We present a method for detection and reconstruction of the gravitational wave (GW) transients with the networks of advanced detectors. Originally designed to search for transients with the initial ...GW detectors, it uses significantly improved algorithms, which enhance both the low-latency searches with rapid localization of GW events for the electromagnetic follow-up and high confidence detection of a broad range of the transient GW sources. In this paper, we present the analytic framework of the method. Following a short description of the core analysis algorithms, we introduce a novel approach to the reconstruction of the GW polarization from a pattern of detector responses to a GW signal. This polarization pattern is a unique signature of an arbitrary GW signal that can be measured independently from the other source parameters. The polarization measurements enable rapid reconstruction of the GW waveforms, sky localization, and helps identification of the source origin.
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In this paper, we investigate the morphology of the events from the GWTC-1 catalog of compact binary coalescences as reconstructed by a method based on coherent excess power: we use an open-source ...version of the coherent WaveBurst (cWB) analysis pipeline, which does not make use of waveform models. The coherent response of the LIGO-Virgo network of detectors is estimated by using loose bounds on the duration and bandwidth of the signal. This pipeline version reproduces the same results that are reported for cWB in recent publications by the LIGO and Virgo collaborations. In particular, the sky localization and waveform reconstruction are in a good agreement with those produced by methods which exploit the detailed theoretical knowledge of the expected waveform for compact binary coalescences. However, in some cases cWB also detects features in excess in well-localized regions of the time-frequency plane. Here we focus on such deviations and present the methods devised to assess their significance. Out of the 11 events reported in the GWTC-1, in two cases-GW151012 and GW151226-cWB detects an excess of coherent energy after the coalescence (Δt≃0.2 and ≃0.1 s, respectively) with p-values that call for further investigations (0.004 and 0.03, respectively), though they are not sufficient to exclude noise fluctuations. We discuss the morphological properties and plausible interpretations of these features. In case they are genuine, we anticipate that several more such outliers will be uncovered by our methodology in the ongoing advanced LIGO-Virgo observation run (O3).
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Decision-making is often viewed as a two-stage process, where subjective values are first assigned to each option and then the option of the highest value is selected. Converging evidence suggests ...that these subjective values are represented in the striatum and medial prefrontal cortex (MPFC). A separate line of evidence suggests that activation in the same areas represents the values of rewards even when choice is not required, as in classical conditioning tasks. However, it is unclear whether the same neural mechanism is engaged in both cases. To address this question we measured brain activation with functional magnetic resonance imaging while human subjects passively viewed individual consumer goods. We then sampled activation from predefined regions of interest and used it to predict subsequent choices between the same items made outside of the scanner. Our results show that activation in the striatum and MPFC in the absence of choice predicts subsequent choices, suggesting that these brain areas represent value in a similar manner whether or not choice is required.
Making appropriate choices often requires the ability to learn the value of available options from experience. Parkinson's disease is characterized by a loss of dopamine neurons in the substantia ...nigra, neurons hypothesized to play a role in reinforcement learning. Although previous studies have shown that Parkinson's patients are impaired in tasks involving learning from feedback, they have not directly tested the widely held hypothesis that dopamine neuron activity specifically encodes the reward prediction error signal used in reinforcement learning models. To test a key prediction of this hypothesis, we fit choice behavior from a dynamic foraging task with reinforcement learning models and show that treatment with dopaminergic drugs alters choice behavior in a manner consistent with the theory. More specifically, we found that dopaminergic drugs selectively modulate learning from positive outcomes. We observed no effect of dopaminergic drugs on learning from negative outcomes. We also found a novel dopamine-dependent effect on decision making that is not accounted for by reinforcement learning models: perseveration in choice, independent of reward history, increases with Parkinson's disease and decreases with dopamine therapy.
Abstract
Gravitational waves (GWs) emitted during the coalescence of binary neutron star (BNS) systems carry information about the equation of state (EoS) describing the extremely dense matter inside ...neutron stars (NSs). In particular, the EoS determines the fate of the binary after the merger: a prompt collapse to black hole (BH), or the formation of a NS remnant that is either stable or survives up to a few seconds before collapsing to a BH. Determining the evolution of a BNS system will therefore place strong constraints on the EoS. We present a morphology-independent method, developed in the framework of the coherentWaveBurst analysis of signals from ground-based interferometric detectors of GWs. The method characterizes the time-frequency postmerger GW emission from a BNS system, and determines whether, after the merger, it formed a remnant NS or promptly collapsed to a BH. We measure the following quantities to characterize the postmerger emission: ratio of signal energies and match of luminosity profile in different frequency bands, weighted central frequency and bandwidth. From these quantities, based on the study of signals simulated through injections of numerical relativity waveforms, we build a statistics to discriminate between the different scenarios after the merger. Finally, we test our method on a set of signals simulated with new models, to estimate its efficiency as a function of the source distance.
