Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness.

Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12 Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.

Attentional effects on local V1 microcircuits explain selective V1-V4 communication.

Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modelled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.

Stimulus-induced visual cortical networks are recapitulated by spontaneous local and interareal synchronization.

Intrinsic covariation of brain activity has been studied across many levels of brain organization. Between visual areas, neuronal activity covaries primarily among portions with similar retinotopic selectivity. We hypothesized that spontaneous interareal coactivation is subserved by neuronal synchronization. We performed simultaneous high-density electrocorticographic recordings across the dorsal aspect of several visual areas in one hemisphere in each of two awake monkeys to investigate spatial patterns of local and interareal synchronization. We show that stimulation-induced patterns of interareal coactivation were reactivated in the absence of stimulation for the visual quadrant covered. Reactivation occurred through both interareal cofluctuation of local activity and interareal phase synchronization. Furthermore, the trial-by-trial covariance of the induced responses recapitulated the pattern of interareal coupling observed during stimulation, i.e., the signal correlation. Reactivation-related synchronization showed distinct peaks in the theta, alpha, and gamma frequency bands. During passive states, this rhythmic reactivation was augmented by specific patterns of arrhythmic correspondence. These results suggest that networks of intrinsic covariation observed at multiple levels and with several recording techniques are related to synchronization and that behavioral state may affect the structure of intrinsic dynamics.

Top-Down Beta Enhances Bottom-Up Gamma.

Several recent studies have demonstrated that the bottom-up signaling of a visual stimulus is subserved by interareal gamma-band synchronization, whereas top-down influences are mediated by alpha-beta band synchronization. These processes may implement top-down control of stimulus processing if top-down and bottom-up mediating rhythms are coupled via cross-frequency interaction. To test this possibility, we investigated Granger-causal influences among awake macaque primary visual area V1, higher visual area V4, and parietal control area 7a during attentional task performance. Top-down 7a-to-V1 beta-band influences enhanced visually driven V1-to-V4 gamma-band influences. This enhancement was spatially specific and largest when beta-band activity preceded gamma-band activity by ∼0.1 s, suggesting a causal effect of top-down processes on bottom-up processes. We propose that this cross-frequency interaction mechanistically subserves the attentional control of stimulus selection.SIGNIFICANCE STATEMENT Contemporary research indicates that the alpha-beta frequency band underlies top-down control, whereas the gamma-band mediates bottom-up stimulus processing. This arrangement inspires an attractive hypothesis, which posits that top-down beta-band influences directly modulate bottom-up gamma band influences via cross-frequency interaction. We evaluate this hypothesis determining that beta-band top-down influences from parietal area 7a to visual area V1 are correlated with bottom-up gamma frequency influences from V1 to area V4, in a spatially specific manner, and that this correlation is maximal when top-down activity precedes bottom-up activity. These results show that for top-down processes such as spatial attention, elevated top-down beta-band influences directly enhance feedforward stimulus-induced gamma-band processing, leading to enhancement of the selected stimulus.

Abnormal hippocampal theta and gamma hypersynchrony produces network and spike timing disturbances in the Fmr1-KO mouse model of Fragile X syndrome.

Neuronal networks can synchronize their activity through excitatory and inhibitory connections, which is conducive to synaptic plasticity. This synchronization is reflected in rhythmic fluctuations of the extracellular field. In the hippocampus, theta and gamma band LFP oscillations are a hallmark of the processing of spatial information and memory. Fragile X syndrome (FXS) is an intellectual disability and the most common genetic cause of autism spectrum disorder (Belmonte and Bourgeron, 2006). Here, we investigated how neuronal network synchronization in the mouse hippocampus is compromised by the Fmr1 mutation that causes FXS (Santos et al., 2014), relating recently observed single-cell level impairments (Arbab et al., 2017) to neuronal network aberrations. We implanted tetrodes in hippocampus of freely moving Fmr1-KO and littermate wildtype (WT) mice (Mientjes et al., 2006), to record spike trains from multiple, isolated neurons as well as LFPs in a spatial exploration paradigm. Compared to wild type mice, Fmr1-KO mice displayed greater power of hippocampal theta oscillations, and higher coherence in the slow gamma band. Additionally, spike trains of Fmr1-KO interneurons show decreased spike-count correlations and they are hypersynchronized with theta and slow gamma oscillations. The hypersynchronization of Fmr1-KO oscillations and spike timing reflects functional deficits in local networks. This network hypersynchronization pathologically decreases the heterogeneity of spike-LFP phase coupling, compromising information processing within the hippocampal circuit. These findings may reflect a pathophysiological mechanism explaining cognitive impairments in FXS and autism, in which there is anomalous processing of social and environmental cues and associated deficits in memory and cognition.

