scholarly journals The Effect of Mindfulness Training On Resting-State Networks In Pre-Adolescent Children With Sub-Clinical Anxiety Related Attention Impairments.

Author(s):  
Michelle F. Kennedy ◽  
Abdalla Z Mohamed ◽  
Paul Schwenn ◽  
Denise Beaudequin ◽  
Zack Shan ◽  
...  

Abstract Background: Mindfulness training has been associated with improved attention and affect regulation in preadolescent children with anxiety related attention impairments, however little is known about the underlying neurobiology. This study sought to investigate the impact of mindfulness training on functional connectivity of attention and limbic brain networks in pre-adolescents.Methods: A total of 47 children (aged 9-11 years) participated in a 10-week mindfulness intervention. Anxiety and attention measures and resting-state fMRI were completed at pre- and post-intervention. Sustained attention was measured using the Conners Continuous Performance Test, while the anxiety levels were measured using the Spence Children’s Anxiety Scale. Functional networks were estimated using independent-component analysis, and voxel-based analysis was used to determine the difference between the time-points to identify the effect of the intervention on the functional connectivity. Results: There was a significant decrease in anxiety symptoms and improvement in attention scores following the intervention. From a network perspective, the results showed increased functional connectivity post intervention in the salience and fronto-parietal networks as well as the medial-inferior temporal component of the default mode network. Positive correlations were identified in the fronto-parietal network with Hit Response Time and the Spence Children’s Anxiety Scale total and between the default mode network and Hit Response Time.Conclusions: A 10-week mindfulness intervention in children was associated with a reduction in anxiety related attention impairments, which were underpinned by concomitant changes in functional connectivity.

2021 ◽  
Vol 15 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized.Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.


2021 ◽  
Author(s):  
Kaley Davis ◽  
Emily Hirsch ◽  
Dylan Gee ◽  
Margaret Andover ◽  
Amy Krain Roy

Abstract Humans are reliant on their caregivers for an extended period of time, offering numerous opportunities for environmental factors, such as parental attitudes and behaviors, to impact brain development. The default mode network is a neural system encompassing the medial prefrontal cortex, posterior cingulate cortex, precuneus, and temporo-parietal junction, which is implicated in aspects of cognition and psychopathology. Delayed default mode network maturation in children and adolescents has been associated with greater general dimensional psychopathology, and positive parenting behaviors have been suggested to serve as protective mechanisms against atypical default mode network development. The current study aimed to extend the existing research by examining whether within- default mode network resting-state functional connectivity would mediate the relation between parental acceptance/warmth and youth psychopathology. Data from the Adolescent Brain and Cognitive Development study, which included a community sample of 9,058 children ages 9-10.9 years, were analyzed to test this prediction. Results from the analysis demonstrated a significant mediation, where greater parental acceptance/warmth predicted greater within- default mode network resting-state functional connectivity, which in turn predicted lower psychopathology. Our study provides preliminary support for the notion that positive parenting traits may reduce the risk for psychopathology in youth through their influence on the default mode network. Due to the cross-sectional nature of this study, we can only draw correlational inference; therefore, these relationships should be tested longitudinally in future investigations.


2019 ◽  
Vol 48 (1-2) ◽  
pp. 61-69 ◽  
Author(s):  
Tingting Zhu ◽  
Lingyu Li ◽  
Yulin Song ◽  
Yu Han ◽  
Chengshu Zhou ◽  
...  

Default mode network (DMN) is an important functional brain network that supports aspects of cognition. Stroke has been reported to be associated with functional connectivity (FC) impairments within DMN. However, whether FC within DMN changes in transient ischemic attack (TIA), an important risk factor for stroke, remains unclear. Forty-eight TIA patients and 41 age- and sex-matched healthy controls (HCs) were recruited in this study. Using resting-state functional magnetic resonance imaging seed-based FC methods, we examined FC alterations within DMN in TIA patients, tested its associations with clinical information, and further explored the ability of FC abnormalities to predict follow-up ischemic attacks. We found significantly decreased FC of left middle temporal gyrus/angular gyrus both with medial prefrontal cortex (mPFC) and posterior cingulate cortex/precuneus (PCC/Pcu) and significantly decreased FC among each pair of mPFC, left PCC, and right Pcu in patients with TIA as compared with HCs. Moreover, the connectivity between mPFC and left PCC could predict future ischemic attacks of the patients. Collectively, these findings may provide insights into further understanding of the underlying pathological mechanism in TIA, and aberrant FC between the hubs within DMN may provide a reference for the imaging diagnosis and early intervention of TIA.


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