Theta-gamma coupling during REM sleep depends on breathing rate

SLEEP ◽  
2021 ◽  
Author(s):  
Maximilian Hammer ◽  
Chrysovalandis Schwale ◽  
Jurij Brankačk ◽  
Andreas Draguhn ◽  
Adriano B L Tort
Keyword(s):  
Rem Sleep ◽  
Large Scale ◽  
Brain Activity ◽  
Gamma Oscillations ◽  
Network Activity ◽  
Breathing Rate ◽  
Nasal Breathing ◽  
Rate Dependent ◽  
Temporal Coupling ◽  
Scale Integration

Abstract 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.

scholarly journals Theta-gamma coupling depends on breathing rate

2020 ◽  
Author(s):  
Maximilian Hammer ◽  
Chrysovalandis Schwale ◽  
Jurij Brankačk ◽  
Andreas Draguhn ◽  
Adriano BL Tort
Keyword(s):  
Large Scale ◽  
Brain Activity ◽  
Gamma Oscillations ◽  
Network Activity ◽  
Breathing Rate ◽  
Nasal Breathing ◽  
Rate Dependent ◽  
Large Scale Integration ◽  
Temporal Coupling ◽  
Scale Integration

AbstractTemporal 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.

scholarly journals Causal relations between cortical network oscillations and breathing frequency

2020 ◽  
Author(s):  
Adriano BL Tort ◽  
Maximilian Hammer ◽  
Jiaojiao Zhang ◽  
Jurij Brankačk ◽  
Andreas Draguhn
Keyword(s):  
Parietal Cortex ◽  
Instantaneous Frequency ◽  
Time Scale ◽  
Brain Activity ◽  
Gamma Oscillations ◽  
Cortical Network ◽  
Breathing Rate ◽  
Breathing Frequency ◽  
Nasal Breathing ◽  
Network Oscillations

AbstractNasal 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 causal 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 theta and gamma oscillations while behavioral activity is minimal, reducing confounding signals. We found that the instantaneous breathing rate strongly correlates with the instantaneous frequency and amplitude of both theta and gamma oscillations. Granger causality analysis revealed specific directionalities for different rhythms: changes in theta activity precede and cause changes in breathing rate, suggesting control of breathing frequency by the functional state of the brain. On the other hand, the instantaneous breathing rate Granger-causes changes in gamma oscillations, suggesting that gamma is influenced by a peripheral reafference signal. These findings show that breathing causally relates to different patterns of rhythmic brain activity, revealing new and complex interactions between elementary physiological functions and neuronal information processing.Significance StatementThe study of the interactions between respiration and brain activity has been focused on phase-entrainment relations, in which cortical networks oscillate phase-locked to breathing cycles. Here we discovered new and much broader interactions which link respiration rate (frequency) to different patterns of oscillatory brain activity. Specifically, we show that the instantaneous breathing rate strongly correlates with the instantaneous frequency and amplitude of theta and gamma oscillations, two major network patterns associated with cognitive functions. Interestingly, causality analyses reveal that changes in breathing rate follow theta, suggesting a central drive, while in contrast, gamma activity follows changes in breathing rate, suggesting the role of a reafferent signal. Our results reveal new mechanisms by which nasal breathing patterns may influence brain functions.

scholarly journals Orientation and color tuning of the human visual gamma rhythm

2021 ◽  
Author(s):  
Ye Li ◽  
William Bosking ◽  
Michael S Beauchamp ◽  
Sameer A Sheth ◽  
Daniel Yoshor ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Brain Activity ◽  
Population Level ◽  
Gamma Oscillations ◽  
Cell Orientation ◽  
Population Activity ◽  
Color Tuning ◽  
Human Visual Cortex ◽  
Gamma Rhythm

