102 research outputs found

    Forced patterns near a Turing-Hopf bifurcation

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    We study time-periodic forcing of spatially-extended patterns near a Turing-Hopf bifurcation point. A symmetry-based normal form analysis yields several predictions, including that (i) weak forcing near the intrinsic Hopf frequency enhances or suppresses the Turing amplitude by an amount that scales quadratically with the forcing strength, and (ii) the strongest effect is seen for forcing that is detuned from the Hopf frequency. To apply our results to specific models, we perform a perturbation analysis on general two-component reaction-diffusion systems, which reveals whether the forcing suppresses or enhances the spatial pattern. For the suppressing case, our results explain features of previous experiments on the CDIMA chemical reaction. However, we also find examples of the enhancing case, which has not yet been observed in experiment. Numerical simulations verify the predicted dependence on the forcing parameters.Comment: 4 pages, 4 figure

    Connexin36 knockout mice display increased sensitivity to pentylenetetrazol-induced seizure-like behaviors

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    Large-scale synchronous firing of neurons during seizures is modulated by electrotonic coupling between neurons via gap junctions. To explore roles for connexin36 (Cx36) gap junctions in seizures, we examined the seizure threshold of connexin36 knockout (Cx36KO) mice using a pentylenetetrazol (PTZ) model

    Linear amplifiers with phase-sensitive noise

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    We present a model for a linear amplifier which adds phase-dependent noise to the input signal. This is achieved by preparing the internal modes of the amplifier in a squeezed vacuum. Such a scheme could be used to amplify a squeezed-signal quadrature with reduced added noise compared with conventional schemes. The model discussed could be realized as nondegenerate parametric amplification

    Approach to the semiconductor cavity QED in high-Q regimes with q-deformed boson

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    The high density Frenkel exciton which interacts with a single mode microcavity field is dealed with in the framework of the q-deformed boson. It is shown that the q-defomation of bosonic commutation relations is satisfied naturally by the exciton operators when the low density limit is deviated. An analytical expression of the physical spectrum for the exciton is given by using of the dressed states of the cavity field and the exciton. We also give the numerical study and compare the theoretical results with the experimental resultsComment: 6 pages, 2 figure

    Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

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    NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep

    Transcultural Diabetes Nutrition Therapy Algorithm: The Asian Indian Application

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    India and other countries in Asia are experiencing rapidly escalating epidemics of type 2 diabetes (T2D) and cardiovascular disease. The dramatic rise in the prevalence of these illnesses has been attributed to rapid changes in demographic, socioeconomic, and nutritional factors. The rapid transition in dietary patterns in India—coupled with a sedentary lifestyle and specific socioeconomic pressures—has led to an increase in obesity and other diet-related noncommunicable diseases. Studies have shown that nutritional interventions significantly enhance metabolic control and weight loss. Current clinical practice guidelines (CPGs) are not portable to diverse cultures, constraining the applicability of this type of practical educational instrument. Therefore, a transcultural Diabetes Nutrition Algorithm (tDNA) was developed and then customized per regional variations in India. The resultant India-specific tDNA reflects differences in epidemiologic, physiologic, and nutritional aspects of disease, anthropometric cutoff points, and lifestyle interventions unique to this region of the world. Specific features of this transculturalization process for India include characteristics of a transitional economy with a persistently high poverty rate in a majority of people; higher percentage of body fat and lower muscle mass for a given body mass index; higher rate of sedentary lifestyle; elements of the thrifty phenotype; impact of festivals and holidays on adherence with clinic appointments; and the role of a systems or holistic approach to the problem that must involve politics, policy, and government. This Asian Indian tDNA promises to help guide physicians in the management of prediabetes and T2D in India in a more structured, systematic, and effective way compared with previous methods and currently available CPGs

    A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation

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    Few models exist that accurately reproduce the complex rhythms of the thalamocortical system that are apparent in measured scalp EEG and at the same time, are suitable for large-scale simulations of brain activity. Here, we present a neural mass model of the thalamocortical system during natural non-REM sleep, which is able to generate fast sleep spindles (12–15 Hz), slow oscillations (<1 Hz) and K-complexes, as well as their distinct temporal relations, and response to auditory stimuli. We show that with the inclusion of detailed calcium currents, the thalamic neural mass model is able to generate different firing modes, and validate the model with EEG-data from a recent sleep study in humans, where closed-loop auditory stimulation was applied. The model output relates directly to the EEG, which makes it a useful basis to develop new stimulation protocols

    Nonlinear analysis of EEG signals at different mental states

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    BACKGROUND: The EEG (Electroencephalogram) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. This work discusses the effect on the EEG signal due to music and reflexological stimulation. METHODS: In this work, nonlinear parameters like Correlation Dimension (CD), Largest Lyapunov Exponent (LLE), Hurst Exponent (H) and Approximate Entropy (ApEn) are evaluated from the EEG signals under different mental states. RESULTS: The results obtained show that EEG to become less complex relative to the normal state with a confidence level of more than 85% due to stimulation. CONCLUSIONS: It is found that the measures are significantly lower when the subjects are under sound or reflexologic stimulation as compared to the normal state. The dimension increases with the degree of the cognitive activity. This suggests that when the subjects are under sound or reflexologic stimuli, the number of parallel functional processes active in the brain is less and the brain goes to a more relaxed stat

    Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

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    Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons
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