Stimulus repetition modulates gamma-band synchronization in primate visual cortex.

When a sensory stimulus repeats, neuronal firing rate and functional MRI blood oxygen level-dependent responses typically decline, yet perception and behavioral performance either stay constant or improve. An additional aspect of neuronal activity is neuronal synchronization, which can enhance the impact of neurons onto their postsynaptic targets independent of neuronal firing rates. We show that stimulus repetition leads to profound changes of neuronal gamma-band (∼40-90 Hz) synchronization. Electrocorticographic recordings in two awake macaque monkeys demonstrated that repeated presentations of a visual grating stimulus resulted in a steady increase of visually induced gamma-band activity in area V1, gamma-band synchronization between areas V1 and V4, and gamma-band activity in area V4. Microelectrode recordings in area V4 of two additional monkeys under the same stimulation conditions allowed a direct comparison of firing rates and gamma-band synchronization strengths for multiunit activity (MUA), as well as for isolated single units, sorted into putative pyramidal cells and putative interneurons. MUA and putative interneurons showed repetition-related decreases in firing rate, yet increases in gamma-band synchronization. Putative pyramidal cells showed no repetition-related firing rate change, but a decrease in gamma-band synchronization for weakly stimulus-driven units and constant gamma-band synchronization for strongly driven units. We propose that the repetition-related changes in gamma-band synchronization maintain the interareal stimulus signaling and sharpen the stimulus representation by gamma-synchronized pyramidal cell spikes.

Visual cortical gamma-band activity during free viewing of natural images.

Gamma-band activity in visual cortex has been implicated in several cognitive operations, like perceptual grouping and attentional selection. So far, it has been studied primarily under well-controlled visual fixation conditions and using well-controlled stimuli, like isolated bars or patches of grating. If gamma-band activity is to subserve its purported functions outside of the laboratory, it should be present during natural viewing conditions. We recorded neuronal activity with a 252-channel electrocorticographic (ECoG) grid covering large parts of the left hemisphere of 2 macaque monkeys, while they freely viewed natural images. We found that natural viewing led to pronounced gamma-band activity in the visual cortex. In area V1, gamma-band activity during natural viewing showed a clear spectral peak indicative of oscillatory activity between 50 and 80 Hz and was highly significant for each of 65 natural images. Across the ECoG grid, gamma-band activity during natural viewing was present over most of the recorded visual cortex and absent over most remaining cortex. After saccades, the gamma peak frequency slid down to 30-40 Hz at around 80 ms postsaccade, after which the sustained 50- to 80-Hz gamma-band activity resumed. We propose that gamma-band activity plays an important role during natural viewing.

A jackknife approach to quantifying single-trial correlation between covariance-based metrics undefined on a single-trial basis.

