scholarly journals The Temporal Dynamics of EEG Microstate Reveals the Neuromodulation Effect of Acupuncture With Deqi

2021 ◽  
Vol 15 ◽  
Author(s):  
Xiaopeng Si ◽  
Shunli Han ◽  
Kuo Zhang ◽  
Ludan Zhang ◽  
Yulin Sun ◽  
...  
Keyword(s):  
Human Brain ◽  
Temporal Dynamics ◽  
Transition Probabilities ◽  
Transition Probability ◽  
Therapeutic Effects ◽  
Dynamic Feature ◽  
Correlation Relationship ◽  
External Stimulation ◽  
Positive Correlation ◽  
Mapping Tool

The electroencephalography (EEG) microstate has recently emerged as a new whole-brain mapping tool for studying the temporal dynamics of the human brain. Meanwhile, the neuromodulation effect of external stimulation on the human brain is of increasing interest to neuroscientists. Acupuncture, which originated in ancient China, is recognized as an external neuromodulation method with therapeutic effects. Effective acupuncture could elicit the deqi effect, which is a combination of multiple sensations. However, whether the EEG microstate could be used to reveal the neuromodulation effect of acupuncture with deqi remains largely unclear. In this study, multichannel EEG data were recorded from 16 healthy subjects during acupuncture manipulation, as well as during pre- and post-manipulation tactile controls and pre- and post-acupuncture rest controls. As the basic acupuncture unit for regulating the central nervous system, the Hegu acupoint was used in this study, and each subject’s acupuncture deqi behavior scores were collected. To reveal the neuroimaging evidence of acupuncture with deqi, EEG microstate analysis was conducted to obtain the microstate maps and microstate parameters for different conditions. Furthermore, Pearson’s correlation was analyzed to investigate the correlation relationship between microstate parameters and deqi behavioral scores. Results showed that: (1) compared with tactile controls, acupuncture manipulation caused significantly increased deqi behavioral scores. (2) Acupuncture manipulation significantly increased the duration, occurrence, and contribution parameters of microstate C, whereas it decreased those parameters of microstate D. (3) Microstate C’s duration parameter showed a significantly positive correlation with acupuncture deqi behavior scores. (4) Acupuncture manipulation significantly increased the transition probabilities with microstate C as node, whereas it reduced the transition probabilities with microstate D as node. (5) Microstate B→C’s transition probability also showed a significantly positive correlation with acupuncture deqi behavior scores. Taken together, the temporal dynamic feature of EEG microstate could be used as objective neuroimaging evidence to reveal the neuromodulation effect of acupuncture with deqi.

scholarly journals Modeling the temporal dynamics of cervicovaginal microbiota identifies targets that may promote reproductive health

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Alexander Munoz ◽  
Matthew R. Hayward ◽  
Seth M. Bloom ◽  
Muntsa Rocafort ◽  
Sinaye Ngcapu ◽  
...  
Keyword(s):  
High Risk ◽  
Bacterial Communities ◽  
High Probability ◽  
Temporal Dynamics ◽  
Transition Probabilities ◽  
Low Risk ◽  
Sub Saharan Africa ◽  
Reproductive Outcomes ◽  
Bacterial Composition ◽  
Sub Saharan

Abstract Background Cervicovaginal bacterial communities composed of diverse anaerobes with low Lactobacillus abundance are associated with poor reproductive outcomes such as preterm birth, infertility, cervicitis, and risk of sexually transmitted infections (STIs), including human immunodeficiency virus (HIV). Women in sub-Saharan Africa have a higher prevalence of these high-risk bacterial communities when compared to Western populations. However, the transition of cervicovaginal communities between high- and low-risk community states over time is not well described in African populations. Results We profiled the bacterial composition of 316 cervicovaginal swabs collected at 3-month intervals from 88 healthy young Black South African women with a median follow-up of 9 months per participant and developed a Markov-based model of transition dynamics that accurately predicted bacterial composition within a broader cross-sectional cohort. We found that Lactobacillus iners-dominant, but not Lactobacillus crispatus-dominant, communities have a high probability of transitioning to high-risk states. Simulating clinical interventions by manipulating the underlying transition probabilities, our model predicts that the population prevalence of low-risk microbial communities could most effectively be increased by manipulating the movement between L. iners- and L. crispatus-dominant communities. Conclusions The Markov model we present here indicates that L. iners-dominant communities have a high probability of transitioning to higher-risk states. We additionally identify transitions to target to increase the prevalence of L. crispatus-dominant communities. These findings may help guide future intervention strategies targeted at reducing bacteria-associated adverse reproductive outcomes among women living in sub-Saharan Africa.

scholarly journals States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model

