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Ketamine is an NMDA receptor antagonist that has antidepressant and anesthetic properties. At subanesthetic doses, ketamine induces transient psychosis in humans, and is used to model psychosis in experimental animals. In rodents, subanesthetic doses of ketamine increase the power of high-frequency oscillations (HFO, > 100 Hz) in the electroencephalogram (EEG), a frequency band linked to cognitive functions. However, to date, the effects of ketamine in carnivores and primates have been poorly investigated. Here, we examined in the cat, cortical HFO during wakefulness, sleep, and after administering a sub-anesthetic dose of ketamine. Four cats were prepared with cortical electrodes for chronic polysomnographic recordings in head-restrained conditions. The cortical HFO power, connectivity, direction of the information flow using Granger Causality (GC) analysis, their relationships with respiratory activity, and the effect of auditory stimulation were analyzed. During wakefulness, but not during sleep, we found that HFO were coupled with the inspiratory phase of the respiration. After ketamine administration, HFO power was enhanced and remained associated with the inspiratory phase. GC analysis suggests that ketamine-enhanced HFO originate from the olfactory bulb (OB) and stream towards the prefrontal cortex (Pf). Accordingly, occluding the nostrils significantly reduced the power of the ketamine-enhanced HFO in both the OB and Pf. Finally, auditory stimulation did not affect HFO. In conclusion, the HFO are associated with respiration during wakefulness, but not during sleep. The enhancement of this rhythm by ketamine may disrupt cortical information processing, which could contribute to some of the neuropsychiatric effects associated with ketamine.

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5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) is a potent classical psychedelic known to induce changes in locomotion, behaviour, and sleep in rodents. However, there is limited knowledge regarding its acute neurophysiological effects. Local field potentials (LFPs) are commonly used as a proxy for neural activity, but previous studies investigating psychedelics have been hindered by confounding effects of behavioural changes and anaesthesia, which alter these signals. To address this gap, we investigated acute LFP changes in the hippocampus (HP) and medial prefrontal cortex (mPFC) of freely behaving rats, following 5-MeO-DMT administration. 5-MeO-DMT led to an increase of delta power and a decrease of theta power in the HP LFPs, which could not be accounted for by changes in locomotion. Furthermore, we observed a dose-dependent reduction in slow (20-50 Hz) and mid (50-100 Hz) gamma power, as well as in theta phase modulation, even after controlling for the effects of speed and theta power. State map analysis of the spectral profile of waking behaviour induced by 5-MeO-DMT revealed similarities to electrophysiological states observed during slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. Our findings suggest that the psychoactive effects of classical psychedelics are associated with the integration of waking behaviours with sleep-like spectral patterns in LFPs.

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Synchronous excitatory discharges from the entorhinal cortex (EC) to the dentate gyrus (DG) generate fast and prominent patterns in the hilar local field potential (LFP), called dentate spikes (DSs). As sharp-wave ripples in CA1, DSs are more likely to occur in quiet behavioral states, when memory consolidation is thought to take place. However, their functions in mnemonic processes are yet to be elucidated. The classification of DSs into types 1 or 2 is determined by their origin in the lateral or medial EC, as revealed by current source density (CSD) analysis, which requires recordings from linear probes with multiple electrodes spanning the DG layers. To allow the investigation of the functional role of each DS type in recordings obtained from single electrodes and tetrodes, which are abundant in the field, we developed an unsupervised method using Gaussian mixture models to classify such events based on their waveforms. Our classification approach achieved high accuracies (> 80%) when validated in 8 mice with DG laminar profiles. The average CSDs, waveforms, rates, and widths of the DS types obtained through our method closely resembled those derived from the CSD-based classification. As an example of application, we used the technique to analyze single-electrode LFPs from apolipoprotein (apo) E3 and apoE4 knock-in mice. We observed that the latter group, which is a model for Alzheimer's disease, exhibited wider DSs of both types from a young age, with a larger effect size for DS type 2, likely reflecting early pathophysiological alterations in the EC-DG network, such as hyperactivity. In addition to the applicability of the method in expanding the study of DS types, our results show that their waveforms carry information about their origins, suggesting different underlying network dynamics and roles in memory processing.

