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Multimodal MRI of fear network in panic disorder / 中华行为医学与脑科学杂志
Chinese Journal of Behavioral Medicine and Brain Science ; (12): 1051-1056, 2021.
Article in Chinese | WPRIM | ID: wpr-909564
ABSTRACT
The etiology and pathological mechanism of panic disorder (PD) are still unclear, which hinders the development of clinical diagnosis and treatment. In order to clarify the pathogenesis, biological diagnostic markers, curative effect prediction of PD, and ultimately provide a basis for individualized treatment, this article reviews the magnetic resonance imaging (MRI) research on PD in the past 5 years in conjunction with the hypothesis of the " fear network model" . It is found that the brain function and structural abnormalities of PD patients are not limited to the classic " fear network model" , but also a wider range of brain areas such as the cingulate gyrus, fronto-temporal cortex, insula, striatum, thalamus, sensorimotor related brain regions and cerebellum, together with classic brain regions such as the amygdala, form an expanded fear network. Among them, the amygdala, insula, medial prefrontal lobe, somato-motor network (SMN) and cerebellum are specific brain areas that differentiate PD from other anxiety disorders. The changes in the activity of the frontal lobe-limbic loop included in the fear network model can predict the treatment outcome of different methods for PD. This article improved the fear network hypothesis of PD, and more accurately identifies the biological indicators that can be used for accurate diagnosis and efficacy prediction of PD, which lays the foundation for the ultimate realization of personalized diagnosis and treatment of PD.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Behavioral Medicine and Brain Science Year: 2021 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Behavioral Medicine and Brain Science Year: 2021 Type: Article