Measuring functional connectivity using MEG: methodology and comparison with fcMRI

Functional connectivity (FC) between brain regions is thought to be central to the way in which the brain processes information. Abnormal connectivity is thought to be implicated in a number of diseases. The ability to study FC is therefore a key goal for neuroimaging. Functional connectivity (fc) MRI has become a popular tool to make connectivity measurements but the technique is limited by its indirect nature. A multimodal approach is therefore an attractive means to investigate the electrodynamic mechanisms underlying hemodynamic connectivity. In this paper, we investigate resting state FC using fcMRI and magnetoencephalography (MEG). In fcMRI, we exploit the advantages afforded by ultra high magnetic field. In MEG we apply envelope correlation and coherence techniques to source space projected MEG signals. We show that beamforming provides an excellent means to measure FC in source space using MEG data. However, care must be taken when interpreting these measurements since cross talk between voxels in source space can potentially lead to spurious connectivity and this must be taken into account in all studies of this type. We show good spatial agreement between FC measured independently using MEG and fcMRI; FC between sensorimotor cortices was observed using both modalities, with the best spatial agreement when MEG data are filtered into the β band. This finding helps to reduce the potential confounds associated with each modality alone: while it helps reduce the uncertainties in spatial patterns generated by MEG (brought about by the ill posed inverse problem), addition of electrodynamic metric confirms the neural basis of fcMRI measurements. Finally, we show that multiple MEG based FC metrics allow the potential to move beyond what is possible using fcMRI, and investigate the nature of electrodynamic connectivity. Our results extend those from previous studies and add weight to the argument that neural oscillations are intimately related to functional connectivity and the BOLD response.

Beyond the Status Quo: A Role for Beta Oscillations in Endogenous Content (Re)Activation

Among the rhythms of the brain, oscillations in the beta frequency range (∼13-30 Hz) have been considered the most enigmatic. Traditionally associated with sensorimotor functions, beta oscillations have recently become more broadly implicated in top-down processing, long-range communication, and preservation of the current brain state. Here, we extend and refine these views based on accumulating new findings of content-specific beta-synchronization during endogenous information processing in working memory (WM) and decision making. We characterize such content-specific beta activity as short-lived, flexible network dynamics supporting the endogenous (re)activation of cortical representations. Specifically, we suggest that beta-mediated ensemble formation within and between cortical areas may awake, rather than merely preserve, an endogenous cognitive set in the service of current task demands. This proposal accommodates key aspects of content-specific beta modulations in monkeys and humans, integrates with timely computational models, and outlines a functional role for beta that fits its transient temporal characteristics.

Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions

Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions.

Response preparation and inhibition: the role of the cortical sensorimotor beta rhythm

Paradigms requiring either a GO or a NO-GO response are often used to study the neural mechanisms of response inhibition. Here this issue is examined from the perspective of event-related beta (14-30 Hz) oscillatory activity. Two macaque monkeys performed a task that began with a self-initiated lever depression and maintenance (sustained motor output) and required a visual pattern discrimination followed by either a lever release (GO) or continued lever-holding (NO-GO) response. Analyzing simultaneous local field potentials (LFPs) from primary somatosensory, frontal motor, and posterior parietal cortices, we report two results. First, beta oscillation desynchronized shortly after stimulus presentation, the onset of which was approximately the same for both the GO and NO-GO conditions ( approximately 110 ms). Since it is well known that beta desynchronization is a reliable indicator of movement preparation, this result suggests that early motor preparation took place in both conditions. Second, following the GO/NO-GO decision ( approximately 190 ms), beta activity rebounded significantly ( approximately 300 ms) only in the NO-GO condition. Coherence and Granger causality measures revealed that the dynamical organization of the rebounded beta network was similar to that existing during the sustained motor output prior to stimulus onset. This finding suggests that response inhibition led to the restoration of the sensorimotor network to its prestimulus state.

