Support Vector Machine Classification of Resting State fMRI Datasets Using Dynamic Network Clusters

Classification of Resting State fMRI Datasets Using Dynamic Network Clusters

Resting state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating intrinsic and spontaneous brain activity. The application of univariate and multivariate methods such as multi voxel pattern analysis has been instrumental in localizing neural correlates to various cognitive states and psychiatric disease. However, many existing methods of rsfMRI analysis are insu...

Identification of mild cognitive impairment disease using brain functional connectivity and graph analysis in fMRI data

Background: Early diagnosis of patients in the early stages of Alzheimer's, known as mild cognitive impairment, is of great importance in the treatment of this disease. If a patient can be diagnosed at this stage, it is possible to treat or delay Alzheimer's disease. Resting-state functional magnetic resonance imaging (fMRI) is very common in the process of diagnosing Alzheimer's disease. In th...

Multiple-Network Classification of Childhood Autism Using Functional Connectivity Dynamics

Characterization of disease using stationary resting-state functional connectivity (FC) has provided important hallmarks of abnormal brain activation in many domains. Recent studies of resting-state functional magnetic resonance imaging (fMRI), however, suggest there is a considerable amount of additional knowledge to be gained by investigating the variability in FC over the course of a scan. W...

Dimensionality of ICA in resting-state fMRI investigated by feature optimized classification of independent components with SVM

Different machine learning algorithms have recently been used for assisting automated classification of independent component analysis (ICA) results from resting-state fMRI data. The success of this approach relies on identification of artifact components and meaningful functional networks. A limiting factor of ICA is the uncertainty of the number of independent components (NIC). We aim to deve...

Support vector classification analysis of resting state functional connectivity fMRI