Influence of ROI selection on resting state functional connectivity: an individualized approach for resting state fMRI analysis

Influence of ROI selection on resting state functional connectivity: an individualized approach for resting state fMRI analysis

The differences in how our brain is connected are often thought to reflect the differences in our individual personalities and cognitive abilities. Individual differences in brain connectivity has long been recognized in the neuroscience community however it has yet to manifest itself in the methodology of resting state analysis. This is evident as previous studies use the same region of intere...

Brain Connections – Resting State fMRI Functional Connectivity

With the introduction of electroencephalography (EEG) in 1930, researchers began to explore spontaneous activity in the brain by recording the individual, independently of any task. Subsequently, evoked potential studies, where electrical potentials were recorded at the onset of a stimulus, marked a milestone in brain research. Utilizing such methods coupled with experimental psychology, resear...

Support vector classification analysis of resting state functional connectivity fMRI

Resting State fMRI Functional Connectivity Analysis Using Dynamic Time Warping

Traditional resting-state network concept is based on calculating linear dependence of spontaneous low frequency fluctuations of the BOLD signals of different brain areas, which assumes temporally stable zero-lag synchrony across regions. However, growing amount of experimental findings suggest that functional connectivity exhibits dynamic changes and a complex time-lag structure, which cannot ...

A Longitudinal Model for Functional Connectivity Using Resting-State fMRI

Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. The current fMRI modeling literature lacks a generally applicable model appropriate for longitudinal designs. In this work, we build a novel longitudinal functional connectivity (FC) model using a variance components approach. First, for all subjects’ visits, we account for the autocorr...