Spontaneous Neural Oscillations Bias Perception by Modulating Baseline Excitability

The brain exhibits organized fluctuations of neural activity, even in the absence of tasks or sensory input. A prominent type of such spontaneous activity is the alpha rhythm, which influences perception and interacts with other ongoing neural activity. It is currently hypothesized that states of decreased prestimulus α oscillations indicate enhanced neural excitability, resulting in improved perceptual acuity. Nevertheless, it remains debated how changes in excitability manifest at the behavioral level in perceptual tasks. We addressed this issue by comparing two alternative models describing the effect of spontaneous α power on signal detection. The first model assumes that decreased α power increases baseline excitability, amplifying the response to both signal and noise, predicting a liberal detection criterion with no effect on sensitivity. The second model predicts that decreased α power increases the trial-by-trial precision of the sensory response, resulting in improved sensitivity. We tested these models in two EEG experiments in humans where we analyzed the effects of prestimulus α power on visual detection and discrimination using a signal detection framework. Both experiments provide strong evidence that decreased α power reflects a more liberal detection criterion, rather than improved sensitivity, consistent with the baseline model. In other words, when the task requires detecting stimulus presence versus absence, reduced α oscillations make observers more likely to report the stimulus regardless of actual stimulus presence. Contrary to previous interpretations, these results suggest that states of decreased α oscillations increase the global baseline excitability of sensory systems without affecting perceptual acuity.

SIGNIFICANCE STATEMENT

Spontaneous fluctuations of brain activity explain why a faint sensory stimulus is sometimes perceived and sometimes not. The prevailing view is that heightened neural excitability, indexed by decreased α oscillations, promotes better perceptual performance. Here, we provide evidence that heightened neural excitability instead reflects a state of biased perception, during which a person is more likely to see a stimulus, whether or not it is actually present. Therefore, we propose that changes in neural excitability leave the precision of sensory processing unaffected. These results establish the link between spontaneous brain activity and the variability in human perception.

Top-down control of the phase of alpha-band oscillations as a mechanism for temporal prediction

The physiological state of the brain before an incoming stimulus has substantial consequences for subsequent behavior and neural processing. For example, the phase of ongoing posterior alpha-band oscillations (8-14 Hz) immediately before visual stimulation has been shown to predict perceptual outcomes and downstream neural activity. Although this phenomenon suggests that these oscillations may phasically route information through functional networks, many accounts treat these periodic effects as a consequence of ongoing activity that is independent of behavioral strategy. Here, we investigated whether alpha-band phase can be guided by top-down control in a temporal cueing task. When participants were provided with cues predictive of the moment of visual target onset, discrimination accuracy improved and targets were more frequently reported as consciously seen, relative to unpredictive cues. This effect was accompanied by a significant shift in the phase of alpha-band oscillations, before target onset, toward each participant's optimal phase for stimulus discrimination. These findings provide direct evidence that forming predictions about when a stimulus will appear can bias the phase of ongoing alpha-band oscillations toward an optimal phase for visual processing, and may thus serve as a mechanism for the top-down control of visual processing guided by temporal predictions.

A study of problems encountered in Granger causality analysis from a neuroscience perspective

Granger causality methods were developed to analyze the flow of information between time series. These methods have become more widely applied in neuroscience. Frequency-domain causality measures, such as those of Geweke, as well as multivariate methods, have particular appeal in neuroscience due to the prevalence of oscillatory phenomena and highly multivariate experimental recordings. Despite its widespread application in many fields, there are ongoing concerns regarding the applicability of Granger causality methods in neuroscience. When are these methods appropriate? How reliably do they recover the system structure underlying the observed data? What do frequency-domain causality measures tell us about the functional properties of oscillatory neural systems? In this paper, we analyze fundamental properties of Granger-Geweke (GG) causality, both computational and conceptual. Specifically, we show that (i) GG causality estimates can be either severely biased or of high variance, both leading to spurious results; (ii) even if estimated correctly, GG causality estimates alone are not interpretable without examining the component behaviors of the system model; and (iii) GG causality ignores critical components of a system's dynamics. Based on this analysis, we find that the notion of causality quantified is incompatible with the objectives of many neuroscience investigations, leading to highly counterintuitive and potentially misleading results. Through the analysis of these problems, we provide important conceptual clarification of GG causality, with implications for other related causality approaches and for the role of causality analyses in neuroscience as a whole.

