It has recently been reported that statistical signatures of brain criticality, obtained from distributions of neuronal avalanches, can depend on the cortical state. We revisit these claims with a completely different and independent approach, employing a maximum entropy model to test whether signatures of criticality appear in urethane-anesthetized rats. To account for the spontaneous variation of cortical states, we parse the time series and perform the maximum entropy analysis as a function of the variability of the population spiking activity. To compare data sets with different numbers of neurons, we define a normalized distance to criticality that takes into account the peak and width of the specific heat curve. We found a universal collapse of the normalized distance to criticality dependence on the cortical state, on an animal by animal basis. This indicates a universal dynamics and a critical point at an intermediate value of spiking variability.
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http://dx.doi.org/10.1103/PhysRevE.102.012408 | DOI Listing |
ACS Appl Mater Interfaces
December 2024
School of Materials Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Magnetocaloric high-entropy alloys (HEAs) have recently garnered significant interest owing to their potential applications in magnetic refrigeration, offering a wide working temperature range and large refrigerant capacity. In this study, we thoroughly investigated the structural, magnetic, and magnetocaloric properties of equiatomic GdDyHoErTm HEAs. The as-cast alloy exhibits a single hexagonal phase, a randomly distributed grain orientation, and complex magnetism.
View Article and Find Full Text PDFInorg Chem
December 2024
School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
The interplay between quantum effects from magnetic frustration, low-dimensionality, spin-orbit coupling, and crystal electric field in rare-earth materials leads to nontrivial ground states with unusual magnetic excitations. Here, we investigate YbTaO, which hosts a buckled square net of Yb ions with = 1/2 moments. The observed Curie-Weiss temperature is about -1 K, implying an antiferromagnetic coupling between the Yb moments.
View Article and Find Full Text PDFNanomaterials (Basel)
December 2024
School of Intelligent Manufacturing, Luoyang Institute of Science and Technology, Luoyang 471023, China.
(AlCrMoNiTi)N high-entropy alloy nitride (HEAN) films were synthesized at various bias voltages using the co-filter cathodic vacuum arc (co-FCVA) deposition technique. This study systematically investigates the effect of bias voltage on the microstructure and performance of HEAN films. The results indicate that an increase in bias voltage enhances the energy of ions while concomitantly reducing the deposition rate.
View Article and Find Full Text PDFFront Public Health
December 2024
Department of Statistics, College of Science, Bahir Dar University, Bahir Dar, Ethiopia.
Introduction: Dynamic Bayesian networks improve the modeling of complex systems by incorporating continuous probabilistic relationships between covariates that change over time. This study aimed to analyze the complex causal links contributing to child undernutrition using dynamic Bayesian network modeling, examining both the best- and worst-case scenarios. The Young Cohort of the Ethiopian Young Lives dataset from 2002-2016 was used to analyze the complex relationships among various covariates influencing child undernutrition.
View Article and Find Full Text PDFBrain Res
December 2024
Department of Nuclear Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China. Electronic address:
The brain is a highly complex and delicate system, and its internal neural processes are manifested as the interweaving and superposition of multi-frequency neural signals. However, traditional brain network studies are often limited to the whole frequency band or a specific frequency band, ignoring the potentially profound impact of the diversity of information within the frequency on the dynamics of brain networks. To comprehensively and deeply analyze this phenomenon, the present study is devoted to exploring the specific performance of brain networks at different frequencies.
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