CLNCQMJul 11, 2025

Beyond vividness: Content analysis of induced hallucinations reveals the hidden structure of individual differences in visual imagery

arXiv:2507.09011v1h-index: 12
Originality Synthesis-oriented
AI Analysis

This research addresses individual differences in visual imagery for cognitive neuroscience, though it is incremental in applying existing tools to a new context.

The study analyzed Ganzflicker-induced hallucinations in over 4,000 participants to investigate how visual imagery differences affect hallucination content, finding that strong imagers described complex, naturalistic content while weak imagers reported simple geometric patterns.

A rapidly alternating red and black display known as Ganzflicker induces visual hallucinations that reflect the generative capacity of the visual system. Recent proposals regarding the imagery spectrum, that is, differences in the visual system of individuals with absent imagery, typical imagery, and vivid imagery, suggest these differences should impact the complexity of other internally generated visual experiences. Here, we used tools from natural language processing to analyze free-text descriptions of hallucinations from over 4,000 participants, asking whether people with different imagery phenotypes see different things in their mind's eye during Ganzflicker-induced hallucinations. Strong imagers described complex, naturalistic content, while weak imagers reported simple geometric patterns. Embeddings from vision language models better captured these differences than text-only language models, and participants with stronger imagery used language with richer sensorimotor associations. These findings may reflect individual variation in coordination between early visual areas and higher-order regions relevant for the imagery spectrum.

Foundations

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