Causal Evidence for a Role of Theta and Alpha Oscillations in the Control of Working Memory

Working memory (WM) relies on the prioritization of relevant information and suppression of irrelevant information [1, 2]. Prioritizing relevant information has been linked to theta frequency neural oscillations in lateral prefrontal cortex and suppressing irrelevant information has been linked to alpha oscillations in occipito-parietal cortex [3,11]. Here, we used a retrospective-cue WM paradigm to manipulate prioritization and suppression task demands designed to drive theta oscillations in prefrontal cortex and alpha oscillations in parietal cortex, respectively. To causally test the role of these neural oscillations, we applied rhythmic transcranial magnetic stimulation (TMS) in either theta or alpha frequency to prefrontal and parietal regions identified using functional MRI. The effect of rhythmic TMS on WM performance was dependent on whether the TMS frequency matched or mismatched the expected underlying task-driven oscillations of the targeted region. Functional MRI in the targeted regions predicted subsequent TMS effects across subjects supporting a model by which theta oscillations are excitatory to neural activity, and alpha oscillations are inhibitory. Together, these results causally establish dissociable roles for prefrontal theta oscillations and parietal alpha oscillations in the control of internally maintained WM representations.

Hierarchical organization of gamma and theta oscillatory dynamics in schizophrenia

BACKGROUND

Schizophrenia patients have deficits across a broad range of important cognitive and clinical domains. Synchronization of oscillations in the gamma frequency range (~40 Hz) is associated with many normal cognitive functions and underlies at least some of the deficits observed in schizophrenia patients. Recent studies have demonstrated that gamma oscillations are modulated by the phase of theta waves, and this cross-frequency coupling indicates that a complex and hierarchical organization governs neural oscillatory dynamics. The aims of the present study were to determine if schizophrenia patients have abnormalities in the amplitude, synchrony, and cross-frequency coupling of gamma and theta oscillations in response to gamma-frequency steady-state stimulation and if abnormal neural oscillatory dynamics are associated with cognitive deficits in schizophrenia.

METHODS

Schizophrenia patients (n = 234) and healthy control subjects (n = 188) underwent electroencephalography testing in response to 40-Hz auditory steady-state stimulation. Cognitive functions were assessed with a battery of neuropsychological tests.

RESULTS

Schizophrenia patients had significantly reduced gamma intertrial phase coherence, increased theta amplitude, and intact cross-frequency coupling relative to healthy control subjects. In schizophrenia patients, increased theta amplitude was associated with poor verbal memory performance.

CONCLUSIONS

Results suggest that schizophrenia patients have specific alterations in both gamma and theta oscillations, but these deficits occur in the context of an intact hierarchical organization of their cross-frequency modulation in response to 40-Hz steady-state stimulation. Cortical oscillatory dynamics may be useful for understanding the neural mechanisms that underlie the disparate cognitive and functional impairments of schizophrenia.

Spatiotemporal dynamics of auditory attention synchronize with speech

Attention plays a fundamental role in selectively processing stimuli in our environment despite distraction. Spatial attention induces increasing and decreasing power of neural alpha oscillations (8-12 Hz) in brain regions ipsilateral and contralateral to the locus of attention, respectively. This study tested whether the hemispheric lateralization of alpha power codes not just the spatial location but also the temporal structure of the stimulus. Participants attended to spoken digits presented to one ear and ignored tightly synchronized distracting digits presented to the other ear. In the magnetoencephalogram, spatial attention induced lateralization of alpha power in parietal, but notably also in auditory cortical regions. This alpha power lateralization was not maintained steadily but fluctuated in synchrony with the speech rate and lagged the time course of low-frequency (1-5 Hz) sensory synchronization. Higher amplitude of alpha power modulation at the speech rate was predictive of a listener's enhanced performance of stream-specific speech comprehension. Our findings demonstrate that alpha power lateralization is modulated in tune with the sensory input and acts as a spatiotemporal filter controlling the read-out of sensory content.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

Phase-Amplitude Coupling and Long-Range Phase Synchronization Reveal Frontotemporal Interactions during Visual Working Memory

It has been suggested that cross-frequency phase-amplitude coupling (PAC), particularly in temporal brain structures, serves as a neural mechanism for coordinated working memory storage. In this magnetoencephalography study, we show that during visual working memory maintenance, temporal cortex regions, which exhibit enhanced PAC, interact with prefrontal cortex via enhanced low-frequency phase synchronization. Healthy human participants were engaged in a visual delayed match-to-sample task with pictures of natural objects. During the delay period, we observed increased spectral power of beta (20-28 Hz) and gamma (40-94 Hz) bands as well as decreased power of theta/alpha band (7-9 Hz) oscillations in visual sensory areas. Enhanced PAC between the phases of theta/alpha and the amplitudes of beta oscillations was found in the left inferior temporal cortex (IT), an area known to be involved in visual object memory. Furthermore, the IT was functionally connected to the prefrontal cortex by increased low-frequency phase synchronization within the theta/alpha band. Together, these results point to a mechanism in which the combination of PAC and long-range phase synchronization subserves enhanced large-scale brain communication. They suggest that distant brain regions might coordinate their activity in the low-frequency range to engage local stimulus-related processing in higher frequencies via the combination of long-range, within-frequency phase synchronization and local cross-frequency PAC.

