•We elucidate the neural dynamics of detecting a moving object by a moving observer.•Object detection was predicted by machine learning based on motion-sensitive and fronto-parietal ...areas.•Connectivity verified the cortical dynamics which machine learning relied on.
Relatively little is known about how the human brain identifies movement of objects while the observer is also moving in the environment. This is, ecologically, one of the most fundamental motion processing problems, critical for survival. To study this problem, we used a task which involved nine textured spheres moving in depth, eight simulating the observer’s forward motion while the ninth, the target, moved independently with a different speed towards or away from the observer. Capitalizing on the high temporal resolution of magnetoencephalography (MEG) we trained a Support Vector Classifier (SVC) using the sensor-level data to identify correct and incorrect responses. Using the same MEG data, we addressed the dynamics of cortical processes involved in the detection of the independently moving object and investigated whether we could obtain confirmatory evidence for the brain activity patterns used by the classifier. Our findings indicate that response correctness could be reliably predicted by the SVC, with the highest accuracy during the blank period after motion and preceding the response. The spatial distribution of the areas critical for the correct prediction was similar but not exclusive to areas underlying the evoked activity. Importantly, SVC identified frontal areas otherwise not detected with evoked activity that seem to be important for the successful performance in the task. Dynamic connectivity further supported the involvement of frontal and occipital-temporal areas during the task periods. This is the first study to dynamically map cortical areas using a fully data-driven approach in order to investigate the neural mechanisms involved in the detection of moving objects during observer’s self-motion.
ABSTRACT
We present a study designed to measure the average Lyman-continuum escape fraction (〈fesc〉) of star-forming galaxies at z ≃ 3.5. We assemble a sample of 148 galaxies from the VANDELS ...spectroscopic survey at 3.35 ≤ zspec ≤ 3.95, selected to minimize line-of-sight contamination of their photometry. For this sample, we use ultra-deep, ground-based, U-band imaging and Hubble Space Telescope V-band imaging to robustly measure the distribution of $\mathcal {R_{\rm obs}}\, =(L_{\rm LyC}/L_{\rm UV})_{\rm obs}$. We then model the $\mathcal {R_{\rm obs}}$ distribution as a function of 〈fesc〉, carefully accounting for attenuation by dust, the intergalactic medium and the circumgalactic medium. A maximum likelihood fit to the $\mathcal {R_{\rm obs}}$ distribution returns a best-fitting value of $\langle f_{\rm esc}\rangle =0.07^{+0.02}_{-0.02}$, a result confirmed using an alternative Bayesian inference technique (both techniques exclude 〈fesc〉 = 0.0 at >3σ). By splitting our sample in two, we find evidence that 〈fesc〉 is positively correlated with Ly α equivalent width (Wλ(Ly α)), with high and low Wλ(Lyα) subsamples returning values of $\langle f_{\rm esc}\rangle =0.12^{+0.06}_{-0.04}$ and $\langle f_{\rm esc} \rangle =0.02^{+0.02}_{-0.01}$, respectively. In contrast, we find evidence that 〈fesc〉 is anticorrelated with intrinsic UV luminosity and UV dust attenuation; with low UV luminosity and dust attenuation subsamples both returning best fits in the range 0.10 ≤ 〈fesc〉 ≤ 0.22. We do not find a clear correlation between fesc and galaxy stellar mass, suggesting stellar mass is not a primary indicator of fesc. Although larger samples are needed to further explore these trends, our results suggest that it is entirely plausible that the low dust, low-metallicity galaxies found at z ≥ 6 will display the 〈fesc〉 ≥ 0.1 required to drive reionization.
Abstract
The everyday environment brings to our sensory systems competing inputs from different modalities. The ability to filter these multisensory inputs in order to identify and efficiently ...utilize useful spatial cues is necessary to detect and process the relevant information. In the present study, we investigate how feature-based attention affects the detection of motion across sensory modalities. We were interested to determine how subjects use intramodal, cross-modal auditory, and combined audiovisual motion cues to attend to specific visual motion signals. The results showed that in most cases, both the visual and the auditory cues enhance feature-based orienting to a transparent visual motion pattern presented among distractor motion patterns. Whereas previous studies have shown cross-modal effects of spatial attention, our results demonstrate a spread of cross-modal feature-based attention cues, which have been matched for the detection threshold of the visual target. These effects were very robust in comparisons of the effects of valid vs. invalid cues, as well as in comparisons between cued and uncued valid trials. The effect of intramodal visual, cross-modal auditory, and bimodal cues also increased as a function of motion-cue salience. Our results suggest that orienting to visual motion patterns among distracters can be facilitated not only by intramodal priors, but also by feature-based cross-modal information from the auditory system.
