Parallel detection of theta and respiration-coupled oscillations throughout the mouse brain

Hippocampal-prefrontal interactions during spatial decision-making

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.

Respiration modulates oscillatory neural network activity at rest

Despite recent advances in understanding how respiration affects neural signalling to influence perception, cognition, and behaviour, it is yet unclear to what extent breathing modulates brain oscillations at rest. We acquired respiration and resting state magnetoencephalography (MEG) data from human participants to investigate if, where, and how respiration cyclically modulates oscillatory amplitudes (2 to 150 Hz). Using measures of phase-amplitude coupling, we show respiration-modulated brain oscillations (RMBOs) across all major frequency bands. Sources of these modulations spanned a widespread network of cortical and subcortical brain areas with distinct spectrotemporal modulation profiles. Globally, delta and gamma band modulations varied with distance to the head centre, with stronger modulations at distal (versus central) cortical sites. Overall, we provide the first comprehensive mapping of RMBOs across the entire brain, highlighting respiration-brain coupling as a fundamental mechanism to shape neural processing within canonical resting state and respiratory control networks (RCNs).

Respiration-Driven Brain Oscillations in Emotional Cognition

Respiration paces brain oscillations and the firing of individual neurons, revealing a profound impact of rhythmic breathing on brain activity. Intriguingly, respiration-driven entrainment of neural activity occurs in a variety of cortical areas, including those involved in higher cognitive functions such as associative neocortical regions and the hippocampus. Here we review recent findings of respiration-entrained brain activity with a particular focus on emotional cognition. We summarize studies from different brain areas involved in emotional behavior such as fear, despair, and motivation, and compile findings of respiration-driven activities across species. Furthermore, we discuss the proposed cellular and network mechanisms by which cortical circuits are entrained by respiration. The emerging synthesis from a large body of literature suggests that the impact of respiration on brain function is widespread across the brain and highly relevant for distinct cognitive functions. These intricate links between respiration and cognitive processes call for mechanistic studies of the role of rhythmic breathing as a timing signal for brain activity.

Distributed cell assemblies spanning prefrontal cortex and striatum

Highly synchronous neuronal assembly activity is deemed essential for cognitive brain function. In theory, such synchrony could coordinate multiple brain areas performing complementary processes. However, cell assemblies have been observed only in single structures, typically cortical areas, and little is known about their synchrony with downstream subcortical structures, such as the striatum. Here, we demonstrate distributed cell assemblies activated at high synchrony (∼10 ms) spanning prefrontal cortex and striatum. In addition to including neurons at different brain hierarchical levels, surprisingly, they synchronized functionally distinct limbic and associative sub-regions. These assembly activations occurred when members shifted their firing phase relative to ongoing 4 Hz and theta rhythms, in association with high gamma oscillations. This suggests that these rhythms could mediate the emergence of cross-structural assemblies. To test for the role of assemblies in behavior, we trained the rats to perform a task requiring cognitive flexibility, alternating between two different rules in a T-maze. Overall, assembly activations were correlated with task-relevant parameters, including impending choice, reward, rule, or rule order. Moreover, these behavioral correlates were more robustly expressed by assemblies than by their individual member neurons. Finally, to verify whether assemblies can be endogenously generated, we found that they were indeed spontaneously reactivated during sleep and quiet immobility. Thus, cell assemblies are a more general coding mechanism than previously envisioned, linking distributed neocortical and subcortical areas at high synchrony.

Opioids cause dissociated states of consciousness in C57BL/6J mice

The electroencephalogram (EEG) provides an objective, neural correlate of consciousness. Opioid receptors modulate mammalian neuronal excitability, and this fact was used to characterize how opioids administered to mice alter EEG power and states of consciousness. The present study tested the hypothesis that antinociceptive doses of fentanyl, morphine, or buprenorphine differentially alter the EEG and states of sleep and wakefulness in adult, male C57BL/6J mice. Mice were anesthetized and implanted with telemeters that enabled wireless recordings of cortical EEG and electromyogram (EMG). After surgical recovery, EEG and EMG were used to objectively score states of consciousness as wakefulness, rapid eye movement (REM) sleep, or non-REM (NREM) sleep. Measures of EEG power (dB) were quantified as δ (0.5-4 Hz), θ (4-8 Hz), α (8-13 Hz), σ (12-15 Hz), β (13-30 Hz), and γ (30-60 Hz). Compared with saline (control), fentanyl and morphine decreased NREM sleep, morphine eliminated REM sleep, and buprenorphine eliminated NREM sleep and REM sleep. Opioids significantly and differentially disrupted the temporal organization of sleep/wake states, altered specific EEG frequency bands, and caused dissociated states of consciousness. The results are discussed relative to the fact that opioids, pain, and sleep modulate interacting states of consciousness.NEW & NOTEWORTHY This study discovered that antinociceptive doses of fentanyl, morphine, and buprenorphine significantly and differentially disrupt EEG-defined states of consciousness in C57BL/6J mice. These data are noteworthy because: 1) buprenorphine is commonly used in medication-assisted therapy for opioid addiction, and 2) there is evidence that disordered sleep can promote addiction relapse. The results contribute to community phenotyping efforts by making publicly available all descriptive and inferential statistics from this study (Supplemental Tables S1-S8).

Theta-gamma coupling during REM sleep depends on breathing rate

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.

SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals

Neuronal signals generally represent activation of the neuronal networks and give insights into brain functionalities. They are considered as fingerprints of actions and their processing across different structures of the brain. These recordings generate a large volume of data that are susceptible to noise and artifacts. Therefore, the review of these data to ensure high quality by automatically detecting and removing the artifacts is imperative. Toward this aim, this work proposes a custom-developed automatic artifact removal toolbox named, SANTIA (SigMate Advanced: a Novel Tool for Identification of Artifacts in Neuronal Signals). Developed in Matlab, SANTIA is an open-source toolbox that applies neural network-based machine learning techniques to label and train models to detect artifacts from the invasive neuronal signals known as local field potentials.

Neuron-astrocyte networking: astrocytes orchestrate and respond to changes in neuronal network activity across brain states and behaviors

Astrocytes are known to play many important roles in brain function. However, research underscoring the extent to which astrocytes modulate neuronal activity is still underway. Here we review the latest evidence regarding the contribution of astrocytes to neuronal oscillations across the brain, with a specific focus on how astrocytes respond to changes in brain state (e.g., sleep, arousal, stress). We then discuss the general mechanisms by which astrocytes signal to neurons to modulate neuronal activity, ultimately driving changes in behavior, followed by a discussion of how astrocytes contribute to respiratory rhythms in the medulla. Finally, we contemplate the possibility that brain stem astrocytes could modulate brainwide oscillations by communicating the status of oxygenation to higher cortical areas.