2021 ◽  
Vol 18 (14) ◽  
pp. 7449
Author(s):  
Juan Xiong ◽  
Qiyu Fang ◽  
Jialing Chen ◽  
Yingxin Li ◽  
Huiyi Li ◽  
...  
Keyword(s):  
Postpartum Depression ◽  
Markov Model ◽  
Normal State ◽  
Sojourn Time ◽  
Transition Probabilities ◽  
Transition Probability ◽  
Public Health Problem ◽  
Mental States ◽  
Hazard Ratio ◽  
Multiple Time

Background: Postpartum depression (PPD) has been recognized as a severe public health problem worldwide due to its high incidence and the detrimental consequences not only for the mother but for the infant and the family. However, the pattern of natural transition trajectories of PPD has rarely been explored. Methods: In this research, a quantitative longitudinal study was conducted to explore the PPD progression process, providing information on the transition probability, hazard ratio, and the mean sojourn time in the three postnatal mental states, namely normal state, mild PPD, and severe PPD. The multi-state Markov model was built based on 912 depression status assessments in 304 Chinese primiparous women over multiple time points of six weeks postpartum, three months postpartum, and six months postpartum. Results: Among the 608 PPD status transitions from one visit to the next visit, 6.2% (38/608) showed deterioration of mental status from the level at the previous visit; while 40.0% (243/608) showed improvement at the next visit. A subject in normal state who does transition then has a probability of 49.8% of worsening to mild PPD, and 50.2% to severe PPD. A subject with mild PPD who does transition has a 20.0% chance of worsening to severe PPD. A subject with severe PPD is more likely to improve to mild PPD than developing to the normal state. On average, the sojourn time in the normal state, mild PPD, and severe PPD was 64.12, 6.29, and 9.37 weeks, respectively. Women in normal state had 6.0%, 8.5%, 8.7%, and 8.8% chances of progress to severe PPD within three months, nine months, one year, and three years, respectively. Increased all kinds of supports were associated with decreased risk of deterioration from normal state to severe PPD (hazard ratio, HR: 0.42–0.65); and increased informational supports, evaluation of support, and maternal age were associated with alleviation from severe PPD to normal state (HR: 1.46–2.27). Conclusions: The PPD state transition probabilities caused more attention and awareness about the regular PPD screening for postnatal women and the timely intervention for women with mild or severe PPD. The preventive actions on PPD should be conducted at the early stages, and three yearly; at least one yearly screening is strongly recommended. Emotional support, material support, informational support, and evaluation of support had significant positive associations with the prevention of PPD progression transitions. The derived transition probabilities and sojourn time can serve as an importance reference for health professionals to make proactive plans and target interventions for PPD.

Further enhancement on H∞ sliding mode control design for singular Markovian jump systems with partly known transition probabilities

2021 ◽  
pp. 107754632198920
Author(s):  
Zeinab Fallah ◽  
Mahdi Baradarannia ◽  
Hamed Kharrati ◽  
Farzad Hashemzadeh
Keyword(s):  
Transition Probabilities ◽  
Sliding Mode ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Linear Matrix ◽  
Sliding Mode Controller ◽  
Sliding Surface ◽  
Markovian Jump ◽  
Markovian Jump System ◽  
Singular Markovian Jump Systems

This study considers the designing of the H ∞ sliding mode controller for a singular Markovian jump system described by discrete-time state-space realization. The system under investigation is subject to both matched and mismatched external disturbances, and the transition probability matrix of the underlying Markov chain is considered to be partly available. A new sufficient condition is developed in terms of linear matrix inequalities to determine the mode-dependent parameter of the proposed quasi-sliding surface such that the stochastic admissibility with a prescribed H ∞ performance of the sliding mode dynamics is guaranteed. Furthermore, the sliding mode controller is designed to assure that the state trajectories of the system will be driven onto the quasi-sliding surface and remain in there afterward. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design algorithms.

Human Brain Like Memory Behavior in the Magnetic Domain Expansion Type Magneto-Optical Disk

2001 ◽  
Vol 674 ◽  
Author(s):  
Norio Ota ◽  
Hiroyuki Awano ◽  
Manabu Tani ◽  
Susumu Imai
Keyword(s):  
Magnetic Field ◽  
Human Brain ◽  
Magnetic Domain ◽  
Field Pattern ◽  
Human Response ◽  
External Stimulation ◽  
Stored Information ◽  
The Magnetic Field ◽  
Timing Phase ◽  
Coherent Amplification

ABSTRACTMagnetic Amplifying Magneto-Optical System (MAMMOS) shows human brain like memory behavior. Magnetic field and laser power have threshold to recover the stored memory like the human response of remembering. MAMMOS also has a feature to amplify very small recorded signals like our recovery of memory, e.g. fifty years ago episode.By adding the meaningful information on the magnetic field pattern, we can get some correlation between our memory and external stimulation. Such scheme is named as “the Active readout MAMMOS” which is analogues to the human process of remembering the memory.If the applied field pattern and timing phase just coincide with stored information, there occurs the coherent amplification of MAMMOS signal. We can utilize such phenomena as the trigger of “Memory Association”.

scholarly journals The brain timewise: how timing shapes and supports brain function

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140170 ◽  
Author(s):  
Riitta Hari ◽  
Lauri Parkkonen
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Generative Models ◽  
Network Activity ◽  
Brain Diseases ◽  
Specific Information ◽  
Non Invasive ◽  
The Brain

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.

