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Orchestration of brain oscillations: principles and functions

2018; Wiley; Volume: 48; Issue: 7 Linguagem: Inglês

10.1111/ejn.14189

1460-9568

Ali Mazaheri, Heleen A. Slagter, Gregor Thut, John J. Foxe,

Neuroscience and Neuropharmacology Research

The year 2018 marks the 100th anniversary of the passing of the French composer Claude Debussy. Debussy's view of composing music could be compared to how some scientists view neural oscillations. He is reported to have said that music is not in the notes, but rather in the silences in between. Without regular periods of lull, it is not possible to have a rhythm, without which it is impossible to have melody. This special issue of The European Journal of Neuroscience endeavors to bring together the latest empirical findings, reviews and theoretical viewpoints on the role that rhythmic neural activity plays in the many facets of sensation, perception and cognition. Today, few would argue against a crucial role for neural oscillations as an organizing mechanism of information transfer and coordinated neural processing, but there is much yet to be learned and discussed. In the very comprehensive literature review contributed herein by Ohki & Takei (2018), the authors propose that neural oscillations play a central role in the extraction and maintenance of high level information. Along the same lines, in a provocative opinion article contributed by Singer (2017), he argues that the temporal patterning of neuronal activity enables the parsing of time that is necessary as a first step to form interactions between distributed assemblies of neurons during cognition. The literature review contributed by Meyer (2017) presents evidence supporting this view and specifically applies this framework to linguistic processing. The empirical study contributed by Teng et al. (2017) further provides compelling evidence that theta oscillations play a role in the segmentation of auditory stimuli, a critical prerequisite for understanding speech. Heideman et al. (2017) demonstrate that lateralization of beta oscillations over sensorimotor areas, in anticipation of the response associated with an upcoming target location, aligns to the expected timing of these forthcoming events, also suggesting that oscillations may create optimal time windows for neural responding. These works taken together provide a compelling argument that one role of neural oscillations is to provide the momentary periods of lull needed for the processing, encoding, and appraisal of our environment to take place. Given that neural oscillations across multiple frequency bands clearly play a key role in healthy cognition, it follows that dysfunction of these processes may be a causal component of abnormal sensory-perceptual and cognitive processes seen in many neurological and neuropsychiatric conditions. The review article contributed by Sherif and colleagues provides a comprehensive framework within cannabinoid and glutamatergic systems to account for deficits in maintaining synchronized theta and gamma oscillations commonly reported in schizophrenia patients in the awake state (Sherif et al., 2017). Similarly, Castelnovo et al. (2017) provide a detailed review of research investigating the oscillatory markers underlying aberrant sleep patterns in schizophrenia patients, Levesque et al. (2017) review the link between aberrant inter-octal high-frequency oscillations and epilepsy. A review contributed by Singh focuses on the various observations of aberrant oscillatory activity within the cortico-basal ganglia-thalamic (CBT) observed in patients with Parkinson Disease (Singh, 2018), and an empirical study by Pittman-Polletta et al. (2018) describes the potential mechanism underlying these anomalies. Another neurodevelopmental condition oft-linked with aberrant oscillatory functioning is autism (Murphy et al., 2014), especially so in the gamma band (David et al., 2016). In a sizeable cohort of young adults from the general population, De Groot & Van Strien (2018) ask whether autism-related traits in these ostensibly neurotypical individuals, might also be related to power across the gamma band. However, no such relationship was supported. We would note here that the reporting of negative results such as these is crucial to the integrity of the whole scientific enterprise and is to be strongly encouraged by all editors working in the field. What is clear from these clinical studies is that aberrations in oscillatory activity are prevalent across many neurological and neuropsychiatric conditions and could potentially one day serve as endophenotypes (i.e. neuromarkers) against which to assess both risk for disease and potentially the efficacy of interventions and therapeutics. Debussy's famed suite Pour le piano, roughly described, consists of a mixture of slow-moving sounds superimposed beneath a melody in the middle range, as well as counter melodies in the upper range of the piano. With a little imagination one can see the resemblance of this piece to the time-frequency decomposition of electrophysiological data. Electrophysiological data recorded at the scalp and intracranially contain cross-frequency interactions between different frequency bands, often across distributed regions of the cortex. The review article contributed by Palva & Palva (2017) provides an in-depth account of the various types of cross-frequency interactions that have been substantiated to date. The authors propose that one type of cross-frequency interaction, cross-frequency phase alignment between high and low frequencies, can be considered as a candidate mechanism by which the brain coordinates and integrates neuronal processing that is distributed across different regions of the cortex. In this vein, Cavelli et al. (2017) found that the interaction of the power of high-frequency oscillations (> 101–160 Hz) with theta phase differed depending on whether rodents were in active wakefulness or rapid eye-movement (REM) sleep, the functional significance of which remains to be fully elucidated. Lockmann et al. (2017) observed that beta activity in the olfactory cortex appeared to drive beta activity