Common Dysfunction of Large-Scale Neurocognitive Networks Across Psychiatric Disorders

Zhiqiang Sha; Tor D Wager; Andrea Mechelli; Yong He

doi:10.1016/j.biopsych.2018.11.011

Common Dysfunction of Large-Scale Neurocognitive Networks Across Psychiatric Disorders

Biol Psychiatry. 2019 Mar 1;85(5):379-388. doi: 10.1016/j.biopsych.2018.11.011. Epub 2018 Nov 23.

Authors

Zhiqiang Sha¹, Tor D Wager², Andrea Mechelli³, Yong He⁴

Affiliations

¹ National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
² Department of Psychology and Neuroscience, University of Colorado, Boulder, Colorado; Institute of Cognitive Science, University of Colorado, Boulder, Colorado.
³ Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
⁴ National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China. Electronic address: yong.he@bnu.edu.cn.

PMID: 30612699
DOI: 10.1016/j.biopsych.2018.11.011

Abstract

Background: Cognitive dysfunction is one of the most prominent characteristics of psychiatric disorders. Currently, the neural correlates of cognitive dysfunction across psychiatric disorders are poorly understood. The aim of this study was to investigate functional connectivity and structural perturbations across psychiatric diagnoses in three neurocognitive networks of interest: the default mode network (DMN), the frontoparietal network (FPN), and the salience network (SN).

Methods: We performed meta-analyses of resting-state functional magnetic resonance imaging whole-brain seed-based functional connectivity in 8298 patients (involving eight disorders) and 8165 healthy control subjects and a voxel-based morphometry analysis of structural magnetic resonance imaging data in 14,027 patients (involving eight disorders) and 14,504 healthy control subjects. To aid the interpretation of the results, we examined neurocognitive function in 776 healthy participants from the Human Connectome Project.

Results: We found that the three neurocognitive networks of interest were characterized by shared alterations of functional connectivity architecture across psychiatric disorders. More specifically, hypoconnectivity was expressed between the DMN and ventral SN and between the SN and FPN, whereas hyperconnectivity was evident between the DMN and FPN and between the DMN and dorsal SN. This pattern of network alterations was associated with gray matter reductions in patients and was localized in regions that subserve general cognitive performance.

Conclusions: This study is the first to provide meta-analytic evidence of common alterations of functional connectivity within and between neurocognitive networks. The findings suggest a shared mechanism of network interactions that may associate with the generalized cognitive deficits observed in psychiatric disorders.

Keywords: Connectomics; Default mode network; Frontoparietal network; Meta-analysis; Resting-state fMRI; Salience network.

Publication types

Meta-Analysis
Research Support, Non-U.S. Gov't

MeSH terms

Adult
Brain / pathology*
Brain / physiopathology*
Case-Control Studies
Cognition Disorders / complications
Cognition Disorders / physiopathology*
Connectome
Female
Functional Neuroimaging
Gray Matter / pathology
Humans
Magnetic Resonance Imaging
Male
Mental Disorders / complications
Mental Disorders / physiopathology*
Neural Pathways / pathology*
Neural Pathways / physiopathology*
Young Adult