13 research outputs found

    Development of a Possible General Magnitude System for Number and Space

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    There is strong evidence for a link between numerical and spatial processing. However, whether this association is based on a common general magnitude system is far from conclusive and the impact of development is not yet known. Hence, the present study aimed to investigate the association between discrete non-symbolic number processing (comparison of dot arrays) and continuous spatial processing (comparison of angle sizes) in children between the third and sixth grade (N = 367). Present findings suggest that the processing of comparisons of number of dots or angle are related to each other, but with angle processing developing earlier and being more easily comparable than discrete number representations for children of this age range. Accordingly, results favor the existence of a more complex underlying magnitude system consisting of dissociated but closely interacting representations for continuous and discrete magnitudes

    Resisting Sleep Pressure:Impact on Resting State Functional Network Connectivity

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    In today's 24/7 society, sleep restriction is a common phenomenon which leads to increased levels of sleep pressure in daily life. However, the magnitude and extent of impairment of brain functioning due to increased sleep pressure is still not completely understood. Resting state network (RSN) analyses have become increasingly popular because they allow us to investigate brain activity patterns in the absence of a specific task and to identify changes under different levels of vigilance (e.g. due to increased sleep pressure). RSNs are commonly derived from BOLD fMRI signals but studies progressively also employ cerebral blood flow (CBF) signals. To investigate the impact of sleep pressure on RSNs, we examined RSNs of participants under high (19 h awake) and normal (10 h awake) sleep pressure with three imaging modalities (arterial spin labeling, BOLD, pseudo BOLD) while providing confirmation of vigilance states in most conditions. We demonstrated that CBF and pseudo BOLD signals (measured with arterial spin labeling) are suited to derive independent component analysis based RSNs. The spatial map differences of these RSNs were rather small, suggesting a strong biological substrate underlying these networks. Interestingly, increased sleep pressure, namely longer time awake, specifically changed the functional network connectivity (FNC) between RSNs. In summary, all FNCs of the default mode network with any other network or component showed increasing effects as a function of increased 'time awake'. All other FNCs became more anti-correlated with increased 'time awake'. The sensorimotor networks were the only ones who showed a within network change of FNC, namely decreased connectivity as function of 'time awake'. These specific changes of FNC could reflect both compensatory mechanisms aiming to fight sleep as well as a first reduction of consciousness while becoming drowsy. We think that the specific changes observed in functional network connectivity could imply an impairment of information transfer between the affected RSNs

    Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: findings from the ENIGMA ADHD, ASD, and OCD Working Groups

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    Objective Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders. Methods Structural T1-weighted whole-brain MRI of controls (n=5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures). Results We found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed. Conclusion Our findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders

    Development of a Possible General Magnitude System for Number and Space

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    There is strong evidence for a link between numerical and spatial processing. However, whether this association is based on a common general magnitude system is far from conclusive and the impact of development is not yet known. Hence, the present study aimed to investigate the association between discrete non-symbolic number processing (comparison of dot arrays) and continuous spatial processing (comparison of angle sizes) in children between the third and sixth grade (N = 367). Present findings suggest that the processing of comparisons of number of dots or angle are related to each other, but with angle processing developing earlier and being more easily comparable than discrete number representations for children of this age range. Accordingly, results favor the existence of a more complex underlying magnitude system consisting of dissociated but closely interacting representations for continuous and discrete magnitudes

    Altered white matter microstructure is related to cognition in adults with congenital heart disease

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    Adults with congenital heart disease are at risk for persisting executive function deficits, which are known to affect academic achievement and quality of life. Alterations in white -matter microstructure are associated with cognitive impairments in adolescents with congenital heart disease. This study aimed to identify microstructural alterations potentially associated with executive function deficits in adults with congenital heart disease. Diffusion tensor imaging and tract-based spatial statistics were conducted in 45 patients (18 females) and 54 healthy controls (26 females) aged 18–32 years. Fractional anisotropy of white matter diffusion was compared between groups and correlated with an executive function score, derived from an extensive neuropsychological test battery. Patients showed widespread bilateral reduction in fractional anisotropy (P < 0.05, multiple comparison corrected) compared to controls. Lower fractional anisotropy was driven by patients with moderate and severe defect complexity (compared to controls: P < 0.001). Executive function scores were lower in patients (P < 0.05) and associated with lower fractional anisotropy in the left superior corona radiata and the corticospinal tract (corrected P < 0.05). Our findings confirm alterations of white matter microstructure in adults with congenital heart disease, mainly in those patients of moderate to severe complexity. These alterations are associated with impairments in executive functioning. A better understanding of the neurocognitive deficits may help counselling and care of patients with congenital heart disease across their lifespan and have the potential to improve their outcome and quality of life

    Mitochondrial Transporter Defects: Successful Treatment with Ketogenic Diet Therapy

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    Background/Purpose: No causal treatment for mitochondrial disease exists. Exome sequencing allows to identify specific mitochondrial defects (theoretically) amenable to dietary intervention. The mitochondrial transporters aspartate glutamate carrier 1 (AGC1) and mitochondrial pyruvate carrier 1 (MPC1) are tightly linked to glucose catabolism. Successful pathomechanism-based treatment of such defects with ketogenic diet (KD) was reported in two patients with AGC1-deficiency and a MPC1-deficient mouse model. Methods: The Munich exome database was queried for AGC1- and MPC1-deficient patients. Clinical and neuroradiological details were collected and literature cases reviewed. Results: Six MPC1-deficient individuals (4 reported, 2 novel) were identified and outcome on KD reported in 2 (1 novel). The phenotype beside developmental impairment (6/6) and elevated serum lactate (6/6) was variable with epilepsy (3/6), microcephaly (3/6), and the first report of one patient with splenomegaly, diabetes mellitus and bone fractures. In contrast to the previously reported infant, our severely affected patient improved distinctly on KD, with seizure freedom and developmental progress. Thirteen AGC1-deficient individuals (8 reported, 5 novel) were identified. Seven of 13 received KD. All had infantile-onset epilepsy, severe developmental impairment and muscular hypotonia. MRI revealed brain atrophy (9/9) and reduced myelination (7/9), MRS showed reduced n-acetyl-aspartate (5/6). Elevated serum lactate was found in 8 of 13. In six of seven patients, KD showed impressive improvement on seizure frequency, development, and neuroradiological features. Conclusion: Treatment with KD is beneficial in patients with AGC1 and MPC1 deficiency. This underlines the importance for early genetic diagnostics in patients with epilepsy especially with additional markers raising suspicion of mitochondrial disease

    Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis

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    Attention-deficit/hyperactivity disorder (ADHD) affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences of the disorder, it is not clear if adults with ADHD have similar neuroanatomical differences as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural differences for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that are common to ADHD in childhood and adulthood. These results support the continuity of ADHD’s brain differences from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity.publishedVersio
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