Brain Rhythms Research Articles

Reduction of somatosensory functional connectivity by transcranial alternating current stimulation at endogenous mu-frequency

Alpha, the most prominent human brain rhythm, might reflect a mechanism of functional inhibition for gating neural processing. This concept has been derived predominantly from local measures of inhibition, while large-scale network mechanisms to guide information flow are largely unknown. Here, we investigated functional connectivity changes on a whole-brain level by concurrent transcranial alternating current stimulation (tACS) and resting-state functional MRI in humans. We specifically focused on somatosensory alpha-band oscillations by adjusting the tACS frequency to each individual´s somatosensory (mu-) alpha peak frequency (mu-tACS). Potential differences of Eigenvector Centrality of primary somatosensory cortex (S1) as well as on a whole brain level between mu-tACS and sham were analyzed. Our results demonstrate that mu-tACS induces a locally-specific decrease in whole-brain functional connectivity of left S1. An additional exploratory analysis revealed that this effect primarily depends on a decrease in functional connectivity between S1 and a network of regions that are crucially involved in somatosensory processing. Furthermore, the decrease in functional centrality was specific to mu-tACS and was not observed when tACS was applied in the gamma-range in an independent study. Our findings provide evidence that modulated somatosensory (mu-) alpha-activity may affect whole-brain network level activity by decoupling primary sensory areas from other hubs involved in sensory processing.

The Role of Motor and Environmental Visual Rhythms in Structuring Auditory Cortical Excitability.

SummaryPrevious studies indicate that motor sampling patterns modulate neuronal excitability in sensory brain regions by entraining brain rhythms, a process termed motor-initiated entrainment. In addition, rhythms of the external environment are also capable of entraining brain rhythms. Our first goal was to investigate the properties of motor-initiated entrainment in the auditory system using a prominent visual motor sampling pattern in primates, saccades. Second, we wanted to determine whether/how motor-initiated entrainment interacts with visual environmental entrainment. We examined laminar profiles of neuronal ensemble activity in primary auditory cortex and found that whereas motor-initiated entrainment has a suppressive effect, visual environmental entrainment has an enhancive effect. We also found that these processes are temporally coupled, and their temporal relationship ensures that their effect on excitability is complementary rather than interfering. Altogether, our results demonstrate that motor and sensory systems continuously interact in orchestrating the brain's context for the optimal sampling of our multisensory environment.

A pulse of hope in the fight against Alzheimer’s

Flashes of strobe lights and the beat of stereo speakers filled the otherwise pitch-black, shoebox-sized cages. The mice inside may not have danced, but their brains caught the rhythm. Pulses of light and sound delivered to mouse brains at a frequency of 40 hertz appeared to reduce the number of amyloid plaques and tau protein tangles, hallmarks of the Alzheimer’s brain—seen here in a coronal slice from a patient with Alzheimer’s disease ( Left ), compared with normal brain ( Right ). Image credit: Science Source/Alfred Pasieka. The pulses of light and sound, delivered at a frequency of 40 per second, or 40 hertz, jumpstarted the mice’s neurons to fire electrical signals in time with the pulses—and subsequently reduced the number of amyloid plaques and tau protein tangles in their brains, two hallmarks of Alzheimer’s disease. Hour-long sessions on seven days in the nightclub-esque boxes also improved the animals’ working memory, sensory processing, and spatial navigation (1). “Every result seems to be too good to be true,” says Li-Huei Tsai, director of The Picower Institute for Learning and Memory at the Massachusetts Institute of Technology in Cambridge, who led the experiment. The synchronous rhythmic firing of neurons is critical for a healthy, functioning brain (2)—one that can accurately recall old memories and efficiently process new information. Large groups of neurons oscillating on and off together generate brain waves. Although it’s not yet clear why, this synchrony seems to strengthen coordination across brain regions and between different types of brain cells. “Brain rhythms are known to participate in all forms of cognition. And changes of brain rhythms appear to be implicated in all forms of neurological disease,” says Nancy Kopell, a math professor and director of the Cognitive Rhythms Collaborative at Boston University in MA. Growing evidence indicates that neurons in many animals, including humans, …

MondoA:MLX complex regulates glucose-dependent gene expression and links to circadian rhythm in liver and brain of the freeze-tolerant wood frog, Rana sylvatica.

