Gamma amplitude is coupled to opposed hippocampal theta-phase states during the encoding and retrieval of episodic memories in humans.

Computational models and in vivo studies in rodents suggest that the emergence of gamma activity (40-140 Hz) during memory encoding and retrieval is coupled to opposed-phase states of the underlying hippocampal theta rhythm (4-9 Hz).1,2,3,4,5,6,7,8,9,10 However, direct evidence for whether human hippocampal gamma-modulated oscillatory activity in memory processes is coupled to opposed-phase states of the ongoing theta rhythm remains elusive. Here, we recorded local field potentials (LFPs) directly from the hippocampus of 10 patients with epilepsy, using depth electrodes. We used a memory encoding and retrieval task whereby trial unique sequences of pictures depicting real-life episodes were presented, and 24 h later, participants were asked to recall them upon the appearance of the first picture of the encoded episodic sequence. We found theta-to-gamma cross-frequency coupling that was specific to the hippocampus during both the encoding and retrieval of episodic memories. We also revealed that gamma was coupled to opposing theta phases during both encoding and recall processes. Additionally, we observed that the degree of theta-gamma phase opposition between encoding and recall was associated with participants' memory performance, so gamma power was modulated by theta phase for both remembered and forgotten trials, although only for remembered trials the dominant theta phase was different for encoding and recall trials. The current results offer direct empirical evidence in support of hippocampal theta-gamma phase opposition models in human long-term memory and provide fundamental insights into mechanistic predictions derived from computational and animal work, thereby contributing to establishing similarities and differences across species.

LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics.

A topic of growing interest in computational neuroscience is the discovery of fundamental principles underlying global dynamics and the self-organization of the brain. In particular, the notion that the brain operates near criticality has gained considerable support, and recent work has shown that the dynamics of different brain states may be modeled by pairwise maximum entropy Ising models at various distances from a phase transition, i.e., from criticality. Here we aim to characterize two brain states (psychedelics-induced and placebo) as captured by functional magnetic resonance imaging (fMRI), with features derived from the Ising spin model formalism (system temperature, critical point, susceptibility) and from algorithmic complexity. We hypothesized, along the lines of the entropic brain hypothesis, that psychedelics drive brain dynamics into a more disordered state at a higher Ising temperature and increased complexity. We analyze resting state blood-oxygen-level-dependent (BOLD) fMRI data collected in an earlier study from fifteen subjects in a control condition (placebo) and during ingestion of lysergic acid diethylamide (LSD). Working with the automated anatomical labeling (AAL) brain parcellation, we first create "archetype" Ising models representative of the entire dataset (global) and of the data in each condition. Remarkably, we find that such archetypes exhibit a strong correlation with an average structural connectome template obtained from dMRI (r = 0.6). We compare the archetypes from the two conditions and find that the Ising connectivity in the LSD condition is lower than in the placebo one, especially in homotopic links (interhemispheric connectivity), reflecting a significant decrease of homotopic functional connectivity in the LSD condition. The global archetype is then personalized for each individual and condition by adjusting the system temperature. The resulting temperatures are all near but above the critical point of the model in the paramagnetic (disordered) phase. The individualized Ising temperatures are higher in the LSD condition than in the placebo condition (p = 9 × 10-5). Next, we estimate the Lempel-Ziv-Welch (LZW) complexity of the binarized BOLD data and the synthetic data generated with the individualized model using the Metropolis algorithm for each participant and condition. The LZW complexity computed from experimental data reveals a weak statistical relationship with condition (p = 0.04 one-tailed Wilcoxon test) and none with Ising temperature (r(13) = 0.13, p = 0.65), presumably because of the limited length of the BOLD time series. Similarly, we explore complexity using the block decomposition method (BDM), a more advanced method for estimating algorithmic complexity. The BDM complexity of the experimental data displays a significant correlation with Ising temperature (r(13) = 0.56, p = 0.03) and a weak but significant correlation with condition (p = 0.04, one-tailed Wilcoxon test). This study suggests that the effects of LSD increase the complexity of brain dynamics by loosening interhemispheric connectivity-especially homotopic links. In agreement with earlier work using the Ising formalism with BOLD data, we find the brain state in the placebo condition is already above the critical point, with LSD resulting in a shift further away from criticality into a more disordered state.

