Integrated Calendar

Behavioral and neuroimaging studies have demonstrated that throughout evolution, visual signals that has been associated with threats enjoy automated and prioritized processing. Based on this, we hypothesized an ability to detect threats also via our nose. In this talk, I will provide an overview of findings from our recent project on olfactory threat signals originating from various sources. Our findings demonstrate that, much like other animals, humans are able to extract odor information that alert us about the presence of specific threats and that this information affect both our neural processing of sensory stimuli as well as the perception of the same.

Drinking enough water is commonly recommended for health, but drinking too much water is dangerous. Therefore, animals have evolved sophisticated mechanisms to prevent harmful overhydration: for one thing, excess intake of water rapidly makes us feel nauseated and avoid further drinking. How do neural circuits mediate this phenomenon? To shed light on this question, we first identified a genetically defined subpopulation of neurons in the parabrachial nucleus (PB) that is activated by water intake. Using fiber photometry, we show that these neurons are activated by the ingestion of fluids, but not solids, and the responses are time-locked to the onset and offset of drinking. Extensive sets of recording experiments demonstrate that the detection mechanism for fluid intake is likely mechanosensory, and the fluid intake signals originate from all parts of the upper digestive tract. By manipulating the activity of the PB neurons, we establish that these neurons are both sufficient and necessary for limiting fluid intake, possibly by recruiting the projection to the median preoptic area. Together, our results identify 1) a central circuit node that can signal and limit fluid intake, 2) the detection mechanism for fluid intake in the periphery, and 3) the neural pathways by which the fluid intake signals are transmitted to the central nervous system.

In our LCDM paradigm, galaxies form and reside in dark matter halos. Establishing the (statistical) relation between galaxies and dark matter halos, the `Galaxy-Halo connection', therefore gives important insight into galaxy formation, and also is a gateway to using the distribution of galaxies to constrain cosmological parameters. After a brief introduction to how clustering and gravitational lensing can be used to constrain the galaxy-halo connection, I show that several independent analyses all point towards a significant tension in cosmological parameters compared to the recent CMB results from the Planck satellite. I discuss the potential impact of assembly bias, and present satellite kinematics as a complementary and competitive method to constrain the galaxy-halo connection. After a brief historical overview of the use of satellite kinematics, I present two new analyses, and show how they can be used to improve our knowledge of the galaxy-halo connection.

Atherosclerosis causes heart attack and stroke and is a major fatal disease in the Western world. The formation of atherosclerotic plaques in the artery walls is the result of LDL particle uptake, and consequently of cholesterol accumulation in macrophage cells. Excess cholesterol accumulation eventually results in cholesterol crystal deposition, the hallmark of mature atheromas. We study the formation of cholesterol monohydrate crystal polymorphs on lipid bilayer membranes and in cells enriched with cholesterol. This work may provide information on the crystal growth mechanisms involved, once the factors that favor the formation of different structures are understood

The Lindblad equation allows to explore general properties of open quantum systems. Whenever strong decoherence processes are present, one expects the system to become classical. Namely, the evolution of the surviving diagonal terms of the density matrix is Markovian. Surprisingly enough, many interesting aspects of the quantum system can be inferred from the classical limit. Among which we will explore some transport properties as well as a condensation transition for interacting quantum particles. Moreover, we will be interested in the quantum corrections to Fick’s law in diffusive systems

Information theory, originally developed for mathematical analysis of communication systems, has been applied to molecular biology for decades. In this context, the concept of entropy is utilized to measure the compositional complexity of genomes, wherein all of the hereditary information necessary to build and maintain an organism is stored. The recent explosion in the availability of genomic data, coupled with the considerable improvements in computational processing power, presents opportunities for investigating genomes far beyond the scope and depth previously achievable. In this work, we propose to characterize the informational properties of ~5000 genomes by assessing the statistical abundance and sequence space coverage of fixed-length substrings (known as ‘kmers’). Additionally, we aim to identify unique kmers that can be used as genome-specific markers for taxonomic profiling purposes.