Temporal Relations between Cortical Network Oscillations and Breathing Frequency during REM Sleep

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.

The breathing brain: The potential of neural oscillations for the understanding of respiratory perception in health and disease

Dyspnea or breathlessness is a symptom occurring in multiple acute and chronic illnesses, however, the understanding of the neural mechanisms underlying its subjective experience is limited. In this topical review, we propose neural oscillatory dynamics and cross-frequency coupling as viable candidates for a neural mechanism underlying respiratory perception, and a technique warranting more attention in respiration research. With the evidence for the potential of neural oscillations in the study of normal and disordered breathing coming from disparate research fields with a limited history of interdisciplinary collaboration, the main objective of the review was to converge the existing research and suggest future directions. The existing findings show that distinct limbic and cortical activations, as measured by hemodynamic responses, underlie dyspnea, however, the time-scale of these activations is not well understood. The recent findings of oscillatory neural activity coupled with the respiratory rhythm could provide the solution to this problem, however, more research with a focus on dyspnea is needed. We also touch on the findings of distinct spectral patterns underlying the changes in breathing due to experimental manipulations, meditation and disease. Subsequently, we suggest general research directions and specific research designs to supplement the current knowledge using neural oscillation techniques. We argue for the benefits of interdisciplinary collaboration and the converging of neuroimaging and behavioral methods to best explain the emergence of the subjective and aversive individual experience of dyspnea.

Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators

One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Square (OLS) estimation, a viable alternative is to use Artificial Neural Networks (ANNs) implemented in a simple structure with one input and one output layer and trained in a way such that the weights matrix corresponds to the matrix of VAR parameters. In this work, we introduce an ANN combined with SS models for the computation of GC. The ANN is trained through the Stochastic Gradient Descent L1 (SGD-L1) algorithm, and a cumulative penalty inspired from penalized regression is applied to the network weights to encourage sparsity. Simulating networks of coupled Gaussian systems, we show how the combination of ANNs and SGD-L1 allows to mitigate the strong reduction in accuracy of OLS identification in settings of low ratio between number of time series points and of VAR parameters. We also report how the performances in GC estimation are influenced by the number of iterations of gradient descent and by the learning rate used for training the ANN. We recommend using some specific combinations for these parameters to optimize the performance of GC estimation. Then, the performances of ANN and OLS are compared in terms of GC magnitude and statistical significance to highlight the potential of the new approach to reconstruct causal coupling strength and network topology even in challenging conditions of data paucity. The results highlight the importance of of a proper selection of regularization parameter which determines the degree of sparsity in the estimated network. Furthermore, we apply the two approaches to real data scenarios, to study the physiological network of brain and peripheral interactions in humans under different conditions of rest and mental stress, and the effects of the newly emerged concept of remote synchronization on the information exchanged in a ring of electronic oscillators. The results highlight how ANNs provide a mesoscopic description of the information exchanged in networks of multiple interacting physiological systems, preserving the most active causal interactions between cardiovascular, respiratory and brain systems. Moreover, ANNs can reconstruct the flow of directed information in a ring of oscillators whose statistical properties can be related to those of physiological networks.

Ultrasonic Vocalizations Emission across Development in Rats: Coordination with Respiration and Impact on Brain Neural Dynamics

Rats communicate using ultrasonic vocalizations (USV) throughout their life when confronted with emotionally stimulating situations, either negative or positive. The context of USV emission and the psychoacoustic characteristics of the vocalizations change greatly between infancy and adulthood. Importantly, the production of USV is tightly coordinated with respiration, and respiratory rhythm is known to influence brain activity and cognitive functions. This review goes through the acoustic characteristics and mechanisms of production of USV both in infant and adult rats and emphasizes the tight relationships that exist between USV emission and respiration throughout the rat's development. It further describes how USV emission and respiration collectively affect brain oscillatory activities. We discuss the possible association of USV emission with emotional memory processes and point out several avenues of research on USV that are currently overlooked and could fill gaps in our knowledge.

Delta-range coupling between prefrontal cortex and hippocampus supported by respiratory rhythmic input from the olfactory bulb in freely behaving rats

Respiratory rhythm (RR) during sniffing is known to couple with hippocampal theta rhythm. However, outside of the short sniffing bouts, a more stable ~ 2 Hz RR was recently shown to rhythmically modulate non-olfactory cognitive processes, as well. The underlying RR coupling with wide-spread forebrain activity was confirmed using advanced techniques, creating solid premise for investigating how higher networks use this mechanism in their communication. Here we show essential differences in the way prefrontal cortex (PFC) and hippocampus (HC) process the RR signal from the olfactory bulb (OB) that may support dynamic, flexible PFC-HC coupling utilizing this input. We used inter-regional coherences and their correlations in rats, breathing at low rate (~ 2 Hz), outside of the short sniffing bouts. We found strong and stable OB-PFC coherence in wake states, contrasting OB-HC coherence which was low but highly variable. Importantly, this variability was essential for establishing PFC-HC synchrony at RR, whereas variations of RRO in OB and PFC had no significant effect. The findings help to understand the mechanism of rhythmic modulation of non-olfactory cognitive processes by the on-going regular respiration, reported in rodents as well as humans. These mechanisms may be impaired when nasal breathing is limited or in OB-pathology, including malfunctions of the olfactory epithelium due to infections, such as in Covid-19.

The deep and slow breathing characterizing rest favors brain respiratory-drive

A respiration-locked activity in the olfactory brain, mainly originating in the mechano-sensitivity of olfactory sensory neurons to air pressure, propagates from the olfactory bulb to the rest of the brain. Interestingly, changes in nasal airflow rate result in reorganization of olfactory bulb response. By leveraging spontaneous variations of respiratory dynamics during natural conditions, we investigated whether respiratory drive also varies with nasal airflow movements. We analyzed local field potential activity relative to respiratory signal in various brain regions during waking and sleep states. We found that respiration regime was state-specific, and that quiet waking was the only vigilance state during which all the recorded structures can be respiration-driven whatever the respiratory frequency. Using CO₂-enriched air to alter respiratory regime associated to each state and a respiratory cycle based analysis, we evidenced that the large and strong brain drive observed during quiet waking was related to an optimal trade-off between depth and duration of inspiration in the respiratory pattern, characterizing this specific state. These results show for the first time that changes in respiration regime affect cortical dynamics and that the respiratory regime associated with rest is optimal for respiration to drive the brain.

