We present the results of a search for galaxy substructures in a sample of 11 gravitational lens galaxies from the Sloan Lens ACS Survey by Bolton et al. We find no significant detection of mass ...clumps, except for a luminous satellite in the system SDSS J0956+5110. We use these non-detections, in combination with a previous detection in the system SDSS J0946+1006, to derive constraints on the substructure mass function in massive early-type host galaxies with an average redshift 〈z
lens〉 ∼ 0.2 and an average velocity dispersion 〈σeff〉 ∼ 270 km s−1. We perform a Bayesian inference on the substructure mass function, within a median region of about 32 kpc2 around the Einstein radius (〈R
ein〉 ∼ 4.2 kpc). We infer a mean projected substructure mass fraction f =
$0.0076_{-0.0052}^{+0.0208}$
at the 68 per cent confidence level and a substructure mass function slope α < 2.93 at the 95 per cent confidence level for a uniform prior probability density on α. For a Gaussian prior based on cold dark matter (CDM) simulations, we infer f =
$0.0064^{+0.0080}_{-0.0042}$
and a slope of α =
$1.90^{+0.098}_{-0.098}$
at the 68 per cent confidence level. Since only one substructure was detected in the full sample, we have little information on the mass function slope, which is therefore poorly constrained (i.e. the Bayes factor shows no positive preference for any of the two models). The inferred fraction is consistent with the expectations from CDM simulations and with inference from flux ratio anomalies at the 68 per cent confidence level.
Resting-state functional magnetic resonance imaging (fMRI) has highlighted the rich structure of brain activity in absence of a task or stimulus. A great effort has been dedicated in the last two ...decades to investigate functional connectivity (FC), i.e. the functional interplay between different regions of the brain, which was for a long time assumed to have stationary nature. Only recently was the dynamic behaviour of FC revealed, showing that on top of correlational patterns of spontaneous fMRI signal fluctuations, connectivity between different brain regions exhibits meaningful variations within a typical resting-state fMRI experiment. As a consequence, a considerable amount of work has been directed to assessing and characterising dynamic FC (dFC), and several different approaches were explored to identify relevant FC fluctuations. At the same time, several questions were raised about the nature of dFC, which would be of interest only if brought back to a neural origin. In support of this, correlations with electroencephalography (EEG) recordings, demographic and behavioural data were established, and various clinical applications were explored, where the potential of dFC could be preliminarily demonstrated. In this review, we aim to provide a comprehensive description of the dFC approaches proposed so far, and point at the directions that we see as most promising for the future developments of the field. Advantages and pitfalls of dFC analyses are addressed, helping the readers to orient themselves through the complex web of available methodologies and tools.
Display omitted
•A great effort has been spent on dynamic functional connectivity characterization.•We exhaustively describe existing approaches, their advantages and pitfalls.•We discuss future analytical directions: frame-wise analysis and temporal modeling.•Frame-wise analysis extracts the meaningful functional networks from events.•Temporal modeling parameterizes brain dynamics in flexible and realistic manners.
Modern neuroimaging techniques provide us with unique views on brain structure and function; i.e., how the brain is wired, and where and when activity takes place. Data acquired using these ...techniques can be analyzed in terms of its network structure to reveal organizing principles at the systems level. Graph representations are versatile models where nodes are associated to brain regions and edges to structural or functional connections. Structural graphs model neural pathways in white matter, which are the anatomical backbone between regions. Functional graphs are built based on functional connectivity, which is a pairwise measure of statistical interdependency between pairs of regional activity traces. Therefore, most research to date has focused on analyzing these graphs reflecting structure or function. Graph signal processing (GSP) is an emerging area of research where signals recorded at the nodes of the graph are studied atop the underlying graph structure. An increasing number of fundamental operations have been generalized to the graph setting, allowing to analyze the signals from a new viewpoint. Here, we review GSP for brain imaging data and discuss their potential to integrate brain structure, contained in the graph itself, with brain function, residing in the graph signals. We review how brain activity can be meaningfully filtered based on concepts of spectral modes derived from brain structure. We also derive other operations such as surrogate data generation or decompositions informed by cognitive systems. In sum, GSP offers a novel framework for the analysis of brain imaging data.
Abstract
Alterations in activity and connectivity of brain circuits implicated in emotion processing and emotion regulation have been observed during resting-state for different clinical phases of ...bipolar disorders (BD), but longitudinal investigations across different mood states in the same patients are still rare. Furthermore, measuring dynamics of functional connectivity patterns offers a powerful method to explore changes in the brain’s intrinsic functional organization across mood states. We used a novel co-activation pattern (CAP) analysis to explore the dynamics of amygdala connectivity at rest in a cohort of 20 BD patients prospectively followed-up and scanned across distinct mood states: euthymia (20 patients; 39 sessions), depression (12 patients; 18 sessions), or mania/hypomania (14 patients; 18 sessions). We compared them to 41 healthy controls scanned once or twice (55 sessions). We characterized temporal aspects of dynamic fluctuations in amygdala connectivity over the whole brain as a function of current mood. We identified six distinct networks describing amygdala connectivity, among which an interoceptive-sensorimotor CAP exhibited more frequent occurrences during hypomania compared to other mood states, and predicted more severe symptoms of irritability and motor agitation. In contrast, a default-mode CAP exhibited more frequent occurrences during depression compared to other mood states and compared to controls, with a positive association with depression severity. Our results reveal distinctive interactions between amygdala and distributed brain networks in different mood states, and foster research on interoception and default-mode systems especially during the manic and depressive phase, respectively. Our study also demonstrates the benefits of assessing brain dynamics in BD.
