Advances and Pitfalls in the Analysis and Interpretation of Resting-State FMRI Data

Recently, inference of functional connectivity between brain regions using resting state fMRI (rsfMRI) data has attracted significant interests in the neuroscience community. This paper proposes a novel fiber-centered approach to study the…

In this paper, we conduct an investigation of the null hypothesis distribution for functional magnetic resonance imaging (fMRI) time series using multiscale analysis tools, SiZer (significance of zero crossings of the derivative) and wavelets. Most…

Independent component analysis (ICA) is one of the most valuable explorative methods for analyzing resting-state networks (RSNs) in fMRI, representing a data-driven approach that enables decomposition of high-dimensional data into discrete…

Background: Functional brain imaging studies have indicated that distinct anatomical brain regions can show coherent spontaneous neuronal activity during rest. Regions that show such correlated behavior are said to form resting-state networks…

For resting-state fMRI data, independent component analysis (ICA) is an excellent method which enables the decomposition of high-dimensional data into discrete spatial and temporal components. Fully exploratory network ICA (FENICA), a fully…

Resting-state fMRI fluctuations show correlation patterns which to some extent resemble known anatomical connectivity patterns in the brain. In this abstract we address the question at what level these fluctuations are organized by using a…

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However,…

Epilepsy is a brain disorder with the essential basis of abnormal cortical and/or subcortical networks. Currently, most of the evidence of seizure networks come from ictal EEG observations. Resting-state functional connectivity studies can be…

Objective: To examine the feasibility of functional localization in the human brain with resting-state (task-free) fMRI data using independent component analysis (ICA). Methods: ICA was used to study the functional connectivity in resting-state in…

A variety of methods have been developed to identify brain networks with spontaneous, coherent activity in resting-state functional magnetic resonance imaging (fMRI). We propose here a generic statistical framework to quantify the stability of such…