Beta2 Oscillations in Hippocampal-Cortical Circuits During Novelty Detection

Novelty detection is a core feature of behavioral adaptation and involves cascades of neuronal responses-from initial evaluation of the stimulus to the encoding of new representations-resulting in the behavioral ability to respond to unexpected inputs. In the past decade, a new important novelty detection feature, beta2 (~20-30 Hz) oscillations, has been described in the hippocampus (HC). However, the interactions between beta2 and the hippocampal network are unknown, as well as the role-or even the presence-of beta2 in other areas involved with novelty detection. In this work, we combined multisite local field potential (LFP) recordings with novelty-related behavioral tasks in mice to describe the oscillatory dynamics associated with novelty detection in the CA1 region of the HC, parietal cortex, and mid-prefrontal cortex. We found that transient beta2 power increases were observed only during interaction with novel contexts and objects, but not with familiar contexts and objects. Also, robust theta-gamma phase-amplitude coupling was observed during the exploration of novel environments. Surprisingly, bursts of beta2 power had strong coupling with the phase of delta-range oscillations. Finally, the parietal and mid-frontal cortices had strong coherence with the HC in both theta and beta2. These results highlight the importance of beta2 oscillations in a larger hippocampal-cortical circuit, suggesting that beta2 plays a role in the mechanism for detecting and modulating behavioral adaptation to novelty.

Delta-range coupling between prefrontal cortex and hippocampus supported by respiratory rhythmic input from the olfactory bulb in freely behaving rats

An explosion of recent findings firmly demonstrated that brain activity and cognitive function in rodents and humans are modulated synchronously with nasal respiration. Rhythmic respiratory (RR) coupling of wide-spread forebrain activity was confirmed using advanced techniques, including current source density analysis, single unit firing, and phase modulation of local gamma activity, creating solid premise for investigating how higher networks use this mechanism in their communication. Here we show essential differences in the way prefrontal cortex (PFC) and hippocampus (HC) process the RR signal from the olfactory bulb (OB) allowing dynamic PFC-HC coupling utilizing this input. We used inter-regional coherences and their correlations in rats, breathing at low rate (∼2 Hz) at rest, outside of the short sniffing bouts. We found strong and stable OB-PFC coherence, contrasting OB-HC coherence which was low but highly variable. PFC-HC coupling, however, primarily correlated with the latter, indicating that HC access to the PFC output is dynamically regulated by the responsiveness of HC to the common rhythmic drive. This pattern was present in both theta and non-theta states of waking, whereas PFC-HC communication appeared protected from RR synchronization in sleep states. The findings help to understand the mechanism of rhythmic modulation of non-olfactory cognitive processes by the on-going regular respiration, reported in rodents as well as humans. These mechanisms may be impaired when nasal breathing is limited or in OB-pathology, including malfunctions of the OB epithelium due to infections, such as in COVID-19.

Neuronal oscillations and the mouse prefrontal cortex

The mouse prefrontal cortex (PFC) encompasses a collection of agranual brain regions in the rostral neocortex and is considered to be critically involved in the neuronal computations underlying intentional behaviors. Flexible behavioral responses demand coordinated integration of sensory inputs with state, goal and memory information in brain-wide neuronal networks. Neuronal oscillations are proposed to provide a temporal scaffold for coordination of neuronal network activity and routing of information. In the present book chapter, we review findings on the role neuronal oscillations in prefrontal functioning, with a specific focus on research in mice. We discuss discoveries pertaining to local prefrontal processing, as well to interactions with other brain regions. We also discuss how the recent discovery of brain-wide respiration-entrained rhythms (RR) warrant re-evaluation of certain findings on slow oscillations (<10Hz) in prefrontal functioning.

The neuronal associations of respiratory-volume variability in the resting state

The desire to enhance the sensitivity and specificity of resting-state (rs-fMRI) measures has prompted substantial recent research into removing noise components. Chief among contributions to noise in rs-fMRI are physiological processes, and the neuronal implications of respiratory-volume variability (RVT), a main rs-fMRI-relevant physiological process, is incompletely understood. The potential implications of RVT in modulating and being modulated by autonomic nervous regulation, has yet to be fully understood by the rs-fMRI community. In this work, we use high-density electroencephalography (EEG) along with simultaneously acquired RVT recordings to help address this question. We hypothesize that (1) there is a significant relationship between EEG and RVT in multiple EEG bands, and (2) that this relationship varies by brain region. Our results confirm our first hypothesis, although all brain regions are shown to be equally implicated in RVT-related EEG-signal fluctuations. The lag between RVT and EEG is consistent with previously reported values. However, an interesting finding is related to the polarity of the correlation between RVT and EEG. Our results reveal potentially two main regimes of EEG-RVT association, one in which EEG leads RVT with a positive association between the two, and one in which RVT leads EEG but with a negative association between the two. We propose that these two patterns can be interpreted differently in terms of the involvement of higher cognition. These results further suggest that treating RVT simply as noise is likely a questionable practice, and that more work is needed to avoid discarding cognitively relevant information when performing physiological correction rs-fMRI.

Dance on the Brain: Enhancing Intra- and Inter-Brain Synchrony

Dance has traditionally been viewed from a Eurocentric perspective as a mode of self-expression that involves the human body moving through space, performed for the purposes of art, and viewed by an audience. In this Hypothesis and Theory article, we synthesize findings from anthropology, sociology, psychology, dance pedagogy, and neuroscience to propose The Synchronicity Hypothesis of Dance, which states that humans dance to enhance both intra- and inter-brain synchrony. We outline a neurocentric definition of dance, which suggests that dance involves neurobehavioral processes in seven distinct areas including sensory, motor, cognitive, social, emotional, rhythmic, and creative. We explore The Synchronicity Hypothesis of Dance through several avenues. First, we examine evolutionary theories of dance, which suggest that dance drives interpersonal coordination. Second, we examine fundamental movement patterns, which emerge throughout development and are omnipresent across cultures of the world. Third, we examine how each of the seven neurobehaviors increases intra- and inter-brain synchrony. Fourth, we examine the neuroimaging literature on dance to identify the brain regions most involved in and affected by dance. The findings presented here support our hypothesis that we engage in dance for the purpose of intrinsic reward, which as a result of dance-induced increases in neural synchrony, leads to enhanced interpersonal coordination. This hypothesis suggests that dance may be helpful to repattern oscillatory activity, leading to clinical improvements in autism spectrum disorder and other disorders with oscillatory activity impairments. Finally, we offer suggestions for future directions and discuss the idea that our consciousness can be redefined not just as an individual process but as a shared experience that we can positively influence by dancing together.

