Sweet taste and nutrient value subdivide rewarding dopaminergic neurons in Drosophila

Dopaminergic neurons provide reward learning signals in mammals and insects [1-4]. Recent work in Drosophila has demonstrated that water-reinforcing dopaminergic neurons are different to those for nutritious sugars [5]. Here, we tested whether the sweet taste and nutrient properties of sugar reinforcement further subdivide the fly reward system. We found that dopaminergic neurons expressing the OAMB octopamine receptor [6] specifically convey the short-term reinforcing effects of sweet taste [4]. These dopaminergic neurons project to the beta\u272 and gamma4 regions of the mushroom body lobes. In contrast, nutrient-dependent long-term memory requires different dopaminergic neurons that project to the gamma5b regions, and it can be artificially reinforced by those projecting to the beta lobe and adjacent alpha1 region. Surprisingly, whereas artificial implantation and expression of short-term memory occur in satiated flies, formation and expression of artificial long-term memory require flies to be hungry. These studies suggest that short-term and long-term sugar memories have different physiological constraints. They also demonstrate further functional heterogeneity within the rewarding dopaminergic neuron population

Early calcium increase triggers the formation of olfactory long-term memory in honeybees

<p>Abstract</p> <p>Background</p> <p>Synaptic plasticity associated with an important wave of gene transcription and protein synthesis underlies long-term memory processes. Calcium (Ca²⁺) plays an important role in a variety of neuronal functions and indirect evidence suggests that it may be involved in synaptic plasticity and in the regulation of gene expression correlated to long-term memory formation. The aim of this study was to determine whether Ca²⁺is necessary and sufficient for inducing long-term memory formation. A suitable model to address this question is the Pavlovian appetitive conditioning of the proboscis extension reflex in the honeybee <it>Apis mellifera, </it>in which animals learn to associate an odor with a sucrose reward.</p> <p>Results</p> <p>By modulating the intracellular Ca²⁺concentration ([Ca²⁺]i) in the brain, we show that: (i) blocking [Ca²⁺]i increase during multiple-trial conditioning selectively impairs long-term memory performance; (ii) conversely, increasing [Ca²⁺]i during single-trial conditioning triggers long-term memory formation; and finally, (iii) as was the case for long-term memory produced by multiple-trial conditioning, enhancement of long-term memory performance induced by a [Ca²⁺]i increase depends on <it>de novo </it>protein synthesis.</p> <p>Conclusion</p> <p>Altogether our data suggest that during olfactory conditioning Ca²⁺is both a necessary and a sufficient signal for the formation of protein-dependent long-term memory. Ca²⁺therefore appears to act as a switch between short- and long-term storage of learned information.</p

Integration of Parallel Opposing Memories Underlies Memory Extinction.

Accurately predicting an outcome requires that animals learn supporting and conflicting evidence from sequential experience. In mammals and invertebrates, learned fear responses can be suppressed by experiencing predictive cues without punishment, a process called memory extinction. Here, we show that extinction of aversive memories in Drosophila requires specific dopaminergic neurons, which indicate that omission of punishment is remembered as a positive experience. Functional imaging revealed co-existence of intracellular calcium traces in different places in the mushroom body output neuron network for both the original aversive memory and a new appetitive extinction memory. Light and ultrastructural anatomy are consistent with parallel competing memories being combined within mushroom body output neurons that direct avoidance. Indeed, extinction-evoked plasticity in a pair of these neurons neutralizes the potentiated odor response imposed in the network by aversive learning. Therefore, flies track the accuracy of learned expectations by accumulating and integrating memories of conflicting events.S.W. was funded by a Wellcome Principal Research Fellowship (200846/Z/16/Z), by the Gatsby Charitable Foundation (GAT3237), and by the Bettencourt-Schueller Foundation. J.F. was supported by the DFG (FE 1563/1-1). G.S.X.E.J. was funded by Medical Research Council. D.D.B. funded by HHMI. G.S.X.E.J., D.D.B., and S.W. were funded by a Wellcome Collaborative Award (203261/Z/16/Z)

Associative memory: without a trace

Some transient sensory stimuli can cause prolonged activity in the brain. Trace conditioning experiments can reveal the time over which these lasting representations can be utilized and where they reside

Modulation of aversive value coding in the vertebrate and invertebrate brain

International audienceAvoiding potentially dangerous situations is key for the survival of any organism. Throughout life, animals learn to avoid environments, stimuli or actions that can lead to bodily harm. While the neural bases for appetitive learning, evaluation and valuebased decision-making have received much attention, recent studies have revealed more complex computations for aversive signals during learning and decision-making than previously thought. Furthermore, previous experience, internal state and systems level appetitive-aversive interactions seem crucial for learning specific aversive value signals and making appropriate choices. The emergence of novel methodologies (computation analysis coupled with large-scale neuronal recordings, neuronal manipulations at unprecedented resolution offered by genetics, viral strategies and connectomics) has helped to provide novel circuit-based models for aversive (and appetitive) valuation. In this review, we focus on recent vertebrate and invertebrate studies yielding strong evidence that aversive value information can be computed by a multitude of interacting brain regions, and that past experience can modulate future aversive learning and therefore influence value-based decisions

Estimating replicability of classifier learning experiments

Replicability of machine learning experiments measures how likely it is that the outcome of one experiment is repeated when performed with a different randomization of the data. In this paper, we present an estimator of replicability of an experiment that is efficient. More precisely, the estimator is unbiased and has lowest variance in the class of estimators formed by a linear combination of outcomes of experiments on a given data set. We gathered empirical data for comparing experiments consisting of different sampling schemes and hypothesis tests. Both factors are shown to have an impact on replicability of experiments. The data suggests that sign tests should not be used due to low replicability. Ranked sum tests show better performance, but the combination of a sorted runs sampling scheme with a t-test gives the most desirable performance judged on Type I and II error and replicability

Un preprocesseur parallele pour le logiciel de mecanique des fluides HPCN3S

SIGLEAvailable from INIST (FR), Document Supply Service, under shelf-number : 26165 F, issue : a.1997 n.48 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Fiber based sensors for the monitoring of liquid Nitrogen levels

Fiber based sensors for the monitoring of liquid Nitrogen levels

Study of Earth and Jupiter-like plasmas for atmospheric entries using a non-transferred arc torch

International audienceThis paper presents the results obtained by a 100 kW non-transferred arc plasma torch dedicated to the studies of plasmas characteristics of atmospheric entries of spatial probes, especially Earth and Jupiter entries. Spectra acquisition of the produced plasmas is achieved using optical emission spectroscopy. For Earth entry conditions, air plasma was obtained with a maximal temperature around 6800 K with a good agreement using atomic lines of oxygen and nitrogen (and also copper coming from electrode's ablation) and molecular bands of N2, CN and $\text{N}_{2}^{+}$ , testifying to a good thermal equilibrium. As the first step in the study of Jupiter atmospheric entry, pure helium plasma was produced with the same maximal temperature of about 7500 K. Helium plasma was achieved for the first time using the plasma torch. Recorded spectra show a continuum, He I lines as well as copper. He II lines are not detected