The wood frog, Rana sylvatica, is one of only a few vertebrate species that display natural freeze tolerance. Frogs survive the freezing of about two-thirds of their body water as extracellular ice over the winter months. Multiple adaptations support freeze tolerance including metabolic rate depression and the production of huge amounts of glucose (often 200mM or more) as a cryoprotectant that protects cells from freeze damage. To understand how high glucose levels affect gene expression, we studied MondoA, a glucose sensing transcription factor, and its partner MLX (Max-like protein) to assess their ability to modulate the expression of genes involved in glucose metabolism and circadian rhythm. Wood frog liver and brain tissues were analyzed, assessing protein levels, nuclear distribution, and DNA binding activity of MondoA:MLX during freezing (24h at - 2.5°C) and subsequent thawing (8h returned to 5°C), as compared with 5°C controls. Downstream targets of MondoA:MLX were also evaluated: TXNIP (thioredoxin interacting protein), ARRDC4 (arrestin domain containing 4), HK-2 (hexokinase-2), PFKFB-3 (6-phosphofructo-2-kinase isozyme 3) and KLF-10 (Kruppel-like factor-10). Both KLF-10 and PFKFB-3 are also involved in circadian dependant regulation which was also explored in the current study via analysis of BMAL-1 (aryl hydrocarbon receptor nuclear translocator-like protein 1) and CLOCK (circadian locomotor output cycles kaput) proteins. Our data establish the MondoA-MLX complex as active under the hyperglycemic conditions in liver to regulate glucose metabolism and may also link to circadian rhythm in liver via KLF-10 and PFKFB-3 but not in brain.

Astrocytic Ca2+ signaling is reduced during sleep and is involved in the regulation of slow wave sleep

Astrocytic Ca2+ signaling has been intensively studied in health and disease but has not been quantified during natural sleep. Here, we employ an activity-based algorithm to assess astrocytic Ca2+ signals in the neocortex of awake and naturally sleeping mice while monitoring neuronal Ca2+ activity, brain rhythms and behavior. We show that astrocytic Ca2+ signals exhibit distinct features across the sleep-wake cycle and are reduced during sleep compared to wakefulness. Moreover, an increase in astrocytic Ca2+ signaling precedes transitions from slow wave sleep to wakefulness, with a peak upon awakening exceeding the levels during whisking and locomotion. Finally, genetic ablation of an important astrocytic Ca2+ signaling pathway impairs slow wave sleep and results in an increased number of microarousals, abnormal brain rhythms, and an increased frequency of slow wave sleep state transitions and sleep spindles. Our findings demonstrate an essential role for astrocytic Ca2+ signaling in regulating slow wave sleep.

Differential effects of vagus nerve stimulation paradigms guide clinical development for Parkinson’s disease

BackgroundVagus nerve stimulation (VNS) modifies brain rhythms in the locus coeruleus (LC) via the solitary nucleus. Degeneration of the LC in Parkinson’s disease (PD) is an early catalyst of the spreading neurodegenerative process, suggesting that stimulating LC output with VNS has the potential to modify disease progression. We previously showed in a lesion PD model that VNS delivered twice daily reduced neuroinflammation and motor deficits, and attenuated tyrosine hydroxylase (TH)-positive cell loss. ObjectiveThe goal of this study was to characterize the differential effects of three clinically-relevant VNS paradigms in a PD lesion model. MethodsEleven days after DSP-4 (N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine, noradrenergic lesion, administered systemically)/6-OHDA (6-hydroxydopamine, dopaminergic lesion, administered intrastriatally) rats were implanted with VNS devices, and received either low-frequency VNS, standard-frequency VNS, or high-frequency microburst VNS. After 10 days of treatment and behavioral assessment, rats were euthanized, right prefrontal cortex (PFC) was dissected for norepinephrine assessment, and the left striatum, bilateral substantia nigra (SN), and LC were sectioned for immunohistochemical detection of catecholamine neurons, α-synuclein, astrocytes, and microglia. ResultsAt higher VNS frequencies, specifically microburst VNS, greater improvements occurred in motor function, attenuation of TH-positive cell loss in SN and LC, and norepinephrine concentration in the PFC. Additionally, higher VNS frequencies resulted in lower intrasomal α-synuclein accumulation and glial density in the SN. ConclusionsThese data indicate that higher stimulation frequencies provided the greatest attenuation of behavioral and pathological markers in this PD model, indicating therapeutic potential for these VNS paradigms.