Narrowband gamma oscillations (NBG: ~20-60Hz) in visual cortex reflect rhythmic fluctuations in population activity generated by underlying circuits tuned for stimulus location, orientation, and color. Consequently, the amplitude and frequency of induced NBG activity is highly sensitive to these stimulus features. For example, in the non-human primate, NBG displays biases in orientation and color tuning at the population level. Such biases may relate to recent reports describing the large-scale organization of single-cell orientation and color tuning in visual cortex, thus providing a potential bridge between measurements made at different scales. Similar biases in NBG population tuning have been predicted to exist in the human visual cortex, but this has yet to be fully examined. Using intracranial recordings from human visual cortex, we investigated the tuning of NBG to orientation and color, both independently and in conjunction. NBG was shown to display a cardinal orientation bias (horizontal) and also an end- and mid-spectral color bias (red/blue and green). When jointly probed, the cardinal bias for orientation was attenuated and an end-spectral preference for red and blue predominated. These data both elaborate on the close, yet complex, link between the population dynamics driving NBG oscillations and known feature selectivity biases in visual cortex, adding to a growing set of stimulus dependencies associated with the genesis of NBG. Together, these two factors may provide a fruitful testing ground for examining multi-scale models of brain activity, and impose new constraints on the functional significance of the visual gamma rhythm.

scholarly journals GABA-Glutamate supramammillary neurons control theta and gamma oscillations in the dentate gyrus during paradoxical (REM) sleep

2019 ◽  
Author(s):  
Francesca Billwiller ◽  
Laura Castillo ◽  
Heba Elseedy ◽  
Anton Ivanovich Ivanov ◽  
Jennyfer Scapula ◽  
...  
Keyword(s):  
Dentate Gyrus ◽  
Rem Sleep ◽  
Slow Wave Sleep ◽  
Granule Cells ◽  
Structural Connectivity ◽  
Gamma Oscillations ◽  
Network Activity ◽  
Projection Neurons ◽  
Theta Power ◽  
Gamma Power

AbstractSeveral studies suggest that neurons from the lateral region of the SuM (SuML) innervating the dorsal dentate gyrus (DG) display a dual GABAergic and glutamatergic transmission and are specifically activated during paradoxical (REM) sleep (PS). The objective of the present study is to fully characterize the anatomical, neurochemical and electrophysiological properties of the SuML-DG projection neurons and to determine how they control DG oscillations and neuronal activation during PS and other vigilance states. For this purpose, we combine structural connectivity techniques using neurotropic viral vectors (rabies virus, AAV), neurochemical anatomy (immunohistochemistry, in situ hybridization) and imaging (light, electron and confocal microscopy) with in vitro (patch clamp) and in vivo (LFP, EEG) optogenetic and electrophysiological recordings performed in transgenic VGLUT2-cre male mice. At the cellular level, we show that the SuML-DG neurons co-release GABA and glutamate on dentate granule cells and increase the activity of a subset of DG granule cells. At the network level, we show that activation of the SuML-DG pathway increases theta power and frequency during PS as well as gamma power during PS and waking in the DG. At the behavioral level, we show that the activation of this pathway does not change animal behavior during PS, induces awakening during slow wave sleep and increases motor activity during waking. These results suggest that the SuML-DG pathway is capable of supporting the increase of theta and gamma power in the DG observed during PS and plays an important modulatory role of DG network activity during this state.Significant statementAn increase of theta and gamma power in the dentate gyrus (DG) is an hallmark of paradoxical (REM) sleep (PS) and is suggested to promote learning and memory consolidation by synchronizing hippocampal networks and increasing its outputs to cortical targets. However the neuronal networks involved in such control of DG activity during PS are poorly understood. The present study identifies a population of GABA/Glutamate neurons in the lateral supramammllary nucleus (SuML) innervating the DG that could support such control during PS. Indeed, we show that activation of these SuML-DG projections increase theta power and frequency as well as gamma power in the DG specifically during PS and modulate activity of a subset of DG granule cells.

scholarly journals GABA–glutamate supramammillary neurons control theta and gamma oscillations in the dentate gyrus during paradoxical (REM) sleep

2020 ◽  
Vol 225 (9) ◽  
pp. 2643-2668 ◽  
Author(s):  
Francesca Billwiller ◽  
Laura Castillo ◽  
Heba Elseedy ◽  
Anton Ivanovich Ivanov ◽  
Jennyfer Scapula ◽  
...  
Keyword(s):  
Dentate Gyrus ◽  
Rem Sleep ◽  
Slow Wave Sleep ◽  
Granule Cells ◽  
Structural Connectivity ◽  
Gamma Oscillations ◽  
Network Activity ◽  
Projection Neurons ◽  
Gamma Power

