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Bagherzadeh-Azbari S, Khazaie H, Zarei M, Spiegelhalder K, Walter M, Leerssen J, Van Someren EJW, Sepehry AA, Tahmasian M. Neuroimaging insights into the link between depression and Insomnia: A systematic review. J Affect Disord 2019; 258:133-143. [PMID: 31401541 DOI: 10.1016/j.jad.2019.07.089] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Revised: 07/06/2019] [Accepted: 07/30/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Insomnia is a common symptom of Major Depressive Disorder (MDD) and genome-wide association studies pointed to their strong genetic association. Although the prevalence of insomnia symptoms in MDD is noticeable and evidence supports their strong bidirectional association, the number of available neuroimaging findings on patients of MDD with insomnia symptoms is limited. However, such neuroimaging studies could verily improve our understanding of their shared pathophysiology and advance corresponding theories. METHODS Based on the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guideline, we have conducted a literature search using PubMed, EMBASE, and Scopus databases and systematically explored 640 studies using various neuroimaging modalities in MDD patients with different degrees of insomnia symptoms. RESULTS Despite inconsistencies, current findings from eight studies suggested structural and functional disturbances in several brain regions including the amygdala, prefrontal cortex and anterior cingulate cortex and insula. The aberrant functional connectivity within and between the main hubs of the salience and default mode networks could potentially yield new insights into the link between MDD and insomnia, which needs further assessment. LIMITATIONS The number of studies reviewed herein is limited. The applied methods for assessing structural and functional neural mechanisms of insomnia and depression were variable. CONCLUSION Neuroimaging methods demonstrated the overlapping underlying neural mechanisms between MDD and insomnia. Future studies may facilitate better understanding of their pathophysiology to allow development of specific treatment.
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Affiliation(s)
- Shadi Bagherzadeh-Azbari
- Institute of Medical Sciences and Technology, Shahid Beheshti University, Tehran, Iran; Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Habibolah Khazaie
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mojtaba Zarei
- Institute of Medical Sciences and Technology, Shahid Beheshti University, Tehran, Iran
| | - Kai Spiegelhalder
- Department of Psychiatry and Psychotherapy, Medical Centre - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Martin Walter
- Department of Psychiatry, University of Tübingen, Tübingen, Germany; Clinical Affective Neuroimaging Laboratory, Leibniz Institute for Neurobiology, Otto-von-Guericke University, Magdeburg, Germany
| | - Jeanne Leerssen
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, 1105 BA, Amsterdam, Netherlands; Departments of Psychiatry and Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universtiteit Amsterdam, Amsterdam UMC, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
| | - Eus J W Van Someren
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, 1105 BA, Amsterdam, Netherlands; Departments of Psychiatry and Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universtiteit Amsterdam, Amsterdam UMC, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
| | - Amir A Sepehry
- Clinical and Counselling Psychology Program, Adler University, Vancouver, BC, Canada
| | - Masoud Tahmasian
- Institute of Medical Sciences and Technology, Shahid Beheshti University, Tehran, Iran.
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Guldenmund P, Gantner IS, Baquero K, Das T, Demertzi A, Boveroux P, Bonhomme V, Vanhaudenhuyse A, Bruno MA, Gosseries O, Noirhomme Q, Kirsch M, Boly M, Owen AM, Laureys S, Gómez F, Soddu A. Propofol-Induced Frontal Cortex Disconnection: A Study of Resting-State Networks, Total Brain Connectivity, and Mean BOLD Signal Oscillation Frequencies. Brain Connect 2016; 6:225-37. [PMID: 26650183 DOI: 10.1089/brain.2015.0369] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Propofol is one of the most commonly used anesthetics in the world, but much remains unknown about the mechanisms by which it induces loss of consciousness. In this resting-state functional magnetic resonance imaging study, we examined qualitative and quantitative changes of resting-state networks (RSNs), total brain connectivity, and mean oscillation frequencies of the regional blood oxygenation level-dependent (BOLD) signal, associated with propofol-induced mild sedation and loss of responsiveness in healthy subjects. We found that detectability of RSNs diminished significantly with loss of responsiveness, and total brain connectivity decreased strongly in the frontal cortex, which was associated with increased mean oscillation frequencies of the BOLD signal. Our results suggest a pivotal role of the frontal cortex in propofol-induced loss of responsiveness.
