Anterior Hippocampus and Goal-Directed Spatial Decision Making

Contains fulltext : 115487.pdf (publisher's version ) (Open Access

Establishing the boundaries: the hippocampal contribution to imagining scenes

When we visualize scenes, either from our own past or invented, we impose a viewpoint for our “mind's eye” and we experience the resulting image as spatially coherent from that viewpoint. The hippocampus has been implicated in this process, but its precise contribution is unknown. We tested a specific hypothesis based on the spatial firing properties of neurons in the hippocampal formation of rats, that this region supports the construction of spatially coherent mental images by representing the locations of the environmental boundaries surrounding our viewpoint. Using functional magnetic resonance imaging, we show that hippocampal activation increases parametrically with the number of enclosing boundaries in the imagined scene. In contrast, hippocampal activity is not modulated by a nonspatial manipulation of scene complexity nor to increasing difficulty of imagining the scenes in general. Our findings identify a specific computational role for the hippocampus in mental imagery and episodic recollection

Generalized statistical mechanics of cosmic rays

We consider a generalized statistical mechanics model for the creation process of cosmic rays which takes into account local temperature fluctuations. This model yields Tsallis statistics for the cosmic ray spectrum. It predicts an entropic index q given by q=11/9 at largest energies (equivalent to a spectral index of alpha=5/2), and an effective temperature given by (5/9)T_H, where kT_H approximately equal to 180 MeV is the Hagedorn temperature measured in collider experiments. Our theoretically obtained formula is in very good agreement with the experimentally measured energy spectrum of primary cosmic rays.Comment: 10 pages, 2 figure

Rapid determination of LISA sensitivity to extreme mass ratio inspirals with machine learning

Gravitational wave observations of the inspiral of stellar-mass compact objects into massive black holes (MBHs), extreme mass ratio inspirals (EMRIs), enable precision measurements of parameters such as the MBH mass and spin. The Laser Interferometer Space Antenna is expected to detect sufficient EMRIs to probe the underlying source population, testing theories of the formation and evolution of MBHs and their environments. Population studies are subject to selection effects that vary across the EMRI parameter space, which bias inference results if unaccounted for. This bias can be corrected, but evaluating the detectability of many EMRI signals is computationally expensive. We mitigate this cost by (i) constructing a rapid and accurate neural network interpolator capable of predicting the signal-to-noise ratio of an EMRI from its parameters, and (ii) further accelerating detectability estimation with a neural network that learns the selection function, leveraging our first neural network for data generation. The resulting framework rapidly estimates the selection function, enabling a full treatment of EMRI detectability in population inference analyses. We apply our method to an astrophysically motivated EMRI population model, demonstrating the potential selection biases and subsequently correcting for them. Accounting for selection effects, we predict that LISA will measure the MBH mass function slope to a precision of 8.8%, the CO mass function slope to a precision of 4.6%, the width of the MBH spin magnitude distribution to a precision of 10% and the event rate to a precision of 12% with EMRIs at redshifts below z=6.Comment: 12 pages, 4 figure

Lie groups in nonequilibrium thermodynamics: Geometric structure behind viscoplasticity

Poisson brackets provide the mathematical structure required to identify the reversible contribution to dynamic phenomena in nonequilibrium thermodynamics. This mathematical structure is deeply linked to Lie groups and their Lie algebras. From the characterization of all the Lie groups associated with a given Lie algebra as quotients of a universal covering group, we obtain a natural classification of rheological models based on the concept of discrete reference states and, in particular, we find a clear-cut and deep distinction between viscoplasticity and viscoelasticity. The abstract ideas are illustrated by a naive toy model of crystal viscoplasticity, but similar kinetic models are also used for modeling the viscoplastic behavior of glasses. We discuss some implications for coarse graining and statistical mechanics.Comment: 11 pages, 1 figure, accepted for publication in J. Non-Newtonian Fluid Mech. Keywords: Elastic-viscoplastic materials, Nonequilibrium thermodynamics, GENERIC, Lie groups, Reference state

A Dataset and an Approach for Identity Resolution of 38 Million Author IDs extracted from 2B Git Commits

The data collected from open source projects provide means to model large software ecosystems, but often suffer from data quality issues, specifically, multiple author identification strings in code commits might actually be associated with one developer. While many methods have been proposed for addressing this problem, they are either heuristics requiring manual tweaking, or require too much calculation time to do pairwise comparisons for 38M author IDs in, for example, the World of Code collection. In this paper, we propose a method that finds all author IDs belonging to a single developer in this entire dataset, and share the list of all author IDs that were found to have aliases. To do this, we first create blocks of potentially connected author IDs and then use a machine learning model to predict which of these potentially related IDs belong to the same developer. We processed around 38 million author IDs and found around 14.8 million IDs to have an alias, which belong to 5.4 million different developers, with the median number of aliases being 2 per developer. This dataset can be used to create more accurate models of developer behaviour at the entire OSS ecosystem level and can be used to provide a service to rapidly resolve new author IDs

Dielectric properties of thin Cr2O3 films grown on elemental and oxide metallic substrates

In an attempt to optimize leakage characteristics of α-Cr2O3 thin films, its dielectric properties were investigated at local and macroscopic scale. The films were grown on Pd(111), Pt(111), and V2O3 (0001), supported on Al2O3 substrate. The local conductivity was measured by conductive atomic force microscopy mapping of Cr2O3 surfaces, which revealed the nature of defects that formed conducting paths with the bottom Pd or Pt layer. A strong correlation was found between these electrical defects and the grain boundaries revealed in the corresponding topographic scans. In comparison, the Cr2O3 film on V2O3 exhibited no leakage paths at similar tip bias value. Electrical resistance measurements through e-beam patterned top electrodes confirmed the resistivity mismatch between the films grown on different electrodes. The x-ray analysis attributes this difference to the twin free Cr2O3 growth on V2O3 seeding

Characteristics of Useful Code Reviews: An Empirical Study at Microsoft

Abstract-Over the past decade, both open source and commercial software projects have adopted contemporary peer code review practices as a quality control mechanism. Prior research has shown that developers spend a large amount of time and effort performing code reviews. Therefore, identifying factors that lead to useful code reviews can benefit projects by increasing code review effectiveness and quality. In a three-stage mixed research study, we qualitatively investigated what aspects of code reviews make them useful to developers, used our findings to build and verify a classification model that can distinguish between useful and not useful code review feedback, and finally we used this classifier to classify review comments enabling us to empirically investigate factors that lead to more effective code review feedback. In total, we analyzed 1.5 millions review comments from five Microsoft projects and uncovered many factors that affect the usefulness of review feedback. For example, we found that the proportion of useful comments made by a reviewer increases dramatically in the first year that he or she is at Microsoft but tends to plateau afterwards. In contrast, we found that the more files that are in a change, the lower the proportion of comments in the code review that will be of value to the author of the change. Based on our findings, we provide recommendations for practitioners to improve effectiveness of code reviews