Literature DB >> 31919551

[Brain imaging in schizophrenia : A review of current trends and developments].

Igor Nenadić1.   

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


  41 in total

1.  Structural correlates of auditory hallucinations in schizophrenia: a meta-analysis.

Authors:  Lena Palaniyappan; Vijender Balain; Joaquim Radua; Peter F Liddle
Journal:  Schizophr Res       Date:  2012-02-16       Impact factor: 4.939

Review 2.  Transdiagnostic neuroimaging in psychiatry: A review.

Authors:  Serge A Mitelman
Journal:  Psychiatry Res       Date:  2019-01-08       Impact factor: 3.222

3.  Functional network connectivity impairments and core cognitive deficits in schizophrenia.

Authors:  Bhim M Adhikari; L Elliot Hong; Hemalatha Sampath; Joshua Chiappelli; Neda Jahanshad; Paul M Thompson; Laura M Rowland; Vince D Calhoun; Xiaoming Du; Shuo Chen; Peter Kochunov
Journal:  Hum Brain Mapp       Date:  2019-07-16       Impact factor: 5.038

4.  Machine-learning based brain age estimation in major depression showing no evidence of accelerated aging.

Authors:  Bianca Besteher; Christian Gaser; Igor Nenadić
Journal:  Psychiatry Res Neuroimaging       Date:  2019-06-11       Impact factor: 2.376

5.  Distinct pattern of brain structural deficits in subsyndromes of schizophrenia delineated by psychopathology.

Authors:  Igor Nenadic; Heinrich Sauer; Christian Gaser
Journal:  Neuroimage       Date:  2009-10-13       Impact factor: 6.556

6.  Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis.

Authors:  Nikolaos Koutsouleris; Thomas Wobrock; Birgit Guse; Berthold Langguth; Michael Landgrebe; Peter Eichhammer; Elmar Frank; Joachim Cordes; Wolfgang Wölwer; Francesco Musso; Georg Winterer; Wolfgang Gaebel; Göran Hajak; Christian Ohmann; Pablo E Verde; Marcella Rietschel; Raees Ahmed; William G Honer; Dominic Dwyer; Farhad Ghaseminejad; Peter Dechent; Berend Malchow; Peter M Kreuzer; Tim B Poeppl; Thomas Schneider-Axmann; Peter Falkai; Alkomiet Hasan
Journal:  Schizophr Bull       Date:  2018-08-20       Impact factor: 9.306

7.  Neuroanatomy of auditory verbal hallucinations in schizophrenia: a quantitative meta-analysis of voxel-based morphometry studies.

Authors:  Gemma Modinos; Sergi G Costafreda; Marie-José van Tol; Philip K McGuire; André Aleman; Paul Allen
Journal:  Cortex       Date:  2012-02-01       Impact factor: 4.027

8.  Identification of a common neurobiological substrate for mental illness.

Authors:  Madeleine Goodkind; Simon B Eickhoff; Desmond J Oathes; Ying Jiang; Andrew Chang; Laura B Jones-Hagata; Brissa N Ortega; Yevgeniya V Zaiko; Erika L Roach; Mayuresh S Korgaonkar; Stuart M Grieve; Isaac Galatzer-Levy; Peter T Fox; Amit Etkin
Journal:  JAMA Psychiatry       Date:  2015-04       Impact factor: 21.596

9.  Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.

Authors:  T G M van Erp; D P Hibar; J M Rasmussen; D C Glahn; G D Pearlson; O A Andreassen; I Agartz; L T Westlye; U K Haukvik; A M Dale; I Melle; C B Hartberg; O Gruber; B Kraemer; D Zilles; G Donohoe; S Kelly; C McDonald; D W Morris; D M Cannon; A Corvin; M W J Machielsen; L Koenders; L de Haan; D J Veltman; T D Satterthwaite; D H Wolf; R C Gur; R E Gur; S G Potkin; D H Mathalon; B A Mueller; A Preda; F Macciardi; S Ehrlich; E Walton; J Hass; V D Calhoun; H J Bockholt; S R Sponheim; J M Shoemaker; N E M van Haren; H E Hulshoff Pol; H E H Pol; R A Ophoff; R S Kahn; R Roiz-Santiañez; B Crespo-Facorro; L Wang; K I Alpert; E G Jönsson; R Dimitrova; C Bois; H C Whalley; A M McIntosh; S M Lawrie; R Hashimoto; P M Thompson; J A Turner
Journal:  Mol Psychiatry       Date:  2015-06-02       Impact factor: 15.992

10.  Cognitive Subtypes of Schizophrenia Characterized by Differential Brain Volumetric Reductions and Cognitive Decline.

Authors:  Danielle Weinberg; Rhoshel Lenroot; Isabella Jacomb; Katherine Allen; Jason Bruggemann; Ruth Wells; Ryan Balzan; Dennis Liu; Cherrie Galletly; Stanley V Catts; Cynthia Shannon Weickert; Thomas W Weickert
Journal:  JAMA Psychiatry       Date:  2016-12-01       Impact factor: 21.596

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