Aversive memory formation in humans involves an amygdala-hippocampus phase code.

Memory for aversive events is central to survival but can become maladaptive in psychiatric disorders. Memory enhancement for emotional events is thought to depend on amygdala modulation of hippocampal activity. However, the neural dynamics of amygdala-hippocampal communication during emotional memory encoding remain unknown. Using simultaneous intracranial recordings from both structures in human patients, here we show that successful emotional memory encoding depends on the amygdala theta phase to which hippocampal gamma activity and neuronal firing couple. The phase difference between subsequently remembered vs. not-remembered emotional stimuli translates to a time period that enables lagged coherence between amygdala and downstream hippocampal gamma. These results reveal a mechanism whereby amygdala theta phase coordinates transient amygdala -hippocampal gamma coherence to facilitate aversive memory encoding. Pacing of lagged gamma coherence via amygdala theta phase may represent a general mechanism through which the amygdala relays emotional content to distant brain regions to modulate other aspects of cognition, such as attention and decision-making.

A personalizable autonomous neural mass model of epileptic seizures.

Work in the last two decades has shown that neural mass models (NMM) can realistically reproduce and explain epileptic seizure transitions as recorded by electrophysiological methods (EEG, SEEG). In previous work, advances were achieved by increasing excitation and heuristically varying network inhibitory coupling parameters in the models. Based on these early studies, we provide a laminar NMM capable of realistically reproducing the electrical activity recorded by SEEG in the epileptogenic zone during interictal to ictal states. With the exception of the external noise input into the pyramidal cell population, the model dynamics are autonomous. By setting the system at a point close to bifurcation, seizure-like transitions are generated, including pre-ictal spikes, low voltage fast activity, and ictal rhythmic activity. A novel element in the model is a physiologically motivated algorithm for chloride dynamics: the gain of GABAergic post-synaptic potentials is modulated by the pathological accumulation of chloride in pyramidal cells due to high inhibitory input and/or dysfunctional chloride transport. In addition, in order to simulate SEEG signals for comparison with real seizure recordings, the NMM is embedded first in a layered model of the neocortex and then in a realistic physical model. We compare modeling results with data from four epilepsy patient cases. By including key pathophysiological mechanisms, the proposed framework captures succinctly the electrophysiological phenomenology observed in ictal states, paving the way for robust personalization methods based on NMMs.

Correction: Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories.

[This corrects the article DOI: 10.1371/journal.pbio.3001436.].

Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories.

Persistently active neurons during mnemonic periods have been regarded as the mechanism underlying working memory maintenance. Alternatively, neuronal networks could instead store memories in fast synaptic changes, thus avoiding the biological cost of maintaining an active code through persistent neuronal firing. Such "activity-silent" codes have been proposed for specific conditions in which memories are maintained in a nonprioritized state, as for unattended but still relevant short-term memories. A hallmark of this "activity-silent" code is that these memories can be reactivated from silent, synaptic traces. Evidence for "activity-silent" working memory storage has come from human electroencephalography (EEG), in particular from the emergence of decodability (EEG reactivations) induced by visual impulses (termed pinging) during otherwise "silent" periods. Here, we reanalyze EEG data from such pinging studies. We find that the originally reported absence of memory decoding reflects weak statistical power, as decoding is possible based on more powered analyses or reanalysis using alpha power instead of raw voltage. This reveals that visual pinging EEG "reactivations" occur in the presence of an electrically active, not silent, code for unattended memories in these data. This crucial change in the evidence provided by this dataset prompts a reinterpretation of the mechanisms of EEG reactivations. We provide 2 possible explanations backed by computational models, and we discuss the relationship with TMS-induced EEG reactivations.

A ventromedial prefrontal dysrhythmia in obsessive-compulsive disorder is attenuated by nucleus accumbens deep brain stimulation.