The quantification of covariance between neuronal activities (functional connectivity) requires the observation of correlated changes and therefore multiple observations. The strength of such neuronal correlations may itself undergo moment-by-moment fluctuations, which might e.g. lead to fluctuations in single-trial metrics such as reaction time (RT), or may co-fluctuate with the correlation between activity in other brain areas. Yet, quantifying the relation between moment-by-moment co-fluctuations in neuronal correlations is precluded by the fact that neuronal correlations are not defined per single observation. The proposed solution quantifies this relation by first calculating neuronal correlations for all leave-one-out subsamples (i.e. the jackknife replications of all observations) and then correlating these values. Because the correlation is calculated between jackknife replications, we address this approach as jackknife correlation (JC). First, we demonstrate the equivalence of JC to conventional correlation for simulated paired data that are defined per observation and therefore allow the calculation of conventional correlation. While the JC recovers the conventional correlation precisely, alternative approaches, like sorting-and-binning, result in detrimental effects of the analysis parameters. We then explore the case of relating two spectral correlation metrics, like coherence, that require multiple observation epochs, where the only viable alternative analysis approaches are based on some form of epoch subdivision, which results in reduced spectral resolution and poor spectral estimators. We show that JC outperforms these approaches, particularly for short epoch lengths, without sacrificing any spectral resolution. Finally, we note that the JC can be applied to relate fluctuations in any smooth metric that is not defined on single observations.

How to detect the Granger-causal flow direction in the presence of additive noise?

Granger-causality metrics have become increasingly popular tools to identify directed interactions between brain areas. However, it is known that additive noise can strongly affect Granger-causality metrics, which can lead to spurious conclusions about neuronal interactions. To solve this problem, previous studies have proposed the detection of Granger-causal directionality, i.e. the dominant Granger-causal flow, using either the slope of the coherency (Phase Slope Index; PSI), or by comparing Granger-causality values between original and time-reversed signals (reversed Granger testing). We show that for ensembles of vector autoregressive (VAR) models encompassing bidirectionally coupled sources, these alternative methods do not correctly measure Granger-causal directionality for a substantial fraction of VAR models, even in the absence of noise. We then demonstrate that uncorrelated noise has fundamentally different effects on directed connectivity metrics than linearly mixed noise, where the latter may result as a consequence of electric volume conduction. Uncorrelated noise only weakly affects the detection of Granger-causal directionality, whereas linearly mixed noise causes a large fraction of false positives for standard Granger-causality metrics and PSI, but not for reversed Granger testing. We further show that we can reliably identify cases where linearly mixed noise causes a large fraction of false positives by examining the magnitude of the instantaneous influence coefficient in a structural VAR model. By rejecting cases with strong instantaneous influence, we obtain an improved detection of Granger-causal flow between neuronal sources in the presence of additive noise. These techniques are applicable to real data, which we demonstrate using actual area V1 and area V4 LFP data, recorded from the awake monkey performing a visual attention task.

Functions of gamma-band synchronization in cognition: from single circuits to functional diversity across cortical and subcortical systems.

Gamma-band activity (30-90 Hz) and the synchronization of neural activity in the gamma-frequency range have been observed in different cortical and subcortical structures and have been associated with different cognitive functions. However, it is still unknown whether gamma-band synchronization subserves a single universal function or a diversity of functions across the full spectrum of cognitive processes. Here, we address this question reviewing the mechanisms of gamma-band oscillation generation and the functions associated with gamma-band activity across several cortical and subcortical structures. Additionally, we raise a plausible explanation of why gamma rhythms are found so ubiquitously across brain structures. Gamma band activity originates from the interplay between inhibition and excitation. We stress that gamma oscillations, associated with this interplay, originate from basic functional motifs that conferred advantages for low-level system processing and multiple cognitive functions throughout evolution. We illustrate the multifunctionality of gamma-band activity by considering its role in neural systems for perception, selective attention, memory, motivation and behavioral control. We conclude that gamma-band oscillations support multiple cognitive processes, rather than a single one, which, however, can be traced back to a limited set of circuit motifs which are found universally across species and brain structures.

A novel task to investigate vibrotactile detection in mice.

