What Shapes the Content of Charles Bonnet Hallucinations?

A new analysis explains how predictive processing shapes the content of visual hallucinations in Charles Bonnet Syndrome, suggesting that learned expectations sculpt bursts of neural activity into persistent hallucinations. The theory builds on deafferentation and predictive processing to account for why hallucinations often relate to specific activities or contexts.

Charles Bonnet Syndrome /us/basics/charles-bonnet-syndrome What Shapes the Content of Charles Bonnet Hallucinations? How predictive processing may help to explain visual hallucinations in CBS. Posted July 7, 2026 Reviewed by Monica Vilhauer Ph.D. /us/docs/editorial-process Key points - Deafferentation theory proposes that loss of sensory input plays a role in Charles Bonnet hallucinations. - Predictive processing suggests that learned expectations influence the form taken by hallucinations. - Learned expectations may sculpt bursts of neural activity into persistent hallucinations. People whose sight loss is the result of damage to incoming sensory pathways to the brain may develop the visual hallucinations of Charles Bonnet Syndrome CBS . The primary feature of CBS is complex visual hallucinations: fully formed animate or inanimate objects that are unrelated to serious psychiatric https://www.psychologytoday.com/us/basics/psychiatry disorders Altieri & Battaglini, 2026; Pang, 2016 . In fact, people with CBS typically show full or partial “insight into the unreality of their hallucinations.” For about two years after the onset of my blindness, I hallucinated people, bicycles, pillows, and plants. The hallucinations that intrigued me most were those that occurred repeatedly when I performed certain activities. For instance, when I was learning to use a white cane, I sometimes found myself in the middle of a crowd of hallucinated white-cane learners. And for a time, I hallucinated a keyboard in front of me whenever I used my laptop. Why did I repeatedly have those particular hallucinations? And why do I no longer have them? In this post, I will discuss current thinking in vision science to explore possible answers to those questions. How the Visual System Works Visual perception in sighted people begins when light activates sensory receptors in the eyes. The activated receptors produce neural https://www.psychologytoday.com/us/basics/neuroscience signals that are transmitted to visual areas in the cerebral cortex—the large outer layer of the brain Mars et al., 2025 . The brain’s visual system is organized hierarchically Powers et al., 2016 . The “early visual cortex” i.e., the first areas receiving sensory input from the eyes specialize in processing basic features of incoming sensory signals. The “later visual cortex” i.e., visual areas in upper levels of the hierarchy specialize in processing increasingly abstract and complex features of sensory input. For example, Dominic Ffytche and colleagues 1998 showed that the content of CBS hallucinations corresponded to the perceptual features typically processed by the higher-level cortical areas active during the hallucinations. For example, when someone hallucinated a face, an area specialized to perceive faces was active. But no visual area is ever solely responsible for constructing a particular “visual percept” a conscious visual perception . The visual system operates as a highly integrated network. Information flows in both directions, with many “back-and-forth” interactions occurring between visual areas at different levels of the hierarchy Powers et al., 2016 . The two-way flow of information serves as the basis for two interdependent perceptual processes: - Bottom-up processing analyzes the incoming sensory information into its component perceptual features. - Top-down processing refers to the use of prior knowledge to reduce ambiguity in incoming sensory signals. This view of perception assumes that the processing of sensory input involves interpretation, not reproduction, of what the eyes are looking at. For example, after hearing about a person’s encounter with a poisonous desert snake, you might become sensitized to this possibility when walking along a desert trail. You may even briefly misinterpret a fallen tree branch as a snake. An approach known as “predictive processing” may help to explain this experience Clark, 2024; Peelen et al., 2024 . Your brain may have used past experiences to predict the sensory input that would occur if an object was a snake. Your brain then would evaluate the degree of mismatch between the predicted sensory evidence and the actual sensory evidence. If the mismatch was minimal, your visual system might see a snake. A second look might lead you to revise your prediction, so that you now saw the tree