The task of parceling perceived visual motion into self- and object motion components is critical to safe and accurate visually guided navigation. In this paper, we used functional magnetic resonance ...imaging to determine the cortical areas functionally active in this task and the pattern connectivity among them to investigate the cortical regions of interest and networks that allow subjects to detect object motion separately from induced self-motion. Subjects were presented with nine textured objects during simulated forward self-motion and were asked to identify the target object, which had an additional, independent motion component toward or away from the observer. Cortical activation was distributed among occipital, intra-parietal and fronto-parietal areas. We performed a network analysis of connectivity data derived from partial correlation and multivariate Granger causality analyses among functionally active areas. This revealed four coarsely separated network clusters: bilateral V1 and V2; visually responsive occipito-temporal areas, including bilateral LO, V3A, KO (V3B) and hMT; bilateral VIP, DIPSM and right precuneus; and a cluster of higher, primarily left hemispheric regions, including the central sulcus, post-, pre- and sub-central sulci, pre-central gyrus, and FEF. We suggest that the visually responsive networks are involved in forming the representation of the visual stimulus, while the higher, left hemisphere cluster is involved in mediating the interpretation of the stimulus for action. Our main focus was on the relationships of activations during our task among the visually responsive areas. To determine the properties of the mechanism corresponding to the visual processing networks, we compared subjects’ psychophysical performance to a model of object motion detection based solely on relative motion among objects and found that it was inconsistent with observer performance. Our results support the use of scene context (e.g., eccentricity, depth) in the detection of object motion. We suggest that the cortical activation and visually responsive networks provide a potential substrate for this computation.
Context. The study of statistically significant samples of star-forming dwarf galaxies (SFDGs) at different cosmic epochs is essential for the detailed understanding of galaxy assembly and chemical ...evolution. However, the main properties of this large population of galaxies at intermediate redshift are still poorly known. Aims. We present the discovery and spectrophotometric characterization of a large sample of 164 faint (iAB~ 23–25 mag) SFDGs at redshift 0.13 ≤ z ≤ 0.88 selected by the presence of bright optical emission lines in the VIMOS Ultra Deep Survey (VUDS). We investigate their integrated physical properties and ionization conditions, which are used to discuss the low-mass end of the mass-metallicity relation (MZR) and other key scaling relations. Methods. We use optical VUDS spectra in the COSMOS, VVDS-02h, and ECDF-S fields, as well as deep multi-wavelength photometry that includes HST-ACS F814W imaging, to derive stellar masses, extinction-corrected star-formation rates (SFR), and gas-phase metallicities of SFDGs. For the latter, we use the direct method and a Te-consistent approach based on the comparison of a set of observed emission lines ratios with the predictions of detailed photoionization models. Results. The VUDS SFDGs are compact (median re~ 1.2 kpc), low-mass (M∗~ 107–109M⊙) galaxies with a wide range of star-formation rates (SFR(Hα) ~ 10-3–101M⊙/yr) and morphologies. Overall, they show a broad range of subsolar metallicities (12 +log (O/H) =7.26–8.7; 0.04 ≲Z/Z⊙≲ 1). Nearly half of the sample are extreme emission-line galaxies (EELGs) characterized by high equivalent widths and emission line ratios indicative of higher excitation and ionization conditions. The MZR of SFDGs shows a flatter slope compared to previous studies of galaxies in the same mass range and redshift. We find the scatter of the MZR is partly explained in the low mass range by varying specific SFRs and gas fractions amongst the galaxies in our sample. In agreement with recent studies, we find the subclass of EELGs to be systematically offset to lower metallicity compared to SFDGs at a given stellar mass and SFR, suggesting a younger starburst phase. Compared with simple chemical evolution models we find that most SFDGs do not follow the predictions of a “closed-box” model, but those from a gas-regulating model in which gas flows are considered. While strong stellar feedback may produce large-scale outflows favoring the cessation of vigorous star formation and promoting the removal of metals, younger and more metal-poor dwarfs may have recently accreted large amounts of fresh, very metal-poor gas, that is used to fuel current star formation.
