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.

EVOKED OSCILLATIONS AND EARLY COMPONENTS OF EVENT-RELATED POTENTIALS: AN ANALYSIS

2004 ◽  
Vol 14 (02) ◽  
pp. 705-718 ◽  
Author(s):  
WOLFGANG KLIMESCH ◽  
MANUEL SCHABUS ◽  
MICHAEL DOPPELMAYR ◽  
WALTER GRUBER ◽  
PAUL SAUSENG
Keyword(s):  
Working Memory ◽  
Large Scale ◽  
Event Related Potentials ◽  
Theoretical Framework ◽  
Network Systems ◽  
General Hypothesis ◽  
Alpha Oscillations ◽  
Related Potentials ◽  
Individual Alpha Frequency ◽  
Scale Integration

In the present work, we provide new arguments and data indicating that early ERP components are generated at least in part by evoked theta and alpha oscillations. We proceed from the general hypothesis, originally proposed by Erol Basar that ERP's are generated by a superposition of evoked oscillations with different frequencies. Based on findings about event-related desynchronization/synchronization (ERD/ERS), we analyze the following specific hypotheses. If evoked theta and alpha oscillations contribute to the generation of ERP components and if their functional role, type of reactivity and frequency specificity are similar to those of event-related oscillations (measured by ERD/ERS), we expect (i) to see the same functional relationship between frequency and cognitive processes, (ii) the same type of "reactivity" and a (iii) dependency of latency measures of evoked components on IAF. By reviewing respective data, we demonstrate that similar to research about event-related oscillations, evoked alpha reflects attention, whereas evoked theta reflects working memory processes. Furthermore, it was found that individual alpha frequency (IAF) has a significant influence on P1 latency in particular. For a better understanding of these findings, we outline a new theoretical framework. We assume that the P1–N1 complex is generated by an interplay between the synchronous activation of three neuronal network systems, a working memory, attentional, and semantic memory system, each operating with a different frequency, the first in the theta (about 6 Hz), the second in the lower alpha (about 8 Hz) and the third in the upper alpha (about 12 Hz) frequency range. The implications of this theoretical framework are discussed by reviewing research using phase sensitive measures to analyze "local" and "large scale" integration processes between different neural networks.

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.

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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