Normative Evidence Accumulation in Unpredictable Environments

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals

Temporal variability in a synfire chain model of birdsong

https://doi.org/10.1186/1471-2202-9-S1-P2

Topographic and Stochastic Influences on Pahoehoe Lava Lobe Emplacement

A detailed understanding of phoehoe emplacement is necessary for developing accurate models of flow field development, assessing hazards, and interpreting the significance of lava morphology on Earth and other planetary surfaces. Active pahoehoe lobes on Kilauea Volcano, Hawaii, were examined on 21-26 February 2006 using oblique time-series stereo-photogrammetry and differential global positioning system (DGPS) measurements. During this time, the local discharge rate for peripheral lava lobes was generally constant at 0.0061 +/- 0.0019 m3/s, but the areal coverage rate of the lobes exhibited a periodic increase every 4.13 +/- 0.64 minutes. This periodicity is attributed to the time required for the pressure within the liquid lava core to exceed the cooling induced strength of its margins. The pahoehoe flow advanced through a series of down slope and cross-slope breakouts, which began as approximately 0.2 m-thick units (i.e., toes) that coalesced and inflated to become approximately meter-thick lobes. The lobes were thickest above the lowest points of the initial topography and above shallow to reverse facing slopes, defined relative to the local flow direction. The flow path was typically controlled by high-standing topography, with the zone directly adjacent to the final lobe margin having an average relief that was a few centimeters higher than the lava inundated region. This suggests that toe-scale topography can, at least temporarily, exert strong controls on pahoehoe flow paths by impeding the lateral spreading of the lobe. Observed cycles of enhanced areal spreading and inflated lobe morphology are also explored using a model that considers the statistical likelihood of sequential breakouts from active flow margins and the effects of topographic barriers

Highly Volcanic Exoplanets, Lava Worlds, and Magma Ocean Worlds:An Emerging Class of Dynamic Exoplanets of Significant Scientific Priority

Highly volcanic exoplanets, which can be variously characterized as 'lava worlds', 'magma ocean worlds', or 'super-Ios' are high priority targets for investigation. The term 'lava world' may refer to any planet with extensive surface lava lakes, while the term 'magma ocean world' refers to planets with global or hemispherical magma oceans at their surface. 'Highly volcanic planets', including super-Ios, may simply have large, or large numbers of, active explosive or extrusive volcanoes of any form. They are plausibly highly diverse, with magmatic processes across a wide range of compositions, temperatures, activity rates, volcanic eruption styles, and background gravitational force magnitudes. Worlds in all these classes are likely to be the most characterizable rocky exoplanets in the near future due to observational advantages that stem from their preferential occurrence in short orbital periods and their bright day-side flux in the infrared. Transit techniques should enable a level of characterization of these worlds analogous to hot Jupiters. Understanding processes on highly volcanic worlds is critical to interpret imminent observations. The physical states of these worlds are likely to inform not just geodynamic processes, but also planet formation, and phenomena crucial to habitability. Volcanic and magmatic activity uniquely allows chemical investigation of otherwise spectroscopically inaccessible interior compositions. These worlds will be vital to assess the degree to which planetary interior element abundances compare to their stellar hosts, and may also offer pathways to study both the very young Earth, and the very early form of many silicate planets where magma oceans and surface lava lakes are expected to be more prevalent. We suggest that highly volcanic worlds may become second only to habitable worlds in terms of both scientific and public long-term interest.Comment: A white paper submitted in response to the National Academy of Sciences 2018 Exoplanet Science Strategy solicitation, from the NASA Sellers Exoplanet Environments Collaboration (SEEC) of the Goddard Space Flight Center. 6 pages, 0 figure

The Molecular Chaperone Hsp90α Is Required for Meiotic Progression of Spermatocytes beyond Pachytene in the Mouse

