Resting-state functional magnetic resonance imaging (fMRI) in Charles Bonnet syndrome

We aimed to investigate the pattern of visual activation in a patient with Charles Bonnet syndrome (CBS) using independent component analysis (ICA) on resting-state functional magnetic resonance imaging (fMRI). We used group ICA of fMRI toolbox software (http://mialab.mrn.org/software/gift) to extra...

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Bibliographic Details
Main Author: Marta Inês Beleza Nobre (author)
Format: masterThesis
Language:eng
Published: 2021
Subjects:
Online Access:https://hdl.handle.net/10216/139733
Country:Portugal
Oai:oai:repositorio-aberto.up.pt:10216/139733
Description
Summary:We aimed to investigate the pattern of visual activation in a patient with Charles Bonnet syndrome (CBS) using independent component analysis (ICA) on resting-state functional magnetic resonance imaging (fMRI). We used group ICA of fMRI toolbox software (http://mialab.mrn.org/software/gift) to extract the visual component of a 75-year-old woman with severe visual loss and complex visual hallucinations diagnosed as CBS. The visual component of this patient was calculated as a contiguous cluster over a Z-score threshold of 2, and compared with the corresponding component derived from a group of six healthy control subjects (mean age = 68 years; standard deviation = 8.7; range: 57-76 years). The spatial map of the patient's visual component mirrored an extensive network involving the primary, secondary, and visual association cortices, more pronounced than the observed in healthy control subjects. These results are consistent with the proposal that a lack of visual stimulation causes deafferentation resulting in increased excitability of the visual cortex. An increased activation of an ICA-derived visual component might, therefore, contribute as an additional measure useful for the clinical diagnosis of CBS.