| Literature DB >> 31919551 |
Abstract
Imaging methods have become the main approach for identifying dysfunctional neuronal networks in schizophrenia. This review article presents recent results of disorders of neuronal networks at structural and functional levels and summarizes the current developments. Large multicenter analyses have further established patterns of regional brain alterations, while novel methods in magnetic resonance (MR) morphometry have contributed to differentiating early from delayed brain structural changes. The use of machine learning approaches has not only enabled the establishment of classification models using biological data for future differential diagnostic use, it has also facilitated multivariate models for outcome prediction following therapeutic interventions. Novel methods, such as BrainAGE, a surrogate marker of accelerated brain aging processes, have added to longitudinal studies to gain insights into the brain structural dynamics from early brain developmental alterations to progressive structural brain changes after disease onset.Entities:
Keywords: Functional MRI; Machine learning; Magnetic resonance imaging; Morphometry; Structural brain alterations
Year: 2020 PMID: 31919551 DOI: 10.1007/s00115-019-00857-0
Source DB: PubMed Journal: Nervenarzt ISSN: 0028-2804 Impact factor: 1.214