Temporal dynamics of reward anticipation in the human brain

2017 ◽  
Vol 128 ◽  
pp. 89-97 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Qi Li ◽  
Zhao Wang ◽  
Xun Liu ◽  
Ya Zheng
Keyword(s):  
Human Brain ◽  
Temporal Dynamics ◽  
Reward Anticipation

scholarly journals Infinitely divisible random transition probabilities with application to dependent Markov chains

1984 ◽  
Vol 25 (4) ◽  
pp. 463-472
Author(s):  
Peter L. Chesson
Keyword(s):  
Markov Chain ◽  
Markov Chains ◽  
White Noise ◽  
Transition Probabilities ◽  
Transition Probability ◽  
Transition Rates ◽  
Infinitely Divisible ◽  
Random Transition ◽  
Transition Probability Matrices ◽  
Probability Matrices

AbstractRandom transition probability matrices with stationary independent factors define “white noise” environment processes for Markov chains. Two examples are considered in detail. Such environment processes can be used to construct several Markov chains which are dependent, have the same transition probabilities and are jointly a Markov chain. Transition rates for such processes are evaluated. These results have application to the study of animal movements.

Determination of the correlation relationship between irrigation and distribution of agricultural lands

2021 ◽  
Vol 07 (02) ◽  
pp. 29-35
Author(s):  
Kamil Zakir oğlu İbrahimli ◽  
Keyword(s):  
Key Words ◽  
Statistical Method ◽  
Negative Correlation ◽  
Agricultural Lands ◽  
Correlation Relationship ◽  
Positive Correlation ◽  
Correlation Methods ◽  
Correlation Degree ◽  
The Relationship

The importance of the statistical method is great in the study of natural and economic processes. It is possible to conduct analyzes and obtain results with the help of this method. Sometimes phenomena and processes co-exist and develop interdependently. In this case, it is necessary to determine the relationship between them, to express this relationship. Key words: perfect positive correlation, perfect negative correlation, direction of correlation, degree of correlation, methods of calculating correlation, Spearman᾽s method

scholarly journals Fermions on wobbling kinks: normal versus quasinormal modes

2021 ◽  
Vol 2021 (9) ◽  
Author(s):  
João G. F. Campos ◽  
Azadeh Mohammadi
Keyword(s):  
Transition Probabilities ◽  
Transition Probability ◽  
Quasinormal Modes ◽  
Golden Rule ◽  
Coupling Constants ◽  
Large Coupling ◽  
Constant Rate ◽  
Fermi's Golden Rule ◽  
The Impact ◽  
Fermi’S Golden Rule

Abstract The system consisting of a fermion in the background of a wobbling kink is studied in this paper. To investigate the impact of the wobbling on the fermion-kink interaction, we employ the time-dependent perturbation theory formalism in quantum mechanics. To do so, we compute the transition probabilities between states given in terms of the Bogoliubov coefficients. We derive Fermi’s golden rule for the model, which allows the transition to the continuum at a constant rate if the fermion-kink coupling constant is smaller than the wobbling frequency. Moreover, we study the system replacing the shape mode with a quasinormal mode. In this case, the transition rate to continuum decays in time due to the leakage of the mode, and the final transition probability decreases sharply for large coupling constants in a way that is analogous to Fermi’s golden rule. Throughout the paper, we compare the perturbative results with numerical simulations and show that they are in good agreement.

scholarly journals Large Scale Shell Model Calculations of the Negative-Parity States Structure in 24Mg Nucleus

2021 ◽  
Vol 66 (4) ◽  
pp. 293
Author(s):  
A.A. Al-Sammarraie ◽  
F.A. Ahmed ◽  
A.A. Okhunov
Keyword(s):  
Shell Model ◽  
Large Scale ◽  
Transition Probabilities ◽  
Transition Probability ◽  
Energy Levels ◽  
Form Factors ◽  
Model Space ◽  
Negative Parity ◽  
Matrix Elements ◽  
Model Calculations

The negative-parity states of 24Mg nucleus are investigated within the shell model. We are based on the calculations of energy levels, total squared form factors, and transition probability using the p-sd-pf (PSDPF) Hamiltonian in a large model space (0 + 1) hW. The comparison between the experimental and theoretical states showed a good agreement within a truncated model space. The PSDPF-based calculations successfully reproduced the data on the total squared form factors and transition probabilities of the negative-parity states in 24Mg nucleus. These quantities depend on the one-body density matrix elements that are obtained from the PSDPF Hamiltonian. The wave functions of radial one-particle matrix elements calculated with the harmonic-oscillator potential are suitable to predict experimental data by changing the center-of-mass corrections.

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