Search results
Found 16123 matches for
Neighbourhood Poverty, Work Commitment and Unemployment in Early Adulthood: A Longitudinal Study into the Moderating Effect of Personality.
We studied how personality moderates the effect of neighbourhood disadvantage on work commitment and unemployment in early adulthood. Using a personality typology of resilients, overcontrollers, and undercontrollers, we hypothesised that the association between neighbourhood poverty and both work commitment and unemployment would be stronger for overcontrollers and undercontrollers than for resilients. We used longitudinal data (N = 249) to test whether the length of exposure to neighbourhood poverty between age 16 and 21 predicts work commitment and unemployment at age 25. In line with our hypothesis, the findings showed that longer exposure was related to weaker work commitment among undercontrollers and overcontrollers and to higher unemployment among undercontrollers. Resilients' work commitment and unemployment were not predicted by neighbourhood poverty.
Being Poorer Than the Rest of the Neighborhood: Relative Deprivation and Problem Behavior of Youth.
According to the neighborhood effects hypothesis, there is a negative relation between neighborhood wealth and youth's problem behavior. It is often assumed that there are more problems in deprived neighborhoods, but there are also reports of higher rates of behavioral problems in more affluent neighborhoods. Much of this literature does not take into account relative wealth. Our central question was whether the economic position of adolescents' families, relative to the neighborhood in which they lived, was related to adolescents' internalizing and externalizing problem behavior. We used longitudinal data for youth between 12-16 and 16-20 years of age, combined with population register data (N = 926; 55% females). We employ between-within models to account for time-invariant confounders, including parental background characteristics. Our findings show that, for adolescents, moving to a more affluent neighborhood was related to increased levels of depression, social phobia, aggression, and conflict with fathers and mothers. This could be indirect evidence for the relative deprivation mechanism, but we could not confirm this, and we did not find any gender differences. The results do suggest that future research should further investigate the role of individuals' relative position in their neighborhood in order not to overgeneralize neighborhood effects and to find out for whom neighborhoods matter.
Using path signatures to predict a diagnosis of Alzheimer's disease.
The path signature is a means of feature generation that can encode nonlinear interactions in data in addition to the usual linear terms. It provides interpretable features and its output is a fixed length vector irrespective of the number of input points or their sample times. In this paper we use the path signature to provide features for identifying people whose diagnosis subsequently converts to Alzheimer's disease. In two separate classification tasks we distinguish converters from 1) healthy individuals, and 2) individuals with mild cognitive impairment. The data used are time-ordered measurements of the whole brain, ventricles and hippocampus from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We find two nonlinear interactions which are predictive in both cases. The first interaction is change of hippocampal volume with time, and the second is a change of hippocampal volume relative to the volume of the whole brain. While hippocampal and brain volume changes are well known in Alzheimer's disease, we demonstrate the power of the path signature in their identification and analysis without manual feature selection. Sequential data is becoming increasingly available as monitoring technology is applied, and the path signature method is shown to be a useful tool in the processing of this data.
Optimising the acceptability and feasibility of acceptance and commitment therapy for treatment-resistant generalised anxiety disorder in older adults.
BACKGROUND: generalised anxiety disorder (GAD) is common in later life with a prevalence of 3-12%. Many only partially respond to cognitive behavioural therapy or pharmacotherapy and can be classified as treatment resistant. These patients experience poor quality of life, and are at increased risk of comorbid depression, falls and loneliness. Acceptance and commitment therapy (ACT) is an emerging therapy, which may be particularly suited to this population, but has not been tailored to their needs. OBJECTIVES: to optimise the acceptability and feasibility of ACT for older adults with treatment-resistant GAD. DESIGN: a person-based approach to ground the adapted ACT intervention in the perspectives and lives of those who will use it. METHODS: first, we conducted qualitative interviews with 15 older adults with GAD and 36 healthcare professionals to develop guiding principles to inform the intervention. Second, we consulted service users and clinical experts and interviewed the same 15 older adults using 'think aloud' techniques to enhance its acceptability and feasibility. RESULTS: in Stage 1, older adults' concerns and needs were categorised in four themes: 'Expert in one's own condition', 'Deep seated coping strategies', 'Expert in therapy' and 'Support with implementation'. In Stage 2, implications for therapy were identified that included an early focus on values and ACT as a collaborative partnership, examining beliefs around 'self as worrier' and the role of avoidance, validating and accommodating individuals' knowledge and experience and compensating for age-related cognitive changes. DISCUSSION: Our systematic approach combined rigour and transparency to develop a therapeutic intervention tailored to the specific needs of older adults with treatment-resistant GAD.
A randomized control trial of phototherapy and 20% albumin versus phototherapy and saline in Kilifi, Kenya.
