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.

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 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.

Plant hormones, plant growth regulators

2014 ◽  
Vol 155 (26) ◽  
pp. 1011-1018 ◽  
Author(s):  
György Végvári ◽  
Edina Vidéki
Keyword(s):  
Nervous System ◽  
Growth And Development ◽  
Large Scale ◽  
Essential Role ◽  
Higher Plants ◽  
Structure And Function ◽  
Wide Sense ◽  
Large Scale Integration ◽  
Scale Integration ◽  
And Function

Plants seem to be rather defenceless, they are unable to do motion, have no nervous system or immune system unlike animals. Besides this, plants do have hormones, though these substances are produced not in glands. In view of their complexity they lagged behind animals, however, plant organisms show large scale integration in their structure and function. In higher plants, such as in animals, the intercellular communication is fulfilled through chemical messengers. These specific compounds in plants are called phytohormones, or in a wide sense, bioregulators. Even a small quantity of these endogenous organic compounds are able to regulate the operation, growth and development of higher plants, and keep the connection between cells, tissues and synergy beween organs. Since they do not have nervous and immume systems, phytohormones play essential role in plants’ life. Orv. Hetil., 2014, 155(26), 1011–1018.

Behavior Models of Voltage Differencing Inverting Buffered Amplifier and Applications in Circuit Analysis

2019 ◽  
Vol 12 (4) ◽  
pp. 298-303
Author(s):  
YongAn LI
Keyword(s):  
Large Scale ◽  
Vlsi Design ◽  
Circuit Analysis ◽  
Second Order ◽  
Very Large Scale Integration ◽  
Behavioral Models ◽  
Order Filter ◽  
Large Scale Integration ◽  
Scale Integration ◽  
Behavior Models

Background: The symbolic nodal analysis acts as a pivotal part of the very large scale integration (VLSI) design. Methods: In this work, based on the terminal relations for the pathological elements and the voltage differencing inverting buffered amplifier (VDIBA), twelve alternative pathological models for the VDIBA are presented. Moreover, the proposed models are applied to the VDIBA-based second-order filter and oscillator so as to simplify the circuit analysis. Results: The result shows that the behavioral models for the VDIBA are systematic, effective and powerful in the symbolic nodal circuit analysis.</P>

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