The Experts below are selected from a list of 2922 Experts worldwide ranked by ideXlab platform
Nicholas P Ryan - One of the best experts on this subject based on the ideXlab platform.
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Executive function mediates the prospective association between neurostructural differences within the Central Executive Network and anti social behavior after childhood traumatic brain injury
Journal of Child Psychology and Psychiatry, 2021Co-Authors: Nicholas P Ryan, Cathy Catroppa, Nathan Hughes, Felicity L Painter, Stephen J C Hearps, Miriam H Beauchamp, Vicki AndersonAbstract:BACKGROUND Despite increasing evidence of a link between early life brain injury and anti-social behavior, very few studies have assessed factors that explain this association in children with traumatic brain injury (TBI). One hypothesis suggests that childhood TBI elevates risk for anti-social behavior via disruption to anatomically distributed neural Networks implicated in Executive functioning (EF). In this longitudinal prospective study, we employed high-resolution structural neuroimaging to (a) evaluate the impact of childhood TBI on regional morphometry of the Central Executive Network (CEN) and (b) evaluate the prediction that lower EF mediates the prospective relationship between structural differences within the CEN and postinjury anti-social behaviors. METHODS This study involved 155 children, including 112 consecutively recruited, hospital-confirmed cases of mild-severe TBI and 43 typically developing control (TDC) children. T1-weighted brain magnetic resonance imaging (MRI) sequences were acquired sub-acutely in a subset of 137 children [TBI: n = 103; TDC: n = 34]. All participants were evaluated using direct assessment of EF 6 months postinjury, and parents provided ratings of anti-social behavior 12 months postinjury. RESULTS Severe TBI was associated with postinjury volumetric differences within the CEN and its putative hub regions. When compared with TD controls, the TBI group had significantly worse EF, which was associated with more frequent anti-social behaviors and abnormal CEN morphometry. Mediation analysis indicated that reduced EF mediated the prospective association between postinjury volumetric differences within the CEN and more frequent anti-social behavior. CONCLUSIONS Our longitudinal prospective findings suggest that detection of neurostructural abnormalities within the CEN may aid in the early identification of children at elevated risk for postinjury Executive dysfunction, which may in turn contribute to chronic anti-social behaviors after early life brain injury. Findings underscore the potential value of early surveillance and preventive measures for children presenting with neurostructural and/or neurocognitive risk factors.
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Executive function mediates the prospective association between neurostructural differences within the Central Executive Network and anti-social behavior after childhood traumatic brain injury.
Journal of child psychology and psychiatry and allied disciplines, 2021Co-Authors: Nicholas P Ryan, Cathy Catroppa, Nathan Hughes, Felicity L Painter, Stephen J C Hearps, Miriam H Beauchamp, Vicki A AndersonAbstract:Despite increasing evidence of a link between early life brain injury and anti-social behavior, very few studies have assessed factors that explain this association in children with traumatic brain injury (TBI). One hypothesis suggests that childhood TBI elevates risk for anti-social behavior via disruption to anatomically distributed neural Networks implicated in Executive functioning (EF). In this longitudinal prospective study, we employed high-resolution structural neuroimaging to (a) evaluate the impact of childhood TBI on regional morphometry of the Central Executive Network (CEN) and (b) evaluate the prediction that lower EF mediates the prospective relationship between structural differences within the CEN and postinjury anti-social behaviors. This study involved 155 children, including 112 consecutively recruited, hospital-confirmed cases of mild-severe TBI and 43 typically developing control (TDC) children. T1-weighted brain magnetic resonance imaging (MRI) sequences were acquired sub-acutely in a subset of 137 children [TBI: n = 103; TDC: n = 34]. All participants were evaluated using direct assessment of EF 6 months postinjury, and parents provided ratings of anti-social behavior 12 months postinjury. Severe TBI was associated with postinjury volumetric differences within the CEN and its putative hub regions. When compared with TD controls, the TBI group had significantly worse EF, which was associated with more frequent anti-social behaviors and abnormal CEN morphometry. Mediation analysis indicated that reduced EF mediated the prospective association between postinjury volumetric differences within the CEN and more frequent anti-social behavior. Our longitudinal prospective findings suggest that detection of neurostructural abnormalities within the CEN may aid in the early identification of children at elevated risk for postinjury Executive dysfunction, which may in turn contribute to chronic anti-social behaviors after early life brain injury. Findings underscore the potential value of early surveillance and preventive measures for children presenting with neurostructural and/or neurocognitive risk factors. © 2021 Association for Child and Adolescent Mental Health.
