This technical note introduces a dynamic causal model (DCM) for resting state fMRI time series
based upon observed functional connectivity—as measured by the cross spectra among …

The brain is a complex, multiscale dynamical system composed of many interacting regions.
Knowledge of the spatiotemporal organization of these interactions is critical for …

Psychedelics exert unique effects on human consciousness. The thalamic filter model suggests
that core effects of psychedelics may result from gating deficits, based on a disintegration …

An important characteristic of spontaneous brain activity is the anticorrelation between the
core default network (cDN) and the dorsal attention network (DAN) and the salience network (…

Recently, there has been a lot of interest in characterising the connectivity of resting state
brain networks. Most of the literature uses functional connectivity to examine these intrinsic …

Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity
from neuroimaging data. In the 15 years since its introduction, the neural models and …

This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor)
approximation to neuronal dynamics with a neural mass model of the canonical …

With the advancement in artificial intelligence (AI) and machine learning (ML) techniques,
researchers are striving towards employing these techniques for advancing clinical practice. …

This paper considers the identification of large directed graphs for resting-state brain networks
based on biophysical models of distributed neuronal activity, that is, effective connectivity. …

This technical note describes some Bayesian procedures for the analysis of group studies
that use nonlinear models at the first (within-subject) level – eg, dynamic causal models – and …