We report the detection of a dark substructure – undetected in the Hubble Space Telescope HST ACS F814W image – in the gravitational lens galaxy SDSSJ0946+1006 (the ‘double Einstein ring’), through ...direct gravitational imaging. The detection of a small mass concentration in the surface density maps, at 4.3 kpc from the galaxy centre, has a strong statistical significance. We confirm this detection by modelling the substructure with a tidally truncated pseudo-Jaffe density profile; in that case the substructure mass is Msub= (3.51 ± 0.15) × 109 M⊙, precisely where also the surface density map shows a strong convergence peak (Bayes factor ; equivalent to a ∼16σ detection). The result is robust under substantial changes in the model. We set a lower limit of (M/L)V,⊙≳ 120 M⊙/LV,⊙ (3σ) inside a sphere of 0.3 kpc centred on the substructure (rtidal= 1.1 kpc). The mass and luminosity limit of this substructure are consistent with Local Group results if the substructure had a virial mass of ∼1010 M⊙ before accretion and formed at z≳ 10. Our detection implies a projected dark matter mass fraction in substructure at the radius of the inner Einstein ring of f= 2.15+2.05−1.25 per cent 68 per cent confidence level (CL) in the mass range 4 × 106– 4 × 109 M⊙, assuming α= 1.9 ± 0.1 (with dN/dm∝m−α). Assuming a flat prior on α, between 1.0 and 3.0, increases this to f= 2.56+3.26−1.50 per cent (68 per cent CL). The likelihood ratio is ∼0.5 between these fractions and that from simulations (fN-body≈ 0.003). Hence the inferred dark matter mass fraction in substructure, admittedly based on a single-lens system, is large but still consistent with predictions.
Stars and dark matter account for most of the mass of early-type galaxies, but uncertainties in the stellar population and the dark matter profile make it challenging to distinguish between the two ...components. Nevertheless, precise observations of stellar and dark matter are extremely valuable for testing the many models of structure formation and evolution. We present a measurement of the stellar mass and inner slope of the dark matter halo of a massive early-type galaxy at z = 0.222. The galaxy is the foreground deflector of the double Einstein ring gravitational lens system SDSSJ0946+1006, also known as the "Jackpot." By combining the tools of lensing and dynamics we first constrain the mean slope of the total mass density profile (rho sub(tot) is proportional to r super(- gamma ')) within the radius of the outer ring to be gamma ' = 1.98 + or - 0.02 + or - 0.01. Then we obtain a bulge-halo decomposition, assuming a power-law form for the dark matter halo. Our analysis yields = 1.7 + or -0.2 for the inner slope of the dark matter profile, in agreement with theoretical findings on the distribution of dark matter in ellipticals, and a stellar mass from lensing and dynamics M super(LD) sub(*) = 5.5 super(+0.4) sub(-1.3) x 10 super(11) M sub(middot in circle). By comparing this measurement with stellar masses inferred from stellar population synthesis fitting we find that a Salpeter initial mass function (IMF) provides a good description of the stellar population of the lens while the probability of the IMF being heavier than Chabrier is 95%. Our data suggest that growth by accretion of small systems from a compact red nugget is a plausible formation scenario for this object.
Idioms of distress communicate suffering via reference to shared ethnopsychologies, and better understanding of idioms of distress can contribute to effective clinical and public health ...communication. This systematic review is a qualitative synthesis of “thinking too much” idioms globally, to determine their applicability and variability across cultures. We searched eight databases and retained publications if they included empirical quantitative, qualitative, or mixed-methods research regarding a “thinking too much” idiom and were in English. In total, 138 publications from 1979 to 2014 met inclusion criteria. We examined the descriptive epidemiology, phenomenology, etiology, and course of “thinking too much” idioms and compared them to psychiatric constructs. “Thinking too much” idioms typically reference ruminative, intrusive, and anxious thoughts and result in a range of perceived complications, physical and mental illnesses, or even death. These idioms appear to have variable overlap with common psychiatric constructs, including depression, anxiety, and PTSD. However, “thinking too much” idioms reflect aspects of experience, distress, and social positioning not captured by psychiatric diagnoses and often show wide within-cultural variation, in addition to between-cultural differences. Taken together, these findings suggest that “thinking too much” should not be interpreted as a gloss for psychiatric disorder nor assumed to be a unitary symptom or syndrome within a culture. We suggest five key ways in which engagement with “thinking too much” idioms can improve global mental health research and interventions: it (1) incorporates a key idiom of distress into measurement and screening to improve validity of efforts at identifying those in need of services and tracking treatment outcomes; (2) facilitates exploration of ethnopsychology in order to bolster cultural appropriateness of interventions; (3) strengthens public health communication to encourage engagement in treatment; (4) reduces stigma by enhancing understanding, promoting treatment-seeking, and avoiding unintentionally contributing to stigmatization; and (5) identifies a key locally salient treatment target.
