Sleep has been shown to be critical for memory consolidation, with some research
suggesting that certain memories are prioritized for consolidation. Initial strength of a …

Network link inference from measured time series data of the behavior of dynamically
interacting network nodes is an important problem with wide-ranging applications, eg …

We test the adequacies of several proposed and two new statistical methods for recovering
the causal structure of systems with feedback from synthetic BOLD time series. We compare …

Human brain effective connectivity characterizes the causal effects of neural activities
among different brain regions. Studies of brain effective connectivity networks (ECNs) for …

Estimating effective connectivity from functional magnetic resonance imaging (fMRI) time
series data has become a very hot topic in neuroinformatics and brain informatics. However …

Inferring brain-effective connectivity networks from neuroimaging data has become a very
hot topic in neuroinformatics and bioinformatics. In recent years, the search methods based …

Using machine learning methods to estimate brain effective connectivity networks from
functional magnetic resonance imaging (fMRI) data has garnered significant attention in the …

The direction of functional information flow in the sensory thalamocortical circuit may play a
role in stimulus perception, but, surprisingly, this process is poorly understood. We …

We demonstrate a data-driven approach for calculating a “causal connectome” of directed
connectivity from resting-state fMRI data using a greedy adjacency search and pairwise non …

Current studies have shown that the classification of human brain functional networks (BFN)
is a reliable way to diagnose and predict brain diseases. However, a great challenge for …