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Affiliation(s)
- Pieter Guldenmund
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
| | - Ithabi S Gantner
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
| | - Katherine Baquero
- 2 Computer Imaging and Medical Applications Laboratory, National University of Colombia , Bogotá, Colombia
- 3 MoVeRe Group, Cyclotron Research Center, University of Liège , Liège, Belgium
| | - Tushar Das
- 4 Department of Physics and Astronomy, Brain and Mind Institute, University of Western Ontario , London, Ontario, Canada
| | - Athena Demertzi
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
- 5 Department of Neurology, CHU University Hospital, University of Liège , Liège, Belgium
| | - Pierre Boveroux
- 6 Department of Anesthesia and Intensive Care Medicine, CHU University Hospital, University of Liège , Liège, Belgium
| | - Vincent Bonhomme
- 6 Department of Anesthesia and Intensive Care Medicine, CHU University Hospital, University of Liège , Liège, Belgium
- 7 Department of Anesthesia and Intensive Care Medicine, CHR Hospital Citadelle , Liège, Belgium
| | - Audrey Vanhaudenhuyse
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
- 8 Department of Algology and Palliative Care, CHU University Hospital, University of Liège , Liège, Belgium
| | - Marie-Aurélie Bruno
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
- 5 Department of Neurology, CHU University Hospital, University of Liège , Liège, Belgium
| | - Olivia Gosseries
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
- 5 Department of Neurology, CHU University Hospital, University of Liège , Liège, Belgium
| | - Quentin Noirhomme
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
| | - Muriëlle Kirsch
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
- 6 Department of Anesthesia and Intensive Care Medicine, CHU University Hospital, University of Liège , Liège, Belgium
| | - Mélanie Boly
- 9 Department of Neurology, University of Wisconsin , Madison, Wisconsin
| | - Adrian M Owen
- 10 Department of Psychology, Brain and Mind Institute, University of Western Ontario , London, Ontario, Canada
| | - Steven Laureys
- 1 Coma Science Group, Cyclotron Research Center, CHU University Hospital, University of Liège , Liège, Belgium
- 5 Department of Neurology, CHU University Hospital, University of Liège , Liège, Belgium
| | - Francisco Gómez
- 11 Department of Computer Science, Central University of Colombia , Bogotá, Colombia
| | - Andrea Soddu
- 4 Department of Physics and Astronomy, Brain and Mind Institute, University of Western Ontario , London, Ontario, Canada
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Chouchou F, Desseilles M. Heart rate variability: a tool to explore the sleeping brain? Front Neurosci 2014; 8:402. [PMID: 25565936 PMCID: PMC4263095 DOI: 10.3389/fnins.2014.00402] [Citation(s) in RCA: 95] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2014] [Accepted: 11/19/2014] [Indexed: 12/17/2022] Open
Abstract
Sleep is divided into two main sleep stages: (1) non-rapid eye movement sleep (non-REMS), characterized among others by reduced global brain activity; and (2) rapid eye movement sleep (REMS), characterized by global brain activity similar to that of wakefulness. Results of heart rate variability (HRV) analysis, which is widely used to explore autonomic modulation, have revealed higher parasympathetic tone during normal non-REMS and a shift toward sympathetic predominance during normal REMS. Moreover, HRV analysis combined with brain imaging has identified close connectivity between autonomic cardiac modulation and activity in brain areas such as the amygdala and insular cortex during REMS, but no connectivity between brain and cardiac activity during non-REMS. There is also some evidence for an association between HRV and dream intensity and emotionality. Following some technical considerations, this review addresses how brain activity during sleep contributes to changes in autonomic cardiac activity, organized into three parts: (1) the knowledge on autonomic cardiac control, (2) differences in brain and autonomic activity between non-REMS and REMS, and (3) the potential of HRV analysis to explore the sleeping brain, and the implications for psychiatric disorders.