It is well known that hormones affect both brain and behavior, but less is known about the extent to which hormones affect economic decision-making. Numerous studies demonstrate gender differences in ...attitudes to risk and loss in financial decision-making, often finding that women are more loss and risk averse than men. It is unclear what drives these effects and whether cyclically varying hormonal differences between men and women contribute to differences in economic preferences. We focus here on how economic rationality and preferences change as a function of menstrual cycle phase in women. We tested adherence to the Generalized Axiom of Revealed Preference (GARP), the standard test of economic rationality. If choices satisfy GARP then there exists a well-behaved utility function that the subject's decisions maximize. We also examined whether risk attitudes and loss aversion change as a function of cycle phase. We found that, despite large fluctuations in hormone levels, women are as technically rational in their choice behavior as their male counterparts at all phases of the menstrual cycle. However, women are more likely to choose risky options that can lead to potential losses while ovulating; during ovulation women are less loss averse than men and therefore more economically rational than men in this regard. These findings may have market-level implications: ovulating women more effectively maximize expected value than do other groups.
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The quest to observe gravitational waves challenges our ability to discriminate signals from detector noise. This issue is especially relevant for transient gravitational waves searches with a robust ...eyes wide open approach, the so called all-sky burst searches. Here we show how signal classification methods inspired by broad astrophysical characteristics can be implemented in all-sky burst searches preserving their generality. In our case study, we apply a multivariate analyses based on artificial neural networks to classify waves emitted in compact binary coalescences. We enhance by orders of magnitude the significance of signals belonging to this broad astrophysical class against the noise background. Alternatively, at a given level of mis-classification of noise events, we can detect about 1/4 more of the total signal population. We also show that a more general strategy of signal classification can actually be performed, by testing the ability of artificial neural networks in discriminating different signal classes. The possible impact on future observations by the LIGO-Virgo network of detectors is discussed by analysing recoloured noise from previous LIGO-Virgo data with coherent WaveBurst, one of the flagship pipelines dedicated to all-sky searches for transient gravitational waves.
The brain adapts to dishonesty Garrett, Neil; Lazzaro, Stephanie C; Ariely, Dan ...
Nature neuroscience,
12/2016, Volume:
19, Issue:
12
Journal Article
Peer reviewed
Open access
Dishonesty is an integral part of our social world, influencing domains ranging from finance and politics to personal relationships. Anecdotally, digressions from a moral code are often described as ...a series of small breaches that grow over time. Here we provide empirical evidence for a gradual escalation of self-serving dishonesty and reveal a neural mechanism supporting it. Behaviorally, we show that the extent to which participants engage in self-serving dishonesty increases with repetition. Using functional MRI, we show that signal reduction in the amygdala is sensitive to the history of dishonest behavior, consistent with adaptation. Critically, the extent of reduced amygdala sensitivity to dishonesty on a present decision relative to the previous one predicts the magnitude of escalation of self-serving dishonesty on the next decision. The findings uncover a biological mechanism that supports a 'slippery slope': what begins as small acts of dishonesty can escalate into larger transgressions.
Smoking cessation is the one of the most important ways to improve the prognosis of patients with respiratory disease. The Task Force on guidelines for smoking cessation in patients with respiratory ...diseases was convened to provide evidence-based recommendations on smoking cessation interventions in respiratory patients. Based on the currently available evidence and the consensus of an expert panel, the following key recommendations were made. 1) Patients with respiratory disease have a greater and more urgent need to stop smoking than the average smoker, so respiratory physicians must take a proactive and continuing role with all smokers in motivating them to stop and in providing treatment to aid smoking cessation. 2) Smoking cessation treatment should be integrated into the management of the patient's respiratory condition. 3) Therapies should include pharmacological treatment (i.e. nicotine replacement therapy, bupropion or varenicline) combined with behavioural support. 4) Respiratory physicians should receive training to ensure that they have the knowledge, attitudes and skills necessary to deliver these interventions or to refer to an appropriate specialist. 5) Although the cost of implementing these recommendations will partly be offset by a reduction in attendance for exacerbations, etc., a budget should be established to enable implementation. Research is needed to establish optimum treatment strategies specifically for respiratory patients.
Abstract
As the Advanced LIGO and Advanced Virgo interferometers, soon to be joined by the KAGRA interferometer, increase their sensitivity, they detect an ever-larger number of gravitational waves ...with a significant presence of higher multipoles (HMs) in addition to the dominant (2, 2) multipole. These HMs can be detected with different approaches, such as the minimally-modeled burst search methods, and here we discuss one such approach based on the coherent WaveBurst (cWB) pipeline. During the inspiral phase the HMs produce chirps whose instantaneous frequency is a multiple of the dominant (2, 2) multipole, and here we describe how cWB can be used to detect these spectral features. The search is performed within suitable regions of the time-frequency representation; their shape is determined by optimizing the receiver operating characteristics. This novel method has already been used in the GW190814 discovery paper (Abbott
et al
2020
Astrophys. J. Lett.
896
L44) and is very fast and flexible. Here we describe in full detail the procedure used to detect the (3, 3) multipole in GW190814 as well as searches for other HMs during the inspiral phase, and apply it to another event that displays HMs, GW190412, replicating the results obtained with different methods. The procedure described here can be used for the fast analysis of HMs and to support the findings obtained with the model-based Bayesian parameter estimates.
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