in the hippocampus suggesting that beta oscillations mediate the communication between olfactory and hippocampal circuits in the rodent brain. Michaels et al. (2018) document the changes to cross-frequency coupling (CFC) and behavior in a rodent schizophrenia model (chronic ketamine administration) to start looking into the potential relevance of CFC in the pathophysiology of the psychoses. In a provocative piece, Klimesch (2018) explores the frequency architecture of brain oscillations, specifically detailing cross-frequency coupling principles, and extending this notion to mind-body interactions where he asks if oscillatory-like motor activity is simply another version of communication across systems that is governed by coupled oscillators. This theme is echoed in the work of Yang et al. (2017) who discuss cross-frequency coupling during sensorimotor operations, emphasizing that an assumption of linear coupling between systems is not sufficient, and the need for advanced signal-processing approaches that allow for nonlinearity and provide ways to assess the directionality of such nonlinear coupling (be it ascending or descending). The experimentally-driven increase in the amplitude of activity within a given frequency band is often referred to as an event-related synchronization. This amplitude increase is thought to reflect the spatial summation of synchronous post-synaptic potentials of many neurons. Conversely, desynchronization of neuronal population firing interrupts rhythmical post-synaptic activity, and as such, causes a drop in the amplitude of the oscillatory activity or an event-related desynchronization. The precise relationship between synchronization and desynchronization of neural activity and cognitive processes is currently unclear. Neuronal activity exhibits large fluctuations on time scales ranging from hundreds of milliseconds to seconds to days. What is the functional significance of these different rhythmic temporal orders? The study contributed by Benwell et al. (2017) systematically investigates the influence of the fluctuations of alpha activity over short to intermediate time ranges (seconds to minutes) on visual perception. The authors observe that the nominal trial-by-trial neural fluctuations prior to the arrival of stimuli influencing perception have not only a stochastic but also an important deterministic component driven by slow changes over the duration of an experiment. Benedetto et al. (2017) found that background luminance conditions strongly impacted alpha activity at rest as well its visual induced modulation. At the other end of the temporal spectrum, the work contributed by Myung & Pauls (2017) provides evidence that daily fluctuations of activity in the suprachiasmatic nucleus (SCN) serve to encode seasonal information, Belle & Diekman (2018) pick up on this theme of ultra-slow fluctuations in the SCN, reviewing the molecular clock mechanisms underlying circadian rhythm generation. Oscillations may also reverberate/recapitulate daytime experiences during sleep, next to playing an important role in sleep homeostasis, as shown by the study of Dentico et al. (2018) on the effects of meditation training on oscillatory activity during sleep and wakefulness. One general consensus that has emerged in the field of human scalp and intracranial electrophysiology is that modulations in the amplitude of alpha activity (~ 10 Hz) according to cognitive demands reflects a mechanism by which the brain gates information flow across different cortices (Foxe et al., 1998; Worden et al., 2000; Rihs et al., 2007; Jensen & Mazaheri, 2010; Foxe & Snyder, 2011; Gomez-Ramirez et al., 2011). Supporting this view, research from Shatzer et al. (2018) suggests that alpha desynchronization reflects continuous engagement of the visual system during auditory-visual multisensory integration. However, in the current special issue and elsewhere, multiple empirical studies suggest a more nuanced view on the role of alpha modulation in cognitive processes such as in memory encoding (Portoles et al., 2017), memory retention (Portoles et al., 2017; Schroeder et al., 2018), speech segmentation (Shahin & Pitt, 2012), task-set switching (Foxe et al., 2014; Portoles et al., 2017), and selective auditory attention (Tune et al., 2018). Another such example comes from the lesion study reported herein by Piai et al. (2017), which provides evidence for a causal link between posterior alpha-beta power decreases in the left lateral-temporal and inferior parietal lobes and word retrieval. It should be noted, however, that the precise role (or roles) of alpha desynchronization in diverse cognitive processes such attention, memory and language is still a matter of hot debate. The review article by van Ede (2017) provides a critical discussion of the contemporary empirical literature and viewpoints, and the opinion piece contributed by Clayton et al. (2017) endeavors to provide a unified broad account on the role of occipital alpha activity in cognition by assigning five distinct (sometimes overlapping) roles to it: inhibitor, perceiver, predictor, communicator and stabilizer of information. A number of studies in the current issue have also observed theta activity to play various roles in cognitive processing. Moreau et al. (2017) make the intriguing observation that images of humans induce a greater synchronization of theta activity in occipito-temporal areas. The study by Kaiser et al. (2018) suggests a multi-faceted role for low-frequency power in auditory perception: a desynchronization of theta over central electrodes could be involved in processes related to restoration of an interrupted sound, whereas its increase could be reflective of detecting auditory boundaries. On the other hand, the study by Moris Fernandez et al. (2017) observed a synchronization of theta activity modulated by the conflict (i.e. incongruency) of auditory-visual speech inputs during the famous McGurk illusion (McGurk & MacDonald, 1976). This potential relationship of theta-band activity to speech processing is also picked up in the study of Molinaro & Lizarazu (2017). In a clever and well-controlled study, they ask whether entrainment in