SIGNIFICANCE STATEMENT

Working memory maintenance, like other cognitive functions, requires the coordinated engagement of brain areas in local and large-scale networks. However, the mechanisms by which spatially distributed brain regions share and combine information remain primarily unknown. We show that the combination of long-range, low-frequency phase synchronization and local cross-frequency phase-amplitude coupling might serve as a mechanism to coordinate memory processes across distant brain areas. In this study, low-frequency phase synchronization between prefrontal and temporal cortex co-occurred with local cross-frequency phase-amplitude coupling to higher frequencies in the latter. By such means, ongoing working memory storage taking place in higher frequencies in temporal regions might be effectively coordinated by distant frontal brain regions through synchronized activity in the low-frequency range.

Theta-Gamma Coupling and Working Memory in Alzheimer's Dementia and Mild Cognitive Impairment

Working memory deficits are common among individuals with Alzheimer's dementia (AD) or mild cognitive impairment (MCI). Yet, little is known about the mechanisms underlying these deficits. Theta-gamma coupling-the modulation of high-frequency gamma oscillations by low-frequency theta oscillations-is a neurophysiologic process underlying working memory. We assessed the relationship between theta-gamma coupling and working memory deficits in AD and MCI. We hypothesized that: (1) individuals with AD would display the most significant working memory impairments followed by MCI and finally healthy control (HC) participants; and (2) there would be a significant association between working memory performance and theta-gamma coupling across all participants. Ninety-eight participants completed the N-back working memory task during an electroencephalography (EEG) recording: 33 with AD (mean ± SD age: 76.5 ± 6.2), 34 with MCI (mean ± SD age: 74.8 ± 5.9) and 31 HCs (mean ± SD age: 73.5 ± 5.2). AD participants performed significantly worse than control and MCI participants on the 1- and 2-back conditions. Regarding theta-gamma coupling, AD participants demonstrated the lowest level of coupling followed by the MCI and finally control participants on the 2-back condition. Finally, a linear regression analysis demonstrated that theta-gamma coupling (β = 0.69, p < 0.001) was the most significant predictor of 2-back performance. Our results provide evidence for a relationship between altered theta-gamma coupling and working memory deficits in individuals with AD and MCI. They also provide insight into a potential mechanism underlying working memory impairments in these individuals.

Out-of-synch and out-of-sorts: dysfunction of motor-sensory communication in schizophrenia

BACKGROUND

Phase synchronization of neural activity preceding a motor act may reflect an efference copy of the motor plan and its expected sensory consequences (corollary discharge), which is sent to sensory cortex to herald the arrival of self-generated sensations and dampen the resulting sensory experience. We performed time-frequency decomposition of response-locked electroencephalogram (EEG) to examine phase synchronization of oscillations across trials (phase-locking factor [PLF]) to self-paced button presses. If prepress PLF reflects the activity in motor cortex, it should be contralateralized. If it reflects the action of the efference copy, it should be related to subsequent sensory suppression. If efference copy/corollary discharge mechanisms are abnormal in schizophrenia, it should be reduced in patients with schizophrenia.

METHODS

Electroencephalogram was collected while 23 patients (20 schizophrenia; 3 schizoaffective) and 25 age-matched control subjects pressed a button, at will, every 1 to 2 sec. Phase-locking factor preceding and following button presses was calculated from single-trial EEG; averaging single trials yielded response-locked event-related potentials (ERPs) to the tactile response associated with button pressing.

RESULTS

Consistent with its hypothesized reflection of efference copy/corollary discharge signals, prepress gamma band neural synchrony was 1) maximal over the contralateral sensory-motor cortex in healthy subjects, 2) correlated with the ipsilateralized somatosensory ERP amplitude evoked by the press, and 3) reduced in patients. Prepress neural synchrony in the beta band was also reduced in patients, especially those with avolition/apathy.

CONCLUSIONS

These data are consistent with dysfunction of forward model circuitry in schizophrenia and suggest that the specific motor-sensory system affected is selectively linked to symptoms involving that system.

