Large-scale brain network connectivity underlying creativity in resting-state and task fMRI: Cooperation between default network and frontal-parietal network

2018 ◽  
Vol 135 ◽  
pp. 102-111 ◽  
Author(s):  
Liang Shi ◽  
Jiangzhou Sun ◽  
Yunman Xia ◽  
Zhiting Ren ◽  
Qunlin Chen ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Network Connectivity ◽  
Brain Network ◽  
Default Network ◽  
Brain Network Connectivity ◽  
And Task

scholarly journals Childhood Trauma Associated With Abnormal Resting-State Brain Network Connectivity in First-Episode Schizophrenia Patients

2020 ◽  
Author(s):  
Xiangyun Long ◽  
Jiaxin Wu ◽  
Fei Liu ◽  
Ansi Qi ◽  
Nan Huang ◽  
...  
Keyword(s):  
Childhood Trauma ◽  
Resting State ◽  
Network Connectivity ◽  
Brain Network ◽  
Traumatic Experiences ◽  
First Episode ◽  
Resting State Networks ◽  
Attention Network ◽  
Brain Network Connectivity ◽  
First Episode Schizophrenia

Abstract Childhood trauma is a central risk factor for schizophrenia. We explored the correlation between early traumatic experiences and the functional connectivity of resting-state networks. This fMRI study included 28 first-episode schizophrenia patients and 27 healthy controls. In first-episode schizophrenia patients, higher levels of childhood trauma associated with abnormal connections of resting-state networks, and these anomalies distributed among task-positive networks (i.e., ventral attention network, dorsal-ventral attention network and frontal-parietal network), and sensory networks (i.e., visual network and auditory network). These findings mentioned that childhood traumatic experiences may impact resting-state network connectivity in adulthood, mainly involving systems related to attention and execution control.

scholarly journals GAIT VARIABILITY CORRELATES WITH RESTING-STATE BRAIN NETWORK CONNECTIVITY IN AGING AND DISEASE

2018 ◽  
Vol 2 (suppl_1) ◽  
pp. 518-518
Author(s):  
O Lo ◽  
M Halko ◽  
J Zhou ◽  
W Cheong ◽  
R Harrison ◽  
...  
Keyword(s):  
Resting State ◽  
Network Connectivity ◽  
Brain Network ◽  
Gait Variability ◽  
Brain Network Connectivity

scholarly journals Advanced Meditation Alters Resting-State Brain Network Connectivity Correlating With Improved Mindfulness

2021 ◽  
Vol 12 ◽  
Author(s):  
Ramana V. Vishnubhotla ◽  
Rupa Radhakrishnan ◽  
Kestas Kveraga ◽  
Rachael Deardorff ◽  
Chithra Ram ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Network Connectivity ◽  
Blood Oxygen Level Dependent ◽  
Brain Network ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Default Mode ◽  
Before And After ◽  
Brain Network Connectivity

Purpose: The purpose of this study was to investigate the effect of an intensive 8-day Samyama meditation program on the brain functional connectivity using resting-state functional MRI (rs-fMRI).Methods: Thirteen Samyama program participants (meditators) and 4 controls underwent fMRI brain scans before and after the 8-day residential meditation program. Subjects underwent fMRI with a blood oxygen level dependent (BOLD) contrast at rest and during focused breathing. Changes in network connectivity before and after Samyama program were evaluated. In addition, validated psychological metrics were correlated with changes in functional connectivity.Results: Meditators showed significantly increased network connectivity between the salience network (SN) and default mode network (DMN) after the Samyama program (p < 0.01). Increased connectivity within the SN correlated with an improvement in self-reported mindfulness scores (p < 0.01).Conclusion: Samyama, an intensive silent meditation program, favorably increased the resting-state functional connectivity between the salience and default mode networks. During focused breath watching, meditators had lower intra-network connectivity in specific networks. Furthermore, increased intra-network connectivity correlated with improved self-reported mindfulness after Samyama.Clinical Trials Registration: [https://clinicaltrials.gov], Identifier: [NCT04366544]. Registered on 4/17/2020.