Modulation of recognition memory performance by light and its relationship with cortical EEG theta and gamma activities

Acute exposure to light exerts widespread effects on physiology, in addition to its key role in photoentrainment. Although the modulatory effect of light on physiological arousal is well demonstrated in mice, its effect on memory performance is inconclusive, as the direction of the effect depends on the nature of the behavioural task employed and/or the type of stimulus utilised. Moreover, in all rodent studies that reported significant effects of light on performance, brain activity was not assessed during the task and thus it is unclear how brain activity was modulated by light or the exact relationship between light-modulated brain activity and performance. Here we examine the modulatory effects of light of varying intensities on recognition memory performance and frontoparietal waking electroencephalography (EEG) in mice using the spontaneous recognition memory task. We report a light-intensity-dependent disruptive effect on recognition memory performance at the group level, but inspection of individual-level data indicates that light-intensity-dependent facilitation is observed in some cases. Using linear mixed-effects models, we then demonstrate that EEG fast theta (θ) activity at the time of encoding negatively predicts recognition memory performance, whereas slow gamma (γ) activity at the time of retrieval positively predicts performance. These relationships between θ/γ activity and performance are strengthened by increasing light intensity. Thus, light modulates θ and γ band activities involved in attentional and mnemonic processes, thereby affecting recognition memory performance. However, extraneous factors including the phase of the internal clock at which light is presented and homeostatic sleep pressure may determine how photic input is translated into behavioural performance.

Impact of Altered Breathing Patterns on Interaction of EEG and Heart Rate Variability

Background

Altered pattern of respiration has been shown to affect both the cardiac as well as cortical activity, which is the basis of central-autonomic dual interaction concept. On the other hand, effect of this association between altered breathing with slow cortical activity, that is, electroencephalography (EEG) theta waves (associated with learning and relaxed alertness) on the cardiac autonomic balance is largely unclear.

Objective

The study aims to understand this interaction in response to altered respiratory patterns, for example, voluntary apnea, bradypnea, and tachypnea in terms of EEG and heart rate variability (HRV) correlates in normal healthy subjects.

Methods

This study was conducted on 32 adult male subjects. EEG from F3, F4, P3, P4, O1 and O2 cortical areas and Lead II electrocardiography for HRV analysis was continuously recorded during aforesaid respiratory interventions. Power spectral analysis of EEG for theta waves and HRV measures, that is, RMSSD, pNN50, HF, LF, and LF/HF was calculated as % change taking resting value as 100%.

Results

Apnea caused decrease in theta power, whereas an increase in LF/HF was observed in HRV. Bradypnea on the other hand, did not elicit any significant change in power of theta waves. However, decreased RMSSD and pNN50 were observed in HRV. Tachypnea led to increase in theta power with HRV depicting significantly decreased RMSSD and pNN50. Besides, significant correlation between EEG and HRV measures was found during tachypnea, which shifted toward posterior cortical sites as compared to resting condition.

Conclusion

Various altered respiratory patterns caused either depressed parasympathetic or increased sympathetic output, whereas increased theta power along with posterior shift of correlation between theta power and HRV measures observed during post tachypnea might be due to involvement of global brain areas due to respiration-coupled neuronal activity. Thus, a definite link between cortical activity and autonomic output in relation to altered respiratory patterns may be suggested.

Layer 4 organization and respiration locking in the rodent nose somatosensory cortex

Rodents and other mammals acquire sensory information by precisely orchestrated head, whisker, and respiratory movements. We have, however, only limited information about integration of these signals. In the somatosensory domain, the integration of somatosensory information with other modalities is particularly pertinent for body parts such as eyes, ears, and nose, which serve another modality. Here we analyzed the nose/nostril representation in the rodent somatosensory cortex. We identified the representation of the nose/nostril in the rat somatosensory cortex by receptive field mapping and subsequent histological reconstruction. In tangential somatosensory cortical sections, the rat nostril cortex was evident as a prominent stripe-like recess of layer 4 revealed by cytochrome-c oxidase reactivity or by antibodies against the vesicular glutamate-transporter-2 (identifying thalamic afferents). We compared flattened somatosensory cortices of various rodents including rats, mice, gerbils, chinchillas, and chipmunks. We found that such a nose/nostril module was evident as a region with thinned or absent layer 4 at the expected somatotopic position of the nostril. Extracellular spike activity was strongly modulated by respiration in the rat somatosensory cortex, and field potential recordings revealed a stronger locking of nostril recording sites to respiration than for whisker/barrel cortex recoding sites. We conclude that the rodent nose/nostril representation has a conserved architecture and specifically interfaces with respiration signals.NEW & NOTEWORTHY We characterized the rodent nose somatosensory cortex. The nostril representation appeared as a kind of "hole" (i.e., as a stripe-like recess of layer 4) in tangential cortical sections. Neural activity in nose somatosensory cortex was locked to respiration, and simultaneous field recordings indicate that this locking was specific to this region. Our results reveal previously unknown cytoarchitectonic and physiological properties of the rodent nose somatosensory cortex, potentially enabling it to integrate multiple sensory modalities.

Portrait of visual cortical circuits for generating neural oscillation dynamics

The mouse primary visual cortex (V1) has emerged as a classical system to study neural circuit mechanisms underlying visual function and plasticity. A variety of efferent-afferent neuronal connections exists within the V1 and between the V1 and higher visual cortical areas or thalamic nuclei, indicating that the V1 system is more than a mere receiver in information processing. Sensory representations in the V1 are dynamically correlated with neural activity oscillations that are distributed across different cortical layers in an input-dependent manner. Circuits consisting of excitatory pyramidal cells (PCs) and inhibitory interneurons (INs) are the basis for generating neural oscillations. In general, INs are clustered with their adjacent PCs to form specific microcircuits that gate or filter the neural information. The interaction between these two cell populations has to be coordinated within a local circuit in order to preserve neural coding schemes and maintain excitation-inhibition (E-I) balance. Phasic alternations of the E-I balance can dynamically regulate temporal rhythms of neural oscillation. Accumulating experimental evidence suggests that the two major sub-types of INs, parvalbumin-expressing (PV⁺) cells and somatostatin-expressing (SOM⁺) INs, are active in controlling slow and fast oscillations, respectively, in the mouse V1. The review summarizes recent experimental findings on elucidating cellular or circuitry mechanisms for the generation of neural oscillations with distinct rhythms in either developing or matured mouse V1, mainly focusing on visual relaying circuits and distinct local inhibitory circuits.

