Theta activity paradoxically boosts gamma and ripple frequency sensitivity in prefrontal interneurons

Fast oscillations in cortical circuits critically depend on GABAergic interneurons. Which interneuron types and populations can drive different cortical rhythms, however, remains unresolved and may depend on brain state. Here, we measured the sensitivity of different GABAergic interneurons in prefrontal cortex under conditions mimicking distinct brain states. While fast-spiking neurons always exhibited a wide bandwidth of around 400 Hz, the response properties of spike-frequency adapting interneurons switched with the background input’s statistics. Slowly fluctuating background activity, as typical for sleep or quiet wakefulness, dramatically boosted the neurons’ sensitivity to gamma and ripple frequencies. We developed a time-resolved dynamic gain analysis and revealed rapid sensitivity modulations that enable neurons to periodically boost gamma oscillations and ripples during specific phases of ongoing low-frequency oscillations. This mechanism predicts these prefrontal interneurons to be exquisitely sensitive to high-frequency ripples, especially during brain states characterized by slow rhythms, and to contribute substantially to theta-gamma cross-frequency coupling.

From Fast Oscillations to Circadian Rhythms: Coupling at Multiscale Frequency Bands in the Rodent Subcortical Visual System

The subcortical visual system (SVS) is a unique collection of brain structures localised in the thalamus, hypothalamus and midbrain. The SVS receives ambient light inputs from retinal ganglion cells and integrates this signal with internal homeostatic demands to influence physiology. During this processing, a multitude of oscillatory frequency bands coalesces, with some originating from the retinas, while others are intrinsically generated in the SVS. Collectively, these rhythms are further modulated by the day and night cycle. The multiplexing of these diverse frequency bands (from circadian to infra-slow and gamma oscillations) makes the SVS an interesting system to study coupling at multiscale frequencies. We review the functional organisation of the SVS, and the various frequencies generated and processed by its neurons. We propose a perspective on how these different frequency bands couple with one another to synchronise the activity of the SVS to control physiology and behaviour.

Stochastic rectification of fast oscillations on slow manifold closures

The problems of identifying the slow component (e.g., for weather forecast initialization) and of characterizing slow–fast interactions are central to geophysical fluid dynamics. In this study, the related rectification problem of slow manifold closures is addressed when breakdown of slow-to-fast scales deterministic parameterizations occurs due to explosive emergence of fast oscillations on the slow, geostrophic motion. For such regimes, it is shown on the Lorenz 80 model that if 1) the underlying manifold provides a good approximation of the optimal nonlinear parameterization that averages out the fast variables and 2) the residual dynamics off this manifold is mainly orthogonal to it, then no memory terms are required in the Mori–Zwanzig full closure. Instead, the noise term is key to resolve, and is shown to be, in this case, well modeled by a state-independent noise, obtained by means of networks of stochastic nonlinear oscillators. This stochastic parameterization allows, in turn, for rectifying the momentum-balanced slow manifold, and for accurate recovery of the multiscale dynamics. The approach is promising to be further applied to the closure of other more complex slow–fast systems, in strongly coupled regimes.

Ripples reflect a spectrum of synchronous spiking activity in human anterior temporal lobe

Direct brain recordings have provided important insights into how high frequency activity captured through intracranial EEG (iEEG) supports human memory retrieval. The extent to which such activity is comprised of transient fluctuations that reflect the dynamic coordination of underlying neurons, however, remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that fast oscillations within the previously identified 80-120 Hz ripple band contribute to 70-200 Hz high frequency activity in the human cortex. These ripple oscillations exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human temporal lobe is organized into transient bouts of ripple oscillations that reflect underlying bursts of spiking activity.

On the brain networks organization of individuals with high versus average fluid intelligence: a combined DTI and MEG study

The neural underpinning of human fluid intelligence (Gf) has gathered a large interest in the scientific community. Nonetheless, previous research did not provide a full understanding of such intriguing topic. Here, we studied the structural (from diffusion tensor imaging, DTI) and functional (from magnetoencephalography (MEG) resting state) connectivity in individuals with high versus average Gf scores. Our findings showed greater values in the brain areas degree distribution and higher proportion of long-range anatomical connections for high versus average Gfs. Further, the two groups presented different community structures, highlighting the structural and functional integration of the cingulate within frontal subnetworks of the brain in high Gfs. These results were consistently observed for structural connectivity and functional connectivity of delta, theta and alpha. Notably, gamma presented an opposite pattern, showing more segregation and lower degree distribution and connectivity in high versus average Gfs. Our study confirmed and expanded previous perspectives and knowledge on the small-worldness of the brain. Further, it complemented the widely investigated structural brain network of highly intelligent individuals with analyses on fast-scale functional networks in five frequency bands, highlighting key differences in the integration and segregation of information flow between slow and fast oscillations in groups with different Gf.