Dezhong Yao - One of the best experts on this subject based on the ideXlab platform.
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Aberrant Interhemispheric Functional Organization in Children with Dyskinetic Cerebral Palsy.
BioMed research international, 2019Co-Authors: Yun Qin, Cheng Luo, Bo Sun, Huali Zhang, Tao Zhang, Chengyan Sun, Dezhong YaoAbstract:Background. Hemispheric asymmetry is one fundamental principle of neuronal organization. Interhemispheric connectivity and lateralization of intrinsic Networks in the resting-state brain demonstrate the interhemispheric functional organization and can be affected by disease processes. This study aims to investigate the interhemispheric organization in children with dyskinetic cerebral palsy (DCP) based on resting-state functional MRI (fMRI). Methods. 24 children with DCP and 20 healthy children were included. Voxel-mirrored homotopic connectivity (VMHC) was calculated to detect the interhemispheric connectivity, and the lateralization of the resting-state Networks was performed to examine the asymmetry of the intrinsic Networks of brain. Results. Decreased interhemispheric connectivity was found at visual, motor, and motor-control related regions in children with DCP, while high cognitive related Networks including the Central Executive Network, the frontoparietal Network, and the salience Network represented decreased asymmetry in children with DCP. Abnormal VMHC in visual areas, as well as the altered lateralization in inferior parietal lobule and supplementary motor area, showed correlation with the gross motor function and activities of daily living in children with DCP. Conclusion. These findings indicate that the interhemispheric functional organization alteration exists in children with DCP, suggesting that abnormal interhemispheric interaction may be a pathophysiological mechanism of motor and cognitive dysfunction of CP.
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Effects of Cognitive Training on Resting-State Functional Connectivity of Default Mode, Salience, and Central Executive Networks
Frontiers in aging neuroscience, 2016Co-Authors: Weifang Cao, Cheng Luo, Xinyi Cao, Changyue Hou, Yan Cheng, Lijuan Jiang, Dezhong YaoAbstract:Neuroimaging studies have documented that ageing can disrupt certain higher cognitive systems such as the default mode Network (DMN), the salience Network (SN) and the Central Executive Network (CEN). The effect of cognitive training on higher cognitive systems remains unclear. This study used a one-year longitudinal design to explore the cognitive training effect on three higher cognitive Networks in healthy older adults. The community-living healthy older adults were divided into two groups: the multi-domain cognitive training group (24 sessions of cognitive training over a three-month period) and the wait-list control group. All subjects underwent cognitive measurements and resting-state functional magnetic resonance imaging (fMRI) scanning at baseline and at one year after the training ended. We examined training-related changes in functional connectivity (FC) within and between three Networks. Compared with the baseline, we observed maintained or increased FC within all three Networks after training. The scans after training also showed maintained anti-correlation of FC between the DMN and CEN compared to the baseline. These findings demonstrated that cognitive training maintained or improved the functional integration within Networks and the coupling between the DMN and CEN in older adults. Our findings suggested that multi-domain cognitive training can mitigate the ageing-related dysfunction of higher cognitive Networks.
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Functional Integration between Salience and Central Executive Networks: A Role for Action Video Game Experience
Neural Plasticity, 2016Co-Authors: Diankun Gong, Weiyi Ma, Jinnan Gong, Mengting Huang, Dongbo Liu, Jianfu Li, Hui He, Li Dong, Cheng Luo, Dezhong YaoAbstract:Action video games (AVGs) have attracted increasing research attention as they offer a unique perspective into the relation between active learning and neural plasticity. However, little research has examined the relation between AVG experience and the plasticity of neural Network mechanisms. It has been proposed that AVG experience is related to the integration between Salience Network (SN) and Central Executive Network (CEN), which are responsible for attention and working memory, respectively, two cognitive functions essential for AVG playing. This study initiated a systematic investigation of this proposition by analyzing AVG experts’ and amateurs’ resting-state brain functions through graph theoretical analyses and functional connectivity. Results reveal enhanced intra- and interNetwork functional integrations in AVG experts compared to amateurs. The findings support the possible relation between AVG experience and the neural Network plasticity.
Xu Lei - One of the best experts on this subject based on the ideXlab platform.
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Aberrant Awake Spontaneous Brain Activity in Obstructive Sleep Apnea: A Review Focused on Resting-State EEG and Resting-State fMRI.
Frontiers in neurology, 2020Co-Authors: Wenrui Zhao, Xiaoyong Wan, Xinyuan Chen, Xu LeiAbstract:As one of the most common sleep-related respiratory disorders, obstructive sleep apnea (OSA) is characterized by excessive snoring, repetitive apnea, arousal, sleep fragmentation, and intermittent nocturnal hypoxemia. Focused on the resting-state brain imaging techniques, we reviewed the OSA-related resting-state electroencephalogram and resting-state functional magnetic resonance imaging (rsfMRI) studies. Compared with the healthy control group, patients with OSA presented increased frontal and Central δ/θ powers during resting-state wakefulness, and their slow-wave activity showed a positive correlation with apnea-hypopnea index. For rsfMRI, the prefrontal cortex and insula may be the vital regions for OSA and are strongly related to the severity of the disease. Meanwhile, some large-scale brain Networks, such as the default-mode Network, salience Network, and Central Executive Network, play pivotal roles in the pathology of OSA. We then discussed the contribution of resting-state brain imaging as an evaluation approach for disease interventions. Finally, we briefly introduced the effects of OSA-related physiological and mental diseases and discussed some future research directions from the perspective of resting-state brain imaging.
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The brain imaging studies of obstructive sleep apnea: evidence from resting-state EEG and fMRI
Sheng li xue bao : [Acta physiologica Sinica], 2019Co-Authors: Xiaoyong Wan, Wenrui Zhao, Xinyuan Chen, Xu LeiAbstract:Obstructive sleep apnea (OSA) is a common clinic sleep disorder, and characterized by obstruction of upper airway during sleep, resulting in sleep fragmentation and intermittent hypoxemia. We reviewed the brain imaging studies in OSA patients compared with healthy subjects, including studies of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). The resting-state EEG studies showed increased power of δ and θ in the front and Central regions of the cerebral cortex in OSA patients. While resting-state fMRI studies demonstrated altered large-scale Networks in default-mode Network (DMN), Central Executive Network (CEN) and salience Network (SN). Evidence from resting-state studies of both fMRI and EEG focused on the abnormal activity in prefrontal cortex (PFC), which is correlated with OSA severity. These findings suggested that the PFC may play a key role in the abnormal function of OSA patients. Finally, based on the perspectives of treatment effect, multimodal data acquisition, and comorbidities, we discussed the future research direction of the neuroimaging study of OSA.
Ganesh B Chand - One of the best experts on this subject based on the ideXlab platform.
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Disrupted interactions among the hippocampal, dorsal attention, and Central-Executive Networks in amnestic mild cognitive impairment.
Human brain mapping, 2018Co-Authors: Ganesh B Chand, Ihab Hajjar, Deqiang QiuAbstract:Neuroimaging investigations consistently demonstrate that the neural processes involve complex interactions between the large-scale Networks. Among those Networks, the dorsal attention Network (DAN) and the Central-Executive Network (CEN) have been previously shown to exhibit anti-correlated activity with the default-mode Network (DMN) in cognitively normal people. In amnestic mild cognitive impairment (MCI) and Alzheimer's disease, the hippocampal Network (HCN)-a key memory processing system-and its interactions with other Networks have gathered Central interest. The current study aims to evaluate the patterns of functional architectures of the HCN with the three Networks-DAN, CEN, and DMN-in amnestic MCI and normal controls (NC) to test the hypothesis that the interactions of HCN with other Networks alter in MCI. We recorded the resting state functional MRI, assessed patterns of functional architectures between the four Networks using dynamical causal modeling, and compared between NC and MCI. Our analysis showed that the DAN modulates the activity between the HCN and the DMN in both MCI and NC. We further uncovered that the DAN modulates the activity between the HCN and the CEN in NC, but such modulation is impaired in MCI. We found an association between impaired modulation and Montreal cognitive assessment (R = 0.349). Overall, our findings provide important insight in understanding the neuroimaging signature of amnestic MCI and/or Alzheimer's disease.
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interactions of the salience Network and its subsystems with the default mode and the Central Executive Networks in normal aging and mild cognitive impairment
Brain, 2017Co-Authors: Ganesh B Chand, Ihab Hajjar, Deqiang QiuAbstract:Previous functional magnetic resonance imaging (fMRI) investigations suggest that the intrinsically organized large-scale Networks and the interaction between them might be crucial for cognitive activities. A triple Network model, which consists of the default-mode Network, salience Network, and Central-Executive Network, has been recently used to understand the connectivity patterns of the cognitively normal brains versus the brains with disorders. This model suggests that the salience Network dynamically controls the default-mode and Central-Executive Networks in healthy young individuals. However, the patterns of interactions have remained largely unknown in healthy aging or those with cognitive decline. In this study, we assess the patterns of interactions between the three Networks using dynamical causal modeling in resting state fMRI data and compare them between subjects with normal cognition and mild cognitive impairment (MCI). In healthy elderly subjects, our analysis showed that the salience Network, especially its dorsal subNetwork, modulates the interaction between the default-mode Network and the Central-Executive Network (Mann-Whitney U test; p < 0.05), which was consistent with the pattern of interaction reported in young adults. In contrast, this pattern of modulation by salience Network was disrupted in MCI (p < 0.05). Furthermore, the degree of disruption in salience Network control correlated significantly with lower overall cognitive performance measured by Montreal Cognitive Assessment (r = 0.295; p < 0.05). This study suggests that a disruption of the salience Network control, especially the dorsal salience Network, over other Networks provides a neuronal basis for cognitive decline and may be a candidate neuroimaging biomarker of cognitive impairment.
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Interactions of the Salience Network and Its Subsystems with the Default-Mode and the Central-Executive Networks in Normal Aging and Mild Cognitive Impairment.
Brain connectivity, 2017Co-Authors: Ganesh B Chand, Ihab Hajjar, Deqiang QiuAbstract:Previous functional magnetic resonance imaging (fMRI) investigations suggest that the intrinsically organized large-scale Networks and the interaction between them might be crucial for cognitive activities. A triple Network model, which consists of the default-mode Network, salience Network, and Central-Executive Network, has been recently used to understand the connectivity patterns of the cognitively normal brains versus the brains with disorders. This model suggests that the salience Network dynamically controls the default-mode and Central-Executive Networks in healthy young individuals. However, the patterns of interactions have remained largely unknown in healthy aging or those with cognitive decline. In this study, we assess the patterns of interactions between the three Networks using dynamical causal modeling in resting state fMRI data and compare them between subjects with normal cognition and mild cognitive impairment (MCI). In healthy elderly subjects, our analysis showed that the salience Network, especially its dorsal subNetwork, modulates the interaction between the default-mode Network and the Central-Executive Network (Mann-Whitney U test; p
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The salience Network dynamics in perceptual decision-making
NeuroImage, 2016Co-Authors: Ganesh B Chand, Mukesh DhamalaAbstract:Recent neuroimaging studies have demonstrated that the Network consisting of the right anterior insula (rAI), left anterior insula (lAI) and dorsal anterior cingulate cortex (dACC) is activated in sensory stimulus-guided goal-directed behaviors. This Network is often known as the salience Network (SN). When and how a sensory signal enters and organizes within SN before reaching the Central Executive Network including the prefrontal cortices is still a mystery. Previous electrophysiological studies focused on individual nodes of SN, either on dACC or rAI, have reports of conflicting findings of the earliest cortical activity within the Network. Functional magnetic resonance imaging (fMRI) studies are not able to answer these questions in the time-scales of human sensory perception and decision-making. Here, using clear and noisy face-house image categorization tasks and human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study when and how oscillatory activity organizes SN during a perceptual decision. We uncovered that the beta-band (13-30Hz) oscillations bound SN, became most active around 100ms after the stimulus onset and the rAI acted as a main outflow hub within SN for easier decision making task. The SN activities (Granger causality measures) were negatively correlated with the decision response time (decision difficulty). These findings suggest that the SN activity precedes the Executive control in mediating sensory and cognitive processing to arrive at visual perceptual decisions.