A New Unifying Account of the Roles of Neuronal Entrainment

Rhythms are a fundamental and defining feature of neuronal activity in animals including humans. This rhythmic brain activity interacts in complex ways with rhythms in the internal and external environment through the phenomenon of 'neuronal entrainment', which is attracting increasing attention due to its suggested role in a multitude of sensory and cognitive processes. Some senses, such as touch and vision, sample the environment rhythmically, while others, like audition, are faced with mostly rhythmic inputs. Entrainment couples rhythmic brain activity to external and internal rhythmic events, serving fine-grained routing and modulation of external and internal signals across multiple spatial and temporal hierarchies. This interaction between a brain and its environment can be experimentally investigated and even modified by rhythmic sensory stimuli or invasive and non-invasive neuromodulation techniques. We provide a comprehensive overview of the topic and propose a theoretical framework of how neuronal entrainment dynamically structures information from incoming neuronal, bodily and environmental sources. We discuss the different types of neuronal entrainment, the conceptual advances in the field, and converging evidence for general principles.

Delta oscillations are a robust biomarker of dopamine depletion severity and motor dysfunction in awake mice

Delta oscillations (0.5-4 Hz) are a robust feature of basal ganglia pathophysiology in patients with Parkinson's disease (PD) in relationship to tremor, but their relationship to other parkinsonian symptoms has not been investigated. While delta oscillations have been observed in mouse models of PD, they have only been investigated in anesthetized animals, suggesting that the oscillations may be an anesthesia artifact and limiting the ability to relate them to motor symptoms. Here, we establish a novel approach to detect spike oscillations embedded in noise to provide the first study of delta oscillations in awake, dopamine-depleted mice. We find that approximately half of neurons in the substantia nigra pars reticulata (SNr) exhibit delta oscillations in dopamine depletion and that these oscillations are a strong indicator of dopamine loss and akinesia, outperforming measures such as changes in firing rate, irregularity, bursting, and synchrony. These oscillations are typically weakened, but not ablated, during movement. We further establish that these oscillations are caused by the loss of D2-receptor activation and do not originate from motor cortex, contrary to previous findings in anesthetized animals. Instead, SNr oscillations precede those in M1 at a 100- to 300-ms lag, and these neurons' relationship to M1 oscillations can be used as the basis for a novel classification of SNr into two subpopulations. These results give insight into how dopamine loss leads to motor dysfunction and suggest a reappraisal of delta oscillations as a marker of akinetic symptoms in PD.NEW & NOTEWORTHY This work introduces a novel method to detect spike oscillations amidst neural noise. Using this method, we demonstrate that delta oscillations in the basal ganglia are a defining feature of awake, dopamine-depleted mice and are strongly correlated with dopamine loss and parkinsonian motor symptoms. These oscillations arise from a loss of D2-receptor activation and do not require motor cortex. Similar oscillations in human patients may be an underappreciated marker and target for Parkinson's disease (PD) treatment.

Information Transfer in Linear Multivariate Processes Assessed through Penalized Regression Techniques: Validation and Application to Physiological Networks

The framework of information dynamics allows the dissection of the information processed in a network of multiple interacting dynamical systems into meaningful elements of computation that quantify the information generated in a target system, stored in it, transferred to it from one or more source systems, and modified in a synergistic or redundant way. The concepts of information transfer and modification have been recently formulated in the context of linear parametric modeling of vector stochastic processes, linking them to the notion of Granger causality and providing efficient tools for their computation based on the state-space (SS) representation of vector autoregressive (VAR) models. Despite their high computational reliability these tools still suffer from estimation problems which emerge, in the case of low ratio between data points available and the number of time series, when VAR identification is performed via the standard ordinary least squares (OLS). In this work we propose to replace the OLS with penalized regression performed through the Least Absolute Shrinkage and Selection Operator (LASSO), prior to computation of the measures of information transfer and information modification. First, simulating networks of several coupled Gaussian systems with complex interactions, we show that the LASSO regression allows, also in conditions of data paucity, to accurately reconstruct both the underlying network topology and the expected patterns of information transfer. Then we apply the proposed VAR-SS-LASSO approach to a challenging application context, i.e., the study of the physiological network of brain and peripheral interactions probed in humans under different conditions of rest and mental stress. Our results, which document the possibility to extract physiologically plausible patterns of interaction between the cardiovascular, respiratory and brain wave amplitudes, open the way to the use of our new analysis tools to explore the emerging field of Network Physiology in several practical applications.

Perspective on the Multiple Pathways to Changing Brain States

In this review article, we highlight several disparate ideas that are linked to changes in brain state (i.e., sleep to arousal, Down to Up, synchronized to de-synchronized). In any discussion of the brain state, we propose that the cortical pyramidal neuron has a central position. EEG recordings, which typically assess brain state, predominantly reflect the activity of cortical pyramidal neurons. This means that the dominant rhythmic activity that characterizes a particular brain state ultimately has to manifest globally across the pyramidal neuron population. During state transitions, it is the long-range connectivity of these neurons that broadcast the resultant changes in activity to many subcortical targets. Structures like the thalamus, brainstem/hypothalamic neuromodulatory systems, and respiratory systems can also strongly influence brain state, and for many decades we have been uncovering bidirectional pathways that link these structures to state changes in the cerebral cortex. More recently, movement and active behaviors have emerged as powerful drivers of state changes. Each of these systems involve different circuits distributed across the brain. Yet, for a system-wide change in brain state, there must be a collaboration between these circuits that reflects and perhaps triggers the transition between brain states. As we expand our understanding of how brain state changes, our current challenge is to understand how these diverse sets of circuits and pathways interact to produce the changes observed in cortical pyramidal neurons.

High-Frequency Cerebral Activation and Interhemispheric Synchronization Following Sudarshan Kriya Yoga as Global Brain Rhythms: The State Effects

Context:

Respiration is known to modulate neuronal oscillations in the brain and is measured by electroencephalogram (EEG). Sudarshan Kriya Yoga (SKY) is a popular breathing process and is established for its significant effects on the various aspects of physiology and psychology.

Aims:

This study aimed to observe neuronal oscillations in multifrequency bands and interhemispheric synchronization following SKY.

Settings and Design:

This study employed before- and after-study design.

Subjects and Methods:

Forty healthy volunteers (average age 25.45 ± 5.75, 23 males and 17 females) participated in the study. Nineteen-channel EEG was recorded and analyzed for 5 min each: before and after SKY. Spectral power for delta, theta, alpha, beta, and gamma frequency band was calculated using Multi-taper Fast Fourier Transform (Chronux toolbox). The Asymmetry Index was calculated by subtracting the natural log of powers of left (L) hemisphere from the right^® to show interhemispheric synchronization.

Statistical Analysis:

Paired t-test was used for statistical analysis.

