136 research outputs found

    Functional differences between statistical learning with and without explicit training.

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    Humans are capable of rapidly extracting regularities from environmental input, a process known as statistical learning. This type of learning typically occurs automatically, through passive exposure to environmental input. The presumed function of statistical learning is to optimize processing, allowing the brain to more accurately predict and prepare for incoming input. In this study, we ask whether the function of statistical learning may be enhanced through supplementary explicit training, in which underlying regularities are explicitly taught rather than simply abstracted through exposure. Learners were randomly assigned either to an explicit group or an implicit group. All learners were exposed to a continuous stream of repeating nonsense words. Prior to this implicit training, learners in the explicit group received supplementary explicit training on the nonsense words. Statistical learning was assessed through a speeded reaction-time (RT) task, which measured the extent to which learners used acquired statistical knowledge to optimize online processing. Both RTs and brain potentials revealed significant differences in online processing as a function of training condition. RTs showed a crossover interaction; responses in the explicit group were faster to predictable targets and marginally slower to less predictable targets relative to responses in the implicit group. P300 potentials to predictable targets were larger in the explicit group than in the implicit group, suggesting greater recruitment of controlled, effortful processes. Taken together, these results suggest that information abstracted through passive exposure during statistical learning may be processed more automatically and with less effort than information that is acquired explicitly

    Implicit and explicit contributions to statistical learning.

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    Statistical learning allows learners to detect regularities in the environment and appears to emerge automatically as a consequence of experience. Statistical learning paradigms bear many similarities to those of artificial grammar learning and other types of implicit learning. However, whether learning effects in statistical learning tasks are driven by implicit knowledge has not been thoroughly examined. The present study addressed this gap by examining the role of implicit and explicit knowledge within the context of a typical auditory statistical learning paradigm. Learners were exposed to a continuous stream of repeating nonsense words. Learning was tested (a) directly via a forced-choice recognition test combined with a remember/know procedure and (b) indirectly through a novel reaction time (RT) test. Behavior and brain potentials revealed statistical learning effects with both tests. On the recognition test, accurate responses were associated with subjective feelings of stronger recollection, and learned nonsense words relative to nonword foils elicited an enhanced late positive potential indicative of explicit knowledge. On the RT test, both RTs and P300 amplitudes differed as a function of syllable position, reflecting facilitation attributable to statistical learning. Explicit stimulus recognition did not correlate with RT or P300 effects on the RT test. These results provide evidence that explicit knowledge is accrued during statistical learning, while bringing out the possibility that dissociable implicit representations are acquired in parallel. The commonly used recognition measure primarily reflects explicit knowledge, and thus may underestimate the total amount of knowledge produced by statistical learning. Indirect measures may be more sensitive indices of learning, capturing knowledge above and beyond what is reflected by recognition accuracy

    Proton and Pion Production in Au+Au Collisions at 10.8A GeV/c

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    We present proton and pion tranverse momentum spectra and rapidity distributions for Au+Au collisions at 10.8A GeV/c. The proton spectra exhibit collective transverse flow effects. Evidence of the influence of the Coulomb interaction from the fireball is found in the pion transverse momentum spectra. The data are compared with the predictions of the RQMD event generator.Comment: plain tex (revtex), 24 pages Submitted to Phys. Rev.

    Assessing circadian rhythms in propofol PK and PD during prolonged infusion in ICU patients

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    This study evaluates possible circadian rhythms during prolonged propofol infusion in patients in the intensive care unit. Eleven patients were sedated with a constant propofol infusion. The blood samples for the propofol assay were collected every hour during the second day, the third day, and after the termination of the propofol infusion. Values of electroencephalographic bispectral index (BIS), arterial blood pressure, heart rate, blood oxygen saturation and body temperature were recorded every hour at the blood collection time points. A two-compartment model was used to describe propofol pharmacokinetics. Typical values of the central and peripheral volume of distribution and inter-compartmental clearance were VC = 27.7 l, VT = 801 l, and CLD = 2.73 l/min. The systolic blood pressure (SBP) was found to influence the propofol metabolic clearance according to Cl (l/min) = 2.65·(1 − 0.00714·(SBP − 135)). There was no significant circadian rhythm detected with respect to propofol pharmacokinetics. The BIS score was assessed as a direct effect model with EC50 equal 1.98 mg/l. There was no significant circadian rhythm detected within the BIS scores. We concluded that the light–dark cycle did not influence propofol pharmacokinetics and pharmacodynamics in intensive care units patients. The lack of night–day differences was also noted for systolic blood pressure, diastolic blood pressure and blood oxygenation. Circadian rhythms were detected for heart rate and body temperature, however they were severely disturbed from the pattern of healthy patients

    A depauperate immune repertoire precedes evolution of sociality in bees

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    Background Sociality has many rewards, but can also be dangerous, as high population density and low genetic diversity, common in social insects, is ideal for parasite transmission. Despite this risk, honeybees and other sequenced social insects have far fewer canonical immune genes relative to solitary insects. Social protection from infection, including behavioral responses, may explain this depauperate immune repertoire. Here, based on full genome sequences, we describe the immune repertoire of two ecologically and commercially important bumblebee species that diverged approximately 18 million years ago, the North American Bombus impatiens and European Bombus terrestris. Results We find that the immune systems of these bumblebees, two species of honeybee, and a solitary leafcutting bee, are strikingly similar. Transcriptional assays confirm the expression of many of these genes in an immunological context and more strongly in young queens than males, affirming Bateman’s principle of greater investment in female immunity. We find evidence of positive selection in genes encoding antiviral responses, components of the Toll and JAK/STAT pathways, and serine protease inhibitors in both social and solitary bees. Finally, we detect many genes across pathways that differ in selection between bumblebees and honeybees, or between the social and solitary clades. Conclusions The similarity in immune complement across a gradient of sociality suggests that a reduced immune repertoire predates the evolution of sociality in bees. The differences in selection on immune genes likely reflect divergent pressures exerted by parasites across social contexts
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