•Presents first cross-cultural review of the idiom of distress “thinking too much”.•“Thinking too much” idioms are nearly universal yet heterogeneous across settings.•They reference a range of pathological/non-pathological states, not a single psychiatric construct.•They have been used successfully to strengthen measurement scales and clinical interventions.•We highlight strong examples of balancing emic and etic approaches to understanding distress.
Reactive balance, a critical automatic movement pattern in response to a perturbation, is directly linked to fall prevention in older adults. Various exercise interventions have been broadly ...performed to improve reactive balance and thus prevent falls. Curiously, aquatic exercises have been suggested as an effective balance intervention and a safer alternative to exercises on dry land yet the efficacy of aquatic exercises on reactive balance has not been formally investigated. The present clinical trial aims to identify if skills acquired during aquatic exercise are more effectively transferred to a reactive balance task than land exercise. This study is designed as a double-blinded, randomized controlled clinical trial. Forty-four older adults aged 65 years or above who meet the eligibility criteria will be recruited and randomized into an aquatic exercise group or land exercise group. Each group will participate in the same single bout intervention that includes a ball throwing and catching task. A modified lean-and-release test will be implemented on land immediately before, after, and one week after the single bout intervention. The outcomes will include reaction time, rapid response accuracy, and mini-BESTest scores obtained from stepping and grasping reactions. All statistical analyses will be conducted using an intention-to-treat approach. Our conceptual hypothesis is that participants in the aquatic exercise group will demonstrate more improved outcome scores in the lean-and-release test when compared to those in the land exercise group. The results of the present study are expected to provide evidence to support the benefits of aquatic exercises for improving reactive balance in older adults. Further, participants may find aquatic exercises safer and more motivating, thus encouraging them to participate in further aquatic exercise programs.
Erroneous thyroid function test results can occur because of drugs that alter thyroid hormone physiology in one or more aspects, including synthesis, secretion, distribution, and metabolism. Research ...since publication of the last review in the Journal of Veterinary Internal Medicine (JVIM) 20 years ago has evaluated the effects of amiodarone, zonisamide, inhalant anesthetics, clomipramine, trilostane, and toceranib on thyroid function tests in the dog. In addition, recent work on the effects of glucocorticoids, sulfonamides, phenobarbital, and nonsteroidal anti‐inflammatory drugs will be reviewed. Awareness of these effects is necessary to avoid misdiagnosis of hypothyroidism and unnecessary treatment.
We present the current photometric data set for the Sloan Lens ACS (SLACS) Survey, including Hubble Space Telescope (HST) photometry from Advanced Camera for Surveys, WFPC2, and NICMOS. These data ...have enabled the confirmation of an additional 15 grade 'A' (certain) lens systems, bringing the number of SLACS grade 'A' lenses to 85; including 13 grade 'B' (likely) systems, SLACS has identified nearly 100 lenses and lens candidates. Approximately 80% of the grade 'A'systems have elliptical morphologies while ~10% show spiral structure; the remaining lenses have lenticular morphologies. Spectroscopic redshifts for the lens and source are available for every system, making SLACS the largest homogeneous data set of galaxy-scale lenses to date. We have created lens models using singular isothermal ellipsoid mass distributions for the 11 new systems that are dominated by a single mass component and where the multiple images are detected with sufficient signal to noise; these models give a high precision measurement of the mass within the Einstein radius of each lens. We have developed a novel Bayesian stellar population analysis code to determine robust stellar masses with accurate error estimates. We apply this code to deep, high-resolution HST imaging and determine stellar masses with typical statistical errors of 0.1 dex; we find that these stellar masses are unbiased compared to estimates obtained using SDSS photometry, provided that informative priors are used. The stellar masses range from 1010.5 to 1011.8 M and the typical stellar mass fraction within the Einstein radius is 0.4, assuming a Chabrier initial mass function. The ensemble properties of the SLACS lens galaxies, e.g., stellar masses and projected ellipticities, appear to be indistinguishable from other SDSS galaxies with similar stellar velocity dispersions. This further supports that SLACS lenses are representative of the overall population of massive early-type galaxies with M * 1011 M, and are therefore an ideal data set to investigate the kpc-scale distribution of luminous and dark matter in galaxies out to z ~ 0.5.
PDF