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Interactions Among the Brain Default-Mode, Salience, and Central-Executive Networks During Perceptual Decision-Making of Moving Dots
Brain connectivity, 2016Co-Authors: Ganesh B Chand, Mukesh DhamalaAbstract:Abstract Cognitively demanding goal-directed tasks in the human brain are thought to involve the dynamic interplay of several large-scale neural Networks, including the default-mode Network (DMN), salience Network (SN), and Central-Executive Network (CEN). Resting-state functional magnetic resonance imaging (rsfMRI) studies have consistently shown that the CEN and SN negatively regulate activity in the DMN, and this switching is argued to be controlled by the right anterior insula (rAI) of the SN. However, what remains to be investigated is the pattern of directed Network interactions during difficult perceptual decision-making tasks. We recorded fMRI data while participants categorized the left–right motion of moving dots. We defined regions of interest, extracted fMRI time series, and performed directed connectivity analysis using Granger causality techniques. Our analyses demonstrated that the slow oscillation (0.07–0.19 Hz) mediated the interactions within and between the DMN, SN, and CEN nodes both f...
Vinod Menon - One of the best experts on this subject based on the ideXlab platform.
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Dysregulated Brain Dynamics in a Triple-Network Saliency Model of Schizophrenia and Its Relation to Psychosis.
Biological psychiatry, 2018Co-Authors: Kaustubh Supekar, Weidong Cai, Rajeev Krishnadas, Lena Palaniyappan, Vinod MenonAbstract:Abstract Background Schizophrenia is a highly disabling psychiatric disorder characterized by a range of positive “psychosis” symptoms. However, the neurobiology of psychosis and associated systems-level disruptions in the brain remain poorly understood. Here, we test an aberrant saliency model of psychosis, which posits that dysregulated dynamic cross-Network interactions among the salience Network (SN), Central Executive Network, and default mode Network contribute to positive symptoms in patients with schizophrenia. Methods Using task-free functional magnetic resonance imaging data from two independent cohorts, we examined 1) dynamic time-varying cross-Network interactions among the SN, Central Executive Network, and default mode Network in 130 patients with schizophrenia versus well-matched control subjects; 2) accuracy of a saliency model–based classifier for distinguishing dynamic brain Network interactions in patients versus control subjects; and 3) the relation between SN-centered Network dynamics and clinical symptoms. Results In both cohorts, we found that dynamic SN-centered cross-Network interactions were significantly reduced, less persistent, and more variable in patients with schizophrenia compared with control subjects. Multivariate classification analysis identified dynamic SN-centered cross-Network interaction patterns as factors that distinguish patients from control subjects, with accuracies of 78% and 80% in the two cohorts, respectively. Crucially, in both cohorts, dynamic time-varying measures of SN-centered cross-Network interactions were correlated with positive, but not negative, symptoms. Conclusions Aberrations in time-varying engagement of the SN with the Central Executive Network and default mode Network is a clinically relevant neurobiological signature of psychosis in schizophrenia. Our findings provide strong evidence for dysregulated brain dynamics in a triple-Network saliency model of schizophrenia and inform theoretically motivated systems neuroscience approaches for characterizing aberrant brain dynamics associated with psychosis.
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Temporal Dynamics and Developmental Maturation of Salience, Default and Central-Executive Network Interactions Revealed by Variational Bayes Hidden Markov Modeling.
PLoS computational biology, 2016Co-Authors: Srikanth Ryali, Kaustubh Supekar, Weidong Cai, Tianwen Chen, John Kochalka, Jonathan Nicholas, Aarthi Padmanabhan, Vinod MenonAbstract:Little is currently known about dynamic brain Networks involved in high-level cognition and their ontological basis. Here we develop a novel Variational Bayesian Hidden Markov Model (VB-HMM) to investigate dynamic temporal properties of interactions between salience (SN), default mode (DMN), and Central Executive (CEN) Networks-three brain systems that play a critical role in human cognition. In contrast to conventional models, VB-HMM revealed multiple short-lived states characterized by rapid switching and transient connectivity between SN, CEN, and DMN. Furthermore, the three "static" Networks occurred in a segregated state only intermittently. Findings were replicated in two adult cohorts from the Human Connectome Project. VB-HMM further revealed immature dynamic interactions between SN, CEN, and DMN in children, characterized by higher mean lifetimes in individual states, reduced switching probability between states and less differentiated connectivity across states. Our computational techniques provide new insights into human brain Network dynamics and its maturation with development.