Results:

Spectral power increased significantly in all frequency bands bilaterally in frontal, central, parietal, temporal, and occipital regions of the brain after long SKY. Electrical activity shifted from lower to higher frequency range with a significant rise in the gamma and beta powers following SKY. Asymmetry Index values tended toward 0 following SKY.

Conclusions:

A single session of SKY generates global brain rhythm dominantly with high-frequency cerebral activation and initiates appropriate interhemispheric synchronization in brain rhythms as state effects. This suggests that SKY leads to better attention, memory, and emotional and autonomic control along with enhanced cognitive functions, which finally improves physical and mental well-being.

Oscillations in the auditory system and their possible role

GOURÉVITCH, B., C. Martin, O. Postal, J.J. Eggermont. Oscillations in the auditory system, their possible role. NEUROSCI BIOBEHAV REV XXX XXX-XXX, 2020. - Neural oscillations are thought to have various roles in brain processing such as, attention modulation, neuronal communication, motor coordination, memory consolidation, decision-making, or feature binding. The role of oscillations in the auditory system is less clear, especially due to the large discrepancy between human and animal studies. Here we describe many methodological issues that confound the results of oscillation studies in the auditory field. Moreover, we discuss the relationship between neural entrainment and oscillations that remains unclear. Finally, we aim to identify which kind of oscillations could be specific or salient to the auditory areas and their processing. We suggest that the role of oscillations might dramatically differ between the primary auditory cortex and the more associative auditory areas. Despite the moderate presence of intrinsic low frequency oscillations in the primary auditory cortex, rhythmic components in the input seem crucial for auditory processing. This allows the phase entrainment between the oscillatory phase and rhythmic input, which is an integral part of stimulus selection within the auditory system.

Changing phase relationship of the stepping rhythm to neuronal oscillatory theta activity in the septo-hippocampal network of mice

Movement-related sensory and motor activity in the brain contributes to cognitive processes. We have observed that the frequency of stepping rhythm in head-fixed mice running on a jetball overlaps with the range of frequencies that characterize hippocampal rhythmic slow activity, including theta (~ 3 to 10 Hz). On average, step-cycle troughs (i.e. when the paw touches the ground) were weakly coupled to hippocampal theta oscillations. This weak coupling was sustained during a range of running speeds. In short temporal windows, step-cycle troughs were synchronous with hippocampal theta oscillatory cycle troughs, while during other periods they led or lagged behind theta cycles. Furthermore, simultaneously recorded theta rhythmic medial septal neurons in the basal forebrain were phase-coupled to both step-cycles and theta-cycles. We propose that the weak overall phase relationship of step-cycles with theta-cycles signifies a distinct mode of information processing. Transient synchronization of the step-cycle with theta may indicate the engagement of septo-hippocampal-entorhinal network with the current heading of the animal.

Learning improves decoding of odor identity with phase-referenced oscillations in the olfactory bulb

Local field potential oscillations reflect temporally coordinated neuronal ensembles-coupling distant brain regions, gating processing windows, and providing a reference for spike timing-based codes. In phase amplitude coupling (PAC), the amplitude of the envelope of a faster oscillation is larger within a phase window of a slower carrier wave. Here, we characterized PAC, and the related theta phase-referenced high gamma and beta power (PRP), in the olfactory bulb of mice learning to discriminate odorants. PAC changes throughout learning, and odorant-elicited changes in PRP increase for rewarded and decrease for unrewarded odorants. Contextual odorant identity (is the odorant rewarded?) can be decoded from peak PRP in animals proficient in odorant discrimination, but not in naïve mice. As the animal learns to discriminate the odorants the dimensionality of PRP decreases. Therefore, modulation of phase-referenced chunking of information in the course of learning plays a role in early sensory processing in olfaction.

Discovering Precise Temporal Patterns in Large-Scale Neural Recordings through Robust and Interpretable Time Warping

Though the temporal precision of neural computation has been studied intensively, a data-driven determination of this precision remains a fundamental challenge. Reproducible spike patterns may be obscured on single trials by uncontrolled temporal variability in behavior and cognition and may not be time locked to measurable signatures in behavior or local field potentials (LFP). To overcome these challenges, we describe a general-purpose time warping framework that reveals precise spike-time patterns in an unsupervised manner, even when these patterns are decoupled from behavior or are temporally stretched across single trials. We demonstrate this method across diverse systems: cued reaching in nonhuman primates, motor sequence production in rats, and olfaction in mice. This approach flexibly uncovers diverse dynamical firing patterns, including pulsatile responses to behavioral events, LFP-aligned oscillatory spiking, and even unanticipated patterns, such as 7 Hz oscillations in rat motor cortex that are not time locked to measured behaviors or LFP.

Hypothesis: Pulmonary Afferent Activity Patterns During Slow, Deep Breathing Contribute to the Neural Induction of Physiological Relaxation

Control of respiration provides a powerful voluntary portal to entrain and modulate central autonomic networks. Slowing and deepening breathing as a relaxation technique has shown promise in a variety of cardiorespiratory and stress-related disorders, but few studies have investigated the physiological mechanisms conferring its benefits. Recent evidence suggests that breathing at a frequency near 0.1 Hz (6 breaths per minute) promotes behavioral relaxation and baroreflex resonance effects that maximize heart rate variability. Breathing around this frequency appears to elicit resonant and coherent features in neuro-mechanical interactions that optimize physiological function. Here we explore the neurophysiology of slow, deep breathing and propose that coincident features of respiratory and baroreceptor afferent activity cycling at 0.1 Hz entrain central autonomic networks. An important role is assigned to the preferential recruitment of slowly-adapting pulmonary afferents (SARs) during prolonged inhalations. These afferents project to discrete areas in the brainstem within the nucleus of the solitary tract (NTS) and initiate inhibitory actions on downstream targets. Conversely, deep exhalations terminate SAR activity and activate arterial baroreceptors via increases in blood pressure to stimulate, through NTS projections, parasympathetic outflow to the heart. Reciprocal SAR and baroreceptor afferent-evoked actions combine to enhance sympathetic activity during inhalation and parasympathetic activity during exhalation, respectively. This leads to pronounced heart rate variability in phase with the respiratory cycle (respiratory sinus arrhythmia) and improved ventilation-perfusion matching. NTS relay neurons project extensively to areas of the central autonomic network to encode important features of the breathing pattern that may modulate anxiety, arousal, and attention. In our model, pronounced respiratory rhythms during slow, deep breathing also support expression of slow cortical rhythms to induce a functional state of alert relaxation, and, via nasal respiration-based actions on olfactory signaling, recruit hippocampal pathways to boost memory consolidation. Collectively, we assert that the neurophysiological processes recruited during slow, deep breathing enhance the cognitive and behavioral therapeutic outcomes obtained through various mind-body practices. Future studies are required to better understand the physio-behavioral processes involved, including in animal models that control for confounding factors such as expectancy biases.

