Realistic models of apparent dynamic changes in resting-state connectivity in somatosensory cortex.

ABSTRACT: Variations over time in resting-state correlations in blood oxygenation level-dependent (BOLD) signals from different cortical areas may indicate changes in brain functional connectivity. However, apparent variations over time may also arise from stationary signals when the sample duration is finite. Recently, a vector autoregressive (VAR) null model has been proposed to simulate real functional magnetic resonance imaging (fMRI) data, which provides a robust stationary model for identifying possible temporal dynamic changes in functional connectivity. In this work, we propose a simpler model that uses a filtered stationary dataset. The filtered stationary model generates statistically stationary time series from random data with a single prescribed correlation coefficient that is calculate

SUBMITTER: Shi Z 

PROVIDER: S-EPMC5053861 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature