12,995 research outputs found

    ADHD-200 Patient Characterization and Classification using Resting State Networks: A Dissertation

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    Attention Deficit/Hyperactivity Disorder (ADHD) is a common psychiatric disorder of childhood that is characterized by symptoms of inattention, impulsivity/hyperactivity, or a combination of both. Intrinsic brain dysfunction in ADHD can be examined through various methods including resting state functional Magnetic Resonance Imaging (rs-fMRI), which investigates patients’ functional brain connections in the absence of an explicit task. To date, studies of group differences in resting brain connectivity between patients with ADHD and typically developing controls (TDCs) have revealed reduced connectivity within the Default Mode Network (DMN), a resting state network implicated in introspection, mind-wandering, and day-dreaming. However, few studies have addressed the use of resting state connectivity measures as a diagnostic aide for ADHD on the individual patient level. In the current work, we attempted first to characterize the differences in resting state networks, including the DMN and three attention networks (the salience network, the left executive network, and the right executive network), between a group of youth with ADHD and a group of TDCs matched for age, IQ, gender, and handedness. Significant over- and under-connections were found in the ADHD group in all of these networks compared with TDCs. We then attempted to use a support vector machine (SVM) based on the information extracted from resting state network connectivity to classify participants as “ADHD” or “TDC.” The IFGmiddle temporal network (66.8% accuracy), the parietal association network (86.6% specificity and 48.5% PPV), and a physiological noise component (sensitivity 39.7% and NPV 69.6%) performed the best classifications. Finally, we attempted to combine and utilize information from all the resting state networks that we identified to improve classification accuracy. Contrary to our hypothesis, classification accuracy decreased to 54-55% when this information was combined. Overall, the work presented here supports the theory that the ADHD brain is differently connected at rest than that of TDCs, and that this information may be useful for developing a diagnostic aid. However, because ADHD is such a heterogeneous disorder, each ADHD patient’s underlying brain deficits may be unique making it difficult to determine what connectivity information is diagnostically useful

    Network-Level Structural Abnormalities of Cerebral Cortex in Type 1 Diabetes Mellitus

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    Type 1 diabetes mellitus (T1DM) usually begins in childhood and adolescence and causes lifelong damage to several major organs including the brain. Despite increasing evidence of T1DM-induced structural deficits in cortical regions implicated in higher cognitive and emotional functions, little is known whether and how the structural connectivity between these regions is altered in the T1DM brain. Using inter-regional covariance of cortical thickness measurements from high-resolution T1-weighted magnetic resonance data, we examined the topological organizations of cortical structural networks in 81 T1DM patients and 38 healthy subjects. We found a relative absence of hierarchically high-level hubs in the prefrontal lobe of T1DM patients, which suggests ineffective top-down control of the prefrontal cortex in T1DM. Furthermore, inter-network connections between the strategic/executive control system and systems subserving other cortical functions including language and mnemonic/emotional processing were also less integrated in T1DM patients than in healthy individuals. The current results provide structural evidence for T1DM-related dysfunctional cortical organization, which specifically underlie the top-down cognitive control of language, memory, and emotion. © 2013 Lyoo et al

    Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting state study of attention, default mode and salience network connectivity

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    Deficits in task-related attentional engagement in attention-deficit/hyperactivity disorder (ADHD) have been hypothesized to be due to altered interrelationships between attention, default mode and salience networks. We examined the intrinsic connectivity during rest within and between these networks. Six minutes resting state scans were obtained. Using a network-based approach, connectivity within and between the dorsal and ventral attention, the default mode and the salience networks was compared between the ADHD and control group. The ADHD group displayed hyperconnectivity between the two attention networks and within the default mode and ventral attention network. The salience network was hypoconnected to the dorsal attention network. There were trends towards hyperconnectivity within the dorsal attention network and between the salience and ventral attention network in ADHD. Connectivity within and between other networks was unrelated to ADHD. Our findings highlight the altered connectivity within and between attention networks, and between them and the salience network in ADHD. One hypothesis to be tested in future studies is that individuals with ADHD are affected by an imbalance between ventral and dorsal attention systems with the former playing a dominant role during task engagement making individuals with ADHD highly susceptible to distraction by salient task-irrelevant stimuli

    Environmental and genetic influences on neurocognitive development: the importance of multiple methodologies and time-dependent intervention

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    Genetic mutations and environmental factors dynamically influence gene expression and developmental trajectories at the neural, cognitive, and behavioral levels. The examples in this article cover different periods of neurocognitive development—early childhood, adolescence, and adulthood—and focus on studies in which researchers have used a variety of methodologies to illustrate the early effects of socioeconomic status and stress on brain function, as well as how allelic differences explain why some individuals respond to intervention and others do not. These studies highlight how similar behaviors can be driven by different underlying neural processes and show how a neurocomputational model of early development can account for neurodevelopmental syndromes, such as autism spectrum disorders, with novel implications for intervention. Finally, these studies illustrate the importance of the timing of environmental and genetic factors on development, consistent with our view that phenotypes are emergent, not predetermined

    Conservative and disruptive modes of adolescent change in human brain functional connectivity

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    Adolescent changes in human brain function are not entirely understood. Here, we used multiecho functional MRI (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in 298 healthy adolescents scanned 520 times. Participants were aged 14 to 26 y and were scanned on 1 to 3 occasions at least 6 mo apart. We found 2 distinct modes of age-related change in FC: “conservative” and “disruptive.” Conservative development was characteristic of primary cortex, which was strongly connected at 14 y and became even more connected in the period from 14 to 26 y. Disruptive development was characteristic of association cortex and subcortical regions, where connectivity was remodeled: connections that were weak at 14 y became stronger during adolescence, and connections that were strong at 14 y became weaker. These modes of development were quantified using the maturational index (MI), estimated as Spearman’s correlation between edgewise baseline FC (at 14 y, FC14) and adolescent change in FC (ΔFC14−26), at each region. Disruptive systems (with negative MI) were activated by social cognition and autobiographical memory tasks in prior fMRI data and significantly colocated with prior maps of aerobic glycolysis (AG), AG-related gene expression, postnatal cortical surface expansion, and adolescent shrinkage of cortical thickness. The presence of these 2 modes of development was robust to numerous sensitivity analyses. We conclude that human brain organization is disrupted during adolescence by remodeling of FC between association cortical and subcortical areas

    Cortical thickness and sulcal depth: insights on development and psychopathology in paediatric epilepsy.

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    BackgroundThe relationship between cortical thickness (CThick) and sulcal depth (SDepth) changes across brain regions during development. Epilepsy youth have CThick and SDepth abnormalities and prevalent psychiatric disorders.AimsThis study compared the CThick-SDepth relationship in children with focal epilepsy with typically developing children (TDC) and the role played by seizure and psychopathology variables.MethodA surface-based, computational high-resolution three-dimesional (3D) magnetic resonance image analytic technique compared regional CThick-SDepth relationships in 42 participants with focal epilepsy and 46 TDC (6-16 years) imaged in a 1.5 Tesla scanner. Psychiatric interviews administered to each participant yielded psychiatric diagnoses. Parents provided seizure-related information.ResultsThe TDC group alone demonstrated a significant negative medial fronto-orbital CThick-SDepth correlation. Focal epilepsy participants with but not without psychiatric diagnoses showed significant positive pre-central and post-central CThick-SDepth associations not found in TDC. Although the history of prolonged seizures was significantly associated with the post-central CThick-SDepth correlation, it was unrelated to the presence/absence of psychiatric diagnoses.ConclusionsAbnormal CThick-SDepth pre-central and post-central associations might be a psychopathology biomarker in paediatric focal epilepsy.Declaration interestNone.Copyright and usage© 2015 The Royal College of Psychiatrists. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence

    History of early life adversity is associated with increased food addiction and sex-specific alterations in reward network connectivity in obesity.

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    Background:Neuroimaging studies have identified obesity-related differences in the brain's resting state activity. An imbalance between homeostatic and reward aspects of ingestive behaviour may contribute to obesity and food addiction. The interactions between early life adversity (ELA), the reward network and food addiction were investigated to identify obesity and sex-related differences, which may drive obesity and food addiction. Methods:Functional resting state magnetic resonance imaging was acquired in 186 participants (high body mass index [BMI]: ≥25: 53 women and 54 men; normal BMI: 18.50-24.99: 49 women and 30 men). Participants completed questionnaires to assess ELA (Early Traumatic Inventory) and food addiction (Yale Food Addiction Scale). A tripartite network analysis based on graph theory was used to investigate the interaction between ELA, brain connectivity and food addiction. Interactions were determined by computing Spearman rank correlations, thresholded at q < 0.05 corrected for multiple comparisons. Results:Participants with high BMI demonstrate an association between ELA and food addiction, with reward regions playing a role in this interaction. Among women with high BMI, increased ELA was associated with increased centrality of reward and emotion regulation regions. Men with high BMI showed associations between ELA and food addiction with somatosensory regions playing a role in this interaction. Conclusions:The findings suggest that ELA may alter brain networks, leading to increased vulnerability for food addiction and obesity later in life. These alterations are sex specific and involve brain regions influenced by dopaminergic or serotonergic signalling
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