The role of cortical oscillations in brain function has been extensively debated, resulting in a variety of theoretical frameworks. Using interleaved simultaneous electroencephalography–functional magnetic resonance imaging, we examined the layer-specific relationship between oscillatory activity and visual processing. We could demonstrate that γ band activity positively correlates with feature-specific signals in superficial layers, but we were able to report a deep layer contribution as well. In addition, we could demonstrate that α band power not only correlates negatively with the feature-unspecific BOLD signal but is related to feature-specific BOLD as well. Lower frequency α was predominantly related to feature-unspecific superficial layer BOLD, while upper frequency α was found to be related to feature-specific BOLD in superficial and deep layers. We conclude that the role of α band oscillations extends beyond widespread inhibition and might be involved in active stimulus processing on the level of visual features.

The particular role of cortical oscillations has been a long-debated topic that resulted in a variety of theoretical frameworks. Oscillatory activity in the [alpha] band has been associated with sensory processing, attention as well as other cognitive functions, while [gamma] band oscillations is thought to be related to stimulus feature processing. Current theoretical frameworks rely on the separation of the cortical architecture into layers. Recently, methodological advancements have allowed to test layer specific frameworks on the role of oscillations in cortical computations in healthy human participants. Using EEG fMRI, we have investigated for the first time both, stimulus feature specificity (line orientation) and the relationship between the laminar BOLD activity and [alpha] and γ band oscillations. We find γ oscillations to be positively correlated with feature specific signals in superficial layers as predicted by the literature, but we found a deep layer contribution as well. Furthermore we found a layer (and frequency) dissociation within the α band for general, feature unspecific, processes and a feature related process. The power of the α-band correlated negatively with feature unspecific neural activity in all cortical layers. We further found that high frequency α oscillations were specifically related to stimulus feature specific BOLD signal in deep and superficial layers. More interestingly, we also observed a general modulation effect for negative BOLD signal deflections in line with the inhibitory role of α during visual attention in superficial layers. Those findings support the association of γ band oscillations with visual feature processing and further point towards the involvement of multiple α oscillations in more general and feature related processes. ### Competing Interest Statement The authors have declared no competing interest.

Actions are biased by the outcomes they can produce: Humans are more likely to show action under reward prospect, but hold back under punishment prospect. Such motivational biases derive not only from biased response selection, but also from biased learning: humans tend to attribute rewards to their own actions, but are reluctant to attribute punishments to having held back. The neural origin of these biases is unclear. Specifically, it remains open whether motivational biases arise primarily from the architecture of subcortical regions or also reflect cortical influences, the latter being typically associated with increased behavioral flexibility and control beyond stereotyped behaviors. Simultaneous EEG-fMRI allowed us to track which regions encoded biased prediction errors in which order. Biased prediction errors occurred in cortical regions (dorsal anterior and posterior cingulate cortices) before subcortical regions (striatum). These results highlight that biased learning is not a mere feature of the basal ganglia, but arises through prefrontal cortical contributions, revealing motivational biases to be a potentially flexible, sophisticated mechanism.

Laminar functional magnetic resonance imaging (fMRI) holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded electroencephalography (EEG) and high-resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions in visual cortex. Our results indicate that our task-induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent, alpha band oscillations relate to laminar-specific fMRI connectivity. The differential effects for alpha and beta bands indicate that they relate to different feedback-related neural processes that are differentially expressed in intra-region laminar fMRI-based connectivity.

Action selection is biased by the valence of anticipated outcomes. To assess mechanisms by which these motivational biases are expressed and controlled, we measured simultaneous EEG-fMRI during a motivational Go/NoGo learning task (N = 36), leveraging the temporal resolution of EEG and subcortical access of fMRI. VmPFC BOLD encoded cue valence, importantly predicting trial-by-trial valence-driven response speed differences and EEG theta power around cue onset. In contrast, striatal BOLD encoded selection of active Go responses and correlated with theta power around response time. Within trials, theta power ramped in the fashion of an evidence accumulation signal for the value of making a "Go" response, capturing the faster responding to reward cues. Our findings reveal a dual nature of midfrontal theta power, with early components reflecting the vmPFC contribution to motivational biases, and late components reflecting their striatal translation into behavior, in line with influential recent "value of work" theories of striatal processing.