Neural Speech Tracking in the Theta and in the Delta Frequency Band Differentially Encode Clarity and Comprehension of Speech in Noise

Humans excel at understanding speech even in adverse conditions such as background noise. Speech processing may be aided by cortical activity in the delta and theta frequency bands, which have been found to track the speech envelope. However, the rhythm of non-speech sounds is tracked by cortical activity as well. It therefore remains unclear which aspects of neural speech tracking represent the processing of acoustic features, related to the clarity of speech, and which aspects reflect higher-level linguistic processing related to speech comprehension. Here we disambiguate the roles of cortical tracking for speech clarity and comprehension through recording EEG responses to native and foreign language in different levels of background noise, for which clarity and comprehension vary independently. We then use a both a decoding and an encoding approach to relate clarity and comprehension to the neural responses. We find that cortical tracking in the theta frequency band is mainly correlated to clarity, whereas the delta band contributes most to speech comprehension. Moreover, we uncover an early neural component in the delta band that informs on comprehension and that may reflect a predictive mechanism for language processing. Our results disentangle the functional contributions of cortical speech tracking in the delta and theta bands to speech processing. They also show that both speech clarity and comprehension can be accurately decoded from relatively short segments of EEG recordings, which may have applications in future mind-controlled auditory prosthesis.

SIGNIFICANCE STATEMENT Speech is a highly complex signal whose processing requires analysis from lower-level acoustic features to higher-level linguistic information. Recent work has shown that neural activity in the delta and theta frequency bands track the rhythm of speech, but the role of this tracking for speech processing remains unclear. Here we disentangle the roles of cortical entrainment in different frequency bands and at different temporal lags for speech clarity, reflecting the acoustics of the signal, and speech comprehension, related to linguistic processing. We show that cortical speech tracking in the theta frequency band encodes mostly speech clarity, and thus acoustic aspects of the signal, whereas speech tracking in the delta band encodes the higher-level speech comprehension.

Cycle-by-cycle analysis of neural oscillations

Neural oscillations are widely studied using methods based on the Fourier transform, which models data as sums of sinusoids. This has successfully uncovered numerous links between oscillations and cognition or disease. However, neural data are nonsinusoidal, and these nonsinusoidal features are increasingly linked to a variety of behavioral and cognitive states, pathophysiology, and underlying neuronal circuit properties. We present a new analysis framework, one that is complementary to existing Fourier and Hilbert transform-based approaches, that quantifies oscillatory features in the time domain on a cycle-by-cycle basis. We have released this cycle-by-cycle analysis suite as "bycycle," a fully documented, open-source Python package with detailed tutorials and troubleshooting cases. This approach performs tests to assess whether an oscillation is present at any given moment and, if so, quantifies each oscillatory cycle by its amplitude, period, and waveform symmetry, the latter of which is missed with the use of conventional approaches. In a series of simulated event-related studies, we show how conventional Fourier and Hilbert transform approaches can conflate event-related changes in oscillation burst duration as increased oscillatory amplitude and as a change in the oscillation frequency, even though those features were unchanged in simulation. Our approach avoids these errors. Furthermore, we validate this approach in simulation and against experimental recordings of patients with Parkinson's disease, who are known to have nonsinusoidal beta (12-30 Hz) oscillations.NEW & NOTEWORTHY We introduce a fully documented, open-source Python package, bycycle, for analyzing neural oscillations on a cycle-by-cycle basis. This approach is complementary to traditional Fourier and Hilbert transform-based approaches but avoids specific pitfalls. First, bycycle confirms an oscillation is present, to avoid analyzing aperiodic, nonoscillatory data as oscillations. Next, it quantifies nonsinusoidal aspects of oscillations, increasingly linked to neural circuit physiology, behavioral states, and diseases. This approach is tested against simulated and real data.

Prefrontal dopamine in associative learning and memory

Learning to associate specific objects or actions with rewards and remembering the associations are everyday tasks crucial for our flexible adaptation to the environment. These higher-order cognitive processes depend on the prefrontal cortex (PFC) and frontostriatal circuits that connect areas in the frontal lobe with the striatum in the basal ganglia. Both structures are densely innervated by dopamine (DA) afferents that originate in the midbrain. Although the activity of DA neurons is thought to be important for learning, the exact role of DA transmission in frontostriatal circuits during learning-related tasks is still unresolved. Moreover, the neural substrates of this modulation are poorly understood. Here, we review our recent work in monkeys utilizing local pharmacology of DA agents in the PFC to investigate the cellular mechanisms of DA modulation of associative learning and memory. We show that blocking both D1 and D2 receptors in the lateral PFC impairs learning of new stimulus-response associations and cognitive flexibility, but not the memory of highly familiar associations. In addition, D2 receptors may also contribute to motivation. The learning deficits correlated with reductions of neural information about the associations in PFC neurons, alterations in global excitability and spike synchronization, and exaggerated alpha and beta neural oscillations. Our findings provide new insights into how DA transmission modulates associative learning and memory processes in frontostriatal systems.

