scholarly journals Graph theoretical analysis of functional networks and its relationship to cognitive decline in patients with carotid stenosis

2015 ◽  
Vol 36 (4) ◽  
pp. 808-818 ◽  
Author(s):  
Ting-Yu Chang ◽  
Kuo-Lun Huang ◽  
Meng-Yang Ho ◽  
Pei-Shan Ho ◽  
Chien-Hung Chang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Cognitive Decline ◽  
Carotid Stenosis ◽  
Brain Connectivity ◽  
Functional Networks ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Characteristic Path Length ◽  
Global Efficiency

Significant carotid stenosis compromises hemodynamics and impairs cognitive functions. The interplay between these changes and brain connectivity has rarely been investigated. We aimed to discover the changes of functional connectivity and its relation to cognitive decline in carotid stenosis patients. Twenty-seven patients with unilateral carotid stenosis (≥60%) and 20 age- and sex-matched controls underwent neuropsychological tests and resting-state functional magnetic resonance imaging. The patients also received perfusion magnetic resonance imaging. The relationships between cognitive function and functional networks among the patients and controls were evaluated. Graph theory was applied on resting-state functional magnetic resonance imaging network analysis, which revealed that the hemispheres ipsilateral to the stenosis were significantly impaired in “degree” and “global efficiency.” The neuropsychological performances were positively correlated with degree, clustering coefficient, local efficiency, and global efficiency, and negatively correlated with characteristic path length, modularity, and small-worldness in the patients, whereas these relationships were not observed in the controls. In this study, we identified the networks that were impaired in the affected hemispheres in patients with carotid stenosis. Specific indices (global efficiency, characteristic path length, and modularity) were highly correlated with neuropsychological performance in our patients. Analysis of brain connectivity may help to elucidate the relationship between hemodynamic impairment and cognitive decline.

scholarly journals Morphological, Structural, and Functional Networks Highlight the Role of the Cortical-Subcortical Circuit in Individuals With Subjective Cognitive Decline

2021 ◽  
Vol 13 ◽  
Author(s):  
Xiaowen Xu ◽  
Tao Wang ◽  
Weikai Li ◽  
Hai Li ◽  
Boyan Xu ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Cognitive Decline ◽  
Brain Networks ◽  
Subjective Cognitive Decline ◽  
Support Vector ◽  
Functional Networks ◽  
Resonance Imaging ◽  
Potential Biomarkers

Subjective cognitive decline (SCD) is considered the earliest stage of the clinical manifestations of the continuous progression of Alzheimer’s Disease (AD). Previous studies have suggested that multimodal brain networks play an important role in the early diagnosis and mechanisms underlying SCD. However, most of the previous studies focused on a single modality, and lacked correlation analysis between different modal biomarkers and brain regions. In order to further explore the specific characteristic of the multimodal brain networks in the stage of SCD, 22 individuals with SCD and 20 matched healthy controls (HCs) were recruited in the present study. We constructed the individual morphological, structural and functional brain networks based on 3D-T1 structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI), respectively. A t-test was used to select the connections with significant difference, and a multi-kernel support vector machine (MK-SVM) was applied to combine the selected multimodal connections to distinguish SCD from HCs. Moreover, we further identified the consensus connections of brain networks as the most discriminative features to explore the pathological mechanisms and potential biomarkers associated with SCD. Our results shown that the combination of three modal connections using MK-SVM achieved the best classification performance, with an accuracy of 92.68%, sensitivity of 95.00%, and specificity of 90.48%. Furthermore, the consensus connections and hub nodes based on the morphological, structural, and functional networks identified in our study exhibited abnormal cortical-subcortical connections in individuals with SCD. In addition, the functional networks presented more discriminative connections and hubs in the cortical-subcortical regions, and were found to perform better in distinguishing SCD from HCs. Therefore, our findings highlight the role of the cortical-subcortical circuit in individuals with SCD from the perspective of a multimodal brain network, providing potential biomarkers for the diagnosis and prediction of the preclinical stage of AD.

Resting state functional magnetic resonance imaging processing techniques in stroke studies

2016 ◽  
Vol 27 (8) ◽  
pp. 871-885 ◽  
Author(s):  
Golrokh Mirzaei ◽  
Hojjat Adeli
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Brain Connectivity ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Stroke Patients ◽  
Processing Techniques ◽  
The Brain

AbstractIn recent years, there has been considerable research interest in the study of brain connectivity using the resting state functional magnetic resonance imaging (rsfMRI). Studies have explored the brain networks and connection between different brain regions. These studies have revealed interesting new findings about the brain mapping as well as important new insights in the overall organization of functional communication in the brain network. In this paper, after a general discussion of brain networks and connectivity imaging, the brain connectivity and resting state networks are described with a focus on rsfMRI imaging in stroke studies. Then, techniques for preprocessing of the rsfMRI for stroke patients are reviewed, followed by brain connectivity processing techniques. Recent research on brain connectivity using rsfMRI is reviewed with an emphasis on stroke studies. The authors hope this paper generates further interest in this emerging area of computational neuroscience with potential applications in rehabilitation of stroke patients.

scholarly journals Effect of Subanesthetic Ketamine on Intrinsic Functional Brain Connectivity

2012 ◽  
Vol 117 (4) ◽  
pp. 868-877 ◽  
Author(s):  
Marieke Niesters ◽  
Najmeh Khalili-Mahani ◽  
Christian Martini ◽  
Leon Aarts ◽  
Joop van Gerven ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Anterior Cingulate Cortex ◽  
Resting State ◽  
Brain Connectivity ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging

Background The influence of psychoactive drugs on the central nervous system has been investigated with positron emission tomography and task-related functional magnetic resonance imaging. However, it is not known how these drugs affect the intrinsic large-scale interactions of the brain (resting-state functional magnetic resonance imaging connectivity). In this study, the effect of low-dose S(+)-ketamine on intrinsic brain connectivity was investigated. Methods Twelve healthy, male volunteers received a 2-h intravenous S(+)-ketamine infusion (first hour 20 mg/70 kg, second hour 40 mg/70 kg). Before, during, and after S(+)-ketamine administration, resting-state brain connectivity was measured. In addition, heat pain tests were performed between imaging sessions to determine ketamine-induced analgesia. A mixed-effects general linear model was used to determine drug and pain effects on resting-state brain connectivity. Results Ketamine increased the connectivity most importantly in the cerebellum and visual cortex in relation to the medial visual network. A decrease in connectivity was observed in the auditory and somatosensory network in relation to regions responsible for pain sensing and the affective processing of pain, which included the amygdala, insula, and anterior cingulate cortex. Connectivity variations related to fluctuations in pain scores were observed in the anterior cingulate cortex, insula, orbitofrontal cortex, and the brainstem, regions involved in descending inhibition of pain. Conclusions Changes in connectivity were observed in the areas that explain ketamine's pharmacodynamic profile with respect to analgesia and psychedelic and other side effects. In addition, pain and ketamine changed brain connectivity in areas involved in endogenous pain modulation.

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