Throughout the last decades, understanding the neural mechanisms of sensory processing has been a key objective for neuroscientists. Many studies focused on uncovering the microcircuit-level architecture of somatosensation using the rodent whisker system as a model. Although these studies have significantly advanced our understanding of tactile processing, the question remains to what extent the whisker system can provide results translatable to the human somatosensory system. To address this, we developed a restrained vibrotactile detection task involving the limb system in mice. A vibrotactile stimulus was delivered to the hindlimb of head-fixed mice, who were trained to perform a Go/No-go detection task. Mice were able to learn this task with satisfactory performance and with reasonably short training times. In addition, the task we developed is versatile, as it can be combined with diverse neuroscience methods. Thus, this study introduces a novel task to study the neuron-level mechanisms of tactile processing in a system other than the more commonly studied whisker system.

P300 amplitude is insensitive to working memory load in schizophrenia.

BACKGROUND: Working memory (WM) tasks usually elicit a P300 ERP component, whose amplitude decreases with increasing WM load. So far, this effect has not been studied in schizophrenics (SZs), a group that is considered to have an aberrant brain connectivity and impairments in WM capacity. The aim of this study was to determine the dependency of the P300 component on WM load in a sample of SZ subjects. METHODS: We recorded 26 subjects (13 SZ patients and their matched controls) with an 80-channel electroencephalogram. Subjects performed an N-back task, a WM paradigm that manipulates the number of items to be stored in memory. RESULTS: In healthy subjects, P300 amplitude was highest in the low WM load condition, and lowest in both the attentional control condition and the high WM load condition. In contrast, SZs evidenced low P300 amplitude in all conditions. A significant between group difference in P300 amplitude was evidenced only at the low WM load condition (1 -back), being smaller in SZs. CONCLUSIONS: SZ subjects display a lower than normal P300 amplitude, which does not vary as a function of memory load. These results are consistent with a general impairment in WM capacity in these patients.

Increase in Beta Power Reflects Attentional Top-Down Modulation After Psychosocial Stress Induction.

Selective attention depends on goal-directed and stimulus-driven modulatory factors, each relayed by different brain rhythms. Under certain circumstances, stress-related states can change the balance between goal-directed and stimulus-driven factors. However, the neuronal mechanisms underlying these changes remain unclear. In this study, we explored how psychosocial stress can modulate brain rhythms during an attentional task and a task-free period. We recorded the EEG and ECG activity of 42 healthy participants subjected to either the Trier Social Stress Test (TSST), a controlled procedure to induce stress, or a comparable control protocol (same physical and cognitive effort but without the stress component), flanked by an attentional task, a 90 s of task-free period and a state of anxiety questionnaire. We observed that psychosocial stress induced an increase in heart rate (HR), self-reported anxiety, and alpha power synchronization. Also, psychosocial stress evoked a relative beta power increase during correct trials of the attentional task, which correlates positively with anxiety and heart rate increase, and inversely with attentional accuracy. These results suggest that psychosocial stress affects performance by redirecting attentional resources toward internal threat-related thoughts. An increment of endogenous top-down modulation reflected an increased beta-band activity that may serve as a compensatory mechanism to redirect attentional resources toward the ongoing task. The data obtained here may contribute to designing new ways of clinical management of the human stress response in the future and could help to minimize the damaging effects of persistent stressful experiences.

A microsaccadic rhythm modulates gamma-band synchronization and behavior.

Rhythms occur both in neuronal activity and in behavior. Behavioral rhythms abound at frequencies at or below 10 Hz. Neuronal rhythms cover a very wide frequency range, and the phase of neuronal low-frequency rhythms often rhythmically modulates the strength of higher-frequency rhythms, particularly of gamma-band synchronization (GBS). Here, we study stimulus-induced GBS in awake monkey areas V1 and V4 in relation to a specific form of spontaneous behavior, namely microsaccades (MSs), small fixational eye movements. We found that MSs occur rhythmically at a frequency of approximately 3.3 Hz. The rhythmic MSs were predicted by the phase of the 3.3 Hz rhythm in V1 and V4 local field potentials. In turn, the MSs modulated both visually induced GBS and the speed of visually triggered behavioral responses. Fast/slow responses were preceded by a specific temporal pattern of MSs. These MS patterns induced perturbations in GBS that in turn explained variability in behavioral response speed. We hypothesize that the 3.3 Hz rhythm structures the sampling and exploration of the environment through building and breaking neuronal ensembles synchronized in the gamma-frequency band to process sensory stimuli.