BACKGROUND: Obsessive-compulsive disorder (OCD) has consistently been linked to abnormal frontostriatal activity. The electrophysiological disruption in this circuit, however, remains to be characterized. OBJECTIVE/HYPOTHESIS: The primary goal of this study was to investigate the neuronal synchronization in OCD patients. We predicted aberrant oscillatory activity in frontal regions compared to healthy control subjects, which would be alleviated by deep brain stimulation (DBS) of the nucleus accumbens (NAc). METHODS: We compared scalp EEG recordings from nine patients with OCD treated with NAc-DBS with recordings from healthy controls, matched for age and gender. Within the patient group, EEG activity was compared with DBS turned off vs. stimulation at typical clinical settings (3.5 V, frequency of stimulation 130 Hz, pulse width 60 µs). In addition, intracranial EEG was recorded directly from depth macroelectrodes in the NAc in four OCD patients. RESULTS: Cross-frequency coupling between the phase of alpha/low beta oscillations and amplitude of high gamma was significantly increased over midline frontal and parietal electrodes in patients when stimulation was turned off, compared to controls. Critically, in patients, beta (16-25 Hz) -gamma (110-166 Hz) phase amplitude coupling source localized to the ventromedial prefrontal cortex, and was reduced when NAc-DBS was active. In contrast, intracranial EEG recordings showed no beta-gamma phase amplitude coupling. The contribution of non-sinusoidal beta waveforms to this coupling are reported. CONCLUSION: We reveal an increased beta-gamma phase amplitude coupling in fronto-central scalp sensors in patients suffering from OCD, compared to healthy controls, which may derive from ventromedial prefrontal regions implicated in OCD and is normalized by DBS of the nucleus accumbens. This aberrant cross-frequency coupling could represent a biomarker of OCD, as well as a target for novel therapeutic approaches.

The Hidden Spatial Dimension of Alpha: 10-Hz Perceptual Echoes Propagate as Periodic Traveling Waves in the Human Brain.

EEG reverse-correlation techniques have revealed that visual information processing entails a ∼10-Hz (alpha) occipital response that reverberates sensory inputs up to 1 s. However, the spatial distribution of these perceptual echoes remains unknown: are they synchronized across the brain, or do they propagate like a traveling wave? Here, in two experiments with varying stimulus locations, we demonstrate the systematic phase propagation of perceptual echoes. A single stimulation in the upper visual field produced an "echo traveling wave" propagating from posterior to frontal sensors. The simultaneous presentation of two independent stimuli in separate visual hemifields produced two superimposed traveling waves propagating in opposite directions. Strikingly, in each sensor, the phase of the two echoes differed, with a phase advance for the contralateral stimulus. Thus, alpha traveling waves sweep across the human brain, encoding stimulus position in the phase domain, in line with the 70-year-old "cortical scanning" hypothesis (Pitts and McCulloch, 1947).

On the Physiological Modulation and Potential Mechanisms Underlying Parieto-Occipital Alpha Oscillations.

The parieto-occipital alpha (8-13 Hz) rhythm is by far the strongest spectral fingerprint in the human brain. Almost 90 years later, its physiological origin is still far from clear. In this Research Topic I review human pharmacological studies using electroencephalography (EEG) and magnetoencephalography (MEG) that investigated the physiological mechanisms behind posterior alpha. Based on results from classical and recent experimental studies, I find a wide spectrum of drugs that modulate parieto-occipital alpha power. Alpha frequency is rarely affected, but this might be due to the range of drug dosages employed. Animal and human pharmacological findings suggest that both GABA enhancers and NMDA blockers systematically decrease posterior alpha power. Surprisingly, most of the theoretical frameworks do not seem to embrace these empirical findings and the debate on the functional role of alpha oscillations has been polarized between the inhibition vs. active poles hypotheses. Here, I speculate that the functional role of alpha might depend on physiological excitation as much as on physiological inhibition. This is supported by animal and human pharmacological work showing that GABAergic, glutamatergic, cholinergic, and serotonergic receptors in the thalamus and the cortex play a key role in the regulation of alpha power and frequency. This myriad of physiological modulations fit with the view that the alpha rhythm is a complex rhythm with multiple sources supported by both thalamo-cortical and cortico-cortical loops. Finally, I briefly discuss how future research combining experimental measurements derived from theoretical predictions based of biophysically realistic computational models will be crucial to the reconciliation of these disparate findings.

