Research Topic

The Role of Sleep in Major Depressive Disorder: a Perspective from Multi-modal Neuroimaging

About this Research Topic

As a prevalent mood disorder affecting more than 300 million people worldwide, Major depressive disorder (MDD) is characterized by abnormalities in mood, cognition, neurovegetative function as well as psychomotor activity. Among MDD patients, 90% suffer from sleep disturbance which is considered as a shared symptom in diagnosis. Sleep disorder reveals itself in depressive episode before relapse, and with a risk of accompanying patients into later stages. Sleep disorder may lead to under-performance of patients to various treatments thus understanding the neural substrates behind is of great importance to both translational and clinical studies. In order to do so, researchers could leverage state-of-the-art non-invasive in vivo neuroimaging techniques combined with machine learning in data analysis and processing.
In this Research Topic, we aim to bring together the latest neuroimaging researches to enhance our understanding on the link between sleep disturbance and depression, and to further facilitate clinical diagnosis and optimize therapies and treatments. Apart from studies focusing on patients, we are also interested in works addressing the relationships between sleep and depression via neuroimaging healthy participants. Through this topic, we hope to achieve a comprehensive understanding of how sleep disturbance affects the onset, progression and prognosis of depression, and how human respondto various antidepressant therapy. Sleep disturbance to be discussed includes, but not limited to, insomnia, hypersomnia, abnormalities of sleep structure, and obstructive sleep apnea hypopnea syndrome. Submissions revealing brain abnormalities in MDD patients with sleep disturbance via a wide array of neuroimaging techniques including structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), perfusion MRI (pMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG) etc are encouraged, and studies with longitudinal designs attempting to investigate whether causal relationship exist between sleep disturbance and depression are particularly welcomed. We hope to see a collection of original research articles, reviews, meta-analyses and commentaries on existing publications.
Potential topics include, but are not limited to the following:
 Brain structural and/or functional changes related to specific sleep disturbance in MDD
 Applications of advanced/novel neuroimaging analytical techniques to characterize brain changes in MDD patients with sleep disturbance
 Longitudinal studies with interventions that could help determine any causal relationships between sleep disturbance and MDD
 Machine learning researches that identify sleep disturbance-associated neuroimaging biomarkers for depression diagnosis, prognosis and subtyping


Keywords: major depressive disorder, sleep disturbance, neuroimaging, brain, multi-modality, machine learning


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

As a prevalent mood disorder affecting more than 300 million people worldwide, Major depressive disorder (MDD) is characterized by abnormalities in mood, cognition, neurovegetative function as well as psychomotor activity. Among MDD patients, 90% suffer from sleep disturbance which is considered as a shared symptom in diagnosis. Sleep disorder reveals itself in depressive episode before relapse, and with a risk of accompanying patients into later stages. Sleep disorder may lead to under-performance of patients to various treatments thus understanding the neural substrates behind is of great importance to both translational and clinical studies. In order to do so, researchers could leverage state-of-the-art non-invasive in vivo neuroimaging techniques combined with machine learning in data analysis and processing.
In this Research Topic, we aim to bring together the latest neuroimaging researches to enhance our understanding on the link between sleep disturbance and depression, and to further facilitate clinical diagnosis and optimize therapies and treatments. Apart from studies focusing on patients, we are also interested in works addressing the relationships between sleep and depression via neuroimaging healthy participants. Through this topic, we hope to achieve a comprehensive understanding of how sleep disturbance affects the onset, progression and prognosis of depression, and how human respondto various antidepressant therapy. Sleep disturbance to be discussed includes, but not limited to, insomnia, hypersomnia, abnormalities of sleep structure, and obstructive sleep apnea hypopnea syndrome. Submissions revealing brain abnormalities in MDD patients with sleep disturbance via a wide array of neuroimaging techniques including structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), perfusion MRI (pMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG) etc are encouraged, and studies with longitudinal designs attempting to investigate whether causal relationship exist between sleep disturbance and depression are particularly welcomed. We hope to see a collection of original research articles, reviews, meta-analyses and commentaries on existing publications.
Potential topics include, but are not limited to the following:
 Brain structural and/or functional changes related to specific sleep disturbance in MDD
 Applications of advanced/novel neuroimaging analytical techniques to characterize brain changes in MDD patients with sleep disturbance
 Longitudinal studies with interventions that could help determine any causal relationships between sleep disturbance and MDD
 Machine learning researches that identify sleep disturbance-associated neuroimaging biomarkers for depression diagnosis, prognosis and subtyping


Keywords: major depressive disorder, sleep disturbance, neuroimaging, brain, multi-modality, machine learning


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

31 October 2021 Abstract
31 December 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

31 October 2021 Abstract
31 December 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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