Cognitive deficits are a core feature of schizophrenia, account for much of the impaired
functioning associated with the disorder and are not responsive to existing treatments. In this …

Importance Schizophrenia is a common, severe mental illness that most clinicians will
encounter regularly during their practice. This report provides an overview of the clinical …

The organization of human brain networks can be measured by capturing correlated brain
activity with fMRI. There is considerable interest in understanding how brain networks vary …

Deep learning (DL) is a family of machine learning methods that has gained considerable
attention in the scientific community, breaking benchmark records in areas such as speech …

Background Cognitive dysfunction is one of the most prominent characteristics of psychiatric
disorders. Currently, the neural correlates of cognitive dysfunction across psychiatric …

For more than one century, brain processing was mainly thought in a localizationist
framework, in which one given function was underpinned by a discrete, isolated cortical …

Abstract Machine learning techniques have gained prominence for the analysis of resting-
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …

Background A lack of a sufficiently large sample at single sites causes poor generalizability
in automatic diagnosis classification of heterogeneous psychiatric disorders such as …

Dysfunction of the mesocorticolimbic dopaminergic reward system is a core feature of
schizophrenia (SZ), yet its precise contributions to different stages of reward processing and …

Background Current fMRI-based classification approaches mostly use functional
connectivity or spatial maps as input, instead of exploring the dynamic time courses directly …