Increasing robustness of pairwise methods for effective connectivity in Magnetic Resonance Imaging by using fractional moment series of BOLD signal distributions

Estimating causal interactions in the brain from functional magnetic resonance imaging (fMRI) data remains a challenging task. Multiple studies have demonstrated that all current approaches to determine direction of connectivity perform poorly even when applied to synthetic fMRI datasets. Recent advances in this field include methods for pairwise inference, which involve creating a sparse connectome in the first step, and then using a classifier in order to determine the directionality of connection between of every pair of nodes in the second step. In this work, we introduce an advance to the second step of this procedure, by building a classifier based on fractional moments of the BOLD distribution combined into cumulants. The classifier is trained on datasets generated under the Dynamic Causal Modeling (DCM) generative model. The directionality is inferred based upon statistical dependencies between the two node time series, e.g. assigning a causal link from time series of low variance to time series of high variance. Our approach outperforms or performs as well as other methods for effective connectivity when applied to the benchmark datasets. Crucially, it is also more resilient to confounding effects such as differential noise level across different areas of the connectome.Comment: 41 pages, 12 figure

Disentangling causal webs in the brain using functional Magnetic Resonance Imaging: A review of current approaches

In the past two decades, functional Magnetic Resonance Imaging has been used to relate neuronal network activity to cognitive processing and behaviour. Recently this approach has been augmented by algorithms that allow us to infer causal links between component populations of neuronal networks. Multiple inference procedures have been proposed to approach this research question but so far, each method has limitations when it comes to establishing whole-brain connectivity patterns. In this work, we discuss eight ways to infer causality in fMRI research: Bayesian Nets, Dynamical Causal Modelling, Granger Causality, Likelihood Ratios, LiNGAM, Patel's Tau, Structural Equation Modelling, and Transfer Entropy. We finish with formulating some recommendations for the future directions in this area

Effect of density on house prices in the Randstad region

Increasing degree of urbanization has led to a greater pressure of densification in cities across the world. This underlines the pressing need for socially, economically and environmentally efficient spatial planning. It is believed that compact urban living would provide a desirable outcome in this direction. However, the lack of empirical evidence prevents a thorough investigation of the costs and benefits associated with compact urban living. This study contributes to the debate by measuring the impact of localized urban density and characteristics of urban form on house prices in the four largest cities of the Randstad region, namely, Amsterdam, Rotterdam, The Hague and Utrecht. Our results suggest a negative valuation for density, as measured by the floor space index, in Amsterdam and Rotterdam as opposed to a positive valuation in The Hague and especially Utrecht. To the contrary, the valuation for building height and open space appears to follows a reverse trend, and a preference for greater building height generally aligns with a preference for more open space in the neighborhood. Additionally, our results also indicate a preference for mixed land use in the neighborhood. Amongst the case study areas in this study, Amsterdam represents a high-rise and high density urban form while Utrecht represents a relatively low-rise and low density urban form. We believe that it is this difference in the urban character of cities coupled with heterogeneity in household preferences that leads to the contrasting price effects of density between them. Our results also hint at a sorting phenomenon based on differential preferences for urban design characteristics

Structural brain imaging correlates of ASD and ADHD across the lifespan:a hypothesis-generating review on developmental ASD-ADHD subtypes

Contains fulltext : 169832.pdf (publisher's version ) (Open Access)We hypothesize that it is plausible that biologically distinct developmental ASD-ADHD subtypes are present, each characterized by a distinct time of onset of symptoms, progression and combination of symptoms. The aim of the present narrative review was to explore if structural brain imaging studies may shed light on key brain areas that are linked to both ASD and ADHD symptoms and undergo significant changes during development. These findings may possibly pinpoint to brain mechanisms underlying differential developmental ASD-ADHD subtypes. To this end we brought together the literature on ASD and ADHD structural brain imaging symptoms and particularly highlight the adolescent years and beyond. Findings indicate that the vast majority of existing MRI studies has been cross-sectional and conducted in children, and sometimes did include adolescents as well, but without explicitly documenting on this age group. MRI studies documenting on age effects in adults with ASD and/or ADHD are rare, and if age is taken into account, only linear effects are examined. Data from various studies suggest that a crucial distinctive feature underlying different developmental ASD-ADHD subtypes may be the differential developmental thinning patterns of the anterior cingulate cortex and related connections towards other prefrontal regions. These regions are crucial for the development of cognitive/effortful control and socio-emotional functioning, with impairments in these features as key to both ASD and ADHD

On the way to DSM-V

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Influence of prenatal maternal stress, maternal plasma cortisol and cortisol in the amniotic fluid on birth outcomes and child temperament at 3 months

