These results indicate that subjects with MDD differ significantly from healthy control subjects in patterns of brain functional connectivity. A large number of highly significant edges, in all frequency bands, showed higher functional connectivity in MDD as compared to controls. These differences were most notable in the alpha and beta bands. The hub nodes most often involved in increased connectivity were located in the frontopolar and DLPFC regions, although the patterns of connectivity involving these nodes differed by frequency: in the alpha band, these nodes were involved in significantly longer distance edges than in the beta band. Examination of the most significant edges in the alpha band showed that the connections were between the frontopolar or DLPFC regions and the temporal or parietooccipital regions, whereas in the beta band, the connections were most often within the prefrontal, temporal, or less often the parietooccipital regions. Nearest centroid analysis indicated that six connections in the alpha band, five of which showed higher connectivity between the frontopolar and DLPFC or frontopolar and temporal regions, and one of which showed lower connectivity within the parietooccipital region, differentiated MDD from control subjects with 81% accuracy.
The patterns of difference between MDD and control subjects, which are consistent with earlier results from Fingelkurts and colleagues 
, should be interpreted within the context of prior research regarding the role of rhythmic oscillations in regulating brain activity. Rhythmic activity overall helps to bind cell assemblies together into functional units: lower frequency oscillations (in the alpha and theta range) operate at a broader level across the brain, binding more distant areas into functional units through “top-down” control, and modulating the activity of local functional units that are bound together by faster oscillations 
. The present findings are consistent with this functional topography of alpha and beta oscillations in the brain. Increased alpha coherence was observed in edges that span relatively greater distances (e.g., between prefrontal nodes and more distant temporal or parietooccipital regions), whereas increased beta coherence was evidenced in shorter distance edges (e.g., within frontal or temporal regions).
These findings, which suggest a broad loss of selectivity in functional connections in MDD, are consistent with the reports of Sheline and colleagues 
as well the Zhou 
and Greicius 
groups, which showed significant increases in resting-state cortical functional connectivity in MDD using fMRI. The location of the prefrontal hub nodes that showed the most frequent involvement in increased coherence in the present study approximately coincides with the dorsomedial prefrontal cortical area found by Sheline's group to constitute a “dorsal nexus” of increased connectivity 
. The fact that the most significant increases in coherence were found in the alpha frequency band could be interpreted as a failure of the top-down control exerted by rhythmic alpha activity. This rhythm is generated by the cortex under the influence of corticothalamic neuronal loops 
. Greicius and colleagues showed significantly increased thalamic functional connectivity with the default mode network at rest in MDD, supporting the concept of dysfunction in the top-down control circuit that is mediated by rhythmic alpha activity 
. The increases in longer-distance alpha coherence could in turn mediate the local increases seen in beta coherence; there is significant cross-frequency interaction, such that top-down alpha band oscillatory processes and bottom-up high frequency oscillatory processes may be functionally coupled 
. The possibility that increased alpha coherence may in part be the result of a bottom-up input from local processes in the beta frequency band, however, cannot be ruled out.
The present findings establish a new context for interpretation of previous studies showing differences in frontal alpha band power and synchrony between subjects with MDD and normal controls 
. Studies have shown increases in synchronized frontal alpha activity and qEEG alpha power, although the lateralization has varied, with relatively greater alpha power reported both over left and right anterior regions 
. It is possible that shifting power asymmetries previously reported 
may reflect the effects of significantly increased functional connectivity in subjects with MDD. Recent results indicate that interhemispheric interactions are related to shifting lateralization on a moment-to-moment basis in MDD 
. Future studies should examine the role of increased connectivity in modulating asymmetries in frontal power.
Few previous studies have assessed resting state functional connectivity in MDD. Winterer and colleagues reported that depressed alcoholic patients had significant increases in coherence in the alpha and beta bands in the posterior regions, although alcoholics without depression did not 
. Fingelkurts and colleagues examined the “index of structural synchrony,” a different measure of signal synchronization, and found that subjects with MDD had broad significant increases in alpha and theta band functional connectivity 
. These differences consisted primarily of increased short distance functional connections in the left and long-range connections in the right hemisphere. They interpreted these increases as adaptive and compensatory mechanisms aimed at overcoming deficient semantic integration. Hinrikus and colleagues found that depressed subjects had increased coherence between some brain regions, but examined only interhemispheric coherence between small numbers of locations and detected no statistically significant difference 
. Other studies of coherence have used methods that differ from the current study, and have obtained disparate results. Knott and colleagues 
found decreased coherence in MDD subjects compared to normal controls, but calculated coherence between a limited number of individual electrodes, a technique that may not characterize regional measures of brain activity as well as the electrode pairs in the present study 
. Armitage and colleagues have examined coherence during sleep and shown that it is decreased among adolescents with MDD, and is a predictor of recurrence and risk of developing illness 
. The relationship between sleep and resting awake state coherence is unknown.
Greicius and colleagues speculated that the increased functional connectivity in mood regulating networks might be associated with impaired cognitive processing in MDD 
. This speculation is consistent with the established role of oscillatory activity in regulating cognitive networks 
. The ability to modulate alpha rhythmicity and coherence has been linked to the ability to shift and focus attention, and meet working memory and executive demands 
. Successful modulation of beta activity has been related to response preparation and cognitive control 
; “pathological” increases in beta activity are associated with deterioration in cognitive flexibility and control 
. Several neurophysiologic measures of synchronization, including coherence, phase synchronization, and synchronization likelihood, have been related to deficits on measures of attention and working memory, as well as processing of auditory, visual, linguistic, and social cognition information in psychiatric and neurologic illnesses 
. This wide range of cognitive activities overlaps with the cognitive domains and functions that have been reported to be deficient in some subjects with MDD 
. Theta oscillations play a significant role in memory function, with modulated coupling of theta oscillations between the prefrontal, parietal, and temporal cortices prominently involved in memory encoding and recall 
. In the present study, those edges showing significantly increased coherence in the theta band involved connections between prefrontal and temporal regions. These connections may have special functional significance related to memory dysfunction in MDD, and should be explored in future studies.