Pendulum Quasi-Static Drift Effect at Suspension Point Excitation by High-Frequency Polyharmonic Multiple Frequency Vibration

The paper dwells upon the dynamic behavior of a 2d pendulum under polyharmonic vibration. The study shows that the angles between the vertical coordinate axis and the directions of the individual harmonic components effects are generally different. Relying on the well-known approach, we solved the problem in two approximations. The movement of the pendulum contains two components: the "low-frequency" component and the "high-frequency" one. As the frequencies are not multiple, the movement is essentially an aperiodic process. Hence, when deriving the basic relations, it is impossible to use an effective method of averaging the solution within a period of fast oscillations. Dividing the solution by the frequencies of oscillations, we obtained an equation describing the slow motion and an approximate formula based on it for determining the pendulum quasi-static displacement, i.e., the "drift effect". The result is generalized by taking energy dissipation into account. Findings of research show that near the quasi-static position of the pendulum, loss of stability is possible as a result of parametric resonance at the combination frequencies of the external action. The paper gives an example in which an approximate solution is compared with an exact numerical simulation and shows the results of this comparison

EEGs Disclose Significant Brain Activity Correlated with Synaptic Fickleness

We here study a network of synaptic relations mingling excitatory and inhibitory neuron nodes that displays oscillations quite similar to electroencephalogram (EEG) brain waves, and identify abrupt variations brought about by swift synaptic mediations. We thus conclude that corresponding changes in EEG series surely come from the slowdown of the activity in neuron populations due to synaptic restrictions. The latter happens to generate an imbalance between excitation and inhibition causing a quick explosive increase of excitatory activity, which turns out to be a (first-order) transition among dynamic mental phases. Moreover, near this phase transition, our model system exhibits waves with a strong component in the so-called delta-theta domain that coexist with fast oscillations. These findings provide a simple explanation for the observed delta-gamma and theta-gamma modulation in actual brains, and open a serious and versatile path to understand deeply large amounts of apparently erratic, easily accessible brain data.

Coupled oscillations enable rapid temporal recalibration to audiovisual asynchrony

The brain naturally resolves the challenge of integrating auditory and visual signals produced by the same event despite different physical propagation speeds and neural processing latencies. Temporal recalibration manifests in human perception to realign incoming signals across the senses. Recent behavioral studies show it is a fast-acting phenomenon, relying on the most recent exposure to audiovisual asynchrony. Here we show that the physiological mechanism of rapid, context-dependent recalibration builds on interdependent pre-stimulus cortical rhythms in sensory brain regions. Using magnetoencephalography, we demonstrate that individual recalibration behavior is related to subject-specific properties of fast oscillations (>35 Hz) nested within a slower alpha rhythm (8–12 Hz) in auditory cortex. We also show that the asynchrony of a previously presented audiovisual stimulus pair alters the preferred coupling phase of these fast oscillations along the alpha cycle, with a resulting phase-shift amounting to the temporal recalibration observed behaviorally. These findings suggest that cross-frequency coupled oscillations contribute to forming unified percepts across senses.

Basal forebrain parvalbumin neurons modulate vigilant attention.

Attention is impaired in many neuropsychiatric disorders and by sleep disruption, leading to decreased workplace productivity and increased risk of accidents. Thus, understanding the underlying neural substrates is important for developing treatments. The basal forebrain (BF) is a brain region which degenerates in dementia and is implicated in the negative effects of sleep disruption on vigilance and cognition. Previous studies demonstrated that the BF controls cortical fast oscillations that underlie attention and revealed the important role of cholinergic neurons. However, the role of other neurochemically defined BF subtypes is unknown. Recent work has shown that one population of BF GABAergic neurons containing the calcium-binding protein parvalbumin (PV) control cortical fast oscillations and arousals from sleep but their role in awake behavior is unclear. Thus, here we test the hypothesis that BF-PV neurons modulate vigilant attention in mice. A lever release version of the rodent psychomotor vigilance test (rPVT) was used to assess vigilant attention as measured by reaction time. Brief and continuous low power optogenetic excitation of BF-PV neurons (1s,473nm@5mW) that preceded the cue light signal by 0.5s improved vigilant attention as indicated by quicker reaction times. In contrast, both sleep deprivation (8h) and optogenetic inhibition of BF-PV neurons (1s,530nm@10mW) slowed reaction times. Importantly, BF-PV excitation rescued the reaction time deficits in sleep deprived mice. These findings reveal for the first time a role for BF-PV neurons in attention.