Cross-approximate entropy of cortical local field potentials quantifies effects of anesthesia - a pilot study in rats

Background

Anesthetics dose-dependently shift electroencephalographic (EEG) activity towards high-amplitude, slow rhythms, indicative of a synchronization of neuronal activity in thalamocortical networks. Additionally, they uncouple brain areas in higher (gamma) frequency ranges possibly underlying conscious perception. It is currently thought that both effects may impair brain function by impeding proper information exchange between cortical areas. But what happens at the local network level? Local networks with strong excitatory interconnections may be more resilient towards global changes in brain rhythms, but depend heavily on locally projecting, inhibitory interneurons. As anesthetics bias cortical networks towards inhibition, we hypothesized that they may cause excessive synchrony and compromise information processing already on a small spatial scale. Using a recently introduced measure of signal independence, cross-approximate entropy (XApEn), we investigated to what degree anesthetics synchronized local cortical network activity. We recorded local field potentials (LFP) from the somatosensory cortex of three rats chronically implanted with multielectrode arrays and compared activity patterns under control (awake state) with those at increasing concentrations of isoflurane, enflurane and halothane.

Results

Cortical LFP signals were more synchronous, as expressed by XApEn, in the presence of anesthetics. Specifically, XApEn was a monotonously declining function of anesthetic concentration. Isoflurane and enflurane were indistinguishable; at a concentration of 1 MAC (the minimum alveolar concentration required to suppress movement in response to noxious stimuli in 50% of subjects) both volatile agents reduced XApEn by about 70%, whereas halothane was less potent (50% reduction).

Conclusions

The results suggest that anesthetics strongly diminish the independence of operation of local cortical neuronal populations, and that the quantification of these effects in terms of XApEn has a similar discriminatory power as changes of spontaneous action potential rates. Thus, XApEn of field potentials recorded from local cortical networks provides valuable information on the anesthetic state of the brain.

     

Universal occurrence of the phase-flip bifurcation in time-delay coupled systems

Recently, the phase-flip bifurcation has been described as a fundamental transition in time-delay coupled, phase-synchronized nonlinear dynamical systems. The bifurcation is characterized by a change of the synchronized dynamics from being in-phase to antiphase, or vice versa; the phase-difference between the oscillators undergoes a jump of pi as a function of the coupling strength or the time delay. This phase-flip is accompanied by discontinuous changes in the frequency of the synchronized oscillators, and in the largest negative Lyapunov exponent or its derivative. Here we illustrate the phenomenology of the bifurcation for several classes of nonlinear oscillators, in the regimes of both periodic and chaotic dynamics. We present extensive numerical simulations and compute the oscillation frequencies and the Lyapunov spectra as a function of the coupling strength. In particular, our simulations provide clear evidence of the phase-flip bifurcation in excitable laser and Fitzhugh-Nagumo neuronal models, and in diffusively coupled predator-prey models with either limit cycle or chaotic dynamics. Our analysis demonstrates marked jumps of the time-delayed and instantaneous fluxes between the two interacting oscillators across the bifurcation; this has strong implications for the performance of the system as well as for practical applications. We further construct an electronic circuit consisting of two coupled Chua oscillators and provide the first formal experimental demonstration of the bifurcation. In totality, our study demonstrates that the phase-flip phenomenon is of broad relevance and importance for a wide range of physical and natural systems.     