branch. Predictive-processing theory views conscious visual perceptions as the brain’s best guess about what the eyes are looking at. Predictive Processing and CBS Hallucinations CBS hallucinations may be explained by combining two theories: predictive-processing theory and “deafferentation theory” Altieri & Battaglini, 2026; Marschall et al., 2020 . “Deafferentation” refers to the loss of sensory input to perceptual areas in the brain. CBS hallucinations have long been attributed to deafferentation Burke, 2002; Painter et al., 2018 . Some have hypothesized that deafferentation hallucinations are due to changes in the relative influence of bottom-up and top-down processing Marschall et al., 2020 . It may be that the visual system compensates for the loss of sensory input by becoming more easily activated. The changes required for lowering the threshold for activation may create instability in the network. For instance, it may result in the early visual cortex becoming “hyperexcitable,” perhaps even generating its own activity without external sensory input. This spontaneous activity may produce hallucinations. But deafferentation alone cannot explain the content of visual hallucinations Altieri & Battaglini, 2026 . How can hyperexcitable visual areas explain why I repeatedly experienced the same keyboard hallucination each time I used my laptop? Why did I not hallucinate a piano, a cash register, or a furry kitten? It may be that the instability following deafferentation created conditions that facilitated hallucinations. Predictive processing theory may help to explain the form taken by deafferentation-induced activity Altieri & Battaglini, 2026 . Predictive Processing and Hyperexcitability Typing is a well-learned activity. Preparing to type may have created a context that led my brain to expect that a keyboard was in front of me. From this expectation and my many sighted experiences with typing, my brain could have predicted the sensory evidence i.e., the tactile, auditory, visual, and proprioceptive signals that should accompany typing behavior. My brain then may have evaluated the degree of mismatch between the predicted and the actual sensory evidence. If the mismatch was minimal, my brain would have inferred that a keyboard was in front of me. This inference, coupled with the action of turning my face towards the location of the keyboard, may have influenced the visual network to shape internally generated sensory signals into a hallucinated keyboard. This proposed explanation echoes the claim by Albert Powers and colleagues that “we perceive what would need to be present in order for our sensations to make sense.” My CBS hallucinations eventually disappeared, as they do for most people. The brain exhibits neural “plasticity”—it is able to reorganize itself, thereby adjusting to disruptions of its structural and functional organization. In many cases, this reorganization would reduce the instability that may have made hallucinations possible. References Altieri, E., & Battaglini, L. 2026 . Beyond Hyperexcitability: A Review of Neural Mechanisms in Charles Bonnet Syndrome. NeuroSci, 7 2 , Article 31. https://doi.org/10.3390/neurosci7020031 https://doi.org/10.3390/neurosci7020031 Clark, A. 2024 . The experience machine: How our minds predict and shape reality . Random House. Ffytche, D. H., Howard, R. J., Brammer, M. J., David, A., Woodruff, P. W. R., & Williams, S. 1998 . The anatomy of conscious vision: An fMRI study of visual hallucinations . Nature Neuroscience, 1 8 , 738–742. https://doi.org/10.1038/3738 https://doi.org/10.1038/3738 Mars, J. A., Rojas, L. C., & Gurnani, B. 2025, December 13 . Charles Bonnet Syndrome . In StatPearls . StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK585133/ https://www.ncbi.nlm.nih.gov/books/NBK585133/ Marschall, T. M., Brederoo, S. G., Ćurčić-Blake, B., & Sommer, I. E. C. 2020 . Deafferentation as a cause of hallucinations. Current Opinion in Psychiatry, 33 3 , 206–211. https://doi.org/10.1097/YCO.0000000000000586 https://doi.org/10.1097/YCO.0000000000000586 Pang, L. 2016 . Hallucinations Experienced by Visually Impaired: Charles Bonnet Syndrome. Optometry and Vision Science, 93 12 , 1466–1478. https://doi.org/10.1097/OPX.0000000000000959 https://doi.org/10.1097/OPX.0000000000000959 Peelen, M. V., Berlot, E., & de Lange, F. P. 2024 . Predictive processing of scenes and objects. Nature Reviews Psychology, 3 1 , 13–26. https://doi.org/10.1038/s44159-023-00254-0 https://doi.org/10.1038/s44159-023-00254-0 Powers, A. R., III, Kelley, M., & Corlett, P. R. 2016 . Hallucinations as Top-Down Effects on Perception. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 1 5 , 393–400. https://doi.org/10.1016/j.bpsc.2016.04.003 https://doi.org/10.1016/j.bpsc.2016.04.003