Functional Decoupling of Language and Self-Reference Networks in Patients with Persistent Auditory Verbal Hallucinations

Background: Accumulating neuroimaging evidence suggests that abnormal intrinsic neural activity could underlie auditory verbal hallucinations (AVH) in patients with schizophrenia. However, little is known about the functional interplay between distinct intrinsic neural networks and their association...

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Veröffentlicht in:Neuropsychobiology 2020-07, Vol.79 (4-5), p.345-351
Hauptverfasser: Kubera, Katharina M., Wolf, Nadine D., Rashidi, Mahmoud, Hirjak, Dusan, Northoff, Georg, Schmitgen, Mike M., Romanov, Dmitry V., Sambataro, Fabio, Frasch, Karel, Wolf, Robert Christian
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Sprache:eng
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Zusammenfassung:Background: Accumulating neuroimaging evidence suggests that abnormal intrinsic neural activity could underlie auditory verbal hallucinations (AVH) in patients with schizophrenia. However, little is known about the functional interplay between distinct intrinsic neural networks and their association with AVH. Methods: We investigated functional network connectivity (FNC) of distinct resting-state networks as well as the relationship between FNC strength and AVH symptom severity. Resting-state functional MRI data at 3 T were obtained for 14 healthy controls and 10 patients with schizophrenia presenting with persistent AVH. The data were analyzed using a spatial group independent component analysis, followed by constrained maximal lag correlations to determine FNC within and between groups. Results: Four components of interest, comprising language, attention, executive control networks, as well as the default-mode network (DMN), were selected for subsequent FNC analyses. Patients with persistent AVH showed lower FNC between the language network and the DMN (p < 0.05, corrected for false discovery rate). FNC strength, however, was not significantly related to symptom severity, as measured by the Psychotic Symptom Rating Scale. Conclusion: These findings suggest that disrupted FNC between a speech-related system and a network subserving self-referential processing is associated with AVH. The data are consistent with a model of disrupted self-attribution of speech generation and perception.
ISSN:0302-282X
1423-0224
DOI:10.1159/000507630