The network characteristics in schizophrenia with prominent negative symptoms: a multimodal fusion study.
Li KongYao ZhangXu-Ming WuXiao-Xiao WangHai-Su WuShuai-Biao LiMin-Yi ChuYi WangSai Yu Simon LuiQin-Yu LvZheng-Hui YiRaymond C K ChanPublished in: Schizophrenia (Heidelberg, Germany) (2024)
Previous studies on putative neural mechanisms of negative symptoms in schizophrenia mainly used single modal imaging data, and seldom utilized schizophrenia patients with prominent negative symptoms (PNS).This study adopted the multimodal fusion method and recruited a homogeneous sample with PNS. We aimed to identify negative symptoms-related structural and functional neural correlates of schizophrenia. Structural magnetic resonance imaging (sMRI) and resting-state functional MRI (rs-fMRI) were performed in 31 schizophrenia patients with PNS and 33 demographically matched healthy controls.Compared to healthy controls, schizophrenia patients with PNS exhibited significantly altered functional activations in the default mode network (DMN) and had structural gray matter volume (GMV) alterations in the cerebello-thalamo-cortical network. Correlational analyses showed that negative symptoms severity was significantly correlated with the cerebello-thalamo-cortical structural network, but not with the DMN network in schizophrenia patients with PNS.Our findings highlight the important role of the cerebello-thalamo-cortical structural network underpinning the neuropathology of negative symptoms in schizophrenia. Future research should recruit a large sample and schizophrenia patients without PNS, and apply adjustments for multiple comparison, to verify our preliminary findings.
Keyphrases
- bipolar disorder
- resting state
- magnetic resonance imaging
- functional connectivity
- computed tomography
- high resolution
- ejection fraction
- depressive symptoms
- machine learning
- chronic pain
- prognostic factors
- chronic kidney disease
- deep learning
- pain management
- network analysis
- artificial intelligence
- photodynamic therapy