OBJECTIVE: The study evaluated the efficacy of phototherapy and 20% albumin infusion to reduce total serum bilirubin (TSB) in neonates with severe hyperbilirubinemia. The primary outcome was a reduction of TSB at the end of treatment. The secondary outcomes were the need for exchange transfusion, inpatient mortality, neurological outcomes at discharge, and development outcomes at 12-months follow-up. RESULTS: One hundred and eighteen neonates were randomly assigned to phototherapy and 20% albumin (n = 59) and phototherapy and saline (n = 69). The median age at admission was 5 (interquartile range (IQR) 3-6) days, and the median gestation was 36 (IQR 36-38) weeks. No significant differences were found in the change in TSB (Mann-Whitney U =609, p = 0.98) and rate of change in TSB per hour after treatment (Mann-Whitney U = 540, p = 0.39) between the two groups. There were no significant differences between the two groups in the proportion of participants who required exchange transfusion (χ2 (2) = 0.36, p = 0.546); repeat phototherapy (χ2 (2) = 2.37, p = 0.123); and those who died (χ2 (2) = 0.92, p = 0.337). Trial registration The trial was registered in the International Standardized Randomized Controlled Trial Number (ISRCTN); trial registration number ISRCTN89732754.
Musical interaction is influenced by underlying predictive models and musical expertise.
Musical interaction is a unique model for understanding humans' ability to align goals, intentions, and actions, which also allows for the manipulation of participants' internal predictive models of upcoming events. Here we used polyrhythms to construct two joint finger tapping tasks that even when rhythmically dissimilar resulted in equal inter-tap intervals (ITIs). Thus, behaviourally a dyad of two musicians tap isochronously at the same rate, yet with their own distinct rhythmical context model (RCM). We recruited 22 highly skilled musicians (in 11 dyads) and contrasted the effect of having a shared versus non-shared RCM on dyads' synchronization behaviour. As expected, tapping synchronization was significantly worse at the start of trials with non-shared models compared to trials with a shared model. However, the musicians were able to quickly recover when holding dissimilar predictive models. We characterised the directionality in the tapping behaviour of the dyads and found patterns mostly of mutual adaptation. Yet, in a subset of dyads primarily consisting of drummers, we found significantly different synchronization patterns, suggesting that instrument expertise can significantly affect synchronization strategies. Overall, this demonstrates that holding different predictive models impacts synchronization in musicians performing joint finger tapping.
Reliable local dynamics in the brain across sessions are revealed by whole-brain modeling of resting state activity.
Resting state fMRI is a tool for studying the functional organization of the human brain. Ongoing brain activity at "rest" is highly dynamic, but procedures such as correlation or independent component analysis treat functional connectivity (FC) as if, theoretically, it is stationary and therefore the fluctuations observed in FC are thought as noise. Consequently, FC is not usually used as a single-subject level marker and it is limited to group studies. Here we develop an imaging-based technique capable of reliably portraying information of local dynamics at a single-subject level by using a whole-brain model of ongoing dynamics that estimates a local parameter, which reflects if each brain region presents stable, asynchronous or transitory oscillations. Using 50 longitudinal resting-state sessions of one single subject and single resting-state sessions from a group of 50 participants we demonstrate that brain dynamics can be quantified consistently with respect to group dynamics using a scanning time of 20 min. We show that brain hubs are closer to a transition point between synchronous and asynchronous oscillatory dynamics and that dynamics in frontal areas have larger heterogeneity in its values compared to other lobules. Nevertheless, frontal regions and hubs showed higher consistency within the same subject while the inter-session variability found in primary visual and motor areas was only as high as the one found across subjects. The framework presented here can be used to study functional brain dynamics at group and, more importantly, at individual level, opening new avenues for possible clinical applications.
Pessimistic outcome expectancy does not explain ambiguity aversion in decision-making under uncertainty.
When faced with a decision, most people like to know the odds and prefer to avoid ambiguity. It has been suggested that this aversion to ambiguity is linked to people's assumption of worst possible outcomes. We used two closely linked behavioural tasks in 78 healthy participants to investigate whether such pessimistic prior beliefs can explain ambiguity aversion. In the risk-taking task, participants had to decide whether or not they place a bet, while in the beliefs task, participants were asked what they believed would be the outcome. Unexpectedly, we found that in the beliefs task, participants were not overly pessimistic about the outcome in the ambiguity condition and in fact closer to optimal levels of decision-making than in the risk conditions. While individual differences in pessimism could explain outcome expectancy, they had no effect on ambiguity aversion. Consequently, ambiguity aversion is more likely caused by general caution than by expectation of negative outcomes despite pessimism-dependent subjective weighting of probabilities.