AbstractSeveral studies suggest that neurons from the lateral region of the SuM (SuML) innervating the dorsal dentate gyrus (DG) display a dual GABAergic and glutamatergic transmission and are specifically activated during paradoxical (REM) sleep (PS). The objective of the present study is to characterize the anatomical, neurochemical and electrophysiological properties of the SuML-DG projection neurons and to determine how they control DG oscillations and neuronal activation during PS and other vigilance states. For this purpose, we combine structural connectivity techniques using neurotropic viral vectors (rabies virus, AAV), neurochemical anatomy (immunohistochemistry, in situ hybridization) and imaging (light, electron and confocal microscopy) with in vitro (patch clamp) and in vivo (LFP, EEG) optogenetic and electrophysiological recordings performed in transgenic VGLUT2-cre male mice. At the cellular level, we show that the SuML-DG neurons co-release GABA and glutamate on dentate granule cells and increase the activity of a subset of DG granule cells. At the network level, we show that activation of the SuML-DG pathway increases theta power and frequency during PS as well as gamma power during PS and waking in the DG. At the behavioral level, we show that the activation of this pathway does not change animal behavior during PS, induces awakening during slow wave sleep and increases motor activity during waking. These results suggest that the SuML-DG pathway is capable of supporting the increase of theta and gamma power in the DG observed during PS and plays an important modulatory role of DG network activity during this state.

scholarly journals Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms

2019 ◽  
Author(s):  
Jessica S. Flannery ◽  
Michael C. Riedel ◽  
Katherine L. Bottenhorn ◽  
Ranjita Poudel ◽  
Taylor Salo ◽  
...  
Keyword(s):  
Large Scale ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Network ◽  
Reward Processing ◽  
Network Activity ◽  
Reward Learning ◽  
Learning Theories ◽  
Behavior Profiles

ABSTRACTReward learning is a ubiquitous cognitive mechanism guiding adaptive choices and behaviors, and when impaired, can lead to considerable mental health consequences. Reward-related functional neuroimaging studies have begun to implicate networks of brain regions essential for processing various peripheral influences (e.g., risk, subjective preference, delay, social context) involved in the multifaceted reward processing construct. To provide a more complete neurocognitive perspective on reward processing that synthesizes findings across the literature while also appreciating these peripheral influences, we utilized emerging meta-analytic techniques to elucidate brain regions, and in turn networks, consistently engaged in distinct aspects of reward processing. Using a data-driven, meta-analytic, k-means clustering approach, we dissociated seven meta-analytic groupings (MAGs) of neuroimaging results (i.e., brain activity maps) from 749 experimental contrasts across 176 reward processing studies involving 13,358 healthy participants. We then performed an exploratory functional decoding approach to gain insight into the putative functions associated with each MAG. We identified a seven-MAG clustering solution which represented dissociable patterns of convergent brain activity across reward processing tasks. Additionally, our functional decoding analyses revealed that each of these MAGs mapped onto discrete behavior profiles that suggested specialized roles in predicting value (MAG-1 & MAG-2) and processing a variety of emotional (MAG-3), external (MAG-4 & MAG-5), and internal (MAG-6 & MAG-7) influences across reward processing paradigms. These findings support and extend aspects of well-accepted reward learning theories and highlight large-scale brain network activity associated with distinct aspects of reward processing.

scholarly journals The cross-frequency mediation mechanism of intracortical information transactions

2017 ◽  
Author(s):  
RD Pascual-Marqui ◽  
P Faber ◽  
S Ikeda ◽  
R Ishii ◽  
T Kinoshita ◽  
...  
Keyword(s):  
Large Scale ◽  
Gamma Oscillations ◽  
Mediation Effect ◽  
Coupling Coefficients ◽  
Dual Frequency ◽  
Alpha Oscillations ◽  
The Cross ◽  
Statistical Mediation Analysis ◽  
Cortical Regions ◽  
Scale Integration