On the Assessment of Functional Connectivity in an Immersive Brain-Computer Interface During Motor Imagery.

New trends on brain-computer interface (BCI) design are aiming to combine this technology with immersive virtual reality in order to provide a sense of realism to its users. In this study, we propose an experimental BCI to control an immersive telepresence system using motor imagery (MI). The system is immersive in the sense that the users can control the movement of a NAO humanoid robot in a first person perspective (1PP), i.e., as if the movement of the robot was his/her own. We analyze functional brain connectivity between 1PP and 3PP during the control of our BCI using graph theory properties such as degree, betweenness centrality, and efficiency. Changes in these metrics are obtained for the case of the 1PP, as well as for the traditional third person perspective (3PP) in which the user can see the movement of the robot as feedback. As proof-of-concept, electroencephalography (EEG) signals were recorded from two subjects while they performed MI to control the movement of the robot. The graph theoretical analysis was applied to the binary directed networks obtained through the partial directed coherence (PDC). In our preliminary assessment we found that the efficiency in the α brain rhythm is greater in 1PP condition in comparison to the 3PP at the prefrontal cortex. Also, a stronger influence of signals measured at EEG channel C3 (primary motor cortex) to other regions was found in 1PP condition. Furthermore, our preliminary results seem to indicate that α and β brain rhythms have a high indegree at prefrontal cortex in 1PP condition, and this could be possibly related to the experience of sense of agency. Therefore, using the PDC combined with graph theory while controlling a telepresence robot in an immersive system may contribute to understand the organization and behavior of brain networks in these environments.

Stress Assessment by Combining Neurophysiological Signals and Radio Communications of Air Traffic Controllers.

Air Traffic Control (ATC) has been classified as the fourth most stressful job. In this regard, sixteen controllers were asked to perform ecological ATC simulation during which behavioral (Radio Communications with pilots - RCs), subjective (stress perception) and neurophysiological signals (brain activity and skin conductance - SC) were collected. All the considered parameters reported significant changes under high stress conditions. In particular, the theta, alpha, and beta brain rhythms increased significantly (all p<0.05) all over the brain areas, and both the SC components exhibited higher values (p<0.01). Additionally, the number of speech under high stress decreased significantly (p<10-4) while both the mean and median value of the F0 component of the RC increased (p<0.01). The results can be employed to objectively measure and track the controller's stress level while dealing with ATC activities to better tailoring the workshift and maintaining high safety levels.

Lactate Attenuates Synaptic Transmission and Affects Brain Rhythms Featuring High Energy Expenditure.

SummaryLactate shuttled from blood, astrocytes, and/or oligodendrocytes may serve as the major glucose alternative in brain energy metabolism. However, its effectiveness in fueling neuronal information processing underlying complex cortex functions like perception and memory is unclear. We show that sole lactate disturbs electrical gamma and theta-gamma oscillations in hippocampal networks by either attenuation or neural bursts. Bursting is suppressed by elevating the glucose fraction in substrate supply. By contrast, lactate does not affect electrical sharp wave-ripple activity featuring lower energy use. Lactate increases the oxygen consumption during the network states, reflecting enhanced oxidative ATP synthesis in mitochondria. Finally, lactate attenuates synaptic transmission in excitatory pyramidal cells and fast-spiking, inhibitory interneurons by reduced neurotransmitter release from presynaptic terminals, whereas action potential generation in the axon is regular. In conclusion, sole lactate is less effective and potentially harmful during gamma-band rhythms by omitting obligatory ATP delivery through fast glycolysis at the synapse.

