The motor system comprises a network of cortical and subcortical areas interacting via
excitatory and inhibitory circuits, thereby governing motor behaviour. The balance within the …

Bayesian networks are a type of probabilistic graphical models lie at the intersection
between statistics and machine learning. They have been shown to be powerful tools to …

Objective In this paper, we develop a dynamic functional network connectivity (FNC)
analysis approach using correlations between windowed time-courses of different brain …

The accurate identification of obscured and concealed objects in complex environments was
an important skill required for survival during human evolution, and is required today for …

This paper is about inferring or discovering the functional architecture of distributed systems
using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) …

Social impairment is a core feature of schizophrenia that presents a major barrier toward
recovery. Some of the psychotic symptoms are partly ameliorated by medication but the …

Employment provides schizophrenic patients with a positive identity and hope. Cognitive
impairments have been suggested to slow down the progress in work rehabilitation. The …

We pose the problem of network discovery which involves simplifying spatio-temporal data
into cohesive regions (nodes) and relationships between those regions (edges). Such …

Studies on interactions between brain regions estimate effective connectivity,(usually) based
on the causality inferences made on the basis of temporal precedence. In this study, the …

Objective Effective connectivity is an important notion in neuroscience research, useful for
detecting the interactions between regions of the brain. New method Since we are dealing …