Sleep architecture changes in the APP23 mouse model manifest at onset of cognitive deficits

Alzheimer's disease (AD), which accounts for most of the dementia cases, is, aside from cognitive deterioration, often characterized by the presence of non-cognitive symptoms such as activity and sleep disturbances. AD patients typically experience increased sleep fragmentation, excessive daytime sleepiness and night-time insomnia. Here, we sought to investigate the link between sleep architecture, cognition and amyloid pathology in the APP23 amyloidosis mouse model for AD. By means of polysomnographic recordings the sleep-wake cycle of freely-moving APP23 and wild-type (WT) littermates of 3, 6 and 12 months of age was examined. In addition, ambulatory cage activity was assessed by interruption of infrared beams surrounding the home cage. To assess visuo-spatial learning and memory a hidden-platform Morris-type Water Maze (MWM) experiment was performed. We found that sleep architecture is only slightly altered at early stages of pathology, but significantly deteriorates from 12 months of age, when amyloid plaques become diffusely present. APP23 mice of 12 months old had quantitative reductions of NREM and REM sleep and were more awake during the dark phase compared to WT littermates. These findings were confirmed by increased ambulatory cage activity during that phase of the light-dark cycle. No quantitative differences in sleep parameters were observed during the light phase. However, during this light phase, the sleep pattern of APP23 mice was more fragmented from 6 months of age, the point at which also cognitive abilities started to be affected in the MWM. Sleep time also positively correlated with MWM performance. We also found that spectral components in the EEG started to alter at the age of 6 months. To conclude, our results indicate that sleep architectural changes arise around the time the first amyloid plaques start to form and cognitive deterioration becomes apparent. These changes start subtle, but gradually worsen with age, adequately mimicking the clinical condition.

New Insights from 22-kHz Ultrasonic Vocalizations to Characterize Fear Responses: Relationship with Respiration and Brain Oscillatory Dynamics

Fear behavior depends on interactions between the medial prefrontal cortex (mPFC) and the basolateral amygdala (BLA), and the expression of fear involves synchronized activity in θ and γ oscillatory activities. In addition, freezing, the most classical measure of fear response in rodents, temporally coincides with the development of sustained 4-Hz oscillations in prefrontal-amygdala circuits. Interestingly, these oscillations were recently shown to depend on the animal’s respiratory rhythm, supporting the growing body of evidence pinpointing the influence of nasal breathing on brain rhythms. During fearful states, rats also emit 22-kHz ultrasonic vocalizations (USVs) which drastically affect respiratory rhythm. However, the relationship between 22-kHz USV, respiration, and brain oscillatory activities is still unknown. Yet such information is crucial for a comprehensive understanding of how the different components of fear response collectively modulate rat’s brain neural dynamics. Here, we trained male rats in an odor fear conditioning task, while recording simultaneously local field potentials (LFPs) in BLA, mPFC, and olfactory piriform cortex (PIR), together with USV calls and respiration. We show that USV calls coincide with an increase in delta and gamma power and a decrease in theta power. In addition, during USV emission in contrast to silent freezing, there is no coupling between respiratory rate and delta frequency, and the modulation of fast oscillations amplitude relative to the phase of respiration is modified. We propose that sequences of USV calls could result in a differential gating of information within the network of structures sustaining fear behavior, thus potentially modulating fear expression/memory.

Coordinated electrical activity in the olfactory bulb gates the oscillatory entrainment of entorhinal networks in neonatal mice

Although the developmental principles of sensory and cognitive processing have been extensively investigated, their synergy has been largely neglected. During early life, most sensory systems are still largely immature. As a notable exception, the olfactory system is functional at birth, controlling mother–offspring interactions and neonatal survival. Here, we elucidate the structural and functional principles underlying the communication between olfactory bulb (OB) and lateral entorhinal cortex (LEC)—the gatekeeper of limbic circuitry—during neonatal development. Combining optogenetics, pharmacology, and electrophysiology in vivo with axonal tracing, we show that mitral cell–dependent discontinuous theta bursts in OB drive network oscillations and time the firing in LEC of anesthetized mice via axonal projections confined to upper cortical layers. Acute pharmacological silencing of OB activity diminishes entorhinal oscillations, whereas odor exposure boosts OB–entorhinal coupling at fast frequencies. Chronic impairment of olfactory sensory neurons disrupts OB–entorhinal activity. Thus, OB activity shapes the maturation of entorhinal circuits.

Cognitive performance is maximized only through permanent interactions with the environment, yet the contribution of sensory stimuli to cognitive processing has been largely neglected. This is especially true when considering the maturation of limbic circuits accounting for memory and executive abilities. Rodents are blind and deaf, do not whisker, and have limited motor abilities during the first days of life, and therefore, the contribution of sensory inputs to limbic ontogeny has been deemed negligible. As a notable exception, olfactory inputs are processed already early in life and might shape the limbic development. To test this hypothesis, we investigate the principles of communication between the olfactory bulb (OB), the first processing station of olfactory inputs, and lateral entorhinal cortex (LEC)—the gatekeeper of limbic circuits centered on hippocampus and prefrontal cortex—of mice during the first and second postnatal weeks. We show that spontaneously generated patterns of electrical activity in the OB activate the entorhinal circuits via mono- and polysynaptic axonal projections. The activity within the circuitry connecting the OB to the LEC is boosted by odors and disrupted by chronic lesion of the olfactory periphery. Thus, spontaneous and stimulus-induced activity in the OB controls the maturation of neuronal networks in the LEC.

Social isolation impairs the persistence of social recognition memory by disturbing the glutamatergic tonus and the olfactory bulb-dorsal hippocampus coupling

The absence of companion may jeopardize mental health in social animals. Here, we tested the hypothesis that social isolation impairs social recognition memory by altering the excitability and the dialog between the olfactory bulb (OB) and the dorsal hippocampus (dHIP). Adult male Swiss mice were kept grouped (GH) or isolated (SI) for 7 days. Social memory (LTM) was evaluated using social recognition test. SI increased glutamate release in the OB, while decreased in the dHIP. Blocking AMPA and NMDA receptors into the OB or activating AMPA into the dHIP rescued LTM in SI mice, suggesting a cause-effect relationship between glutamate levels and LTM impairment. Additionally, during memory retrieval, phase-amplitude coupling between OB and dHIP decreased in SI mice. Our results indicate that SI impaired the glutamatergic signaling and the normal communication between OB and HIP, compromising the persistence of social memory.