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Synchronous excitatory discharges from the entorhinal cortex (EC) to the dentate gyrus (DG) generate fast and prominent patterns in the hilar local field potential (LFP), called dentate spikes (DSs). As sharp-wave ripples in CA1, DSs are more likely to occur in quiet behavioral states, when memory consolidation is thought to take place. However, their functions in mnemonic processes are yet to be elucidated. The classification of DSs into types 1 or 2 is determined by their origin in the lateral or medial EC, as revealed by current source density (CSD) analysis, which requires recordings from linear probes with multiple electrodes spanning the DG layers. To allow the investigation of the functional role of each DS type in recordings obtained from single electrodes and tetrodes, which are abundant in the field, we developed an unsupervised method using Gaussian mixture models to classify such events based on their waveforms. Our classification approach achieved high accuracies (> 80%) when validated in 8 mice with DG laminar profiles. The average CSDs, waveforms, rates, and widths of the DS types obtained through our method closely resembled those derived from the CSD-based classification. As an example of application, we used the technique to analyze single-electrode LFPs from apolipoprotein (apo) E3 and apoE4 knock-in mice. We observed that the latter group, which is a model for Alzheimer's disease, exhibited wider DSs of both types from a young age, with a larger effect size for DS type 2, likely reflecting early pathophysiological alterations in the EC-DG network, such as hyperactivity. In addition to the applicability of the method in expanding the study of DS types, our results show that their waveforms carry information about their origins, suggesting different underlying network dynamics and roles in memory processing.

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Neuronal interactions give rise to complex dynamics in cortical networks, often described in terms of the diversity of activity patterns observed in a neural signal. Interestingly, the complexity of spontaneous electroencephalographic signals decreases during slow-wave sleep (SWS); however, the underlying neural mechanisms remain elusive. Here, we analyse in-vivo recordings from neocortical and hippocampal neuronal populations in rats and show that the complexity decrease is due to the emergence of synchronous neuronal DOWN states. Namely, we find that DOWN states during SWS force the population activity to be more recurrent, deterministic, and less random than during REM sleep or wakefulness, which, in turn, leads to less complex field recordings. Importantly, when we exclude DOWN states from the analysis, the recordings during wakefulness and sleep become indistinguishable: the spiking activity in all the states collapses to a common scaling. We complement these results by implementing a critical branching model of the cortex, which shows that inducing DOWN states to only a percentage of neurons is enough to generate a decrease in complexity that replicates SWS.

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Gamma oscillations are believed to underlie cognitive processes by shaping the formation of transient neuronal partnerships on a millisecond scale. These oscillations are coupled to the phase of breathing cycles in several brain areas, possibly reflecting local computations driven by sensory inputs sampled at each breath. Here, we investigated the mechanisms and functions of gamma oscillations in the piriform (olfactory) cortex of awake mice to understand their dependence on breathing and how they relate to local spiking activity. Mechanistically, we find that respiration drives gamma oscillations in the piriform cortex, which correlate with local feedback inhibition and result from recurrent connections between local excitatory and inhibitory neuronal populations. Moreover, respiration-driven gamma oscillations are triggered by the activation of mitral/tufted cells in the olfactory bulb and are abolished during ketamine/xylazine anesthesia. Functionally, we demonstrate that they locally segregate neuronal assemblies through a winner-take-all computation leading to sparse odor coding during each breathing cycle. Our results shed new light on the mechanisms of gamma oscillations, bridging computation, cognition, and physiology.

The cerebral cortex is the most recently evolved region of the mammalian brain. There, millions of neurons can synchronize their activity to create brain waves, a series of electric rhythms associated with various cognitive functions. Gamma waves, for example, are thought to be linked to brain processes which require distributed networks of neurons to communicate and integrate information. These waves were first discovered in the 1940s by researchers investigating brain areas involved in olfaction, and they are thought to be important for detecting and recognizing smells. Yet, scientists still do not understand how these waves are generated or what role they play in sensing odors. To investigate these questions, González et al. used a battery of computational approaches to analyze a large dataset of brain activity from awake mice. This revealed that, in the cortical region dedicated to olfaction, gamma waves arose each time the animals completed a breathing cycle ­ that is, after they had sampled the air by breathing in. Each breath was followed by certain neurons relaying olfactory information to the cortex to activate complex cell networks; this included circuits of cells known as feedback interneurons, which can switch off weakly activated neurons, including ones that participated in activating them in the first place. The respiration-driven gamma waves derived from this 'feedback inhibition' mechanism. Further work then examined the role of the waves in olfaction. Smell identification relies on each odor activating a unique set of cortical neurons. The analyses showed that gamma waves acted to select and amplify the best set of neurons for representing the odor sensed during a sniff, and to quieten less relevant neurons. Loss of smell is associated with many conditions which affect the brain, such as Alzheimer's disease or COVID-19. By shedding light on the neuronal mechanisms that underpin olfaction, the work by González et al. could help to better understand how these impairments emerge, and how the brain processes other types of complex information.