the theta and delta bands has specificity for speech or simply reflects a passive synchronization of auditory cortex to the basic frequency content of the signal. That is, can the same entrainment patterns be produced by non-speech control stimuli? Compellingly, this is indeed what they show for the theta band, but they do find increased coherence in the delta band that is specific to speech, suggesting an active higher-order speech processing role for oscillatory activity in this lower frequency band (< 4 Hz). One issue when looking at the spectral dynamics of electrophysiological data relates to scaling. There is tremendous variability between the amplitude of oscillations among individuals. This variability could be considered informative but can also be viewed as a nuisance variable. The contribution of Smulders et al. (2018) makes a strong argument for log-transforming the amplitude of alpha activity in 1 second time windows in order to appropriately scale its amplitude fluctuations during rest. The relevance of resting state brain activity to how the brain implements cognition is demonstrated in the study of Irrmischer et al. (2017), where they show a robust relationship between long-range temporal complexity of ongoing oscillatory activity at rest and performance during an attention task. While a number of studies in the literature have reported that endogenous alpha oscillations appear to entrain to rhythmic stimulation, a very rigorously controlled investigation by Keitel et al. (2018) suggests boundary limits for when the entrainment of alpha generators can occur. The contribution by Cohen (2017) addresses a very basic issue, yet one that is fundamentally important: how does a researcher go about identifying meaningful oscillations in electrophysiological signals produced by multiple sources? Rhythms are the most prominent feature of brain activity observed at the scalp, some visible with the naked eye, while others require painstaking levels of preprocessing and data preparation. Cohen proposes a series of steps relying on source-separation techniques, which aid in identifying weak oscillatory activity embedded in noisy data. Other contributions in terms of analysis approaches in this special issue cover frequency analysis of resting data (Smulders et al., 2018) and identifying co-modulations of pre-stimulus brain oscillations and psychometrics from curve fitting (Benwell et al., 2017). The presence of oscillatory rhythms in human brain activity was first reported by Berger (1929) within just a few years of Claude Debussy's passing in 1918. A century later, researchers are still working to elucidate the origins of these rhythms and the best ways to characterize them. One outstanding issue is that the physiological underpinnings of oscillatory activity need to be better understood at multiple levels, from molecular to cellular scales, from neuronal ensembles to brain circuits, and in turn to the relatively gross signals that can currently be detected at the human scalp. Butler et al. (2018) make an important contribution in this direction by showing, using optogenetic stimulation and pharmacology, that gamma oscillations generated in three regions within the entorhinal-hippocampal system rely on a fast excitatory-inhibitory feedback loop that involves GABAA and AMPA/kainate receptors. Dheerendra et al. (2017) show clear evidence for gamma oscillations in the hippocampus of domestic chicks, and using standard pharmacological manipulations, conclude that these avian hippocampal oscillations are produced by the same micro-circuitry found in mammalian species. Tsanov (2017) provides a detailed review and synthesis of the circuitry responsible for theta band generation in the sub-fields of the septum and hippocampus. Cheron & Cheron (2018) use electrical stimulation to induce coordinated high-frequency oscillatory activity between the inferior olive and deep cerebellar nuclei in mice (at a frequency of ~ 350 Hz), revealing another potentially important oscillatory circuit, although the functional significance of this high-frequency coupling mechanism remains to be elucidated. A vexing question is specifically how oscillations in the various frequency bands recorded in the local field potential relate to actual spiking activity and how this relationship may be governed by fluctuations in brain state. For the human researcher constrained to record only far-field activity non-invasively, an understanding of how oscillations might relate to excitation/inhibition states and multi-unit activity is of paramount importance to advancing the field. Important work from Watson et al. (2017) provides a detailed account of these relationships in the rat brain and points to a number of key methodological considerations as we work to refine our understanding of these couplings. Oscillatory activity shows organization and variability on multiple time scales. The dynamics and nuances of oscillatory activity might not be fully captured by looking at the average power within a bandwidth. The frequency of the ongoing oscillations could fluctuate from moment to moment and from individual to individual, with this variability being functionally meaningful (Haegens et al., 2014; Furman et al., 2018). It is worth mentioning that nearly all the spectral analysis methods utilized in this special issue (except for the piece contributed by Cohen (2017) are based on the assumption that oscillatory brain activity can be characterized in a sinusoidal way. However, there is evidence to support the view that neural oscillations are for the most part non-sinusoidal, and constraining them as such may be constraining the richness of information that can be obtained from them (Cole & Voytek, 2017; Cole et al., 2017). Thus, the shape of an oscillation could be as relevant a parameter as its phase, frequency, and power. It will be interesting to see what the next decade of research will bring forward in the rich and dynamic field of neural oscillations orchestrating brain function. In the meantime, we encourage our readers to delve into this rich and varied issue and to enjoy the exceptional work that has been compiled in this special issue of EJN.