The Rhythm of Perception: Entrainment to Acoustic Rhythms Induces Subsequent Perceptual Oscillation

Acoustic rhythms are pervasive in speech, music, and environmental sounds. Recent evidence for neural codes representing periodic information suggests that they may be a neural basis for the ability to detect rhythm. Further, rhythmic information has been found to modulate auditory-system excitability, which provides a potential mechanism for parsing the acoustic stream. Here, we explored the effects of a rhythmic stimulus on subsequent auditory perception. We found that a low-frequency (3 Hz), amplitude-modulated signal induces a subsequent oscillation of the perceptual detectability of a brief nonperiodic acoustic stimulus (1-kHz tone); the frequency but not the phase of the perceptual oscillation matches the entrained stimulus-driven rhythmic oscillation. This provides evidence that rhythmic contexts have a direct influence on subsequent auditory perception of discrete acoustic events. Rhythm coding is likely a fundamental feature of auditory-system design that predates the development of explicit human enjoyment of rhythm in music or poetry.

Alpha/beta power decreases track the fidelity of stimulus-specific information

Massed synchronised neuronal firing is detrimental to information processing. When networks of task-irrelevant neurons fire in unison, they mask the signal generated by task-critical neurons. On a macroscopic level, such synchronisation can contribute to alpha/beta (8-30 Hz) oscillations. Reducing the amplitude of these oscillations, therefore, may enhance information processing. Here, we test this hypothesis. Twenty-one participants completed an associative memory task while undergoing simultaneous EEG-fMRI recordings. Using representational similarity analysis, we quantified the amount of stimulus-specific information represented within the BOLD signal on every trial. When correlating this metric with concurrently-recorded alpha/beta power, we found a significant negative correlation which indicated that as post-stimulus alpha/beta power decreased, stimulus-specific information increased. Critically, we found this effect in three unique tasks: visual perception, auditory perception, and visual memory retrieval, indicating that this phenomenon transcends both stimulus modality and cognitive task. These results indicate that alpha/beta power decreases parametrically track the fidelity of both externally-presented and internally-generated stimulus-specific information represented within the cortex.

Landau-Ginzburg theory of cortex dynamics: Scale-free avalanches emerge at the edge of synchronization

Understanding the origin, nature, and functional significance of complex patterns of neural activity, as recorded by diverse electrophysiological and neuroimaging techniques, is a central challenge in neuroscience. Such patterns include collective oscillations emerging out of neural synchronization as well as highly heterogeneous outbursts of activity interspersed by periods of quiescence, called "neuronal avalanches." Much debate has been generated about the possible scale invariance or criticality of such avalanches and its relevance for brain function. Aimed at shedding light onto this, here we analyze the large-scale collective properties of the cortex by using a mesoscopic approach following the principle of parsimony of Landau-Ginzburg. Our model is similar to that of Wilson-Cowan for neural dynamics but crucially, includes stochasticity and space; synaptic plasticity and inhibition are considered as possible regulatory mechanisms. Detailed analyses uncover a phase diagram including down-state, synchronous, asynchronous, and up-state phases and reveal that empirical findings for neuronal avalanches are consistently reproduced by tuning our model to the edge of synchronization. This reveals that the putative criticality of cortical dynamics does not correspond to a quiescent-to-active phase transition as usually assumed in theoretical approaches but to a synchronization phase transition, at which incipient oscillations and scale-free avalanches coexist. Furthermore, our model also accounts for up and down states as they occur (e.g., during deep sleep). This approach constitutes a framework to rationalize the possible collective phases and phase transitions of cortical networks in simple terms, thus helping to shed light on basic aspects of brain functioning from a very broad perspective.

