4.7 Review

An integrated network model of psychotic symptoms

Journal

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
Volume 59, Issue -, Pages 238-250

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neubiorev.2015.09.016

Keywords

Psychosis; Schizophrenia; Hallucinations; Delusions; Network science; Integrative science; Attractor network; Neural networks; GABA inhibition; NMDA excitation; Neuromodulation; Dopamine; Default-mode network; Functional neuroimaging; Functional connectivity; Resting-state connectivity; Central executive network; Salience network; Social networks; Scale free

Ask authors/readers for more resources

The full body of research on the nature of psychosis and its determinants indicates that a considerable number of factors are relevant to the development of hallucinations, delusions, and other positive symptoms, ranging from neurodevelopmental parameters and altered connectivity of brain regions to impaired cognitive functioning and social factors. We aimed to integrate these factors in a single mathematical model based on network theory. At the microscopic level this model explains positive symptoms of psychosis in terms of experiential equivalents of robust, high-frequency attractor states of neural networks. At the mesoscopic level it explains them in relation to global brain states, and at the macroscopic level in relation to social-network structures and dynamics. Due to the scale-free nature of biological networks, all three levels are governed by the same general laws, thereby allowing for an integrated model of biological, psychological, and social phenomena involved in the mediation of positive symptoms of psychosis. This integrated network model of psychotic symptoms (INMOPS) is described together with various possibilities for application in clinical practice. (C) 2015 The Authors. Published by Elsevier Ltd.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available