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Rapid eye movement (REM) sleep in rodents is defined by the presence of theta rhythm in the absence of movement. The amplitude and frequency of theta oscillations have been used to distinguish between tonic and phasic REM sleep. However, tonic REM sleep has not been further subdivided, although characteristics of network oscillations such as cross-frequency coupling between theta and gamma vary within this sub-state. Recently, it has been shown that theta-gamma coupling depends on an optimal breathing rate of ~5 Hz. The frequency of breathing varies strongly throughout REM sleep, and the duration of single REM sleep episodes ranges from several seconds to minutes, whereby short episodes predominate. Here we studied the relation between breathing frequency, accelerometer activity, and the length of REM sleep periods. We found that small movements detected with three-dimensional accelerometry positively correlate with breathing rate. Interestingly, breathing is slow in short REM sleep episodes, while faster respiration regimes exclusively occur after a certain delay in longer REM sleep episodes. Thus, merging REM sleep episodes of different lengths will result in a predominance of slow respiration due to the higher occurrence of short REM sleep periods. Moreover, our results reveal that not only do phasic REM sleep epochs predominantly occur during long REM sleep episodes, but that the long episodes also have faster theta and higher gamma activity. These observations suggest that REM sleep can be further divided from a physiological point of view depending on its duration. Higher levels of arousal during REM sleep, indicated by higher breathing rates, can only be captured in long REM sleep episodes.

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Nasal respiration influences brain dynamics by phase-entraining neural oscillations at the same frequency as the breathing rate and by phase-modulating the activity of faster gamma rhythms. Despite being widely reported, we still do not understand the functional roles of respiration-entrained oscillations. A common hypothesis is that these rhythms aid long-range communication and provide a privileged window for synchronization. Here we tested this hypothesis by analyzing electrocorticographic (ECoG) recordings in mice, rats, and cats during the different sleep-wake states. We found that the respiration phase modulates the amplitude of cortical gamma oscillations in the three species, although the modulated gamma frequency bands differed with faster oscillations (90-130 Hz) in mice, intermediate frequencies (60-100 Hz) in rats, and slower activity (30-60 Hz) in cats. In addition, our results also show that respiration modulates olfactory bulb-frontal cortex synchronization in the gamma range, in which each breathing cycle evokes (following a delay) a transient time window of increased gamma synchrony. Long-range gamma synchrony modulation occurs during quiet and active wake states but decreases during sleep. Thus, our results suggest that respiration-entrained brain rhythms orchestrate communication in awake mammals.

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Synchronous oscillations are essential for coordinated activity in neuronal networks and, hence, for behavior and cognition. While most network oscillations are generated within the central nervous system, recent evidence shows that rhythmic body processes strongly influence activity patterns throughout the brain. A major factor is respiration (Resp), which entrains multiple brain regions at the mesoscopic (local field potential) and single-cell levels. However, it is largely unknown how such Resp-driven rhythms interact or compete with internal brain oscillations, especially those with similar frequency domains. In mice, Resp and theta (θ) oscillations have overlapping frequencies and co-occur in various brain regions. Here, we investigated the effects of Resp and θ on neuronal discharges in the mouse parietal cortex during four behavioral states which either show prominent θ (REM sleep and active waking (AW)) or lack significant θ (NREM sleep and waking immobility (WI)). We report a pronounced state-dependence of spike modulation by both rhythms. During REM sleep, θ effects on unit discharges dominate, while during AW, Resp has a larger influence, despite the concomitant presence of θ oscillations. In most states, unit modulation by θ or Resp increases with mean firing rate. The preferred timing of Resp-entrained discharges (inspiration versus expiration) varies between states, indicating state-specific and different underlying mechanisms. Our findings show that neurons in an associative cortex area are differentially and state-dependently modulated by two fundamentally different processes: brain-endogenous θ oscillations and rhythmic somatic feedback signals from Resp.