Actions are biased by the outcomes they can produce: Humans are more likely to show action under reward prospect, but hold back under punishment prospect. Such motivational biases derive not only from biased response selection, but also from biased learning: humans tend to attribute rewards to their own actions, but are reluctant to attribute punishments to having held back. The neural origin of these biases is unclear; in particular, it remains open whether motivational biases arise solely from an evolutionarily old, subcortical architecture or also due to younger, cortical influences. Simultaneous EEG-fMRI allowed us to track which regions encoded biased prediction errors in which order. Biased prediction errors occurred in cortical regions (ACC, vmPFC, PCC) before subcortical regions (striatum). These results highlight that biased learning is not a mere feature of the basal ganglia, but arises through prefrontal cortical contributions, revealing motivational biases to be a potentially flexible, sophisticated mechanism.

Action selection is not only based on acquired knowledge about action-outcome contingencies, but also by evolutionary "priors" such as motivational biases: Organisms show a tendency to invigorate responding when hoping for rewards, and to hold back when attempting to avoid punishments. While these biases are likely adaptive in many situations, they need to be inhibited when maladaptive. We probed the neural basis of overcoming these biases by measuring simultaneous EEG and fMRI. Successful detection and suppression of biases was associated with an increased synchronization in the alpha band 175-325 ms post-stimulus, which on a trial-by-trial basis was negatively correlated with BOLD signal in left MFG and right SMG. At a later time window around responses, there was a much stronger synchronization for executed vs. withheld actions in lower frequencies (peak in theta band), which was positively correlated on a trial-by-trial basis with BOLD signal in ACC/ SMA as well as bilateral motor cortex and operculum. Our work spatially locates oscillatory signatures of action selection and motivational conflict resolution.

This review investigates how laminar fMRI can complement insights into brain function derived from the study of rhythmic neuronal synchronization. Neuronal synchronization in various frequency bands plays an important role in neuronal communication between brain areas, and it does so on the backbone of layer-specific interareal anatomical projections. Feedforward projections originate predominantly in supragranular cortical layers and terminate in layer 4, and this pattern is reflected in inter-laminar and interareal directed gamma-band influences. Thus, gamma-band synchronization likely subserves feedforward signaling. By contrast, anatomical feedback projections originate predominantly in infragranular layers and terminate outside layer 4, and this pattern is reflected in inter-laminar and interareal directed alpha- and/or beta-band influences. Thus, alpha-beta band synchronization likely subserves feedback signaling. Furthermore, these rhythms explain part of the BOLD signal, with independent contributions of alpha-beta and gamma. These findings suggest that laminar fMRI can provide us with a potentially useful method to test some of the predictions derived from the study of neuronal synchronization. We review central findings regarding the role of layer-specific neuronal synchronization for brain function, and regarding the link between neuronal synchronization and the BOLD signal. We discuss the role that laminar fMRI could play by comparing it to invasive and non-invasive electrophysiological recordings. Compared to direct electrophysiological recordings, this method provides a metric of neuronal activity that is slow and indirect, but that is uniquely non-invasive and layer-specific with potentially whole brain coverage.

BACKGROUND:The combination of EEG and ultra-high-field (7 T and above) fMRI holds the promise to relate electrophysiology and hemodynamics with greater signal to noise level and at higher spatial resolutions than conventional field strengths. Technical and safety restrictions have so far resulted in compromises in terms of MRI coil selection, resulting in reduced, signal quality, spatial coverage and resolution in EEG-fMRI studies at 7 T. NEW METHOD:We adapted a 64-channel MRI-compatible EEG cap so that it could be used with a closed 32-channel MRI head coil thus avoiding several of these compromises. We compare functional and anatomical as well as the EEG quality recorded with this adapted setup with those recorded with a setup that uses an open-ended 8-channel head-coil. RESULTS:Our set-up with the adapted EEG cap inside the closed 32 channel coil resulted in the recording of good quality EEG and (f)MRI data. Both functional and anatomical MRI images show no major effects of the adapted EEG cap on MR signal quality. We demonstrate the ability to compute ERPs and changes in alpha and gamma oscillations from the recorded EEG data. COMPARISON WITH EXISTING METHODS:Compared to MRI recordings with an 8-channel open-ended head-coil, the loss in signal quality of the MRI images related to the adapted EEG cap is considerably reduced. CONCLUSIONS:The adaptation of the EEG cap permits the simultaneous recording of good quality whole brain (f)MRI data using a 32 channel receiver coil, while maintaining the quality of the EEG data.

Significance In this study, we demonstrate that α-, β-, and γ-oscillations can be related to activity in different cortical layers in the human brain. These cortical layers are believed to instantiate feedforward and feedback information streams. Electrophysiological oscillations in α- (8–12 Hz), β- (15–30 Hz), and γ- (40–100 Hz) bands have also been associated with different roles in feedforward and feedback processes and to different cortical layers in nonhuman animals. By simultaneously recording laminar functional MRI (fMRI) and EEG, we could directly link oscillatory signals to activity in cortical layers in humans. This research provides an important neural basis for noninvasive research into the role of cortical layers in information processing using laminar fMRI alone or combined with EEG.

