A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory

Feature Model Differences

International audienceFeature models are a widespread means to represent commonality and variability in software product lines. As is the case for other kinds of models, computing and managing feature model differences is useful in various real-world situations. In this paper, we propose a set of novel differencing techniques that combine syntactic and semantic mechanisms, and automatically produce meaningful differences. Practitioners can exploit our results in various ways: to understand, manipulate, visualize and reason about differences. They can also combine them with existing feature model composition and decomposition operators. The proposed automations rely on satisfiability algorithms. They come with a dedicated language and a comprehensive environment. We illustrate and evaluate the practical usage of our techniques through a case study dealing with a configurable component framework

Neural precursors of deliberate and arbitrary decisions in the study of voluntary action

The readiness potential (RP)--a key ERP correlate of upcoming action--is known to precede subjects' reports of their decision to move. Some view this as evidence against a causal role for consciousness in human decision-making and thus against free-will. Yet those studies focused on arbitrary decisions--purposeless, unreasoned, and without consequences. It remains unknown to what degree the RP generalizes to deliberate, more ecological decisions. We directly compared deliberate and arbitrary decision-making during a $1000-donation task to non-profit organizations. While we found the expected RPs for arbitrary decisions, they were strikingly absent for deliberate ones. Our results and drift-diffusion model are congruent with the RP representing accumulation of noisy, random fluctuations that drive arbitrary--but not deliberate--decisions. They further point to different neural mechanisms underlying deliberate and arbitrary decisions, challenging the generalizability of studies that argue for no causal role for consciousness in decision-making to real-life decisions

Neural precursors of deliberate and arbitrary decisions in the study of voluntary action

The readiness potential (RP)--a key ERP correlate of upcoming action--is known to precede subjects' reports of their decision to move. Some view this as evidence against a causal role for consciousness in human decision-making and thus against free-will. Yet those studies focused on arbitrary decisions--purposeless, unreasoned, and without consequences. It remains unknown to what degree the RP generalizes to deliberate, more ecological decisions. We directly compared deliberate and arbitrary decision-making during a $1000-donation task to non-profit organizations. While we found the expected RPs for arbitrary decisions, they were strikingly absent for deliberate ones. Our results and drift-diffusion model are congruent with the RP representing accumulation of noisy, random fluctuations that drive arbitrary--but not deliberate--decisions. They further point to different neural mechanisms underlying deliberate and arbitrary decisions, challenging the generalizability of studies that argue for no causal role for consciousness in decision-making to real-life decisions

Analysing observed star cluster SEDs with evolutionary synthesis models: systematic uncertainties

The definitive version is available at www.blackwell-synergy.com. Copyright Blackwell Publishing DOI : 10.1111/j.1365-2966.2004.07197.xWe discuss the systematic uncertainties inherent to analyses of observed (broad-band) Spectral Energy Distributions (SEDs) of star clusters with evolutionary synthesis models. We investigate the effects caused by restricting oneself to a limited number of available passbands, choices of various passband combinations, finite observational errors, non-continuous model input parameter values, and restrictions in parameter space allowed during analysis. Starting from a complete set of UBVRIJH passbands (respectively their Hubble Space Telescope/WFPC2 equivalents) we investigate to which extent clusters with different combinations of age, metallicity, internal extinction and mass can or cannot be disentangled in the various evolutionary stages throughout their lifetimes and what are the most useful passbands required to resolve the ambi- guities. We find the U and B bands to be of the highest significance, while the V band and near-infrared data provide additional constraints. A code is presented that makes use of luminosities of a star cluster system in all of the possibly available passbands, and tries to find ranges of allowed age-metallicity-extinction-mass combinations for individual members of star cluster systems. Numerous tests and examples are pre- sented. We show the importance of good photometric accuracies and of determining the cluster parameters independently without any prior assumptions.Peer reviewe

Answering a Basic Objection to Bang/Crunch Holography

The current cosmic acceleration does not imply that our Universe is basically de Sitter-like: in the first part of this work we argue that, by introducing matter into *anti-de Sitter* spacetime in a natural way, one may be able to account for the acceleration just as well. However, this leads to a Big Crunch, and the Euclidean versions of Bang/Crunch cosmologies have [apparently] disconnected conformal boundaries. As Maldacena and Maoz have recently stressed, this seems to contradict the holographic principle. In the second part we argue that this "double boundary problem" is a matter not of geometry but rather of how one chooses a conformal compactification: if one chooses to compactify in an unorthodox way, then the appearance of disconnectedness can be regarded as a *coordinate effect*. With the kind of matter we have introduced here, namely a Euclidean axion, the underlying compact Euclidean manifold has an unexpectedly non-trivial topology: it is in fact one of the 75 possible underlying manifolds of flat compact four-dimensional Euclidean spaces.Comment: 29 pages, 3 figures, added references and comparison with "cyclic" cosmology, JHEP versio