This paper deals with the discrete counterpart of 2D elliptic model problems rewritten in terms of Boundary Integral Equations. The study is done within the framework of Isogeometric Analysis based ...on B-splines. In such a context, the problem of constructing appropriate, accurate and efficient quadrature rules for the Symmetric Galerkin Boundary Element Method is here investigated. The new integration schemes, together with row assembly and sum factorization, are used to build a more efficient strategy to derive the final linear system of equations. Key ingredients are weighted quadrature rules tailored for B-splines, that are constructed to be exact in the whole test space, also with respect to the singular kernel. Several simulations are presented and discussed, showing accurate evaluation of the involved integrals and outlining the superiority of the new approach in terms of computational cost and elapsed time with respect to the standard element-by-element assembly.
We identified hyaluronan synthase-2 (Has2) as a likely source of hyaluronan (HA) during embryonic development, and we used gene targeting to study its function in vivo. Has2(-/-) embryos lack HA, ...exhibit severe cardiac and vascular abnormalities, and die during midgestation (E9.5-10). Heart explants from Has2(-/-) embryos lack the characteristic transformation of cardiac endothelial cells into mesenchyme, an essential developmental event that depends on receptor-mediated intracellular signaling. This defect is reproduced by expression of a dominant-negative Ras in wild-type heart explants, and is reversed in Has2(-/-) explants by gene rescue, by administering exogenous HA, or by expressing activated Ras. Conversely, transformation in Has2(-/-) explants mediated by exogenous HA is inhibited by dominant-negative Ras. Collectively, our results demonstrate the importance of HA in mammalian embryogenesis and the pivotal role of Has2 during mammalian development. They also reveal a previously unrecognized pathway for cell migration and invasion that is HA-dependent and involves Ras activation.
Purpose
The aim of this study was to assess the neurologic outcome following extracorporeal cardiopulmonary resuscitation (ECPR) in five European centers.
Methods
Retrospective database analysis of ...prospective observational cohorts of patients undergoing ECPR (January 2012–December 2016) was performed. The primary outcome was 3-month favorable neurologic outcome (FO), defined as the cerebral performance categories of 1–2. Survival to ICU discharge and the number of patients undergoing organ donation were secondary outcomes. A subgroup of patients with stringent selection criteria (i.e., age ≤ 65 years, witnessed bystander CPR, no major co-morbidity and ECMO implemented within 1 h from arrest) was also analyzed.
Results
A total of 423 patients treated with ECPR were included (median age 57 48–65 years; male gender 78%); ECPR was initiated for OHCA in 258 (61%) patients. Time from arrest to ECMO implementation was 65 48–84 min. Eighty patients (19%) had favorable neurological outcome. ICU survival was 24% (
n
= 102); 23 (5%) non-survivors underwent organ donation procedures. Favorable neurological outcome rate was lower (9% vs. 34%,
p
< 0.01) in out-of-hospital than in-hospital cardiac arrest and was significantly associated with shorter time from collapse to ECMO. The application of stringent ECPR criteria (
n
= 105) resulted in 38% of patients with favorable neurologic outcome.
Conclusions
ECPR was associated with intact neurological recovery in 19% of unselected cardiac arrest victims, with 38% favorable outcome if stringent selection criteria would have been applied.
In humans, as well as most animal species, perception of object motion is critical to successful interaction with the surrounding environment. Yet, as the observer also moves, the retinal projections ...of the various motion components add to each other and extracting accurate object motion becomes computationally challenging. Recent psychophysical studies have demonstrated that observers use a flow-parsing mechanism to estimate and subtract self-motion from the optic flow field. We investigated whether concurrent acoustic cues for motion can facilitate visual flow parsing, thereby enhancing the detection of moving objects during simulated self-motion. Participants identified an object (the target) that moved either forward or backward within a visual scene containing nine identical textured objects simulating forward observer translation. We found that spatially co-localized, directionally congruent, moving auditory stimuli enhanced object motion detection. Interestingly, subjects who performed poorly on the visual-only task benefited more from the addition of moving auditory stimuli. When auditory stimuli were not co-localized to the visual target, improvements in detection rates were weak. Taken together, these results suggest that parsing object motion from self-motion-induced optic flow can operate on multisensory object representations.
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