Experimental data also link synchronization of neuronal oscillations to the ability to process emotional information. Kostandov and colleagues reported that processing of the emotional content of facial expression was associated with increases in coherence in the theta and alpha frequency ranges, particularly involving the dorsolateral frontal and temporal cortices 
. Similarly, Balconi and colleagues found that processing of positive and negative visual images, or masked emotional facial expressions 
, was associated with increases in coherence in the delta, theta, and alpha bands, depending on the nature of the task and stimulus, and particularly from the frontal regions. In addition to processing of emotional content, the subject's internal emotional state may be mediated by the degree of synchronization. Andersen and colleagues reported that anxious rumination in healthy volunteers was associated with increases in theta and alpha band coherence 
. This finding is consistent with the results reported here that MDD is associated with an increase in theta and alpha coherence, and also is consistent with Greicius' speculation that increased connectivity associated with MDD may operate to the detriment of other types of brain processing 
. If networks are saturated with the load of processing emotional information, there may be limited capacity to modulate synchronization in response to other processing demands.
Previous reports have highlighted disruption of brain regulatory mechanisms in MDD, focusing on “hubs” of the mood regulatory network such as the rostral anterior cingulate (rACC) 
or the dorsal nexus posited by Sheline and colleagues 
. Disruption of normal connectivity patterns could explain many of the regulatory, cognitive, neurovegetative, and emotional symptoms of MDD 
. It remains unclear what fundamental mechanism underlies and perpetuates network dysregulation. The current results are consistent with a growing body of literature implicating disturbed brain oscillatory activity in the pathogenesis of MDD 
. Modulation of cerebral oscillatory activity plays a central role in regulation of mood, and processing of affective information and emotional stimuli 
. Interestingly, synchronization of oscillatory activity is strongly influenced by central serotonergic tone 
. Serotonergic projections from the medial septal area inhibit hippocampal theta oscillatory synchrony 
, while alpha synchrony is modulated by serotonergic projections from the raphe nuclei to the intralaminar and medial thalamic nuclei 
. Furthermore, oscillatory activity and related behaviors are modulated by administration of antidepressant medication in animals 
. Oscillatory synchrony could represent the neurophysiologic link between neurochemical activity and brain network functions that regulate mood, affect, and processing of emotional information. Oscillatory dysregulation may similarly represent the pathophysiologic link between disturbances in monoaminergic neurotransmission and brain network dysfunction in MDD. Future research should more closely examine the regulation of oscillatory synchrony in subjects at risk for or recovering from MDD, as well as the effect of antidepressant treatments on oscillatory synchrony in MDD.
There are several limitations to the current study. First, limited information was available on the specific symptoms of the MDD subjects and the number of prior episodes they may have had, so we cannot relate the increased connectivity to specific subtypes of the illness. Second, because all subjects in the present study either were experiencing a current major depressive episode or were healthy controls, it is unclear whether elevated connectivity would resolve with treatment or it would be a persistent trait marker for those with a predisposition to the illness. Third, in this study we examined only a single measure of neurophysiologic connectivity, coherence, which indicates the linear association between time-series curves in a frequency band 
. Absence of a statistical association between two processes does not necessarily exclude a physiologic connection 
; conversely, presence of an association does not necessarily indicate a physiologic connection, as EEG signals show a finite correlation even when recorded from separate subjects (secondary to the finite epoch time and similar bandwidth of signal pairs) 
. Finally, although there is strong evidence of correspondence between surface EEG and brain functional activity in underlying structures 
, EEG coherence, like any metric derived from electrical recordings from the scalp does not directly measure brain activity. Connectivity of brain regions is inferred from electrical activity recorded at surface sites overlying the various cortical regions.
There is no single technique that has proven to be ideal to study the interaction between two brain signals from scalp recordings. Coherence measures are susceptible to both volume conduction and electrode reference effects 
, although in the present study both effects were minimized through calculating coherence from closely spaced bipolar electrode pairs 
. This strategy renders these confounding influences negligible for close bipolar pairs separated from one another by more than 4–5 cm 
, although volume conduction still may increase coherence for shorter distances depending upon the frequency band and the orientation of the dipole source 
. It is highly unlikely, however, that any of the differences reported between the MDD and healthy control groups in the current study would arise from volume conduction or reference effects because the electrode montage and recording techniques were identical for both depressed and control groups. Nevertheless, future studies also should consider use of surface Laplacian 
and Independent Component Analysis (ICA) 
EEG methods, as well as phase synchrony 
connectivity measures, that may help further minimize the effects of volume conduction. Use of high-density electrode arrays in future studies also would help to define more clearly the brain regions showing differences in brain connectivity between MDD and control subjects.
These findings indicate that resting state neurophysiologic connectivity is increased broadly across all brain regions in MDD. Future studies also should more closely examine clinical features of subjects with MDD, including cognitive profiles, functional status, and response to treatment in relation to connectivity measures, in order to determine the possible role of increased functional connectivity as a diagnostic or prognostic marker for MDD.