A lack of consistent brain alterations in insomnia disorder: An activation likelihood estimation meta-analysis

Masoud Tahmasian, Khadijeh Noori, Fateme Samea, Mojtaba Zarei, Kai Spiegelhalder, Simon B. Eickhoff, Eus Van Someren, Habibolah Khazaie*, Claudia R. Eickhoff

*Corresponding author for this work

Research output: Contribution to JournalReview articleAcademicpeer-review

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Abstract

Insomnia disorder is a prevalent sleep disorder, which affects about 10% of general population. However, its neural mechanisms are poorly understood. Recently, several structural and functional neuroimaging studies have been conducted in patients with insomnia disorder, but these studies have yielded diverse findings. Here, we aimed to identify consistent patterns of abnormal brain alterations in insomnia disorder by performing a quantitative coordinate-based meta-analysis. Following the preferred reporting for systematic reviews and meta-analyses statement, we searched PubMed database and used reference tracking and finally retrieved 19 eligible studies (six task-based functional magnetic resonance imaging, eight resting-state functional magnetic resonance imaging, three voxel-based morphometry, and two positron emission tomography). We extracted peak coordinates from these studies and tested for convergence using the activation likelihood estimation method. Using this method, we found no significant convergent evidence for combination of structural atrophy and functional disturbances across previous studies (p = 0.914). Inconsistencies across these studies might be related to heterogonous clinical populations, the explorative nature of these studies in combination with small sample sizes, different experimental designs, and various preprocessing and statistical approaches. Future neuroimaging studies on insomnia disorder should include larger well-characterized samples, as well as standard imaging and analysis protocols.

Original languageEnglish
Pages (from-to)111-118
Number of pages8
JournalSleep Medicine Reviews
Volume42
Early online date10 Jul 2018
DOIs
Publication statusPublished - Dec 2018

Funding

This study was supported by Kermanshah University of Medical Sciences (No. 94526 ). Simon B. Eickhoff is supported by the Deutsche Forschungsgemeinschaft ( EI 816/11-1 ), the National Institute of Mental Health ( R01-MH074457 ), the Helmholtz Portfolio Theme “Supercomputing and Modeling for the Human Brain” and the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 7202070 ( HBP SGA1 ) and under Grant Agreement No. 785907 (HBP SGA2). Appendix A

FundersFunder number
Helmholtz Portfolio Theme
National Institute of Mental HealthR01MH074457
European Research CouncilERC-ADG-2014-671084-INSOMNIA
Deutsche ForschungsgemeinschaftEI 816/11-1
Kermanshah University of Medical Sciences94526
Horizon 2020785907, 7202070

    Keywords

    • ALE meta-analysis
    • fMRI
    • Insomnia disorder
    • PET
    • VBM

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