Diminished modulation of preparatory sensorimotor mu rhythm predicts attention-deficit hyperactivity disorder severity

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is characterized by problems in regulating attention and in suppressing disruptive motor activity, i.e. hyperactivity and impulsivity. We recently found evidence that aberrant distribution of posterior α band oscillations (8–12 Hz) is associated with attentional problems in ADHD. The sensorimotor cortex also produces strong 8–12 Hz band oscillations, namely the μ rhythm, and is thought to have a similar inhibitory function. Here, we now investigate whether problems in distributing α band oscillations in ADHD generalize to the μ rhythm in the sensorimotor domain.MethodIn a group of adult ADHD (n = 17) and healthy control subjects (n = 18; aged 21–40 years) oscillatory brain activity was recorded using magnetoencephalography during a visuo-spatial attention task. Subjects had to anticipate a target with unpredictable timing and respond by pressing a button.ResultsPreparing a motor response, the ADHD group failed to increase hemispheric μ lateralization with relatively higher μ power in sensorimotor regions not engaged in the task, as the controls did (F1,33 = 8.70, p = 0.006). Moreover, the ADHD group pre-response μ lateralization not only correlated positively with accuracy (rs = 0.64, p = 0.0052) and negatively with intra-individual reaction time variability (rs = −0.52, p = 0.033), but it also correlated negatively with the score on an ADHD rating scale (rs = −0.53, p = 0.028).ConclusionsWe suggest that ADHD is associated with an inability to sufficiently inhibit task-irrelevant sensorimotor areas by means of modulating μ oscillatory activity. This could explain disruptive motor activity in ADHD. These results provide further evidence that impaired modulation of α band oscillations is involved in the pathogenesis of ADHD.</jats:sec

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 ms). In addition, intracranial EEG was recorded directly from depth macro electrodes 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. (C) 2021 The Authors. Published by Elsevier Inc.This work was supported by Project grants SAF2015-65982-R from the Spanish Ministry of Economy and Competitiveness to BS and PSI2014-58654-JIN to JGR, an FPI Predoctoral Fellowship (BES-2016-079470) to ST, and BIAL Foundation Grant 119/12 to BS. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (ERC-2018-COG 819814)

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

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

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

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

International audienceEEG 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)

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 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 mg 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