Shear and Ellipticity in Gravitational Lenses

Galaxies modeled as singular isothermal ellipsoids with an axis ratio distribution similar to the observed axis ratio distribution of E and S0 galaxies are statistically consistent with both the observed numbers of two-image and four-image lenses and the inferred ellipticities of individual lenses. However, no four-image lens is well fit by the model (typical $\chi^2/N_{dof} \sim 20$), the axis ratio of the model can be significantly different from that of the observed lens galaxy, and the major axes of the model and the galaxy may be slightly misaligned. We found that models with a second, independent, external shear axis could fit the data well (typical $\chi^2/N_{dof} \sim 1$), while adding the same number of extra parameters to the radial mass distribution does not produce such a dramatic improvement in the fit. An independent shear axis can be produced by misalignments between the luminous galaxy and its dark matter halo, or by external shear perturbations due to galaxies and clusters correlated with the primary lens or along the line of sight. We estimate that the external shear perturbations have no significant effect on the expected numbers of two-image and four-image lenses, but that they can be important perturbations in individual lens models. However, the amplitudes of the external shears required to produce the good fits are larger than our estimates for typical external shear perturbations (10-15% shear instead of 1-3% shear) suggesting that the origin of the extra angular structure must be intrinsic to the primary lens galaxy in most cases.Comment: 38 pages, 9 figures, submitted to Ap

Type Ia Supernova Distances at z > 1.5 from the Hubble Space Telescope Multi-Cycle Treasury Programs: The Early Expansion Rate

We present an analysis of 15 Type Ia supernovae (SNe Ia) at redshift z > 1 (9 at 1.5 < z < 2.3) recently discovered in the CANDELS and CLASH Multi-Cycle Treasury programs using WFC3 on the Hubble Space Telescope. We combine these SNe Ia with a new compilation of 1050 SNe Ia, jointly calibrated and corrected for simulated survey biases to produce accurate distance measurements. We present unbiased constraints on the expansion rate at six redshifts in the range 0.07 < z < 1.5 based only on this combined SN Ia sample. The added leverage of our new sample at z > 1.5 leads to a factor of ~3 improvement in the determination of the expansion rate at z = 1.5, reducing its uncertainty to ~20%, a measurement of H(z=1.5)/H0=2.67 (+0.83,-0.52). We then demonstrate that these six measurements alone provide a nearly identical characterization of dark energy as the full SN sample, making them an efficient compression of the SN Ia data. The new sample of SNe Ia at z > 1 usefully distinguishes between alternative cosmological models and unmodeled evolution of the SN Ia distance indicators, placing empirical limits on the latter. Finally, employing a realistic simulation of a potential WFIRST SN survey observing strategy, we forecast optimistic future constraints on the expansion rate from SNe Ia.Comment: 14 pages, 5 figures, 7 tables; submitted to Ap

Supernova Remnants as Clues to Their Progenitors

Supernovae shape the interstellar medium, chemically enrich their host galaxies, and generate powerful interstellar shocks that drive future generations of star formation. The shock produced by a supernova event acts as a type of time machine, probing the mass loss history of the progenitor system back to ages of $\sim$ 10 000 years before the explosion, whereas supernova remnants probe a much earlier stage of stellar evolution, interacting with material expelled during the progenitor's much earlier evolution. In this chapter we will review how observations of supernova remnants allow us to infer fundamental properties of the progenitor system. We will provide detailed examples of how bulk characteristics of a remnant, such as its chemical composition and dynamics, allow us to infer properties of the progenitor evolution. In the latter half of this chapter, we will show how this exercise may be extended from individual objects to SNR as classes of objects, and how there are clear bifurcations in the dynamics and spectral characteristics of core collapse and thermonuclear supernova remnants. We will finish the chapter by touching on recent advances in the modeling of massive stars, and the implications for observable properties of supernovae and their remnants.Comment: A chapter in "Handbook of Supernovae" edited by Athem W. Alsabti and Paul Murdin (18 pages, 6 figures