Nonsinusoidal neuronal oscillations: bug or feature?

There is compiling evidence suggesting that independent neuronal ensembles are coordinated in time and space through cross-frequency coupling (CFC). However, recent studies have convincingly demonstrated that nonsinusoidal oscillations produce serious biases in state of the art CFC metrics. Although most of studies treat nonsinusoidal waves as a nuisance or just ignore them, fortunately some scientists are starting to exploit their neurophysiological relevance opening new research vistas with critical implications.

Different responses of spontaneous and stimulus-related alpha activity to ambient luminance changes.

Alpha oscillations are particularly important in determining our percepts and have been implicated in fundamental brain functions. Oscillatory activity can be spontaneous or stimulus-related. Furthermore, stimulus-related responses can be phase- or non-phase-locked to the stimulus. Non-phase-locked (induced) activity can be identified as the average amplitude changes in response to a stimulation, while phase-locked activity can be measured via reverse-correlation techniques (echo function). However, the mechanisms and the functional roles of these oscillations are far from clear. Here, we investigated the effect of ambient luminance changes, known to dramatically modulate neural oscillations, on spontaneous and stimulus-related alpha. We investigated the effect of ambient luminance on EEG alpha during spontaneous human brain activity at rest (experiment 1) and during visual stimulation (experiment 2). Results show that spontaneous alpha amplitude increased by decreasing ambient luminance, while alpha frequency remained unaffected. In the second experiment, we found that under low-luminance viewing, the stimulus-related alpha amplitude was lower, and its frequency was slightly faster. These effects were evident in the phase-locked part of the alpha response (echo function), but weaker or absent in the induced (non-phase-locked) alpha responses. Finally, we explored the possible behavioural correlates of these modulations in a monocular critical flicker frequency task (experiment 3), finding that dark adaptation in the left eye decreased the temporal threshold of the right eye. Overall, we found that ambient luminance changes impact differently on spontaneous and stimulus-related alpha expression. We suggest that stimulus-related alpha activity is crucial in determining human temporal segmentation abilities.

Diminished Alpha Lateralization During Working Memory but Not During Attentional Cueing in Older Adults.

Aging has been associated with declined performance in tasks that rely on working memory (WM). Because attention and WM are tightly coupled, declined performance on a WM task in older adults could be due to deficits in attention, memory capacity, or both. We used alpha (8-14 Hz) power modulations as an index to assess how changes in attention and memory capacity contribute to decreased WM performance in older adults. We recorded the magnetoencephalogram in healthy older (60-76 years) and younger adults (18-28 years) while they performed a lateralized WM task. At matched difficulty, older adults showed significantly lower memory spans than younger adults. Alpha lateralization during retention was nearly absent in older adults due to a bilateral reduction of alpha power. By contrast, in younger adults alpha power was reduced only contralateral to the attended hemifield. Surprisingly, during the cue interval, both groups showed equal alpha lateralization. The preserved alpha lateralization during attentional cueing, and lack thereof during retention, suggests that reduced WM performance in older adults is due to deficits in WM-related processes, not deficits in attentional orienting, and that a compensatory mechanism in aging permits significant residual WM performance in the absence of alpha lateralization.

Neuronal Oscillations with Non-sinusoidal Morphology Produce Spurious Phase-to-Amplitude Coupling and Directionality.