Augmentation of Whole-Body Metabolic Status by Mind-Body Training: Synchronous Integration of Tissue- and Organ-Specific Mitochondrial Function

The objective of our concise review is to elaborate an evidence-based integrative medicine model that incorporates functional linkages of key aspects of cortically-driven mind-body training procedures to biochemical and molecular processes driving enhanced cellular bioenergetics and whole-body metabolic advantage. This entails the adoption of a unified biological systems approach to selectively elucidate basic biochemical and molecular events responsible for achieving physiological relaxation of complex cellular structures. We provide accumulated evidence in support of the potential synergy of voluntary breathing exercises in combination with meditation and/or complementary cognitive tasks to promote medically beneficial enhancements in whole-body relaxation, anti-stress mechanisms, and restorative sleep. Accordingly, we propose that the widespread metabolic and physiological advantages emanating from a sustained series of complementary mind-body exercises will ultimately engender enhanced functional integration of cortical and limbic areas controlling voluntary respiratory processes with autonomic brainstem neural pattern generators. Finally, a unified mechanism is proposed that links behaviorally-mediated enhancements of whole-body metabolic advantage to optimization of synchronous regulation of mitochondrial oxygen utilization via recycling of nitrite and nitric oxide by iron-sulfur centers of coupled respiratory complexes and nitrite reductases.

Nasal Respiration is Necessary for the Generation of γ Oscillation in the Olfactory Bulb

γ oscillations (30-120 Hz) are generated intrinsically within local networks in the mammalian olfactory bulb (OB). The OB directly receives peripheral input from olfactory sensory neurons (OSNs) that can respond to nasal airflow, and centrifugal input from neuromodulatory systems whose activities are affected by the behavioral states of animal. How peripheral and centrifugal input dynamically modulate γ oscillations is unclear. By simultaneously recording respiration signal and local field potentials (LFPs) in the OB of freely moving mice throughout at least one sleep-wake cycle, we observed that γ oscillations were highest during awake exploratory (AE) state, and successively lower during awake resting (AR) state, rapid eye movement (REM) and non-REM (NREM) sleep. γ activity was further enhanced when animals were exposed to stress condition, which indicated that behavioral states may modulate γ oscillations. Moreover, γ amplitude was phase-locked to respiration-entrained rhythms (RR). RR-high γ (55-120 Hz) coupling strength was strongest during AR state, while RR-low γ (30-55 Hz) coupling strength was strongest during REM sleep. However, in the absence of nasal respiratory input, γ oscillations dramatically decreased or disappeared, and γ power was no longer modulated by behavioral states. Conversely, hippocampal γ oscillations were not altered by nasal respiratory input. These results reveal that nasal respiratory input is necessary for the generation and modulation of γ oscillations in the OB, suggesting that nasal respiration may modulate neural activity and further influence olfactory function.

Defining the Rhythmogenic Elements of Mammalian Breathing

Breathing's remarkable ability to adapt to changes in metabolic, environmental, and behavioral demands stems from a complex integration of its rhythm-generating network within the wider nervous system. Yet, this integration complicates identification of its specific rhythmogenic elements. Based on principles learned from smaller rhythmic networks of invertebrates, we define criteria that identify rhythmogenic elements of the mammalian breathing network and discuss how they interact to produce robust, dynamic breathing.

Subunit-specific NMDAR antagonism dissociates schizophrenia subtype-relevant oscillopathies associated with frontal hypofunction and hippocampal hyperfunction

NMDAR antagonism alters mesolimbic, hippocampal, and cortical function, acutely reproducing the positive, cognitive, and negative symptoms of schizophrenia. These physiological and behavioral effects may depend differentially on NMDAR subtype- and region-specific effects. The dramatic electrophysiological signatures of NMDAR blockade in rodents include potentiated high frequency oscillations (HFOs, ∼140 Hz), likely generated in mesolimbic structures, and increased HFO phase-amplitude coupling (PAC), a phenomenon related to goal-directed behavior and dopaminergic tone. This study examined the impact of subtype-specific NMDAR antagonism on HFOs and PAC. We found that positive-symptom-associated NR2A-preferring antagonism (NVP-AAM077), but not NR2B-specific antagonism (Ro25-6985) or saline control, replicated increases in HFO power seen with nonspecific antagonism (MK-801). However, PAC following NR2A-preferring antagonism was distinct from all other conditions. While θ-HFO PAC was prominent or potentiated in other conditions, NVP-AAM077 increased δ-HFO PAC and decreased θ-HFO PAC. Furthermore, active wake epochs exhibiting narrowband frontal δ oscillations, and not broadband sleep-associated δ, selectively exhibited δ-HFO coupling, while paradoxical sleep epochs having a high CA1 θ to frontal δ ratio selectively exhibited θ-HFO coupling. Our results suggest: (1) NR2A-preferring antagonism induces oscillopathies reflecting frontal hyperfunction and hippocampal hypofunction; and (2) HFO PAC indexes cortical vs. hippocampal control of mesolimbic circuits.

Local cortical activity of distant brain areas can phase-lock to the olfactory bulb's respiratory rhythm in the freely behaving rat

An important unresolved question about neural processing is the mechanism by which distant brain areas coordinate their activities and relate their local processing to global neural events. A potential candidate for the local-global integration are slow rhythms such as respiration. In this study, we asked if there are modulations of local cortical processing that are phase-locked to (peripheral) sensory-motor exploratory rhythms. We studied rats on an elevated platform where they would spontaneously display exploratory and rest behaviors. Concurrent with behavior, we monitored whisking through electromyography and the respiratory rhythm from the olfactory bulb (OB) local field potential (LFP). We also recorded LFPs from dorsal hippocampus, primary motor cortex, primary somatosensory cortex, and primary visual cortex. We defined exploration as simultaneous whisking and sniffing above 5 Hz and found that this activity peaked at ~8 Hz. We considered rest as the absence of whisking and sniffing, and in this case, respiration occurred at ~3 Hz. We found a consistent shift across all areas toward these rhythm peaks accompanying behavioral changes. We also found, across areas, that LFP gamma (70-100 Hz) amplitude could phase-lock to the animal's OB respiratory rhythm, a finding indicative of respiration-locked changes in local processing. In a subset of animals, we also recorded the hippocampal theta activity and found that occurred at frequencies overlapped with respiration but was not spectrally coherent with it, suggesting a different oscillator. Our results are consistent with the notion of respiration as a binder or integrator of activity between brain regions.