functional mri
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Peerapon Kiatkittikul ◽  
Chetsadaporn Promteangtrong ◽  
Anchisa Kunawudhi ◽  
Dheeratama Siripongsatian ◽  
Taweegrit Siripongboonsitti ◽  
Fdg Pet ◽  

2022 ◽  
Joseph Kuchling ◽  
Betty Jurek ◽  
Mariya Kents ◽  
Jakob Kreye ◽  
Christian Geis ◽  

Introduction: While decreased hippocampal connectivity and disruption of functional networks are established MRI features in human anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis, the underlying pathophysiology for brain network alterations remains poorly understood. Application of patient-derived monoclonal antibodies against the NR1 subunit of the NMDAR allows for the investigation of potential functional connectivity alterations in experimental murine NMDAR antibody disease models. Objective: To explore functional connectivity changes in NR1 antibody mouse models using resting-state functional MRI (rs-fMRI). Methods: Adult C57BL/6J mice (n=10) were intrathecally injected with a recombinant human NR1 antibody over 14 days and then studied using rs-fMRI at 7 Tesla. In addition, a newly established mouse model with in utero exposure to a human recombinant NR1 antibody characterized by a neurodevelopmental disorder (NR1-offspring) was investigated with rs-fMRI at the age of 8 weeks (n=15) and 10 months (n=14). Mice exposed to isotype-matched control antibodies served as controls. Independent component analysis (ICA) and dual regression analysis were performed to compare functional connectivity between NMDAR antibody mouse models and control mice. Results: Adult NR1-antibody injected mice showed significantly impaired functional connectivity within the dentate gyrus of the left hippocampus in comparison to controls, resembling impaired hippocampal functional connectivity patterns observed in human patients with NMDAR encephalitis. Similarly, analyses showed significantly reduced functional connectivity in the dentate gyrus in NR1-offspring compared after 8 weeks, and impaired connectivity in the dentate gyrus and CA3 hippocampal subregion in NR1-offspring at the age of 10 months. Conclusion: Functional connectivity changes within the hippocampus resulting from both direct application and in utero exposure to NMDAR antibodies can be modeled in experimental murine systems. With this translational approach, we successfully reproduced functional MRI alterations previously observed in human NMDAR encephalitis patients. Future experimental studies will identify the detailed mechanisms that cause functional network alterations and may eventually allow for non-invasive monitoring of disease activity and therapeutic effects in autoimmune encephalitis.

2022 ◽  
Vol 15 ◽  
Ying Chu ◽  
Guangyu Wang ◽  
Liang Cao ◽  
Lishan Qiao ◽  
Mingxia Liu

Resting-state functional MRI (rs-fMRI) has been widely used for the early diagnosis of autism spectrum disorder (ASD). With rs-fMRI, the functional connectivity networks (FCNs) are usually constructed for representing each subject, with each element representing the pairwise relationship between brain region-of-interests (ROIs). Previous studies often first extract handcrafted network features (such as node degree and clustering coefficient) from FCNs and then construct a prediction model for ASD diagnosis, which largely requires expert knowledge. Graph convolutional networks (GCNs) have recently been employed to jointly perform FCNs feature extraction and ASD identification in a data-driven manner. However, existing studies tend to focus on the single-scale topology of FCNs by using one single atlas for ROI partition, thus ignoring potential complementary topology information of FCNs at different spatial scales. In this paper, we develop a multi-scale graph representation learning (MGRL) framework for rs-fMRI based ASD diagnosis. The MGRL consists of three major components: (1) multi-scale FCNs construction using multiple brain atlases for ROI partition, (2) FCNs representation learning via multi-scale GCNs, and (3) multi-scale feature fusion and classification for ASD diagnosis. The proposed MGRL is evaluated on 184 subjects from the public Autism Brain Imaging Data Exchange (ABIDE) database with rs-fMRI scans. Experimental results suggest the efficacy of our MGRL in FCN feature extraction and ASD identification, compared with several state-of-the-art methods.

Respirology ◽  
2022 ◽  
Harkiran K. Kooner ◽  
Marrissa J. McIntosh ◽  
Vedanth Desaigoudar ◽  
Jonathan H. Rayment ◽  
Rachel L. Eddy ◽  

2022 ◽  
Vol 15 ◽  
Hao Lei ◽  
Rong Hu ◽  
Guanghua Luo ◽  
Tingqian Yang ◽  
Hui Shen ◽  

Type 2 diabetes mellitus (T2DM) is associated with cognitive impairment in many domains. There are several pieces of evidence that changes in neuronal neuropathies and metabolism have been observed in T2DM. Structural and functional MRI shows that abnormal connections and synchronization occur in T2DM brain circuits and related networks. Neuroplasticity and energy metabolism appear to be principal effector systems, which may be related to amyloid beta (Aβ) deposition, although there is no unified explanation that includes the complex etiology of T2DM with cognitive impairment. Herein, we assume that cognitive impairment in diabetes may lead to abnormalities in neuroplasticity and energy metabolism in the brain, and those reflected to MRI structural connectivity and functional connectivity, respectively.

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