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Aberrant Cross-Brain Network Interaction in Children With Attention-Deficit/Hyperactivity Disorder and Its Relation to Attention Deficits: A Multisite and Cross-Site Replication Study
Biological psychiatry, 2015Co-Authors: Weidong Cai, Kaustubh Supekar, Tianwen Chen, Luca Szegletes, Vinod MenonAbstract:Background Attention-deficit/hyperactivity disorder (ADHD) is increasingly viewed as a disorder stemming from disturbances in large-scale brain Networks, yet the exact nature of these impairments in affected children is poorly understood. We investigated a saliency-based triple-Network model and tested the hypothesis that cross-Network interactions between the salience Network (SN), Central Executive Network, and default mode Network are dysregulated in children with ADHD. We also determined whether Network dysregulation measures can differentiate children with ADHD from control subjects across multisite datasets and predict clinical symptoms. Methods Functional magnetic resonance imaging data from 180 children with ADHD and control subjects from three sites in the ADHD-200 database were selected using case-control design. We investigated between-group differences in resource allocation index (RAI) (a measure of SN-centered triple Network interactions), relation between RAI and ADHD symptoms, and performance of multivariate classifiers built to differentiate children with ADHD from control subjects. Results RAI was significantly lower in children with ADHD than in control subjects. Severity of inattention symptoms was correlated with RAI. Remarkably, these findings were replicated in three independent datasets. Multivariate classifiers based on cross-Network coupling measures differentiated children with ADHD from control subjects with high classification rates (72% to 83%) for each dataset. A novel cross-site classifier based on training data from one site accurately (62% to 82%) differentiated children with ADHD on test data from the two other sites. Conclusions Aberrant cross-Network interactions between SN, Central Executive Network, and default mode Network are a reproducible feature of childhood ADHD. The triple-Network model provides a novel, replicable, and parsimonious systems neuroscience framework for characterizing childhood ADHD and predicting clinical symptoms in affected children.
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Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive Network model.
PLoS computational biology, 2012Co-Authors: Kaustubh Supekar, Vinod MenonAbstract:Cognitive skills undergo protracted developmental changes resulting in proficiencies that are a hallmark of human cognition. One skill that develops over time is the ability to problem solve, which in turn relies on cognitive control and attention abilities. Here we use a novel multimodal neurocognitive Network-based approach combining task-related fMRI, resting-state fMRI and diffusion tensor imaging (DTI) to investigate the maturation of control processes underlying problem solving skills in 7-9 year-old children. Our analysis focused on two key neurocognitive Networks implicated in a wide range of cognitive tasks including control: the insula-cingulate salience Network, anchored in anterior insula (AI), ventrolateral prefrontal cortex and anterior cingulate cortex, and the fronto-parietal Central Executive Network, anchored in dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We found that, by age 9, the AI node of the salience Network is a major causal hub initiating control signals during problem solving. Critically, despite stronger AI activation, the strength of causal regulatory influences from AI to the PPC node of the Central Executive Network was significantly weaker and contributed to lower levels of behavioral performance in children compared to adults. These results were validated using two different analytic methods for estimating causal interactions in fMRI data. In parallel, DTI-based tractography revealed weaker AI-PPC structural connectivity in children. Our findings point to a crucial role of AI connectivity, and its causal cross-Network influences, in the maturation of dynamic top-down control signals underlying cognitive development. Overall, our study demonstrates how a unified neurocognitive Network model when combined with multimodal imaging enhances our ability to generalize beyond individual task-activated foci and provides a common framework for elucidating key features of brain and cognitive development. The quantitative approach developed is likely to be useful in investigating neurodevelopmental disorders, in which control processes are impaired, such as autism and ADHD.