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Affiliation(s)
- Florian Chouchou
- NeuroPain Unit, Lyon Neuroscience Research Centre, CRNL - INSERM U 1028/CNRS UMR 5292, University of Lyon France ; Department of Psychology, University of Namur Namur, Belgium
| | - Martin Desseilles
- Department of Psychology, University of Namur Namur, Belgium ; Cyclotron Research Centre, University of Liège Liège, Belgium
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Dijk DJ. Daily variations in sleep: associated genes and effects on affect. J Sleep Res 2014; 23:607-608. [DOI: 10.1111/jsr.12268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Abstract
Human brain dynamics are nowadays routinely explored at the macroscopic level using a wide variety of non-invasive neuroimaging techniques, including single photon emission computed tomography (SPECT) and positron emission tomography (PET), near infrared spectroscopy (NIRS) and functional magnetic resonance imaging (fMRI). In the past decades, the application of brain imaging methods to the study of sleep raised a renewed interest for the field, especially in the domain of neuroscience. Indeed, these studies enabled researchers to characterize the functional neuroanatomy of sleep stages and identify the neural correlates of phasic and tonic sleep mechanisms. Furthermore, they provided the scientific community with tools to address the crucial question of brain plasticity processes during human sleep, the role of sleep-related plasticity for memory consolidation, and how sleep and the lack of post-training sleep impacts brain functioning in the neural networks underlying memory-related cognitive processes. This chapter reviews the contributions of neuroimaging to our understanding of the functional neuroanatomy of sleep and sleep stages, and discusses how sleep contributes to the long-term consolidation of recently acquired memories in light of contemporary neural models for memory consolidation during sleep.
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Affiliation(s)
- Philippe Peigneux
- UR2NF-Neuropsychology and Functional Neuroimaging Research Unit, CRCN-Centre de Recherches Cognition et Neurosciences and UNI-ULB Neurosciences Institute, Université Libre de Bruxelles (ULB), CP191, Av. F Roosevelt 50, 1050, Bruxelles, Belgium,
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Abstract
This review summarizes the brain mechanisms controlling sleep and wakefulness. Wakefulness promoting systems cause low-voltage, fast activity in the electroencephalogram (EEG). Multiple interacting neurotransmitter systems in the brain stem, hypothalamus, and basal forebrain converge onto common effector systems in the thalamus and cortex. Sleep results from the inhibition of wake-promoting systems by homeostatic sleep factors such as adenosine and nitric oxide and GABAergic neurons in the preoptic area of the hypothalamus, resulting in large-amplitude, slow EEG oscillations. Local, activity-dependent factors modulate the amplitude and frequency of cortical slow oscillations. Non-rapid-eye-movement (NREM) sleep results in conservation of brain energy and facilitates memory consolidation through the modulation of synaptic weights. Rapid-eye-movement (REM) sleep results from the interaction of brain stem cholinergic, aminergic, and GABAergic neurons which control the activity of glutamatergic reticular formation neurons leading to REM sleep phenomena such as muscle atonia, REMs, dreaming, and cortical activation. Strong activation of limbic regions during REM sleep suggests a role in regulation of emotion. Genetic studies suggest that brain mechanisms controlling waking and NREM sleep are strongly conserved throughout evolution, underscoring their enormous importance for brain function. Sleep disruption interferes with the normal restorative functions of NREM and REM sleep, resulting in disruptions of breathing and cardiovascular function, changes in emotional reactivity, and cognitive impairments in attention, memory, and decision making.
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Affiliation(s)
- Ritchie E Brown
- Laboratory of Neuroscience, VA Boston Healthcare System and Harvard Medical School, Brockton, Massachusetts 02301, USA
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McCoy JG, Strecker RE. The cognitive cost of sleep lost. Neurobiol Learn Mem 2011; 96:564-82. [PMID: 21875679 DOI: 10.1016/j.nlm.2011.07.004] [Citation(s) in RCA: 177] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2011] [Revised: 07/12/2011] [Accepted: 07/25/2011] [Indexed: 11/25/2022]
Abstract
A substantial body of literature supports the intuitive notion that a good night's sleep can facilitate human cognitive performance the next day. Deficits in attention, learning & memory, emotional reactivity, and higher-order cognitive processes, such as executive function and decision making, have all been documented following sleep disruption in humans. Thus, whilst numerous clinical and experimental studies link human sleep disturbance to cognitive deficits, attempts to develop valid and reliable rodent models of these phenomena are fewer, and relatively more recent. This review focuses primarily on the cognitive impairments produced by sleep disruption in rodent models of several human patterns of sleep loss/sleep disturbance. Though not an exclusive list, this review will focus on four specific types of sleep disturbance: total sleep deprivation, experimental sleep fragmentation, selective REM sleep deprivation, and chronic sleep restriction. The use of rodent models can provide greater opportunities to understand the neurobiological changes underlying sleep loss induced cognitive impairments. Thus, this review concludes with a description of recent neurobiological findings concerning the neuroplastic changes and putative brain mechanisms that may underlie the cognitive deficits produced by sleep disturbances.
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Affiliation(s)
- John G McCoy
- VA Boston Healthcare System, Research Service and Harvard Medical School, Department of Psychiatry, 940 Belmont St., Brockton, MA 02301-5596, USA.
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