How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study
A recent neuroimaging study investigates how humans process AI-generated hallucinations. The research reveals distinct neural dynamics when individuals encounter hallucinated versus non-hallucinated content. Findings suggest that misjudged hallucinations do not activate the typical neurocognitive pathways for fact verification.
- ▪The study involved 27 participants who performed a verification task on image descriptions generated by a multi-modal large language model.
- ▪Distinct cognitive processes such as semantic integration and memory retrieval were observed in response to hallucinated content.
- ▪Neural responses differed significantly between misjudged and correctly judged hallucinations, indicating a failure to trigger standard verification pathways.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.16953 |
| Publication time | Tue, 19 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-19T04:04:57.272Z |
| Last seen | 2026-05-19T04:04:57.272Z |
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Computer Science > Artificial Intelligence arXiv:2605.16953 (cs) [Submitted on 16 May 2026] Title:How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study Authors:Shuqi Zhu, Yi Zhong, Ziyi Ye, Bangde Du, Yujia Zhou, Qingyao Ai, Yiqun Liu View a PDF of the paper titled How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study, by Shuqi Zhu and 6 other authors View PDF HTML (experimental) Abstract:While AI-generated hallucinations pose considerable risks, the underlying cognitive mechanisms by which humans can successfully recognize or be misled by these hallucinations remain unclear. To address this problem, this paper explores humans' neural dynamics to characterize how the brain processes hallucinated content.
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