Harmonized framework for aspects of visual perception relevant to hallucinations

Descending influences are shown in blue, and ascending are shown in red. Horizontal influences are in green. The grey blur over memory, context, emotion, and intention indicates that these factors interact to create complex expectancies. Linking arrows show the specific relationships between concepts while recognizing that the influence of these varies dynamically. The level of detail for each function reflects the need to incorporate distinctions in existing theories; thus, perception and attention are much more fractionated than memory or context. Expectancies act to bias perception and can be conceptualized as brain states that reflect prior information about what is possible or probable in the forthcoming sensory environment, ie, what is expected to be seen in that context (Parr T, Rees G, Friston KJ. Computational neuropsychology and Bayesian inference. Front Hum Neurosci 2018;12:61.). Predictions of sensory-level data are central to state models; in contrast, trait models emphasize higher-order expectances that develop from an interaction between (1) memories of past similar visual environments (memory expectancies), (2) the current visual context (context expectancies), (3) future intentions and motivations (intentional and motivational expectancies), and (4) emotions (emotional expectancies). Emphasizing the circular interactions between these functions, the visual context is created from inputs arising from current visual (and other sensory) perceptions. In addition to their direct role in modifying predicted data, expectancies also indirectly affect sensory data gathering and processing via attention. (Source: Collerton D, Barnes J, Diederich NJ, et al. Understanding visual hallucinations: a new synthesis. Neurosci Biobehav Rev 2023;150:105208. Creative Commons Attribution [CC BY] license.)