Awakening after a sleeping pill: Restoring functional brain networks after severe brain injury.

Some patients with severe brain injury show short-term neurological improvements, such as recovery of consciousness, motor function, or speech after administering zolpidem, a GABA receptor agonist. The working mechanism of this paradoxical phenomenon remains unknown. In this study, we used electroencephalography and magnetoencephalography to investigate a spectacular zolpidem-induced awakening, including the recovery of functional communication and the ability to walk in a patient with severe hypoxic-ischemic brain injury. We show that cognitive deficits, speech loss, and motor impairments after severe brain injury are associated with stronger beta band connectivity throughout the brain and suggest that neurological recovery after zolpidem occurs with the restoration of beta band connectivity. This exploratory work proposes an essential role for beta rhythms in goal-directed behavior and cognition. It advocates further fundamental and clinical research on the role of increased beta band connectivity in the development of neurological deficits after severe brain injury.

The Role of Top-Down Modulation in Shaping Sensory Processing Across Brain States: Implications for Consciousness.

Top-down, feedback projections account for a large portion of all connections between neurons in the thalamocortical system, yet their precise role remains the subject of much discussion. A large number of studies has focused on investigating how sensory information is transformed across hierarchically-distributed processing stages in a feedforward fashion, and computational models have shown that purely feedforward artificial neural networks can even outperform humans in pattern classification tasks. What is then the functional role of feedback connections? Several key roles have been identified, ranging from attentional modulation to, crucially, conscious perception. Specifically, most of the major theories on consciousness postulate that feedback connections would play an essential role in enabling sensory information to be consciously perceived. Consequently, it follows that their efficacy in modulating target regions should drastically decrease in nonconscious brain states [non-rapid eye movement (REM) sleep, anesthesia] compared to conscious ones (wakefulness), and also in instances when a given sensory stimulus is not perceived compared to when it is. Until recently, however, this prediction could only be tested with correlative experiments, due to the lack of techniques to selectively manipulate and measure the activity of feedback pathways. In this article, we will review the most recent literature on the functions of feedback connections across brain states and based on the presence or absence of perception. We will focus on experiments studying mismatch negativity, a phenomenon which has been hypothesized to rely on top-down modulation but which persists during nonconscious states. While feedback modulation is generally dampened in nonconscious states and enhanced when perception occurs, there are clear deviations from this rule. As we will discuss, this may pose a challenge to most theories of consciousness, and possibly require a change in how the level of consciousness in supposedly nonconscious states is assessed.

Mood Detection in Ambiguous Messages: The Interaction Between Text and Emoticons.

Face-to-face communication has several sources of contextual information that enables language comprehension. This information is used, for instance, to perceive mood of interlocutors, clarifying ambiguous messages. However, these contextual cues are absent in text-based communication. Emoticons have been proposed as cues used to stress the emotional intentions on this channel of communication. Most studies have suggested that their role is to contribute to a more accurate perception of emotions. Nevertheless, it is not clear if their influence on disambiguation is independent of their emotional valence and its interaction with text message valence. In the present study, we designed an emotional congruence paradigm, where participants read a set of messages composed by a positive or negative emotional situation sentence followed by a positive or negative emoticon. Participants were instructed to indicate if the sender was in a good or bad mood. With the aim of analyzing the disambiguation process and observing if the role of the emoticons in disambiguation is different according their valence, we measure the rate of responses of perceived mood and the reaction times (RTs) for each condition. Our results showed that the perceived mood in ambiguous messages tends to be more negative regardless of emotion valence. Nonetheless, we observed that this tendency was not the same for positive and negative emoticons. Specifically, negative mood perception was higher for incongruent positive emoticons. On the other hand, RTs for positive emoticons were faster than for the negative ones. Responses for incongruent messages were slower than for the congruent ones. However, the incongruent condition showed different RTs depending on the emoticons' valence. In the incongruent condition, responses for negative emoticons was the slowest. Results are discussed taking into account previous observations about the potential role of emoticons in mood perception and cognitive processing. We concluded that the role of emoticons in disambiguation and mood perception is due to the interaction of emoticon valence with the entire message.