Neural Entrainment Determines the Words We Hear

Low-frequency neural entrainment to rhythmic input has been hypothesized as a canonical mechanism that shapes sensory perception in time. Neural entrainment is deemed particularly relevant for speech analysis, as it would contribute to the extraction of discrete linguistic elements from continuous acoustic signals. However, its causal influence in speech perception has been difficult to establish. Here, we provide evidence that oscillations build temporal predictions about the duration of speech tokens that affect perception. Using magnetoencephalography (MEG), we studied neural dynamics during listening to sentences that changed in speech rate. We observed neural entrainment to preceding speech rhythms persisting for several cycles after the change in rate. The sustained entrainment was associated with changes in the perceived duration of the last word's vowel, resulting in the perception of words with different meanings. These findings support oscillatory models of speech processing, suggesting that neural oscillations actively shape speech perception.

Neural effects of propofol-induced unconsciousness and its reversal using thalamic stimulation

The specific circuit mechanisms through which anesthetics induce unconsciousness have not been completely characterized. We recorded neural activity from the frontal, parietal, and temporal cortices and thalamus while maintaining unconsciousness in non-human primates (NHPs) with the anesthetic propofol. Unconsciousness was marked by slow frequency (~1 Hz) oscillations in local field potentials, entrainment of local spiking to Up states alternating with Down states of little or no spiking activity, and decreased coherence in frequencies above 4 Hz. Thalamic stimulation ‘awakened’ anesthetized NHPs and reversed the electrophysiologic features of unconsciousness. Unconsciousness is linked to cortical and thalamic slow frequency synchrony coupled with decreased spiking, and loss of higher-frequency dynamics. This may disrupt cortical communication/integration.

Directional coupling of slow and fast hippocampal gamma with neocortical alpha/beta oscillations in human episodic memory

Episodic memories hinge upon our ability to process a wide range of multisensory information and bind this information into a coherent, memorable representation. On a neural level, these 2 processes are thought to be supported by neocortical alpha/beta desynchronization and hippocampal theta/gamma synchronization, respectively. Intuitively, these 2 processes should couple to successfully create and retrieve episodic memories, yet this hypothesis has not been tested empirically. We address this by analyzing human intracranial electroencephalogram data recorded during 2 associative memory tasks. We find that neocortical alpha/beta (8 to 20 Hz) power decreases reliably precede and predict hippocampal "fast" gamma (60 to 80 Hz) power increases during episodic memory formation; during episodic memory retrieval, however, hippocampal "slow" gamma (40 to 50 Hz) power increases reliably precede and predict later neocortical alpha/beta power decreases. We speculate that this coupling reflects the flow of information from the neocortex to the hippocampus during memory formation, and hippocampal pattern completion inducing information reinstatement in the neocortex during memory retrieval.

Sleep Spindles and Memory Reprocessing

We propose a framework for the memory function of spindle oscillations during sleep. In this framework, memories are reinstated by spindle events and further reprocessed during subsequent spindle refractory periods. We posit that spindle refractoriness is crucial for protecting memory reprocessing from interference. We further argue that temporally-coordinated spindle refractory periods across local networks facilitate the consolidation of rich, multimodal representations, and that localized spindle refractoriness optimizes oscillatory interactions that support systems consolidation in the sleeping brain.

Distinguishing stimulus and response codes in theta oscillations in prefrontal areas during inhibitory control of automated responses

Response inhibition mechanisms are mediated via cortical and subcortical networks. At the cortical level, the superior frontal gyrus, including the supplementary motor area (SMA) and inferior frontal areas, is important. There is an ongoing debate about the functional roles of these structures during response inhibition as it is unclear whether these structures process different codes or contents of information during response inhibition. In the current study, we examined this question with a focus on theta frequency oscillations during response inhibition processes. We used a standard Go/Nogo task in a sample of human participants and combined different EEG signal decomposition methods with EEG beamforming approaches. The results suggest that stimulus coding during inhibitory control is attained by oscillations in the upper theta frequency band (∼7 Hz). In contrast, response selection codes during inhibitory control appear to be attained by the lower theta frequency band (∼4 Hz). Importantly, these different codes seem to be processed in distinct functional neuroanatomical structures. Although the SMA may process stimulus codes and response selection codes, the inferior frontal cortex may selectively process response selection codes during inhibitory control. Taken together, the results suggest that different entities within the functional neuroanatomical network associated with response inhibition mechanisms process different kinds of codes during inhibitory control. These codes seem to be reflected by different oscillations within the theta frequency band. Hum Brain Mapp 38:5681-5690, 2017. © 2017 Wiley-Liss, Inc.