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The simultaneous, local integration of information from widespread brain regions is an essential feature of cortical computation and particularly relevant for multimodal association areas such as the posterior parietal cortex. Slow, rhythmic fluctuations in the local field potentials (LFPs) are assumed to constitute a global signal aiding interregional communication through the long-range synchronization of neuronal activity. Recent work demonstrated the brain-wide presence of a novel class of slow neuronal oscillations that are entrained by nasal respiration. However, whether there are differences in the influence of the respiration-entrained rhythm (RR) and the endogenous theta (θ) rhythm over local networks is unknown. In this work, we aimed at characterizing the impact of both classes of oscillations on neuronal activity in the posterior parietal cortex of mice. We focused our investigations on a θ-dominated state (rapid eye movement sleep) and an RR-dominated state (wake immobility). Using linear silicon probes implanted along the dorsoventral cortical axis, we found that the LFP-depth distributions of both rhythms show differences in amplitude and coherence but no phase shift. Using tetrode recordings, we demonstrate that a substantial fraction of parietal neurons is modulated by either RR or θ or even by both rhythms simultaneously. Interestingly, the phase and cortical depth dependence of spike-field coupling differ for these oscillations. We further show through intracellular recordings in urethane-anesthetized mice that synaptic inhibition is likely to play a role in generating respiration-entrainment at the membrane potential level. We conclude that θ and respiration differentially affect neuronal activity in the parietal cortex.NEW & NOTEWORTHY Nasal respiration generates a rhythmic signal that entrains large portions of the mammalian brain into respiration-coupled field potentials. Here, we report the simultaneous presence of respiratory rhythm (RR) and θ oscillations in the parietal association cortex of mice. Despite their overlapping frequencies, both rhythms differ in their state-dependent power and differentially entrain the discharge behavior of units. We conclude that network activity in the parietal cortex is synchronized by two different physiological oscillation patterns.

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Episodic memory depends on the recollection of spatial and temporal aspects of past experiences in which the hippocampus plays a critical role. Studies on hippocampal lesions in rodents have shown that dentate gyrus (DG) and CA3 are necessary to detect object displacement in memory tasks. However, the understanding of real-time oscillatory activity underlying memory discrimination of subtle and pronounced displacements remains elusive. Here, we chronically implanted microelectrode arrays in adult male Wistar rats to record network oscillations from DG, CA3, and CA1 of the dorsal hippocampus while animals executed an object recognition task of high and low spatial displacement tests (HD: 108 cm, and LD: 54 cm, respectively). Behavioral analysis showed that the animals discriminate between stationary and displaced objects in the HD but not LD conditions. To investigate the hypothesis that theta and gamma oscillations in different areas of the hippocampus support discrimination processes in a recognition memory task, we compared epochs of object exploration between HD and LD conditions as well as displaced and stationary objects. We observed that object exploration epochs were accompanied by strong rhythmic activity in the theta frequency (6-12 Hz) band in the three hippocampal areas. Comparison between test conditions revealed higher theta band power and higher theta-gamma phase-amplitude coupling in the DG during HD than LD conditions. Similarly, direct comparison between displaced and stationary objects within the HD test showed higher theta band power in CA3 during exploration of displaced objects. Moreover, the discrimination index between displaced and stationary objects directly correlated with CA1 gamma band power in epochs of object exploration. We thus conclude that theta and gamma oscillations in the dorsal hippocampus support the successful discrimination of object displacement in a recognition memory task.

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The field of cannabinoid research has been receiving ever-growing interest. Ongoing debates worldwide about the legislation of medical cannabis further motivates research into cannabinoid function within the central nervous system (CNS). To date, two well-characterized cannabinoid receptors exist. While most research has investigated Cb1 receptors (Cb1Rs), Cb2 receptors (Cb2Rs) in the brain have started to attract considerable interest in recent years. With indisputable evidence showing the wide-distribution of Cb2Rs in the brain of different species, they are no longer considered just peripheral receptors. However, in contrast to Cb1Rs, the functionality of central Cb2Rs remains largely unexplored. Here we review recent studies on hippocampal Cb2Rs. While conflicting results about their function have been reported, we have made significant progress in understanding the involvement of Cb2Rs in modulating cellular properties and network excitability. Moreover, Cb2Rs have been shown to be expressed in different subregions of the hippocampus, challenging our prior understanding of the endocannabinoid system. Although more insight into their functional roles is necessary, we propose that targeting hippocampal Cb2Rs may offer novel therapies for diseases related to memory and adult neurogenesis deficits.