This prospective, longitudinal study aimed to investigate relationships between indicators of maternal prenatal stress, infant birth outcomes and early temperament. We examined the pattern of associations and postulated pathways between physiological (cortisol plasma concentrations) and self-report indices (stress, anxiety) of maternal prenatal stress, cortisol in the amniotic fluid, birth outcomes and infant temperament at 3 months. The sample consisted of 158 women undergoing amniocentesis in the 2nd trimester of pregnancy. Questionnaire measures of maternal stress and anxiety were found to be unrelated to cortisol in plasma or amniotic fluid. Maternal cortisol was related to amniotic cortisol, which in turn was associated with lower birth weight. Birth weight predicted infant fear and distress to limitation at 3 months old. We found trend-like indirect effects of amniotic fluid on infant distress to limitation and fear via birth weight. This is one of the few studies to simultaneously assess the role of maternal and amniotic fluid cortisol on birth outcomes and infant emotional development. The results suggest that foetal cortisol may be an important predictor of infant outcomes and shed light on the mechanisms through which prenatal maternal stress affects infant psychological health

Reconciling specific and unspecific risk factors: the interplay between theory and data

Contains fulltext : 89487.pdf (publisher's version ) (Closed access)1 juni 201

A Systematic Review of Literatures onFactors Associated with Educational ndAcademic Performance in Attention DeficitHyperactivity Disorder

__Abstract__ Attention Deficit Hyperactivity Disorder (ADHD) has been shown to impair major life activities including educational functioning. However, there is no consensus on the specific cause for the impact on this worse educational outcome. This systematic review aims to identify factors that have been associated with educational and academic underperformance of children and adolescents with ADHD. A literature search was conducted using PubMed and the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The study focused on articles presenting results of data-based analyses related to ADHD and keywords related to education. The search resulted in 376 records that were screened by title. Of these, 185 articles were screened by abstract and 35 met the eligibility criteria for inclusion in the review. These 35 articles were related to seven domains: educational training, educational environment, pharmacological treatment, ADHD symptoms, associations of ADHD with academic outcomes, self-concept, and specific skills. The main source of educational challenges seems to be related to the inattentive symptoms (or subtype) of ADHD. This outcome is different than expected, since hyperactive symptoms are pronounced more prominently and often refer children to clinical practice. Inattentive symptoms amongst others refer to difficulties in organization skills and can lead to decreased self-efficacy and development of depressive symptoms. This decreased self-efficacy and the depressive symptoms were also found to be related to influence the relation between ADHD and academic performance. Educational outcomes were shown to be improved using small group work, learning via a computer-based service and as a result of coaching and pharmacological treatment. To help children and adults achieve educational goals that now are out of reach, more attention should be spent to the inattentive symptoms of ADHD and possibilities to overcome experienced problems

Emotion dysregulation as cross-disorder trait in child psychiatry predicting quality of life and required treatment duration

BACKGROUND: Emotion dysregulation (ED) is increasingly under investigation as a cross-disorder trait, and is by some considered as the core feature in mental disorders. The aims of this study were to scrutinize the overlapping and distinct characteristics of ED for internalizing, externalizing and neurodevelopmental disorders and to identify the most pertinent ED characteristics to guide clinicians in treatment choice.METHODS: Information on clinical diagnosis (Attention Deficit/Hyperactivity Disorder ADHD, Autism Spectrum Disorder, Oppositional Defiant Disorder/Conduct Disorder, Anxiety and Mood Disorders), ED (measured by the CBCL-Emotion Dysregulation Index), Quality of Life (Qol, measured by the Kidscreen-27), and treatment duration (measured by Electronic Health Records) was retrieved from two large samples of toddlers (1.5-5  year old; N  = 1,544) and school aged children (6-18 year old; N  = 7,259). Frequency scores and logistic regression were used to study symptom profiles of ED, as measured with CBCL-EDI, across all disorders. Linear regression was used to determine the predictive value of ED (CBCL-EDI total score) regarding QoL and treatment duration in addition to-and in interaction with-clinical diagnosis. RESULTS: Across disorders, equal levels of total ED were found, which predicted lower QoL and a longer treatment duration in addition to clinical diagnosis. The majority of items (11/15 and 16/18) were of equal relevance to the disorders; items that were not, largely reflected disorder specific DSM definitions (i.e., externalizing symptoms in ODD/CD and internalizing symptoms in Anxiety and Mood disorders).CONCLUSION: ED is a clinically useful cross-disorder trait to predict severity of impairment as well as required treatment duration. In addition, ED is largely composed of shared features across disorders, with certain disorder specific colored elements.</p