One Thing After Another: Why the Passage of Time Is Not an Illusion

Does time seem to pass, even though it doesn’t, really? Many philosophers think the answer is ‘Yes’—at least when ‘time’s passing’ is understood in a particular way. They take time’s passing to be a process by which each time in turn acquires a special status, such as the status of being the only time that exists, or being the only time that is present. This chapter suggests that, on the contrary, all we perceive is temporal succession, one thing after another, a notion to which modern physics is not inhospitable. The contents of perception are best described in terms of ‘before’ and ‘after’, rather than ‘past’, ‘present, and ‘future’

Human Vision Reconstructs Time to Satisfy Causal Constraints

The goal of perception is to infer the most plausible source of sensory stimulation. Unisensory perception of temporal order, however, appears to require no inference, because the order of events can be uniquely determined from the order in which sensory signals arrive. Here, we demonstrate a novel perceptual illusion that casts doubt on this intuition: In three experiments (N = 607), the experienced event timings were determined by causality in real time. Adult participants viewed a simple three-item sequence, ACB, which is typically remembered as ABC in line with principles of causality. When asked to indicate the time at which events B and C occurred, participants' points of subjective simultaneity shifted so that the assumed cause B appeared earlier and the assumed effect C later, despite participants' full attention and repeated viewings. This first demonstration of causality reversing perceived temporal order cannot be explained by postperceptual distortion, lapsed attention, or saccades

Developmental profile of temporal binding: from childhood to adulthood

Temporal binding refers to a phenomenon whereby the time interval between a cause and its effect is perceived as shorter than the same interval separating two unrelated events. We examined the developmental profile of this phenomenon by comparing the performance of groups of children (aged 6–7, 7–8, and 9–10 years) and adults on a novel interval estimation task. In Experiment 1, participants made judgements about the time interval between (a) their button press and a rocket launch, and (b) a non-causal predictive signal and rocket launch. In Experiment 2, an additional causal condition was included in which participants made judgements about the interval between an experimenter’s button press and the launch of a rocket. Temporal binding was demonstrated consistently and did not change in magnitude with age: estimates of delay were shorter in causal contexts for both adults and children. In addition, the magnitude of the binding effect was greater when participants themselves were the cause of an outcome compared with when they were mere spectators. This suggests that although causality underlies the binding effect, intentional action may modulate its magnitude. Again, this was true of both adults and children. Taken together, these results are the first to suggest that the binding effect is present and developmentally constant from childhood into adulthood

Generative discriminative models for multivariate inference and statistical mapping in medical imaging

This paper presents a general framework for obtaining interpretable multivariate discriminative models that allow efficient statistical inference for neuroimage analysis. The framework, termed generative discriminative machine (GDM), augments discriminative models with a generative regularization term. We demonstrate that the proposed formulation can be optimized in closed form and in dual space, allowing efficient computation for high dimensional neuroimaging datasets. Furthermore, we provide an analytic estimation of the null distribution of the model parameters, which enables efficient statistical inference and p-value computation without the need for permutation testing. We compared the proposed method with both purely generative and discriminative learning methods in two large structural magnetic resonance imaging (sMRI) datasets of Alzheimer's disease (AD) (n=415) and Schizophrenia (n=853). Using the AD dataset, we demonstrated the ability of GDM to robustly handle confounding variations. Using Schizophrenia dataset, we demonstrated the ability of GDM to handle multi-site studies. Taken together, the results underline the potential of the proposed approach for neuroimaging analyses.Comment: To appear in MICCAI 2018 proceeding

Selection of tuning parameters in bridge regression models via Bayesian information criterion

We consider the bridge linear regression modeling, which can produce a sparse or non-sparse model. A crucial point in the model building process is the selection of adjusted parameters including a regularization parameter and a tuning parameter in bridge regression models. The choice of the adjusted parameters can be viewed as a model selection and evaluation problem. We propose a model selection criterion for evaluating bridge regression models in terms of Bayesian approach. This selection criterion enables us to select the adjusted parameters objectively. We investigate the effectiveness of our proposed modeling strategy through some numerical examples.Comment: 20 pages, 5 figure

Clothes size prediction from dressed-human silhouettes

© 2017, Springer International Publishing AG. We propose an effective and efficient way to automatically predict clothes size for users to buy clothes online. We take human height and dressed-human silhouettes in front and side views as input, and estimate 3D body sizes with a data-driven method. We adopt 20 body sizes which are closely related to clothes size, and use such 3D body sizes to get clothes size by searching corresponding size chart. Previous image-based methods need to calibrate camera to estimate 3D information from 2D images, because the same person has different appearances of silhouettes (e.g. size and shape) when the camera configuration (intrinsic and extrinsic parameters) is different. Our method avoids camera calibration, which is much more convenient. We set up our virtual camera and train the relationship between human height and silhouette size under this camera configuration. After estimating silhouette size, we regress the positions of 2D body landmarks. We define 2D body sizes as the distances between corresponding 2D body landmarks. Finally, we learn the relationship between 2D body sizes and 3D body sizes. The training samples for each regression process come from a database of 3D naked and dressed bodies created by previous work. We evaluate the whole procedure and each process of our framework. We also compare the performance with several regression models. The total time-consumption for clothes size prediction is less than 0.1, s and the average estimation error of body sizes is 0.824, cm, which can satisfy the tolerance for customers to shop clothes online

Pain in the Past and Pleasure in the Future : The Development of Past-Future Preferences for Hedonic Goods

It seems self-evident that people prefer painful experiences to be in the past and pleasurable experiences to lie in the future. Indeed, it has been claimed that, for hedonic goods, this preference is absolute (Sullivan, 2018). Yet very little is known about the extent to which people demonstrate explicit preferences regarding the temporal location of hedonic experiences, about the developmental trajectory of such preferences, and about whether such preferences are impervious to differences in the quantity of envisaged past and future pain or pleasure. We find consistent evidence that, all else being equal, adults and children aged 7 and over prefer pleasure to lie in the future and pain in the past and believe that other people will too. They also predict that other people will be happier when pleasure is in the future rather than the past but sadder when pain is the future rather than the past. Younger children have the same temporal preferences as adults for their own painful experiences, but prefer their pleasure to lie in the past, and do not predict that others’ levels of happiness or sadness vary dependent on whether experiences lie in the past or the future. However, from the age of 7, temporal preferences were typically abandoned at the earliest opportunity when the quantity of past pain or pleasure was greater than the quantity located in the future. Past-future preferences for hedonic goods emerge early developmentally but are surprisingly flexible

Cells' Flow and Immune Cell Priming under alternating g-forces in Parabolic Flight

Gravitational stress in general and microgravity (mu g) in particular are regarded as major stress factors responsible for immune system dysfunction in space. To assess the effects of alternating mu g and hypergravity (hyper-g) on immune cells, the attachment of peripheral blood mononuclear cells (PBMCs) to adhesion molecules under flow conditions and the antigen-induced immune activation in whole blood were investigated in parabolic flight (PF). In contrast to hyper-g (1.8 g) and control conditions (1 g), flow and rolling speed of PBMCs were moderately accelerated during mu g-periods which were accompanied by a clear reduction in rolling rate. Whole blood analyses revealed a "primed" state of monocytes after PF with potentiated antigen-induced pro-inflammatory cytokine responses. At the same time, concentrations of anti-inflammatory cytokines were increased and monocytes displayed a surface molecule pattern that indicated immunosuppression. The results suggest an immunologic counterbalance to avoid disproportionate immune responses. Understanding the interrelation of immune system impairing and enhancing effects under different gravitational conditions may support the design of countermeasures to mitigate immune deficiencies in space