Durhamcrews4407

CNN models achieved higher cross-validation accuracy than handcrafted feature-based machine learning. Moreover, testing on an independent dataset, 3D CNN models greatly outperformed handcrafted feature-based machine learning. This study underscored the potential of CNN for identifying patients with schizophrenia using 3D brain MR images and paved the way for imaging-based individual-level diagnosis and prognosis in psychiatric disorders.Ventromedial prefrontal cortex (vmPFC) is an important brain region involved in many psychological functions. Previous neuroimaging studies have shown disrupted function and altered metabolic level within vmPFC of schizophrenia (SCZ) patients. However, the linkage between the functional connectivity and its underlying neurobiological mechanism in SCZ remains unclear. In this study, we aimed to investigate the altered relationship between the functional connectivity strength (FCS) and metabolic concentrations within vmPFC in drug-naïve first-episode psychosis (FEP) patients using a combined functional magnetic resonance imaging (fMRI) and single-voxel proton magnetic resonance spectroscopy (1H- MRS) technique. There were 26 drug-naïve FEP patients and 27 matched healthy controls participated this study. We have found altered correlation between FCS and N-acetylaspartate (NAA) in drug-naïve FEP patients. In addition, the glutamate and glutamine compounds (Glx) and NAA concentrations were positively correlated with Positive and Negative Symptoms Scale (PANSS) total scores. Our findings revealed the disrupted functional-metabolic coupling within vmPFC in drug-naïve FEP patients and provided useful insights in understanding the etiology of SCZ.Modular functional alterations were shown in obsessive-compulsive disorder (OCD) patients from previous functional magnetic resonance imaging (fMRI) studies. However, most studies considered each module as a specific node and ignore the intramodular connectivity information. In this paper, we investigated the intramodular functional connectivity (FC) alterations in drug naïve OCD patients using a whole brain graph theoretical approach for functional modular parcellation. Seventy-three drug-naïve OCD patients and seventy-eight matched healthy controls were included in this study. We utilized infomap algorithm for modules detection. The functional connectivity strength (FCS) was calculated within each module to obtain the FC between a given voxel and all other voxels in the module. We found increased FCS in precentral and postcentral gyrus within sensor-motor network (SMN) and decreased FCS in insula within salience network (SN). Moreover, FC within SMN was negatively correlated with YBOCS- compulsions scores, while FC within SN was negatively correlated with YBOCS-total, compulsions and obsessions scores. Our findings brought useful insights in understanding the pathophysiology of OCD.Recent reports suggested that even moderate sudden sensorineural hearing loss (SSNHL) can be partly responsible for a loss of gray matter volume in the primary auditory cortex, hence reducing the capacity of the auditory cortical areas to react to sound stimulation. There is also evidence for a plastic reorganization of brain functional networks visible as enhanced local functional connectivity. The aim of this study was to use rs-fMRI, in conjunction with graph- theoretical analysis and a newly developed functional "disruption index" to study whole-brain as well as local functional changes in patients with acute and unilateral sensorineural hearing loss. No statistically significant differences in global or local network measures we found between SSNHL patients and healthy controls. However, when analyzing local metrics through the disruption index k, we found negative values for k which were statistically different from zero both in single subject analysis. Additionally, we found several associations between graph-theoretical metrics and clinical parameters.In 2019, approximately 38 million people were living with human immunodeficiency virus (HIV). Combined antiretroviral therapy (cART) has determined a change in the course of HIV infection, transforming it into a chronic condition which results in cumulative exposure to antiretroviral drugs, inflammatory effects and aging. Relatedly, at least one quarter of HIV-infected patients suffer from cognitive, motor and behavioral disorder, globally known as HIV-associated neurocognitive disorders (HAND). In this context, objective, neuroimaging-based biomarkers are therefore highly desirable in order to detect, quantify and monitor HAND in all disease stages. In this study, we employed functional MRI in conjunction with graph-theoretical analysis as well as a newly developed functional brain network disruption index to assess a putative functional reorganization in HIV positive patients. We found that brain function of HIV patients is deeply reorganized as compared to normal controls. Interestingly, the regions in which we found reorganized hubs are integrated into neuronal networks involved in working memory, motor and executive functions often altered in patients with HAND. Overall, our study demonstrates that rs-fMRI combined with advanced graph theoretical analysis and disruption indices is able to detect early, subtle functional changes of brain networks in HIV patients before structural changes become evident.Afferent nerves that carry interoceptive signals from the viscera to the brain include Aδ and C-fibers. Shikonin supplier Previously, we examined the effects of detrusor distention (conveyed mainly by Aδ fibers) on the static functional network connectivity (FNC) of the brain using independent component analysis (ICA) of fMRI time series. In the present study, we investigate the impact of intravesical cold sensation (thought to be conveyed by C-fibers) on brain FNC using similar ICA approach. Thirteen healthy women were scanned on a 3.0T MRI scanner during a resting state scan and an intravesical cold sensation task fMRI. High dimensional ICA (n = 75) were used to decompose the fMRI data into several intrinsic connectivity networks (ICNs) including the default-mode (DMN), subcortical (SCN; amygdala, thalamus), salience (SN), central executive (CEN), sensorimotor (SMN), and cerebellar/brainstem (CBN) networks. Results demonstrate significant FNC differences in several ICN pairs primarily between the SCN and cognitive networks such as CEN, as well as between SN and CBN and DMN when intravesical cold water condition was compared to rest (FDR-corrected p-value of 0.