More Gamma More Predictions: Gamma-Synchronization as a Key Mechanism for Efficient Integration of Classical Receptive Field Inputs with Surround Predictions.

During visual stimulation, neurons in visual cortex often exhibit rhythmic and synchronous firing in the gamma-frequency (30-90 Hz) band. Whether this phenomenon plays a functional role during visual processing is not fully clear and remains heavily debated. In this article, we explore the function of gamma-synchronization in the context of predictive and efficient coding theories. These theories hold that sensory neurons utilize the statistical regularities in the natural world in order to improve the efficiency of the neural code, and to optimize the inference of the stimulus causes of the sensory data. In visual cortex, this relies on the integration of classical receptive field (CRF) data with predictions from the surround. Here we outline two main hypotheses about gamma-synchronization in visual cortex. First, we hypothesize that the precision of gamma-synchronization reflects the extent to which CRF data can be accurately predicted by the surround. Second, we hypothesize that different cortical columns synchronize to the extent that they accurately predict each other's CRF visual input. We argue that these two hypotheses can account for a large number of empirical observations made on the stimulus dependencies of gamma-synchronization. Furthermore, we show that they are consistent with the known laminar dependencies of gamma-synchronization and the spatial profile of intercolumnar gamma-synchronization, as well as the dependence of gamma-synchronization on experience and development. Based on our two main hypotheses, we outline two additional hypotheses. First, we hypothesize that the precision of gamma-synchronization shows, in general, a negative dependence on RF size. In support, we review evidence showing that gamma-synchronization decreases in strength along the visual hierarchy, and tends to be more prominent in species with small V1 RFs. Second, we hypothesize that gamma-synchronized network dynamics facilitate the emergence of spiking output that is particularly information-rich and sparse.

Functional constraints in the evolution of brain circuits.

Regardless of major anatomical and neurodevelopmental differences, the vertebrate isocortex shows a remarkably well-conserved organization. In the isocortex, reciprocal connections between excitatory and inhibitory neurons are distributed across multiple layers, encompassing modular, dynamical and recurrent functional networks during information processing. These dynamical brain networks are often organized in neuronal assemblies interacting through rhythmic phase relationships. Accordingly, these oscillatory interactions are observed across multiple brain scale levels, and they are associated with several sensory, motor, and cognitive processes. Most notably, oscillatory interactions are also found in the complete spectrum of vertebrates. Yet, it is unknown why this functional organization is so well conserved in evolution. In this perspective, we propose some ideas about how functional requirements of the isocortex can account for the evolutionary stability observed in microcircuits across vertebrates. We argue that isocortex architectures represent canonical microcircuits resulting from: (i) the early selection of neuronal architectures based on the oscillatory excitatory-inhibitory balance, which lead to the implementation of compartmentalized oscillations and (ii) the subsequent emergence of inferential coding strategies (predictive coding), which are able to expand computational capacities. We also argue that these functional constraints may be the result of several advantages that oscillatory activity contributes to brain network processes, such as information transmission and code reliability. In this manner, similarities in mesoscale brain circuitry and input-output organization between different vertebrate groups may reflect evolutionary constraints imposed by these functional requirements, which may or may not be traceable to a common ancestor.

Gamma or no gamma, that is the question.

Numerous studies suggest that gamma-band synchronization is central to visual processing, yet most of them have used artificial stimuli. A new study using electrocorticography (ECoG) in humans reported finding no gamma for many natural images and for visual noise. However, we highlight that sensitive metrics can reveal clear gamma not only for natural images, but for noise stimuli and even during the absence of visual stimuli. This shows the importance of using appropriate metrics for detecting rhythmic synchronization and investigating the function of gamma during natural viewing.