Visual working memory (VWM) is used to maintain sensory information for cognitive operations, and its deficits are associated with several neuropsychological disorders. VWM is based on sustained neuronal activity in a complex cortical network of frontal, parietal, occipital, and temporal areas. The neuronal mechanisms that coordinate this distributed processing to sustain coherent mental images and the mechanisms that set the behavioral capacity limit have remained unknown. We mapped the anatomical and dynamic structures of network synchrony supporting VWM by using a neuro informatics approach and combined magnetoencephalography and electroencephalography. Interareal phase synchrony was sustained and stable during the VWM retention period among frontoparietal and visual areas in α-(10-13 Hz), β-(18-24 Hz), and γ-(30-40 Hz) frequency bands. Furthermore, synchrony was strengthened with increasing memory load among the frontoparietal regions known to underlie executive and attentional functions during memory maintenance. On the other hand, the subjects' individual behavioral VWM capacity was predicted by synchrony in a network in which the intraparietal sulcus was the most central hub. These data suggest that interareal phase synchrony in the α-, β-, and γ-frequency bands among frontoparietal and visual regions could be a systems level mechanism for coordinating and regulating the maintenance of neuronal object representations in VWM.cortical synchrony | graph theory | magnetoencephalography | source modelling | functional connectivity F unctional MRI (fMRI) studies have shown that human visual working memory (VWM) is supported by neuronal activity in several cortical regions in the frontal, parietal, occipital, and temporal lobes (1-6), where the frontoparietal regions mediate attentional and central executive functions (2-4, 7, 8) and the visual areas underlie the formation of neuronal object representations (9-11) and sustain them in VWM (8). However, fMRI does not have the subsecond temporal precision required for revealing the neuronal mechanisms that integrate and coordinate the processing in the functionally distinct regions during VWM maintenance. These functions could be carried out by oscillatory synchrony (i.e., rhythmical millisecond-range temporal correlations of neuronal activity), which modulates neuronal interactions and regulates network communication (12)(13)(14)(15)(16). The functional role of oscillatory synchrony can be studied noninvasively by combining magnetoencephalography and electroencephalography (MEEG) recordings with source reconstruction techniques that reveal the anatomical structures producing the MEEG signals. Earlier studies have considered interactions among approximately three to nine cortical regions of interest and revealed attentional modulations of interareal synchrony (17-19). The interactions underlying VWM have remained uncharacterized. We hypothesized that neuronal synchronization is instrumental for the maintenance of object representations in VWM. To have this role, s...

Our ability to perceive weak signals is correlated among consecutive trials and fluctuates slowly over time. Although this "streaking effect" has been known for decades, the underlying neural network phenomena have remained largely unidentified. We examined the dynamics of human behavioral performance and its correlation with infraslow (0.01-0.1 Hz) fluctuations in ongoing brain activity. Full-band electroencephalography revealed prominent infraslow fluctuations during the execution of a somatosensory detection task. Similar fluctuations were predominant also in the dynamics of behavioral performance. The subjects' ability to detect the sensory stimuli was strongly correlated with the phase, but not with the amplitude of the infraslow EEG fluctuations. These data thus reveal a direct electrophysiological correlate for the slow fluctuations in human psychophysical performance. We then examined the correlation between the phase of infraslow EEG fluctuations and the amplitude of 1-40 Hz neuronal oscillations in six frequency bands. Like the behavioral performance, the amplitudes in these frequency bands were robustly correlated with the phase of the infraslow fluctuations. These data hence suggest that the infraslow fluctuations reflect the excitability dynamics of cortical networks. We conclude that ongoing 0.01-0.1 Hz EEG fluctuations are prominent and functionally significant during execution of cognitive tasks.

When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or "ghost" interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations.

Neuroimaging has revealed robust large-scale patterns of high neuronal activity in the human brain in the classical eyes-closed wakeful rest condition, pointing to the presence of a baseline of sustained endogenous processing in the absence of stimulus-driven neuronal activity. This baseline state has been shown to differ in major depressive disorder. More recently, several studies have documented that despite having a complex temporal structure, baseline oscillatory activity is characterized by persistent autocorrelations for tens of seconds that are highly replicable within and across subjects. The functional significance of these long-range temporal correlations has remained unknown.We recorded neuromagnetic activity in patients with a major depressive disorder and in healthy control subjects during eyes-closed wakeful rest and quantified the long-range temporal correlations in the amplitude fluctuations of different frequency bands. We found that temporal correlations in the theta-frequency band (3-7 Hz) were almost absent in the 5-100 s time range in the patients but prominent in the control subjects. The magnitude of temporal correlations over the left temporocentral region predicted the severity of depression in the patients.These data indicate that long-range temporal correlations in theta oscillations are a salient characteristic of the healthy human brain and may have diagnostic potential in psychiatric disorders. We propose a link between the abnormal temporal structure of theta oscillations in the depressive patients and the systems-level impairments of limbic-cortical networks that have been identified in recent anatomical and functional studies of patients with major depressive disorder.