Differentiating the Functional Contributions of Resting Connectivity Networks to Memory Decision-making: fMRI Support for Multistage Control Processes

Support vector classification analysis of resting state functional connectivity fMRI

Functional Connectivity during Memory Consolidation: A Resting-State fMRI Study

C-W. Li, K-H. Chen, T-L. Chou, K-C. Liang, Y-C. Yu, C-W. Wu, and J-H. Chen Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, Taiwan, Department of Psychology, National Taiwan University, Taipei, Taiwan, Center for Neurobiology and Cognitive Science, National Taiwan University, Taipei, Taiwan Introduction Memory consolidation is a brain process through which a sho...

Resting-state functional connectivity predicts impulsivity in economic decision-making.

Increasing neuroimaging evidence suggests an association between impulsive decision-making behavior and task-related brain activity. However, the relationship between impulsivity in decision-making and resting-state brain activity remains unknown. To address this issue, we used functional MRI to record brain activity from human adults during a resting state and during a delay discounting task (...

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...

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...