Coordination Cost and Super-Efficiency in Teamwork: The Role of Communication, Psychological States, Cardiovascular Responses, and Brain Rhythms

To advance knowledge on the psychophysiological markers of “coordination cost” in team settings, we explored differences in meta-communication patterns (i.e., silence, speaking, listening, and overlap), perceived psychological states (i.e., core affect, attention, efficacy beliefs), heart rate variability (i.e., RMSSD), and brain rhythms (i.e., alpha, beta and theta absolute power) across three studies involving 48 male dyads (Mage = 21.30; SD = 2.03). Skilled participants cooperatively played three consecutive FIFA-17 (Xbox) games in a dyad against the computer, or competed against the computer in a solo condition and a dyad condition. We observed that playing in a team, in contrast to playing alone, was associated with higher alpha peak and global efficiency in the brain and, at the same time, led to an increase in focused attention as evidenced by participants’ higher theta activity in the frontal lobe. Moreover, we observed that overtime participants’ brain dynamics moved towards a state of “neural-efficiency”, characterized by increased theta and beta activity in the frontal lobe, and high alpha activity across the whole brain. Our findings advance the literature by demonstrating that (1) the notion of coordination cost can be captured at the neural level in the initial stages of team development; (2) by decreasing the costs of switching between tasks, teamwork increases both individuals’ attentional focus and global neural efficiency; and (3) communication dynamics become more proficient and individuals’ brain patterns change towards neural efficiency over time, likely due to team learning and decreases in intra-team conflict.

Phase-specific manipulation of rhythmic brain activity by transcranial alternating current stimulation

BackgroundOscillatory phase has been proposed as a key parameter defining the spatiotemporal structure of neural activity. To enhance our understanding of brain rhythms and improve clinical outcomes in pathological conditions, modulation of neural activity by transcranial alternating current stimulation (tACS) emerged as a promising approach. However, the phase-specificity of tACS effects in humans is still critically debated. ObjectiveHere, we investigated the phase-specificity of tACS on visually evoked steady state responses (SSRs) in 24 healthy human participants. MethodsWe used an intermittent electrical stimulation protocol and assessed the influence of tACS on SSR amplitude in the interval immediately following tACS. A neural network model served to validate the plausibility of experimental findings. ResultsWe observed a modulation of SSR amplitudes dependent on the phase shift between flicker and tACS. The tACS effect size was negatively correlated with the strength of flicker-evoked activity. Supported by simulations, data suggest that strong network synchronization limits further neuromodulation by tACS. Neural sources of phase-specific effects were localized in the parieto-occipital cortex within flicker-entrained regions. Importantly, the optimal phase shift between flicker and tACS associated with strongest SSRs was correlated with SSR phase delays in the tACS target region. ConclusionsOverall, our data provide electrophysiological evidence for phase-specific modulations of rhythmic brain activity by tACS in humans. As the optimal timing of tACS application was dependent on cortical SSR phase delays, our data suggest that tACS effects were not mediated by retinal co-stimulation. These findings highlight the potential of tACS for controlled, phase-specific modulations of neural activity.

Spatial multi-scaled chimera states of cerebral cortex network and its inherent structure-dynamics relationship in human brain.

Human cerebral cortex displays various dynamics patterns under different states, however the mechanism how such diverse patterns can be supported by the underlying brain network is still not well understood. Human brain has a unique network structure with different regions of interesting to perform cognitive tasks. Using coupled neural mass oscillators on human cortical network and paying attention to both global and local regions, we observe a new feature of chimera states with multiple spatial scales and a positive correlation between the synchronization preference of local region and the degree of symmetry of the connectivity of the region in the network. Further, we use the concept of effective symmetry in the network to build structural and dynamical hierarchical trees and find close matching between them. These results help to explain the multiple brain rhythms observed in experiments and suggest a generic principle for complex brain network as a structure substrate to support diverse functional patterns.

Assessing the depth of language processing in patients with disorders of consciousness.