Neuronal oscillations support cognitive processing. Modern views suggest that neuronal oscillations do not only reflect coordinated activity in spatially distributed networks, but also that there is interaction between the oscillations at different frequencies. For example, invasive recordings in animals and humans have found that the amplitude of fast oscillations (>40 Hz) occur non-uniformly within the phase of slower oscillations, forming the so-called cross-frequency coupling (CFC). However, the CFC patterns might be influenced by features in the signal that do not relate to underlying physiological interactions. For example, CFC estimates may be sensitive to spectral correlations due to non-sinusoidal properties of the alpha band wave morphology. To investigate this issue, we performed CFC analysis using experimental and synthetic data. The former consisted in a double-blind magnetoencephalography pharmacological study in which participants received either placebo, 0.5 or 1.5 mg of lorazepam (LZP; GABAergic enhancer) in different experimental sessions. By recording oscillatory brain activity with during rest and working memory (WM), we were able to demonstrate that posterior alpha (8-12 Hz) phase was coupled to beta-low gamma band (20-45 Hz) amplitude envelope during all sessions. Importantly, bicoherence values around the harmonics of the alpha frequency were similar both in magnitude and topographic distribution to the cross-frequency coherence (CFCoh) values observed in the alpha-phase to beta-low gamma coupling. In addition, despite the large CFCoh we found no significant cross-frequency directionality (CFD). Critically, simulations demonstrated that a sizable part of our empirical CFCoh between alpha and beta-low gamma coupling and the lack of CFD could be explained by two-three harmonics aligned in zero phase-lag produced by the physiologically characteristic alpha asymmetry in the amplitude of the peaks relative to the troughs. Furthermore, we showed that periodic signals whose waveform deviate from pure sine waves produce non-zero CFCoh with predictable CFD. Our results reveal the important role of the non-sinusoidal wave morphology on state of the art CFC metrics and we recommend caution with strong physiological interpretations of CFC and suggest basic data quality checks to enhance the mechanistic understanding of CFC.

GABAergic modulation of visual gamma and alpha oscillations and its consequences for working memory performance.

BACKGROUND: Impressive in vitro research in rodents and computational modeling has uncovered the core mechanisms responsible for generating neuronal oscillations. In particular, GABAergic interneurons play a crucial role for synchronizing neural populations. Do these mechanistic principles apply to human oscillations associated with function? To address this, we recorded ongoing brain activity using magnetoencephalography (MEG) in healthy human subjects participating in a double-blind pharmacological study receiving placebo, 0.5 mg and 1.5 mg of lorazepam (LZP; a benzodiazepine upregulating GABAergic conductance). Participants performed a demanding visuospatial working memory (WM) task. RESULTS: We found that occipital gamma power associated with WM recognition increased with LZP dosage. Importantly, the frequency of the gamma activity decreased with dosage, as predicted by models derived from the rat hippocampus. A regionally specific gamma increase correlated with the drug-related performance decrease. Despite the system-wide pharmacological intervention, gamma power drug modulations were specific to visual cortex: sensorimotor gamma power and frequency during button presses remained unaffected. In contrast, occipital alpha power modulations during the delay interval decreased parametrically with drug dosage, predicting performance impairment. Consistent with alpha oscillations reflecting functional inhibition, LZP affected alpha power strongly in early visual regions not required for the task demonstrating a regional specific occipital impairment. CONCLUSIONS: GABAergic interneurons are strongly implicated in the generation of gamma and alpha oscillations in human occipital cortex where drug-induced power modulations predicted WM performance. Our findings bring us an important step closer to linking neuronal dynamics to behavior by embracing established animal models.

Common N1 and mismatch negativity neural evoked components are revealed by independent component model-based clustering analysis.

Mismatch negativity (MMN) is an event-related brain potential that appears when an auditory regularity is violated. Two main hypotheses have been proposed to explain it: the adaptation hypothesis and the memory-based hypothesis. Critically, they differ in whether the MMN can be distinguished from the N1. In this study, we assessed the differential contribution of the N1 and the MMN using independent component analysis (ICA) combined with model-based clustering. Our results show that the neural responses associated with the standard and deviant tones are explained by three clusters of reliable ICs with frontocentral scalp distribution. Two of these clusters exhibited a common N1 for both the standard and deviant tones and one cluster showed an enhancement of the anterior N1 at the MMN time range. These results support the adaptation hypothesis, which proposes that MMN is generated by neural mechanisms similar to those associated with auditory N1.