Experimental and modeling assessment of sulfur release from coal under low and high heating rates

Coal combustion releases elevated amounts of pollutants to the atmosphere including SO_X. During the pyrolysis step, sulfur present in the coal is released to the gas phase as many different chemical species such as H₂S, COS, SO₂, CS₂, thiols and larger tars, also called SO_X precursors, as they form SO_X during combustion. Understanding the sulfur release process is crucial to the development of reliable kinetic models, which support the design of improved reactors for cleaner coal conversion processes. Sulfur release from two bituminous coals, Colombian hard coal (K1) and American high sulfur coal (U2), were studied in the present work. Low heating rate (LHR) experiments were performed in a thermogravimetric analyzer coupled with mass spectrometry (TG-MS), allowing to track the mass loss and the evolution of many volatile species (CO, CO₂, CH₄, SO₂, H₂S, COS, HCl and H₂O). High heating rate (HHR) experiments were performed in an entrained flow reactor (drop-tube reactor – DTR), coupled with MS and nondispersive infrared sensor (NDIR). HHR experiments were complemented with CFD simulation of the multidimentional reacting flow field. A kinetic model of coal pyrolysis is employed to reproduce the experiments allowing a comprehensive assessment of the process. The suitability of this model is confirmed for LHR. The combination of HHR experiments with CFD simulations and kinetic modeling revealed the complexity of sulfur chemistry in coal combustion and allowed to better understand of the individual phenomena resulting in the formation of the different SO_X precursors. LHR and HHR operating conditions lead to different distribution of sulfur species released, highly-dependent on the gas-phase temperature and residence time. Higher retention of total sulfur in char is observed at LHR (63%) when compared to HHR (37–44%), at 1273 K. These data support the development of reliable models with improved predictability.     

Quasiregular concentric waves in heterogeneous lattices of coupled oscillators

We study the pattern formation in a lattice of locally coupled phase oscillators with quenched disorder. In the synchronized regime quasiregular concentric waves can arise which are induced by the disorder of the system. Maximal regularity is found at the edge of the synchronization regime. The emergence of the concentric waves is related to the symmetry breaking of the interaction function. An explanation of the numerically observed phenomena is given in a one-dimensional chain of coupled phase oscillators. Scaling properties, describing the target patterns are obtained.     

Proton-detected scalar coupling based assignment strategies in MAS solid-state NMR spectroscopy applied to perdeuterated proteins

Assignment of proteins in MAS (magic angle spinning) solid-state NMR relies so far on correlations among heteronuclei. This strategy is based on well dispersed resonances in the ¹⁵N dimension. In many complex cases like membrane proteins or amyloid fibrils, an additional frequency dimension is desirable in order to spread the amide resonances. We show here that proton detected HNCO, HNCA, and HNCACB type experiments can successfully be implemented in the solid-state. Coherences are sufficiently long lived to allow pulse schemes of a duration greater than 70 ms before incrementation of the first indirect dimension. The achieved resolution is comparable to the resolution obtained in solution-state NMR experiments. We demonstrate the experiments using a triply labeled sample of the SH3 domain of chicken α-spectrin, which was re-crystallized in H₂O/D₂O using a ratio of 1/9. We employ paramagnetic relaxation enhancement (PRE) using EDTA chelated Cu^II to enable rapid data acquisition.     

The effect of oxidation on the surface-near lattice relaxation in FeNi nanoparticles

The near-surface oxidation-induced lattice relaxation and compositional changes of FeNi alloy nano-particles are investigated. Using a newly developed transfer system, the particle structure was characterised by means of aberration-corrected HR-TEM prior to exposing the particles to ambient air. This allows for a comparison of oxidised and un-oxidised particles, respectively. Independent of the oxidation, the surface-near and/or interface-near metal lattice was found to be expanded by up to 3%. EELS profiles clearly reveal an enrichment of Fe at the particle surfaces. MD simulations in combination with HR-TEM contrast simulations were conducted to investigate the effect of the Fe enrichment on the structural relaxation. The results show that a surface-near over-stoichiometric enrichment of Fe indeed causes a dilation that counteracts a compression of the lattice at the particle surface as obtained for homogeneously alloyed particles. Besides, the large lattice mismatch between the metallic cores and the NiFe₂O₄ shells causes the formation of step dislocations in the close vicinities of the interface. In essence, the surface-near lattice relaxation in oxide free particles is found to be due to a segregation of Fe to the surface, whereas in the case of shell–core particles, no systematic influence of the oxide on the lattice relaxation was found.