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

https://doi.org/10.1016/j.pscychresns.2014.02.010Get rights and content

Abstract

Structural and metabolic alterations in prefrontal brain areas, including the subgenual (SGPFC), medial (MPFC) and dorsolateral prefrontal cortex (DLPFC), have been shown in major depressive disorder (MDD). Still it remains largely unknown how brain connectivity within these regions is altered at the level of neuronal oscillations. Therefore, the goal was to analyze prefrontal electroencephalographic phase synchronization in MDD and its changes after antidepressant treatment. In 60 unmedicated patients and 60 healthy controls (HC), a 15-min resting electroencephalogram (EEG) was recorded in subjects at baseline and in a subgroup of patients after 2 weeks of antidepressant medication. EEG functional connectivity between the SGPFC and the MPFC/DLPFC was assessed with eLORETA (low resolution brain electromagnetic tomography) by means of lagged phase synchronization. At baseline, patients revealed increased prefrontal connectivity at the alpha frequency between the SGPFC and the left DLPFC/MPFC. After treatment, an increased connectivity between the SGPFC and the right DLPFC/MPFC at the beta frequency was found for MDD. A positive correlation was found for baseline beta connectivity and reduction in scores on the Hamilton depression rating scale. MDD is characterized by increased EEG functional connectivity within frontal brain areas. These EEG markers of disturbed neuronal communication might have potential value as biomarkers.

Introduction

Major depressive disorder (MDD) is a severe and life-threatening disorder. Although the underlying pathomechanisms are yet to be understood, the prefrontal cortex (PFC), including the subgenual prefrontal cortex (SGPFC), the medial prefrontal cortex (MPFC) and the dorsolateral prefrontal cortex (DLPFC), has been a focus of research (Price and Drevets, 2010, Price and Drevets, 2012). These brain areas have been associated with the identification of emotional stimuli and affective response regulation (Phillips et al., 2003), reward processing (Pochon et al., 2002, Liu et al., 2011) and experience of negative mood states or transient sadness (Mayberg et al., 1999, Lévesque et al., 2011); a prefrontal dysfunction is thought to account for core symptoms of depression such as anhedonia and cognitive deficits (Pizzagalli et al., 2004, Diener et al., 2012, Duman and Aghajanian, 2012). Structural imaging studies have shown altered in vivo cortical volume in MDD in prefrontal areas, including the SGPFC with decreased grey matter volume (Drevets et al., 1997, van Tol et al., 2010) and the DLPFC with reduced in vitro neuronal cell size and decreased glial cell density (Cotter et al., 2002).

These findings are paralleled by metabolic alterations revealed by positron emission tomography (PET) studies that show, for example, decreased glucose metabolism in prefrontal areas such as the SGPFC (Drevets et al., 1997, Pizzagalli et al., 2004). Functional magnetic resonance imaging (fMRI) studies have revealed a primarily prefrontal focus of altered blood-oxygen-level-dependent (BOLD) signals in MDD compared with healthy controls (Lemogne et al., 2012), while the SGPFC has been found to yield increased fMRI-based functional connectivity patterns within the default mode network (Greicius et al., 2007) and the dorsomedial prefrontal cortex (Davey et al., 2012). Recently, the BOLD-signal time courses at the left DLPFC, a location shown to be the most clinically efficacious target in transcranial magnetic stimulation (TMS) treatment, were found to be negatively correlated with the BOLD signal of the SGPFC, underpinning the value of connectivity analysis (Fox et al., 2012a).

MDD is characterized by disturbed emotional processing (Diener et al., 2012). Findings from EEG-connectivity studies that used paradigms with emotional stimuli have shed light on the underlying electrophysiological connectivity patterns during emotional processing in healthy subjects. In particular, alterations within the beta frequency band have been associated with emotional stimuli. For example, increased EEG coherence, as a measure of functional connectivity, has been found during emotional stimulation (Miskovic and Schmidt, 2010), while a decrease in beta coherence has been associated with reduced control over emotional information in healthy subjects (Reiser et al., 2012). Besides this evidence for the association between EEG coherence and emotional processing, characteristic alterations that mainly involve increased coherence have also been reported during the resting state in MDD: Fingelkurts et al. (2007) found increased synchronization in the EEG alpha and theta bands in patients with MDD, and Leuchter et al. (2012) recently reported an increased topographic EEG coherence between frontal brain areas in MDD in the EEG alpha, beta and theta bands. Further Lee et al. (2011) found that responders to antidepressant treatment, compared with non-responders, showed increased coupling of EEG power at the delta and theta frequencies between right fronto-parietal electrodes.