Reduced structural connectivity in Insomnia Disorder
<jats:title>Abstract</jats:title><jats:p>Insomnia Disorder is the most prevalent sleep disorder and it involves both sleep difficulties and daytime complaints. The neural underpinnings of Insomnia Disorder are poorly understood. Existing neuroimaging studies are limited by their focus on local measures and specific regions of interests. To address this shortcoming, we applied a data-driven approach to assess differences in whole-brain structural connectivity between adults with Insomnia Disorder and matched controls without sleep complaints. We used diffusion tensor imaging and probabilistic tractography to assess whole-brain structural connectivity and examined group differences using Network-Based Statistics. The results revealed a significant difference in the structural connectivity of the two groups. Participants with Insomnia Disorder showed reduced connectivity in a subnetwork that was largely left lateralized, including mainly fronto-subcortical connections with the insula as a key region. By taking a whole-brain network perspective, our study succeeds at integrating previous inconsistent findings, and our results reveal that reduced structural connectivity of the left insula and the connections between frontal and subcortical regions are central neurobiological features of Insomnia Disorder. The importance of these areas for interoception, emotional processing, stress responses and the generation of slow wave sleep may help guide the development of neurobiology-based models of the highly prevalent condition of Insomnia Disorder.</jats:p>
The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core
<jats:title>Abstract</jats:title><jats:p>In the human brain, spontaneous activity during resting state consists of rapid transitions between functional network states over time but the underlying mechanisms are not understood. We use connectome based computational brain network modeling to reveal fundamental principles of how the human brain generates large-scale activity observable by noninvasive neuroimaging. By including individual structural and functional neuroimaging data into brain network models we construct personalized brain models. With this novel approach, we reveal that the human brain during resting state operates at maximum metastability, i.e. in a state of maximum network switching. In addition, we investigate cortical heterogeneity across areas. Optimization of the spectral characteristics of each local brain region revealed the dynamical cortical core of the human brain, which is driving the activity of the rest of the whole brain. Personalized brain network modelling goes beyond correlational neuroimaging analysis and reveals non-trivial network mechanisms underlying non-invasive observations. Our novel findings significantly pertain to the important role of computational connectomics in understanding principles of brain function.</jats:p>
Brain songs framework used for discovering the relevant timescale of the human brain.
A key unresolved problem in neuroscience is to determine the relevant timescale for understanding spatiotemporal dynamics across the whole brain. While resting state fMRI reveals networks at an ultraslow timescale (below 0.1 Hz), other neuroimaging modalities such as MEG and EEG suggest that much faster timescales may be equally or more relevant for discovering spatiotemporal structure. Here, we introduce a novel way to generate whole-brain neural dynamical activity at the millisecond scale from fMRI signals. This method allows us to study the different timescales through binning the output of the model. These timescales can then be investigated using a method (poetically named brain songs) to extract the spacetime motifs at a given timescale. Using independent measures of entropy and hierarchy to characterize the richness of the dynamical repertoire, we show that both methods find a similar optimum at a timescale of around 200 ms in resting state and in task data.
Altered ability to access a clinically relevant control network in patients remitted from major depressive disorder.
Neurobiological models to explain vulnerability of major depressive disorder (MDD) are scarce and previous functional magnetic resonance imaging studies mostly examined "static" functional connectivity (FC). Knowing that FC constantly evolves over time, it becomes important to assess how FC dynamically differs in remitted-MDD patients vulnerable for new depressive episodes. Using a recently developed method to examine dynamic FC, we characterized re-emerging FC states during rest in 51 antidepressant-free MDD patients at high risk of recurrence (≥2 previous episodes), and 35 healthy controls. We examined differences in occurrence, duration, and switching profiles of FC states after neutral and sad mood induction. Remitted MDD patients showed a decreased probability of an FC state (p < 0.005) consisting of an extensive network connecting frontal areas-important for cognitive control-with default mode network, striatum, and salience areas, involved in emotional and self-referential processing. Even when this FC state was observed in patients, it lasted shorter (p < 0.005) and was less likely to switch to a smaller prefrontal-striatum network (p < 0.005). Differences between patients and controls decreased after sad mood induction. Further, the duration of this FC state increased in remitted patients after sad mood induction but not in controls (p < 0.05). Our findings suggest reduced ability of remitted-MDD patients, in neutral mood, to access a clinically relevant control network involved in the interplay between externally and internally oriented attention. When recovering from sad mood, remitted recurrent MDD appears to employ a compensatory mechanism to access this FC state. This study provides a novel neurobiological profile of MDD vulnerability.
Short-Term Orchestral Music Training Modulates Hyperactivity and Inhibitory Control in School-Age Children: A Longitudinal Behavioural Study.