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The hippocampus has been linked to memory encoding and spatial navigation, while the prefrontal cortex is associated with cognitive functions such as decision-making. These regions are hypothesized to communicate in tasks that demand both spatial navigation and decision-making processes. However, the electrophysiological signatures underlying this communication remain to be better elucidated. To investigate the dynamics of the hippocampal-prefrontal interactions, we have analyzed their local field potentials and spiking activity recorded from rats performing a spatial alternation task on a figure eight-shaped maze. We found that the phase coherence of theta peaked around the choice point area of the maze. Moreover, Granger causality revealed a hippocampus → prefrontal cortex directionality of information flow at theta frequency, peaking at starting areas of the maze, and on the reverse direction at delta frequency, peaking near the turn onset. Additionally, the patterns of phase-amplitude cross-frequency coupling within and between the regions also showed spatial selectivity, and hippocampal theta and prefrontal delta modulated not only gamma amplitude but also inter-regional gamma synchrony. Finally, we found that the theta rhythm dynamically modulated neurons in both regions, with the highest modulation at the choice area; interestingly, prefrontal cortex neurons were more strongly modulated by the hippocampal theta rhythm than by their local field rhythm. In all, our results reveal maximum electrophysiological interactions between the hippocampus and the prefrontal cortex near the decision-making period of the spatial alternation task, corroborating the hypothesis that a dynamic interplay between these regions takes place during spatial decisions.

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Temporal coupling between theta and gamma oscillations is a hallmark activity pattern of several cortical networks and becomes especially prominent during REM sleep. In a parallel approach, nasal breathing has been recently shown to generate phase-entrained network oscillations which also modulate gamma. Both slow rhythms (theta and respiration-entrained oscillations) have been suggested to aid large-scale integration but they differ in frequency, display low coherence, and modulate different gamma sub-bands. Respiration and theta are therefore believed to be largely independent. In the present work, however, we report an unexpected but robust relation between theta-gamma coupling and respiration in mice. Interestingly, this relation takes place not through the phase of individual respiration cycles, but through respiration rate: the strength of theta-gamma coupling exhibits an inverted V-shaped dependence on breathing rate, leading to maximal coupling at breathing frequencies of 4-6 Hz. Noteworthy, when subdividing sleep epochs into phasic and tonic REM patterns, we find that breathing differentially relates to theta-gamma coupling in each state, providing new evidence for their physiological distinctiveness. Altogether, our results reveal that breathing correlates with brain activity not only through phase-entrainment but also through rate-dependent relations with theta-gamma coupling. Thus, the link between respiration and other patterns of cortical network activity is more complex than previously assumed.

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Nasal breathing generates a rhythmic signal which entrains cortical network oscillations in widespread brain regions on a cycle-to-cycle time scale. It is unknown, however, how respiration and neuronal network activity interact on a larger time scale: are breathing frequency and typical neuronal oscillation patterns correlated? Is there any directionality or temporal relationship? To address these questions, we recorded field potentials from the posterior parietal cortex of mice together with respiration during REM sleep. In this state, the parietal cortex exhibits prominent θ and γ oscillations while behavioral activity is minimal, reducing confounding signals. We found that the instantaneous breathing frequency strongly correlates with the instantaneous frequency and amplitude of both θ and γ oscillations. Cross-correlograms and Granger causality revealed specific directionalities for different rhythms: changes in θ activity precede and Granger-cause changes in breathing frequency, suggesting control by the functional state of the brain. On the other hand, the instantaneous breathing frequency Granger causes changes in γ frequency, suggesting that γ is influenced by a peripheral reafference signal. These findings show that changes in breathing frequency temporally relate to changes in different patterns of rhythmic brain activity. We hypothesize that such temporal relations are mediated by a common central drive likely to be located in the brainstem.