To bring together findings of structural and metabolic alterations with reports of increased topographical electrophysiological coherence in MDD, the goal of this study was to explore EEG-based phase synchronization as a measure of electrophysiological brain connectivity between anatomical structures such as the SGPFC and other prefrontal brain areas including the DLPFC and the MPFC in MDD patients in comparison to healthy controls (HC) under resting conditions. Therefore, region of interest (ROI)-based time series of intracortical EEG-source estimates were used instead of pairs of EEG-channel time series for assessment of functional EEG connectivity.

The underlying concept of phase synchronization is that different brain areas are thought to be more connected, directly or via a third source, the higher the non-linear coherence, i.e., phase synchronization, between the two signals is (for a review of the concept, see Fell and Axmacher, 2011). For computation of phase synchronization of EEG signals, the so-called “lagged non-linear connectivity” (Pascual-Marqui et al., 2011) measure was used. It is independent of the signal amplitude and strictly relies on the synchronization of phases. According to previous topographical EEG studies (Fingelkurts et al., 2007, Leuchter et al., 2012), it was hypothesized that patients with MDD would reveal increased connectivity between the SGPFC and the DLPFC or the MPFC within the delta, theta, alpha and beta frequency range.

In addition, we explored the changes of the connectivity measure in a subgroup of MDD patients after 2 weeks of antidepressant treatment compared with findings in HC after the same retest interval. An exploratory analysis analyzed the association between the connectivity measure and scores on the Hamilton depression rating scale (HDRS) and their changes over time.

Section snippets

Patients and controls

The study was approved by the local ethics committee. Written informed consent was obtained before the study began according to the Declaration of Helsinki. The study group comprised 60 patients (Table 1) with a current DSM-IV diagnosis of major depressive disorder (MDD). All patients were recruited from inpatients and outpatients admitted to the Psychiatric Department at the University Hospital of Leipzig between 2007 and 2011. Diagnosis of MDD was determined for each patient after clinical

Sociodemographic variables and data quality

No age or sex differences were found between patients and HC (see Table 1). Also, there were no differences between the subsample of antidepressant-treated patients and HC (see Table 1 for details), and both patients and controls were compared in a second EEG performed after 14 days.

Concerning the analysed EEG data, out of 450 2-s segments from the resting period, in average 421.6 segments (SD 22.0) for patients with MDD and 424.6 segments (SD 11.5) for HC entered the analysis after removal of

Discussion

The results show an increased functional connectivity by means of EEG lagged phase synchronization during rest between the subgenual prefrontal cortex and the left dorsolateral prefrontal cortex and the left medial prefrontal cortex within the EEG alpha frequency band in MDD in comparison to findings in healthy controls. In an EEG retest of a subgroup of HC after 2 weeks, the phase synchronization did not show any significant changes, providing evidence for the retest stability of the measure.

Conclusion

The synchronization and desynchronization of neuronal activity as assessed by EEG is one footprint of the working brain. The distributed but coupled rhythmic activity at distinct brain areas during rest represents the steadily ongoing self-organization of neuronal activity that makes the brain distinct from a matrix of random oscillations. MDD is characterized by disturbances of neuronal interaction, especially in prefrontal regions such as the SGPFC and the DLPFC. By bridging

Financial disclosures

U. Hegerl has been or is participating in advisory boards of Lilly, Wyeth, Lundbeck, and Sanofi-Aventis. He received financial support for an Investigator Initiated Trial from Lundbeck. He received honoraria for single lectures as well as sponsorships for symposia and an Internet service from Cephalon and other pharmaceutical companies, health insurance companies, and other parties. The remaining authors PS, SO, AT and TC report no biomedical financial interests or potential conflicts of

Acknowledgements

We thank Mrs. I. Thomas and Mrs. M. Siebert for their technical assistance.

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