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bioRxiv · 10.1101/2022.07.15.500190

Resting State Neural Networks at Complex Visual Hallucinations in Charles Bonnet Syndrome

Abstract

BackgroundCharles Bonnet syndrome (CBS) is a prototype phenomenon for investigating complex visual hallucination. Our research focuses on resting state neural networks features of CBS patients with a comparison of patients with equally matched visual loss and healthy subjects in order to investigate the mechanism behind complex visual hallucinations. Material and MethodsFour CBS patients CBS(+), three patients with visual loss but no visual hallucinations CBS(-) and 15 healthy individuals (HS) undergo resting state fMRI recordings and their resting state data is analyzed for Default Mode Network (DMN) changes through dual regression analysis. Cognitive functions of the participants were also evaluated through Mini Mental State Examination and University of Miami - Parkinsons Disease Hallucination Questionnaire (um-PDHQ) ResultsAlthough we found no difference in Default Mode Networks between CBS(-) and CBS(+), and between the CBS(-) and HC groups, we detected decreased connectivity in CBS(+) compared to the HC group especially in visual heteromodal association centers (bilateral lateral occipital gyrus, bilateral lingual gyrus, occipital pole, right medial temporal cortex, right temporo-occipital cortex) when left angular gyrus was selected as ROI. Similarly, we detected decreased connectivity in CBS(+) compared to HC in right medial frontal gyrus, right posterior cingulate gyrus, left inferior temporal gyrus, right supramarginal gyrus, and right angular gyrus when selected right superior frontal gyrus as ROI. In contrast, increased connectivity was detected in CBS +compared to HC, in bilateral occipital poles, bilateral occipital fusiform gyrus, bilateral intracalcarine cortex, right lingual gyrus and precuneus regions when left medial temporal gyrus was selected as ROI. ConclusionOur findings suggest a combined mechanism in CBS related to increased internal created images caused by decreased visual external input causing visual hallucinations as well as impaired frontotemporal resource tracking system that together impair cognitive processing.

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BibTeXRIS

Hanoglu, T., Velioglu, H. A., Salar, B. A., Yıldız, S., Bayraktaroglu, Z., Yulug, B., Hanoglu, L.. 2022-07-16. Resting State Neural Networks at Complex Visual Hallucinations in Charles Bonnet Syndrome. https://doi.org/10.1101/2022.07.15.500190

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