Functional connectivity in major depression: Increased phase synchronization between frontal cortical EEG-source estimates

Olbrich, Sebastian; Tränkner, Anja; Chittka, Tobias; Hegerl, Ulrich; Schönknecht, Peter

doi:10.1016/j.pscychresns.2014.02.010

Cited by 115 publications

(87 citation statements)

References 57 publications

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“…Successful antidepressant treatment has also been shown to modify sgACC metabolism (Drevets et al, 2008) and connectivity (McCabe and Mishor, 2011; Olbrich et al, 2014). Furthermore, deep brain stimulation of the sgACC was also found to result in an antidepressant effect (Mayberg et al, 2005), and the antidepressant efficacy of transcranial magnetic stimulation (TMS) stimulation at specific loci within the dorsolateral prefrontal cortex (DLPFC) was strongly correlated with functional connectivity between the DLPFC site and the sgACC (Fox et al, 2012; Fox et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Preliminary differences in resting state MEG functional connectivity pre- and post-ketamine in major depressive disorder

Nugent

Robinson

Coppola

et al. 2016

Psychiatry Research: Neuroimaging

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Functional neuroimaging techniques including magnetoencephalography (MEG) have demonstrated that the brain is organized into networks displaying correlated activity. Group connectivity differences between healthy controls and participants with major depressive disorder (MDD) can be detected using temporal independent components analysis (ICA) on beta-bandpass filtered Hilbert envelope MEG data. However, the response of these networks to treatment is unknown. Ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, exerts rapid antidepressant effects. We obtained MEG recordings before and after open-label infusion of 0.5mg/kg ketamine in MDD subjects (N=13) and examined networks previously shown to differ between healthy individuals and those with MDD. Connectivity between the amygdala and an insulo-temporal component decreased post-ketamine in MDD subjects towards that observed in control subjects at baseline. Decreased baseline connectivity of the subgenual anterior cingulate cortex (sgACC) with a bilateral precentral network had previously been observed in MDD compared to healthy controls, and the change in connectivity post-ketaminewas proportional to the change in sgACC glucose metabolism in a subset (N=8) of subjects receiving [11F]FDG-PET imaging. Ketamine appeared to reduce connectivity, regardless of whether connectivity was abnormally high or low compared to controls at baseline. These preliminary findings suggest that sgACC connectivity may be directly related to glutamate levels.

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Section: Discussionmentioning

confidence: 99%

Preliminary differences in resting state MEG functional connectivity pre- and post-ketamine in major depressive disorder

Nugent

Robinson

Coppola

et al. 2016

Psychiatry Research: Neuroimaging

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show abstract

“…More recent studies used a huge variety of connectivity measures like partial directed coherence, Granger causality, structural synchrony index and phase synchrony index. Some found decreased EEG connectivity in MDD [122,132,133,134] while others report of increased EEG connectivity in MDD, mainly in the alpha band [135,136,137,138]. More studies are needed to disentangle the complex relationship between the different connectivity measures and their physiological interpretation and to estimate the value for treatment prediction.…”

Section: Biomarkersmentioning

confidence: 99%

“…More studies are needed to disentangle the complex relationship between the different connectivity measures and their physiological interpretation and to estimate the value for treatment prediction. In this context, one study [138] found an association between increased phase connectivity in the beta band between the subgenual prefrontal cortex and the right medial frontal cortex and treatment response. As suggested above in relation to theta activity, these approaches, when replicated, could further shed light onto the controversy between increased or decreased metabolism in the rACC/SCC.…”

Section: Biomarkersmentioning

confidence: 99%

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

2015

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Personalized medicine in psychiatry is in need of biomarkers that resemble central nervous system function at the level of neuronal activity. Electroencephalography (EEG) during sleep or resting-state conditions and event-related potentials (ERPs) have not only been used to discriminate patients from healthy subjects, but also for the prediction of treatment outcome in various psychiatric diseases, yielding information about tailored therapy approaches for an individual. This review focuses on baseline EEG markers for two psychiatric conditions, namely major depressive disorder and attention deficit hyperactivity disorder. It covers potential biomarkers from EEG sleep research and vigilance regulation, paroxysmal EEG patterns and epileptiform discharges, quantitative EEG features within the EEG main frequency bands, connectivity markers and ERP components that might help to identify favourable treatment outcome. Further, the various markers are discussed in the context of their potential clinical value and as research domain criteria, before giving an outline for future studies that are needed to pave the way to an electrophysiological biomarker-based personalized medicine.

