Comet 1P/Halley multifluid MHD model for the Giotto fly-by

The interaction of comets with the solar wind has been the focus of many studies including numerical modeling. We compare the results of our multifluid MHD simulation of comet 1P/Halley to data obtained during the flyby of the European Space Agency's Giotto spacecraft in 1986. The model solves the full set of MHD equations for the individual fluids representing the solar wind protons, the cometary light and heavy ions, and the electrons. The mass loading, charge-exchange, dissociative ion-electron recombination, and collisional interactions between the fluids are taken into account. The computational domain spans over several million kilometers, and the close vicinity of the comet is resolved to the details of the magnetic cavity. The model is validated by comparison to the corresponding Giotto observations obtained by the Ion Mass Spectrometer, the Neutral Mass Spectrometer, the Giotto magnetometer experiment, and the Johnstone Plasma Analyzer instrument. The model shows the formation of the bow shock, the ion pile-up, and the diamagnetic cavity and is able to reproduce the observed temperature differences between the pick-up ion populations and the solar wind protons. We give an overview of the global interaction of the comet with the solar wind and then show the effects of the Lorentz force interaction between the different plasma populations.

What do brain network interactions tell about cognitive processes? How to seek causality?

Optimal adjustment of brain networks allows the biased processing of information in response to the demand of environments and is therefore prerequisite for adaptive behaviour. It is widely shown that a biased state of networks is associated with a particular cognitive process. However, those associations were identified by backward categorization of trials and cannot provide a causal association with cognitive processes. This problem still remains a big obstacle to advance the state of our field in particular human cognitive neuroscience. In my talk, I will present two approaches to address the causal relationships between brain network interactions and behaviour. Firstly, we combined connectivity analysis of fMRI data and a machine leaning method to predict inter-individual differences of behaviour and responsiveness to environmental demands. The connectivity-based classification approach outperforms local activation-based classification analysis, suggesting that interactions in brain networks carry information of instantaneous cognitive processes. Secondly, we have recently established a brand new method combining transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and EEG. We use the method to measure signal transmission between brain areas while introducing extrinsic oscillatory brain activity and to study causal association between oscillatory activity and behaviour. We show that phase-matched oscillatory activity creates the phase-dependent modulation of signal transmission between brain areas, while phase-shifted oscillatory activity blunts the phase-dependent modulation. The results suggest that phase coherence between brain areas plays a cardinal role in signal transmission in the brain networks. In sum, I argue that causal approaches will provide more concreate backbones to cognitive neuroscience.

Lung Structure and the Intrinsic Challenges of Gas Exchange

Structural and functional complexities of the mammalian lung evolved to meet a unique set of challenges, namely, the provision of efficient delivery of inspired air to all lung units within a confined thoracic space, to build a large gas exchange surface associated with minimal barrier thickness and a microvascular network to accommodate the entire right ventricular cardiac output while withstanding cyclic mechanical stresses that increase several folds from rest to exercise. Intricate regulatory mechanisms at every level ensure that the dynamic capacities of ventilation, perfusion, diffusion, and chemical binding to hemoglobin are commensurate with usual metabolic demands and periodic extreme needs for activity and survival. This article reviews the structural design of mammalian and human lung, its functional challenges, limitations, and potential for adaptation. We discuss (i) the evolutionary origin of alveolar lungs and its advantages and compromises, (ii) structural determinants of alveolar gas exchange, including architecture of conducting bronchovascular trees that converge in gas exchange units, (iii) the challenges of matching ventilation, perfusion, and diffusion and tissue-erythrocyte and thoracopulmonary interactions. The notion of erythrocytes as an integral component of the gas exchanger is emphasized. We further discuss the signals, sources, and limits of structural plasticity of the lung in alveolar hypoxia and following a loss of lung units, and the promise and caveats of interventions aimed at augmenting endogenous adaptive responses. Our objective is to understand how individual components are matched at multiple levels to optimize organ function in the face of physiological demands or pathological constraints. © 2016 American Physiological Society. Compr Physiol 6:827-895, 2016.