Assessing residual consciousness and cognitive abilities in unresponsive patients is a major clinical concern and a challenge for cognitive neuroscience. Although neuroimaging studies have demonstrated a potential for informing diagnosis and prognosis in unresponsive patients, these methods involve sophisticated brain imaging technologies, which limit their clinical application. In this study, we adopted a new language paradigm that elicited rhythmic brain responses tracking the single-word, phrase and sentence rhythms in speech, to examine whether bedside electroencephalography (EEG) recordings can help inform diagnosis and prognosis. EEG-derived neural signals, including both speech-tracking responses and temporal dynamics of global brain states, were associated with behavioral diagnosis of consciousness. Crucially, multiple EEG measures in the language paradigm were robust to predict future outcomes in individual patients. Thus, EEG-based language assessment provides a new and reliable approach to objectively characterize and predict states of consciousness and to longitudinally track individual patients' language processing abilities at the bedside.

Boosting Slow Oscillations during Sleep to Improve Memory Function in Elderly People: A Review of the Literature.

Sleep represents a crucial time window for the consolidation of memory traces. In this view, some brain rhythms play a pivotal role, first of all the sleep slow waves. In particular, the neocortical slow oscillations (SOs), in coordination with the hippocampal ripples and the thalamocortical spindles, support the long-term storage of the declarative memories. The aging brain is characterized by a disruption of this complex system with outcomes on the related cognitive functions. In recent years, the advancement of the comprehension of the sleep-dependent memory consolidation mechanisms has encouraged the development of techniques of SO enhancement during sleep to induce cognitive benefits. In this review, we focused on the studies reporting on the application of acoustic or electric stimulation procedures in order to improve sleep-dependent memory consolidation in older subjects. Although the current literature is limited and presents inconsistencies, there is promising evidence supporting the perspective to non-invasively manipulate the sleeping brain electrophysiology to improve cognition in the elderly, also shedding light on the mechanisms underlying the sleep-memory relations during healthy and pathological aging.

Cognitive Control: Brain Oscillations Coordinate Human Working Memory

A new study has found that rhythmical brain stimulation at theta frequency (5Hz) over prefrontal cortex and stimulation at alpha frequency (10Hz) over posterior parietal cortex increase visual working memory capacity, the effects being due respectively to prioritisation of target information and suppression of distracting information.

Dynamic network interactions among distinct brain rhythms as a hallmark of physiologic state and function

Brain rhythms are associated with a range of physiologic states, and thus, studies have traditionally focused on neuronal origin, temporal dynamics and fundamental role of individual brain rhythms, and more recently on specific pair-wise interactions. Here, we aim to understand integrated physiologic function as an emergent phenomenon of dynamic network interactions among brain rhythms. We hypothesize that brain rhythms continuously coordinate their activations to facilitate physiologic states and functions. We analyze healthy subjects during sleep, and we demonstrate the presence of stable interaction patterns among brain rhythms. Probing transient modulations in brain wave activation, we discover three classes of interaction patterns that form an ensemble representative for each sleep stage, indicating an association of each state with a specific network of brain-rhythm communications. The observations are universal across subjects and identify networks of brain-rhythm interactions as a hallmark of physiologic state and function, providing new insights on neurophysiological regulation with broad clinical implications.

A Self-Operating Time Crystal Model of the Human Brain: Can We Replace Entire Brain Hardware with a 3D Fractal Architecture of Clocks Alone?

Time crystal was conceived in the 1970s as an autonomous engine made of only clocks to explain the life-like features of a virus. Later, time crystal was extended to living cells like neurons. The brain controls most biological clocks that regenerate the living cells continuously. Most cognitive tasks and learning in the brain run by periodic clock-like oscillations. Can we integrate all cognitive tasks in terms of running clocks of the hardware? Since the existing concept of time crystal has only one clock with a singularity point, we generalize the basic idea of time crystal so that we could bond many clocks in a 3D architecture. Harvesting inside phase singularity is the key. Since clocks reset continuously in the brain–body system, during reset, other clocks take over. So, we insert clock architecture inside singularity resembling brain components bottom-up and top-down. Instead of one clock, the time crystal turns to a composite, so it is poly-time crystal. We used century-old research on brain rhythms to compile the first hardware-free pure clock reconstruction of the human brain. Similar to the global effort on connectome, a spatial reconstruction of the brain, we advocate a global effort for more intricate mapping of all brain clocks, to fill missing links with respect to the brain’s temporal map. Once made, reverse engineering the brain would remain a mere engineering challenge.