1. AbstractIn a seminal paper by von Stein and Sarnthein (2000), it was hypothesized that “bottom-up” information processing of “content” elicits local, high frequency (beta-gamma) oscillations, whereas “top-down” processing is “contextual”, characterized by large scale integration spanning distant cortical regions, and implemented by slower frequency (theta-alpha) oscillations. This corresponds to a mechanism of cortical information transactions, where synchronization of beta-gamma oscillations between distant cortical regions is mediated by widespread theta-alpha oscillations. It is the aim of this paper to express this hypothesis quantitatively, in terms of a model that will allow testing this type of information transaction mechanism. The basic methodology used here corresponds to statistical mediation analysis, originally developed by (Baron and Kenny 1986). We generalize the classical mediator model to the case of multivariate complex-valued data, consisting of the discrete Fourier transform coefficients of signals of electric neuronal activity, at different frequencies, and at different cortical locations. The “mediation effect” is quantified here in a novel way, as the product of “dual frequency RV-coupling coefficients”, that were introduced in (Pascual-Marqui et al 2016, http://arxiv.org/abs/1603.05343). Relevant statistical procedures are presented for testing the cross-frequency mediation mechanism in general, and in particular for testing the von Stein & Sarnthein hypothesis.

scholarly journals Local Perturbations of Cortical Excitability Propagate Differentially Through Large-Scale Functional Networks

2020 ◽  
Vol 30 (5) ◽  
pp. 3352-3369 ◽  
Author(s):  
Zachary P Rosenthal ◽  
Ryan V Raut ◽  
Ping Yan ◽  
Deima Koko ◽  
Andrew W Kraft ◽  
...  
Keyword(s):  
Large Scale ◽  
Cortical Excitability ◽  
Brain Activity ◽  
Field Potential ◽  
Brain Network ◽  
Network Activity ◽  
Wide Field ◽  
Activity Levels ◽  
Electrophysiological Recordings ◽  
Parvalbumin Interneuron

Abstract Electrophysiological recordings have established that GABAergic interneurons regulate excitability, plasticity, and computational function within local neural circuits. Importantly, GABAergic inhibition is focally disrupted around sites of brain injury. However, it remains unclear whether focal imbalances in inhibition/excitation lead to widespread changes in brain activity. Here, we test the hypothesis that focal perturbations in excitability disrupt large-scale brain network dynamics. We used viral chemogenetics in mice to reversibly manipulate parvalbumin interneuron (PV-IN) activity levels in whisker barrel somatosensory cortex. We then assessed how this imbalance affects cortical network activity in awake mice using wide-field optical neuroimaging of pyramidal neuron GCaMP dynamics as well as local field potential recordings. We report 1) that local changes in excitability can cause remote, network-wide effects, 2) that these effects propagate differentially through intra- and interhemispheric connections, and 3) that chemogenetic constructs can induce plasticity in cortical excitability and functional connectivity. These findings may help to explain how focal activity changes following injury lead to widespread network dysfunction.

Brain activity and temporal coupling related to eye movements during REM sleep: EEG and MEG results

2008 ◽  
Vol 1235 ◽  
pp. 82-91 ◽  
Author(s):  
María Corsi-Cabrera ◽  
Miguel Angel Guevara ◽  
Yolanda del Río-Portilla
Keyword(s):  
Eye Movements ◽  
Rem Sleep ◽  
Brain Activity ◽  
Sleep Eeg ◽  
Temporal Coupling

scholarly journals Exploring Frequency-dependent Brain Networks from ongoing EEG using Spatial ICA during music listening

2019 ◽  
Author(s):  
Yongjie Zhu ◽  
Chi Zhang ◽  
Petri Toiviainen ◽  
Minna Huotilainen ◽  
Klaus Mathiak ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Activity ◽  
Brain Networks ◽  
Brain Network ◽  
Network Activity ◽  
Sensor Data ◽  
Frequency Dependent ◽  
Feature Processing ◽  
Ongoing Eeg ◽  
Musical Feature

AbstractRecently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during free-listening to music. We used a data-driven method that combined music information retrieval with spatial Independent Components Analysis (ICA) to probe the interplay between the spatial profiles and the spectral patterns. We projected the sensor data into cortical space using a minimum-norm estimate and applied the Short Time Fourier Transform (STFT) to obtain frequency information. Then, spatial ICA was made to extract spatial-spectral-temporal information of brain activity in source space and five long-term musical features were computationally extracted from the naturalistic stimuli. The spatial profiles of the components whose temporal courses were significantly correlated with musical feature time series were clustered to identify reproducible brain networks across the participants. Using the proposed approach, we found brain networks of musical feature processing are frequency-dependent and three plausible frequency-dependent networks were identified; the proposed method seems valuable for characterizing the large-scale frequency-dependent brain activity engaged in musical feature processing.

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