A Normative Theory of Forgetting: Lessons from the Fruit Fly

Recent experiments revealed that the fruit fly Drosophila melanogaster has a dedicated mechanism for forgetting: blocking the G-protein Rac leads to slower and activating Rac to faster forgetting. This active form of forgetting lacks a satisfactory functional explanation. We investigated optimal decision making for an agent adapting to a stochastic environment where a stimulus may switch between being indicative of reward or punishment. Like Drosophila, an optimal agent shows forgetting with a rate that is linked to the time scale of changes in the environment. Moreover, to reduce the odds of missing future reward, an optimal agent may trade the risk of immediate pain for information gain and thus forget faster after aversive conditioning. A simple neuronal network reproduces these features. Our theory shows that forgetting in Drosophila appears as an optimal adaptive behavior in a changing environment. This is in line with the view that forgetting is adaptive rather than a consequence of limitations of the memory system.

Social motility of African trypanosomes is a property of a distinct life-cycle stage that occurs early in tsetse fly transmission

The protozoan pathogen Trypanosoma brucei is transmitted between mammals by tsetse flies. The first compartment colonised by trypanosomes after a blood meal is the fly midgut lumen. Trypanosomes present in the lumen-designated as early procyclic forms-express the stage-specific surface glycoproteins EP and GPEET procyclin. When the trypanosomes establish a mature infection and colonise the ectoperitrophic space, GPEET is down-regulated, and EP becomes the major surface protein of late procyclic forms. A few years ago, it was discovered that procyclic form trypanosomes exhibit social motility (SoMo) when inoculated on a semi-solid surface. We demonstrate that SoMo is a feature of early procyclic forms, and that late procyclic forms are invariably SoMo-negative. In addition, we show that, apart from GPEET, other markers are differentially expressed in these two life-cycle stages, both in culture and in tsetse flies, indicating that they have different biological properties and should be considered distinct stages of the life cycle. Differentially expressed genes include two closely related adenylate cyclases, both hexokinases and calflagins. These findings link the phenomenon of SoMo in vitro to the parasite forms found during the first 4-7 days of a midgut infection. We postulate that ordered group movement on plates reflects the migration of parasites from the midgut lumen into the ectoperitrophic space within the tsetse fly. Moreover, the process can be uncoupled from colonisation of the salivary glands. Although they are the major surface proteins of procyclic forms, EP and GPEET are not essential for SoMo, nor, as shown previously, are they required for near normal colonisation of the fly midgut.

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.