The molecular chaperone Hsp90 has been found to be essential for viability in all tested eukaryotes, from the budding yeast to Drosophila. In mammals, two genes encode the two highly similar and functionally largely redundant isoforms Hsp90α and Hsp90β. Although they are co-expressed in most if not all cells, their relative levels vary between tissues and during development. Since mouse embryos lacking Hsp90β die at implantation, and despite the fact that Hsp90 inhibitors being tested as anti-cancer agents are relatively well tolerated, the organismic functions of Hsp90 in mammals remain largely unknown. We have generated mouse lines carrying gene trap insertions in the Hsp90α gene to investigate the global functions of this isoform. Surprisingly, mice without Hsp90α are apparently normal, with one major exception. Mutant male mice, whose Hsp90β levels are unchanged, are sterile because of a complete failure to produce sperm. While the development of the male reproductive system appears to be normal, spermatogenesis arrests specifically at the pachytene stage of meiosis I. Over time, the number of spermatocytes and the levels of the meiotic regulators and Hsp90 interactors Hsp70-2, NASP and Cdc2 are reduced. We speculate that Hsp90α may be required to maintain and to activate these regulators and/or to disassemble the synaptonemal complex that holds homologous chromosomes together. The link between fertility and Hsp90 is further supported by our finding that an Hsp90 inhibitor that can cross the blood-testis barrier can partially phenocopy the genetic defects

Food Systems Resilience : Towards an Interdisciplinary Research Agenda

In this article, we offer a contribution to the ongoing study of food by advancing a conceptual framework and interdisciplinary research agenda – what we term ‘food system resilience’. In recent years, the concept of resilience has been extensively used in a variety of fields, but not always consistently or holistically. Here we aim to theorise systematically resilience as an analytical concept as it applies to food systems research. To do this, we engage with and seek to extend current understandings of resilience across different disciplines. Accordingly, we begin by exploring the different ways in which the concept of resilience is understood and used in current academic and practitioner literatures - both as a general concept and as applied specifically to food systems research. We show that the social-ecological perspective, rooted in an appreciation of the complexity of systems, carries significant analytical potential. We first underline what we mean by the food system and relate our understanding of this term to those commonly found in the extant food studies literature. We then apply our conception to the specific case of the UK. Here we distinguish between four subsystems at which our ‘resilient food systems’ can be applied. These are, namely, the agro-food system; the value chain; the retail-consumption nexus; and the governance and regulatory framework. On the basis of this conceptualisation we provide an interdisciplinary research agenda, using the case of the UK to illustrate the sorts of research questions and innovative methodologies that our food systems resilience approach is designed to promote

A Generative Model for Measuring Latent Timing Structure in Motor Sequences

<div><p>Motor variability often reflects a mixture of different neural and peripheral sources operating over a range of timescales. We present a statistical model of sequence timing that can be used to measure three distinct components of timing variability: global tempo changes that are spread across the sequence, such as might stem from neuromodulatory sources with widespread influence; fast, uncorrelated timing noise, stemming from noisy components within the neural system; and timing jitter that does not alter the timing of subsequent elements, such as might be caused by variation in the motor periphery or by measurement error. In addition to quantifying the variability contributed by each of these latent factors in the data, the approach assigns maximum likelihood estimates of each factor on a trial-to-trial basis. We applied the model to adult zebra finch song, a temporally complex behavior with rich structure on multiple timescales. We find that individual song vocalizations (syllables) contain roughly equal amounts of variability in each of the three components while overall song length is dominated by global tempo changes. Across our sample of syllables, both global and independent variability scale with average length while timing jitter does not, a pattern consistent with the Wing and Kristofferson (1973) model of sequence timing. We also find significant day-to-day drift in all three timing sources, but a circadian pattern in tempo only. In tests using artificially generated data, the model successfully separates out the different components with small error. The approach provides a general framework for extracting distinct sources of timing variability within action sequences, and can be applied to neural and behavioral data from a wide array of systems.</p> </div

Circadian rhythm and day-to-day drift in the latent timing variables.

<p>A, Average tempo by hour of the day (defined from lights on) by bird (blue lines) and averaged across birds (black). B, example of day-to-day drift in tempo for one bird over a 1-month period. C, example of drift in independent variability for two different song segments in the same bird. All data in plots A-C are group means from a two-factor ANOVA that have been adjusted for unequal samples of factor combinations (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037616#s2" target="_blank">Results</a>), while dotted lines in B and C indicate adjusted means ± standard error. D, The estimated amount of variance in tempo explained by both hour of the day (black) and day (white) across all 11 birds. E and F, histograms of the amount of variance in the independent and jitter variables respectively, explained by both hour of the day and day (same color code). Generally the data show significant circadian variation in tempo only, and day-to-day drift in all three latent timing variables.</p