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Ibogaine is a psychedelic alkaloid that has attracted large scientific interest because of its antiaddictive properties in observational studies in humans as well as in animal models. Its subjective effect has been described as intense, vivid dream-like experiences occurring while awake; hence, ibogaine is often referred to as an oneirogenic psychedelic. While this unique dream-like profile has been hypothesized to aid the antiaddictive effects, the electrophysiological signatures of this psychedelic state remain unknown. We previously showed in rats that ibogaine promotes a waking state with abnormal motor behavior along with a decrease in NREM and REM sleep. Here, we performed an in-depth analysis of the intracranial electroencephalogram during "ibogaine wakefulness". We found that ibogaine induces gamma oscillations that, despite having larger power than control levels, are less coherent and less complex. Further analysis revealed that this profile of gamma activity compares to that of natural REM sleep. Thus, our results provide novel biological evidence for the association between the psychedelic state and REM sleep, contributing to the understanding of the brain mechanisms associated with the oneirogenic psychedelic effect of ibogaine.

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Diazepam has been broadly accepted as an anxiolytic drug and is often used as a positive control in behavioral experiments with mice. However, as opposed to this general assumption, the effect of diazepam on mouse behavior can be considered rather controversial from an evidence point of view. Here we revisit this issue by studying the effect of diazepam on a benchmark task in the preclinical anxiety literature: the elevated plus maze. We evaluated the minute-by-minute time-course of the diazepam effect along the 10 min of the task at three different doses (0.5, 1 and 2 mg/kg i.p. 30 min before the task) in female and male C57BL/6J mice. Furthermore, we contrasted the effects of diazepam with those of a selective serotoninergic reuptake inhibitor (paroxetine, 10 mg/kg i.p. 1 h before the task). Diazepam had no anxiolytic effect at any of the tested doses, and, at the highest dose, it impaired locomotor activity, likely due to sedation. Noteworthy, our results held true when examining male and female mice separately, when only examining the first 5 min of the task, and when animals were subjected to one hour of restrain-induced stress prior to diazepam treatment. In contrast, paroxetine significantly reduced anxiety-like behavior without inducing sedative effects. Our results therefore suggest that preclinical studies for screening new anxiolytic drugs should be cautious with diazepam use as a potential positive control.

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INTRODUCTION: The millenarian breathing exercises from Yoga, commonly called Pranayamas, are known to induce meditative states, reduce stress, and increase lung capacity. However, the physiological mechanisms by which these practices modulate the human nervous system still need to be unveiled. OBJECTIVES: The aim of this work was to review studies describing the influence of breathing exercises on the brain/mind of humans. METHODOLOGY: We reviewed articles written in English and published between 2008 and 2018. Inclusion and exclusion criteria were based on the PRISMA recommendations to filter articles from Science Direct, PubMed, and Virtual Health Library databases. Patient/Population, Intervention, Comparison, and Outcome technique and Prospective Register of Systematic Reviews registration were also considered. RESULTS: From a total of 1588 articles, 14 attended the criteria. They were critically compared to each other and presented in a table divided into study; country; sample size; gender; age; objective; technique; outcome. DISCUSSION: In general, the 14 papers highlight the impact of yogic breathing techniques on emotional and cognitive performance. CONCLUSION: In-depth studies focusing on specific aspects of the practices such as retentions, prolonged expiration, attention on fluid respiration, and abdominal/thoracic respiration should better elucidate the effects of Yogic Breathing Techniques (YBT).

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The theory of communication through coherence (CTC) posits the synchronization of brain oscillations as a key mechanism for information sharing and perceptual binding. In a parallel literature, hippocampal theta activity (4-10 Hz) has been shown to modulate the appearance of neocortical fast gamma oscillations (100-150 Hz), a phenomenon known as cross-frequency coupling (CFC). Even though CFC has also been previously associated with information routing, it remains to be determined whether it directly relates to CTC. In particular, for the theta-fast gamma example at hand, a critical question is to know if the phase of the theta cycle influences gamma synchronization across the neocortex. To answer this question, we combined CFC (modulation index) and CTC (phase-locking value) metrics in order to detect the modulation of the cross-regional high-frequency synchronization by the phase of slower oscillations. Upon applying this method, we found that the inter-hemispheric synchronization of neocortical fast gamma during REM sleep depends on the instantaneous phase of the theta rhythm. These results show that CFC is likely to aid long-range information transfer by facilitating the synchronization of faster rhythms, thus consistent with classical CTC views.

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