Frequency-Dependent Functional Connectivity Analysis of fMRI Data in Fourier and Wavelet Domains

A spectral graphical model approach for learning brain connectivity network of children's narrative comprehension

Narrative comprehension is a fundamental cognitive skill that involves the coordination of different functional brain regions. We develop a spectral graphical model with model averaging to study the connectivity networks underlying these brain regions using fMRI data collected from a story comprehension task. Based on the spectral density matrices in the frequency domain, this model captures the temporal dependency of the entire fMRI time series between brain regions. A Bayesian model averaging procedure is then applied to select the best directional links that constitute the brain network. Using this model, brain networks of three distinct age groups are constructed to assess the dynamic change of network connectivity with respect to age.

Cortical network dynamics with time delays reveals functional connectivity in the resting brain

In absence of all goal-directed behavior, a characteristic network of cortical regions involving prefrontal and cingulate cortices consistently shows temporally coherent fluctuations. The origin of these fluctuations is unknown, but has been hypothesized to be of stochastic nature. In the present paper we test the hypothesis that time delays in the network dynamics play a crucial role in the generation of these fluctuations. By tuning the propagation velocity in a network based on primate connectivity, we scale the time delays and demonstrate the emergence of the resting state networks for biophysically realistic parameters.