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Wang Y.,Beijing University of Technology | Ji J.,Beijing University of Technology | Liang P.,Capital Medical University | Liang P.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics
Journal of X-Ray Science and Technology | Year: 2016

Pattern classification has been increasingly used in functional magnetic resonance imaging (fMRI) data analysis. However, the classification performance is restricted by the high dimensional property and noises of the fMRI data. In this paper, a new feature selection method (named as "NMI-F") was proposed by sequentially combining the normalized mutual information (NMI) and fisher discriminant ratio. In NMI-F, the normalized mutual information was firstly used to evaluate the relationships between features, and fisher discriminant ratio was then applied to calculate the importance of each feature involved. Two fMRI datasets (task-related and resting state) were used to test the proposed method. It was found that classification base on the NMI-F method could differentiate the brain cognitive and disease states effectively, and the proposed NMI-F method was prior to the other related methods. The current results also have implications to the future studies. © 2016 - IOS Press and the authors. All rights reserved. Source

Li K.-C.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics
Chinese Journal of Contemporary Neurology and Neurosurgery | Year: 2014

Alzheimer's disease is the most common neurodegenerative disease which gives rise to senile dementia. High morbidity and poor efficacy of Alzheimer's disease have brought about much pressure to the aging society. However, based on early diagnosis, early clinical intervention may slow down the progression of disease and improve its prognosis. In this review, we attempt to introduce the progress of early neuroimaging diagnosis of Alzheimer's disease. Source

Wang Z.,Capital Medical University | Xia M.,Beijing Normal University | Dai Z.,Beijing Normal University | Liang X.,Beijing Normal University | And 4 more authors.
Brain Structure and Function | Year: 2013

Recent research on Alzheimer's disease (AD) has shown that the altered structure and function of the inferior parietal lobule (IPL) provides a promising indicator of AD. However, little is known about the functional connectivity of the IPL subregions in AD subjects. In this study, we collected resting-state functional magnetic resonance imaging data from 32 AD patients and 38 healthy controls. We defined seven subregions of the IPL according to probabilistic cytoarchitectonic atlases and mapped the whole-brain resting-state functional connectivity for each subregion. Using hierarchical clustering analysis, we identified three distinct functional connectivity patterns of the IPL subregions: the anterior IPL connected with the sensorimotor network (SMN) and salience network (SN); the central IPL had connectivity with the executive-control network (ECN); and the posterior IPL exhibited connections with the default-mode network (DMN). Compared with the controls, the AD patients demonstrated distinct disruptive patterns of the IPL subregional connectivity with these different networks (SMN, SN, ECN and DMN), which suggests the impairment of the functional integration in the IPL. Notably, we also observed that the IPL subregions showed increased connectivity with the posterior part of the DMN in AD patients, which potentially indicates a compensatory mechanism. Finally, these abnormal IPL functional connectivity changes were closely associated with cognitive performance. Collectively, we show that the subregions of the IPL present distinct functional connectivity patterns with various functional networks that are differentially impaired in AD patients. Our results also suggest that functional disconnection and compensation in the IPL may coexist in AD. © 2013 Springer-Verlag Berlin Heidelberg. Source

Wang Z.,Capital Medical University | Wang J.,Pennsylvania State University | Zhang H.,Hangzhou Normal University | Mchugh R.,Pennsylvania State University | And 4 more authors.
PLoS ONE | Year: 2015

Neuroimaging studies have demonstrated that patients with Alzheimer's disease presented disconnection syndrome. However, little is known about the alterations of interhemispheric functional interactions and underlying structural connectivity in the AD patients. In this study, we combined resting-state functional MRI and diffusion tensor imaging (DTI) to investigate interhemispheric functional and structural connectivity in 16 AD, 16 mild cognitive impairment (MCI), as well as 16 cognitive normal healthy subjects (CN). The pattern of the resting state interhemispheric functional connectivity was measured with a voxel-mirrored homotopic connectivity (VMHC) method. Decreased VMHC was observed in AD and MCI subjects in anterior brain regions including the prefrontal cortices and subcortical regions with a pattern of AD Source

Wang Z.,Capital Medical University | Liang P.,Capital Medical University | Liang P.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics | Zhao Z.,Capital Medical University | And 7 more authors.
PLoS ONE | Year: 2014

Our objective is to clarify the effects of acupuncture on hippocampal connectivity in patients with Alzheimer disease (AD) using functional magnetic resonance imaging (fMRI). Twenty-eight right-handed subjects (14 AD patients and 14 healthy elders) participated in this study. Clinical and neuropsychological examinations were performed on all subjects. MRI was performed using a SIEMENS verio 3-Tesla scanner. The fMRI study used a single block experimental design. We first acquired baseline resting state data during the initial 3 minutes and then performed acupuncture stimulation on the Tai chong and He gu acupoints for 3 minutes. Last, we acquired fMRI data for another 10 minutes after the needle was withdrawn. The preprocessing and data analysis were performed using statistical parametric mapping (SPM5) software. Two-sample t-tests were performed using data from the two groups in different states. We found that during the resting state, several frontal and temporal regions showed decreased hippocampal connectivity in AD patients relative to control subjects. During the resting state following acupuncture, AD patients showed increased connectivity in most of these hippocampus related regions compared to the first resting state. In conclusion, we investigated the effect of acupuncture on AD patients by combing fMRI and traditional acupuncture. Our fMRI study confirmed that acupuncture at Tai chong and He gu can enhance the hippocampal connectivity in AD patients. Source

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