Mapping Mind-Brain Development: Towards a Comprehensive Theory.

The relations between the developing mind and developing brain are explored. We outline a theory of intellectual development postulating that the mind comprises four systems of processes (domain-specific, attention and working memory, reasoning, and cognizance) developing in four cycles (episodic, realistic, rule-based, and principle-based representations, emerging at birth, 2, 6, and 11 years, respectively), with two phases in each. Changes in reasoning relate to processing efficiency in the first phase and working memory in the second phase. Awareness of mental processes is recycled with the changes in each cycle and drives their integration into the representational unit of the next cycle. Brain research shows that each type of processes is served by specialized brain networks. Domain-specific processes are rooted in sensory cortices; working memory processes are mainly rooted in hippocampal, parietal, and prefrontal cortices; abstraction and alignment processes are rooted in parietal, frontal, and prefrontal and medial cortices. Information entering these networks is available to awareness processes. Brain networks change along the four cycles, in precision, connectivity, and brain rhythms. Principles of mind-brain interaction are discussed.

Universal theory of brain waves: from linear loops to nonlinear synchronized spiking and collective brain rhythms.

An inhomogeneous anisotropic physical model of the brain cortex is presented that predicts the emergence of non-evanescent (weakly damped) wave-like modes propagating in the thin cortex layers transverse to both the mean neural fiber direction and to the cortex spatial gradient. Although the amplitude of these modes stays below the typically observed axon spiking potential, the lifetime of these modes may significantly exceed the spiking potential inverse decay constant. Full brain numerical simulations based on parameters extracted from diffusion and structural MRI confirm the existence and extended duration of these wave modes. Contrary to the standard paradigm that the neural fibers determine the pathways for signal propagation in the brain, the signal propagation due to the cortex wave modes in highly folded areas will exhibit no apparent correlation with the fiber directions. The results are consistent with numerous recent experimental animal and human brain studies demonstrating the existence of electrostatic field activity in the form of traveling waves (including studies where neuronal connections were severed) and with wave loop induced peaks observed in EEG spectra. In addition, we demonstrate that the resonant and non-resonant terms of the nonlinear coupling between multiple modes produce both synchronous spiking-like high frequency wave activity as well as low frequency wave rhythms as a result of their unique dispersion properties. Numerical simulation of forced multiple mode dynamics shows that as forcing increases there is a transition from damped to oscillatory regime that subsequently decays away as over-excitation is reached. The resonant nonlinear coupling results in the emergence of low frequency rhythms with frequencies that are several orders of magnitude below the linear frequencies of modes taking part in the coupling. The localization and persistence of these cortical wave modes, and this new mechanism for understanding the nature of spiking behavior, have significant implications in particular for neuroimaging methods that detect electromagnetic physiological activity, such as EEG and MEG, and in general for the understanding of brain activity, including mechanisms of memory.

Modulation in phase and frequency of neural oscillations during epileptiform activity induced by neonatal Zika virus infection in mice

Modulation of brain activity is one of the main mechanisms capable of demonstrating the synchronization dynamics of neural oscillations. In epilepsy, modulation is a key concept since seizures essentially result from neural hypersynchronization and hyperexcitability. In this study, we have introduced a time-dependent index based on the Kullback-Leibler divergence to quantify the effects of phase and frequency modulations of neural oscillations in neonatal mice exhibiting epileptiform activity induced by Zika virus (ZIKV) infection. Through this index, we demonstrate that fast oscillations (gamma and beta 2) are the more susceptible modulated rhythms in terms of phase, during seizures, whereas slow waves (delta and theta) mainly undergo changes in frequency. The index also allowed detection of specific patterns associated with the interdependent modulation of phase and frequency in neural activity. Furthermore, by comparing ZIKV modulations with the general computational model Epileptors, we verify different signatures related to the brain rhythms modulation in phase and frequency. These findings instigate new studies on the effects of ZIKV infection on neuronal networks from electrophysiological activities, and how different mechanisms can trigger epilepsy.