This paper introduces an approach for classifying adolescents suffering from MDD using
resting-state fMRI. Accurate diagnosis of MDD involves interviews with adolescent patients …

Objective: Inferring causal or effective connectivity between measured timeseries is crucial
to understanding directed interactions in complex systems. This task is especially …

Background Recent advances in biotechnology enable the acquisition of high-dimensional
data on individuals, posing challenges for prediction models which traditionally use …

Objective: This paper explores the predictive capability of dynamic functional connectivity
extracted from functional magnetic resonance imaging (fMRI) of the human brain, in contrast …

Abstract Machine learning approaches are increasingly being applied to neuroimaging data
from patients with psychiatric disorders to extract brain-based features for diagnosis and …

Scientific research has been facing the problem of increase in size and complexity. Hence,
the utilization of scientometric methodology for management of science has been expected …

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that often
persists into adulthood. Core symptoms of ADHD, such as impulsivity, are caused by an …

Background Obsessive-compulsive symptomatology (OCS) is common in adolescence but
usually does not meet the diagnostic threshold for obsessive-compulsive disorder …

The goal of this paper is to use graph theory network measures derived from non-invasive
electroencephalography (EEG) to develop neural decoders that can differentiate Parkinson's …

The past two decades have seen an explosion in the methods and directions of
neuroscience research. Along with many others, complexity research has rapidly gained …