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“…Treatment-based EEG studies established once more the importance of the subgenual ACC. Indeed, depressed patients appear to show enhanced connectivity within nodes of the DMN and between nodes of the DMN and the CEN (3, 92). Specifically, enhanced connectivity in alpha frequency band (8–12 Hz) between the subgenual ACC and left mPFC is observed before antidepressant treatment, which switched into enhanced connectivity in beta frequency band (12.5–20 Hz) between the subgenual ACC and right mPFC after antidepressant treatment, thus underlying the recurrent asymmetrical connectivity patterns observed in MDD patients’ frontal lobe (92, 95).…”

Section: Abnormal Connectivity In Psychiatric Disorders: Where Do Wementioning

confidence: 99%

“…Indeed, depressed patients appear to show enhanced connectivity within nodes of the DMN and between nodes of the DMN and the CEN (3, 92). Specifically, enhanced connectivity in alpha frequency band (8–12 Hz) between the subgenual ACC and left mPFC is observed before antidepressant treatment, which switched into enhanced connectivity in beta frequency band (12.5–20 Hz) between the subgenual ACC and right mPFC after antidepressant treatment, thus underlying the recurrent asymmetrical connectivity patterns observed in MDD patients’ frontal lobe (92, 95). Moreover, it has been suggested that alterations in frontotemporal connectivity in delta/theta (1–8 Hz) frequency range could be used a marker to predict responders and non-responders to antidepressant medication (i.e., selective serotonin reuptake inhibitor), with hyperconnectivity between these areas being associated to poorer response (96).…”

Section: Abnormal Connectivity In Psychiatric Disorders: Where Do Wementioning

confidence: 99%

Alterations of Intrinsic Brain Connectivity Patterns in Depression and Bipolar Disorders: A Critical Assessment of Magnetoencephalography-Based Evidence

et al. 2017

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Despite being the object of a thriving field of clinical research, the investigation of intrinsic brain network alterations in psychiatric illnesses is still in its early days. Because the pathological alterations are predominantly probed using functional magnetic resonance imaging (fMRI), many questions about the electrophysiological bases of resting-state alterations in psychiatric disorders, particularly among mood disorder patients, remain unanswered. Alongside important research using electroencephalography (EEG), the specific recent contributions and future promise of magnetoencephalography (MEG) in this field are not fully recognized and valued. Here, we provide a critical review of recent findings from MEG resting-state connectivity within major depressive disorder (MDD) and bipolar disorder (BD). The clinical MEG resting-state results are compared with those previously reported with fMRI and EEG. Taken together, MEG appears to be a promising but still critically underexploited technique to unravel the neurophysiological mechanisms that mediate abnormal (both hyper- and hypo-) connectivity patterns involved in MDD and BD. In particular, a major strength of MEG is its ability to provide source-space estimations of neuromagnetic long-range rhythmic synchronization at various frequencies (i.e., oscillatory coupling). The reviewed literature highlights the relevance of probing local and interregional rhythmic synchronization to explore the pathophysiological underpinnings of each disorder. However, before we can fully take advantage of MEG connectivity analyses in psychiatry, several limitations inherent to MEG connectivity analyses need to be understood and taken into account. Thus, we also discuss current methodological challenges and outline paths for future research. MEG resting-state studies provide an important window onto perturbed spontaneous oscillatory brain networks and hence supply an important complement to fMRI-based resting-state measurements in psychiatric populations.

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Functional connectivity in major depression: Increased phase synchronization between frontal cortical EEG-source estimates

Cited by 115 publications

References 57 publications

Preliminary differences in resting state MEG functional connectivity pre- and post-ketamine in major depressive disorder

Preliminary differences in resting state MEG functional connectivity pre- and post-ketamine in major depressive disorder

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder

Alterations of Intrinsic Brain Connectivity Patterns in Depression and Bipolar Disorders: A Critical Assessment of Magnetoencephalography-Based Evidence

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