Survey studies have shown that participating in music groups produces several benefits, such as discipline, cooperation and responsibility. Accordingly, recent longitudinal studies showed that orchestral music training has a positive impact on inhibitory control in school-age children. However, most of these studies examined long periods of training not always feasible for all families and institutions and focused on children's measures ignoring the viewpoint of the teachers. Considering the crucial role of inhibitory control on hyperactivity, inattention and impulsivity, we wanted to explore if short orchestral music training would promote a reduction of these impulsive behaviors in children. This study involved 113 Italian children from 8 to 10 years of age. 55 of them attended 3 months of orchestral music training. The training included a 2-hour lesson per week at school and a final concert. The 58 children in the control group did not have any orchestral music training. All children were administered tests and questionnaires measuring inhibitory control and hyperactivity near the beginning and end of the 3-month training period. We also collected information regarding the levels of hyperactivity of the children as perceived by the teachers at both time points. Children in the music group showed a significant improvement in inhibitory control. Moreover, in the second measurement the control group showed an increase in self-reported hyperactivity that was not found in the group undergoing the music training program. This change was not noticed by the teachers, implying a discrepancy between self-reported and observed behavior at school. Our results suggest that even an intense and brief period of orchestral music training is sufficient to facilitate the development of inhibitory control by modulating the levels of self-reported hyperactivity. This research has implications for music pedagogy and education especially in children with high hyperactivity. Future investigations will test whether the findings can be extended to children diagnosed with ADHD.
A randomized controlled trial of bedtime music for insomnia disorder.
Music is often used as a self-help tool to alleviate insomnia. To evaluate the effect of bedtime music listening as a strategy for improving insomnia, we conducted an assessor-blinded randomized controlled trial. Fifty-seven persons with insomnia disorder were included and randomized to music intervention (n = 19), audiobook control (n = 19) or a waitlist control group (n = 19). The primary outcome measure was the Insomnia Severity Index. In addition, we used polysomnography and actigraphy to evaluate objective measures of sleep, and assessed sleep quality and quality of life. The results showed no clear effect of music on insomnia symptoms as the group × time interaction only approached significance (effect size = 0.71, p = .06), though there was a significant improvement in insomnia severity within the music group. With regard to the secondary outcomes, we found a significant effect of the music intervention on perceived sleep improvement and quality of life, but no changes in the objective measures of sleep. In conclusion, music listening at bedtime appears to have a positive impact on sleep perception and quality of life, but no clear effect on insomnia severity. Music is safe and easy to administer, but further research is needed to assess the effect of music on different insomnia subtypes, and as an adjunctive or preventive intervention.
Realizing the Clinical Potential of Computational Psychiatry: Report from the Banbury Center Meeting, February 2019
<p>In February 2019 a workshop was convened at the Banbury Centre at Cold Spring Harbor, NY. The purpose of the meeting was to identify key developments required in the practice and infrastructure of computational psychiatry research to accelerate its ability to address real world clinical problems in the near future. This report provides a summary of the conclusions of the meeting. At its core are suggestions to improve the measurement properties of computational assays through a rapid, iterative process that leverages coordinated waves of online and clinical testing, followed by deployment of the assays in innovative study designs to address clinically relevant questions. We particularly focus on theory-driven tasks but, where possible, the potential of data-driven approaches is also highlighted. Finally, the report suggests that for the promise of computational psychiatry to be realized, the research environment must be developed to encourage large-scale, collaborative, interdisciplinary consortia.</p>
Side effect profile and comparative tolerability of 21 antidepressants in the acute treatment of major depression in adults: protocol for a network meta-analysis.
INTRODUCTION: We have recently compared all second-generation as well as selected first-generation antidepressants in terms of efficacy and acceptability in the acute treatment of major depression. Here we present a protocol for a network meta-analysis aimed at extending these results, updating the evidence base and comparing all second-generation as well as selected first-generation antidepressants in terms of specific adverse events and tolerability in the acute treatment of major depression in adults. METHODS AND ANALYSIS: We will include all double-blind randomised controlled trials comparing one active drug with another or with placebo in the acute treatment major depression in adults. We will compare the following active agents: agomelatine, amitriptyline, bupropion, citalopram, clomipramine, desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, milnacipran, mirtazapine, nefazodone, paroxetine, reboxetine, sertraline, trazodone, venlafaxine, vilazodone and vortioxetine. The main outcomes will include the total number of patients experiencing specific adverse events; experiencing serious adverse events; and experiencing at least one adverse event. Published and unpublished studies will be retrieved through relevant database searches, trial registries and websites; reference selection and data extraction will be completed by at least two independent reviewers. For each outcome we will undertake a network meta-analysis to synthesise all evidence. We will use local and global methods to evaluate consistency. We will perform all analyses in R. We will assess the quality of evidence contributing to network estimates with the Confidence in Network Meta-Analysis web application. DISCUSSION: This work will provide an in- depth analysis and an insight into the specific adverse events of individual antidepressants. ETHICS AND DISSEMINATION: This review does not require ethical approval. PROSPERO REGISTRATION NUMBER: CRD42019128141.