Given the limited processing capabilities of the sensory system, it is essential that attended information is gated to downstream areas, whereas unattended information is blocked. While it has been proposed that alpha band (8-13 Hz) activity serves to route information to downstream regions by inhibiting neuronal processing in task-irrelevant regions, this hypothesis remains untested. Here we investigate how neuronal oscillations detected by electroencephalography in visual areas during working memory encoding serve to gate information reflected in the simultaneously recorded blood-oxygenation-level-dependent (BOLD) signals recorded by functional magnetic resonance imaging in downstream ventral regions. We used a paradigm in which 16 participants were presented with faces and landscapes in the right and left hemifields; one hemifield was attended and the other unattended. We observed that decreased alpha power contralateral to the attended object predicted the BOLD signal representing the attended object in ventral object-selective regions. Furthermore, increased alpha power ipsilateral to the attended object predicted a decrease in the BOLD signal representing the unattended object. We also found that the BOLD signal in the dorsal attention network inversely correlated with visual alpha power. This is the first demonstration, to our knowledge, that oscillations in the alpha band are implicated in the gating of information from the visual cortex to the ventral stream, as reflected in the representationally specific BOLD signal. This link of sensory alpha to downstream activity provides a neurophysiological substrate for the mechanism of selective attention during stimulus processing, which not only boosts the attended information but also suppresses distraction. Although previous studies have shown a relation between the BOLD signal from the dorsal attention network and the alpha band at rest, we demonstrate such a relation during a visuospatial task, indicating that the dorsal attention network exercises top-down control of visual alpha activity.

Neural oscillations in the alpha band (8-12 Hz) are increasingly viewed as an active inhibitory mechanism that gates and controls sensory information processing as a function of cognitive relevance. Extending this view, phase synchronization of alpha oscillations across distant cortical regions could regulate integration of information. Here, we investigated whether such long-range cross-region coupling in the alpha band is intrinsically and selectively linked to activity in a distinct functionally specialized brain network. If so, this would provide new insight into the functional role of alpha band phase synchrony. We adapted the phase-locking value to assess fluctuations in synchrony that occur over time in ongoing activity. Concurrent EEG and functional magnetic resonance imaging (fMRI) were recorded during resting wakefulness in 26 human subjects. Fluctuations in global synchrony in the upper alpha band correlated positively with activity in several prefrontal and parietal regions (as measured by fMRI). fMRI intrinsic connectivity analysis confirmed that these regions correspond to the well known fronto-parietal (FP) network. Spectral correlations with this network's activity confirmed that no other frequency band showed equivalent results. This selective association supports an intrinsic relation between large-scale alpha phase synchrony and cognitive functions associated with the FP network. This network has been suggested to implement phasic aspects of top-down modulation such as initiation and change in moment-to-moment control. Mechanistically, long-range upper alpha band synchrony is well suited to support these functions. Complementing our previous findings that related alpha oscillation power to neural structures serving tonic control, the current findings link alpha phase synchrony to neural structures underpinning phasic control of alertness and task requirements.

In the past decade, the fast and transient coupling and uncoupling of functionally related brain regions into networks has received much attention in cognitive neuroscience. Empirical tools to study network coupling include functional magnetic resonance imaging (fMRI)-based functional and/or effective connectivity, and electroencephalography (EEG)/magnetoencephalography-based measures of neuronal synchronization. Here we use simultaneously recorded EEG and fMRI to assess whether fMRI-based connectivity and frequency-specific EEG power are related. Using data collected during resting state, we studied whether posterior EEG alpha power fluctuations are correlated with connectivity within the visual network and between the visual cortex and the rest of the brain. The results show that when alpha power increases, BOLD connectivity between the primary visual cortex and occipital brain regions decreases and that the negative relation of the visual cortex with the anterior/medial thalamus decreases and the ventral-medial prefrontal cortex is reduced in strength. These effects were specific for the alpha band, and not observed in other frequency bands. The decreased connectivity within the visual system may indicate an enhanced functional inhibition during a higher alpha activity. This higher inhibition level also attenuates long-range intrinsic functional antagonism between the visual cortex and the other thalamic and cortical regions. Together, these results illustrate that power fluctuations in posterior alpha oscillations result in local and long-range neural connectivity changes.