter, we review definitions and possible underlying mechanisms of these phenomena and then review what is known about specific conditions that are associated with them, including ophthalmic causes, migraine, epilepsy, Parkinson's disease, and schizophrenia. We then discuss specific syndromes including the Charles Bonnet syndrome, visual snow syndrome, Alice in Wonderland syndrome, and peduncular hallucinosis. The scientific study of illusions and hallucinations has contributed significantly to our understanding of how eye and brain process vision and contribute to perception. Important concepts are the distinction between topologic and hodologic mechanisms underlying hallucinations and the involvement of attentional networks. This chapter examines the various ways in which pathological illusions and hallucinations might arise in relation to the phenomenology and known pathology of the various conditions associated with them.