Altered electroencephalography resting state network coherence in remitted MDD

2021 ◽  
Author(s):  
Kimberly L Ray ◽  
Nicholas Griffin ◽  
Jason Shumake ◽  
Alexandra Alario ◽  
John B. Allen ◽  
...  
Keyword(s):  
Resting State ◽  
Network Connectivity ◽  
Brain Network ◽  
Healthy Adults ◽  
Average Reference ◽  
Brain Network Connectivity ◽  
Eeg Connectivity ◽  
Eeg Power ◽  
Remitted Depression ◽  
Power Analyses

Individuals with remitted depression are at greater risk for subsequent depression and therefore may provide a unique opportunity to understand the neurophysiological correlates underlying the risk of depression. Research has identified abnormal resting-state electroencephalography (EEG) power metrics and functional connectivity patterns associated with major depression, however little is known about these neural signatures in individuals with remitted depression. We investigate the spectral dynamics of 64-channel EEG surface power and source-estimated network connectivity during resting states in 37 individuals with depression, 56 with remitted depression, and 49 healthy adults that did not differ on age, education, and cognitive ability across theta, alpha, and beta frequencies. Average reference spectral EEG surface power analyses identified greater left and midfrontal theta in remitted depression compared to healthy adults. Using Network Based Statistics, we also demonstrate within and between network alterations in LORETA transformed EEG source-space coherence across the default mode, fronto-parietal, and salience networks where individuals with remitted depression exhibited enhanced coherence compared to those with depression, and healthy adults. This work builds upon our currently limited understanding of resting EEG connectivity in depression, and helps bridge the gap between aberrant EEG power and brain network connectivity dynamics in this disorder. Further, our unique examination of remitted depression relative to both healthy and depressed adults may be key to identifying brain-based biomarkers for those at high risk for future, or subsequent depression.

scholarly journals Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback

2017 ◽  
Author(s):  
Michal Ramot ◽  
Sara Kimmich ◽  
Javier Gonzalez-Castillo ◽  
Vinai Roopchansingh ◽  
Haroon Popal ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Real Time ◽  
Resting State ◽  
Network Connectivity ◽  
Autism Spectrum ◽  
Brain Network ◽  
Spectrum Disorder ◽  
Control Group ◽  
Connectivity Patterns ◽  
Brain Network Connectivity

ABSTRACTThe existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained 3 brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. 17 ASD participants and 10 control participants were scanned over multiple sessions (123 sessions in total). Desired network connectivity patterns were reinforced in real-time, without participants’ awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns.Significance StatementMany disorders are characterized by underlying abnormalities in network connectivity. These abnormalities are difficult to address with explicit training procedures (which are unlikely to target the specific abnormalities). Covert neurofeedback however, can directly target these networks, positively reinforcing the desired connections. We have developed a method for reinforcing correlations in real-time, and show that such training is effective, inducing significant, long-lasting changes in connectivity between aberrant networks in Autism Spectrum Disorder. This provides a potential mechanism for modulating aberrant correlation structures in other clinical groups as well.

scholarly journals Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity

2020 ◽  
Author(s):  
N. Kohn ◽  
J. Szopinska-Tokov ◽  
A. Llera ◽  
C. Beckmann ◽  
A. Arias Vasquez ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Default Mode Network ◽  
Large Scale ◽  
Network Connectivity ◽  
Brain Network ◽  
Imaging Data ◽  
Microbial Composition ◽  
Attention Networks ◽  
Default Mode ◽  
Brain Network Connectivity

AbstractResearch on the gut-brain axis has accelerated substantially over the course of the last years. Many reviews have outlined the important implications of understanding the relation of the gut microbiota with human brain function and behavior. One substantial drawback in integrating gut microbiome and brain data is the lack of integrative multivariate approaches that enable capturing variance in both modalities simultaneously. To address this issue, we applied a linked independent component analysis (LICA) to microbiota and brain connectivity data.We analyzed data from 58 healthy females (mean age = 21.5 years). Magnetic Resonance Imaging data were acquired using resting state functional imaging data. The assessment of gut microbial composition from feces was based on sequencing of the V4 16S rRNA gene region. We used the LICA model to simultaneously factorize the subjects’ large-scale brain networks and microbiome relative abundance data into 10 independent components of spatial and abundance variation.LICA decomposition resulted in four components with non-marginal contribution of the microbiota data. The default mode network featured strongly in three components, whereas the two-lateralized fronto-parietal attention networks contributed to one component. The executive-control (with the default mode) network was associated to another component. We found the abundance of Prevotella genus was associated to the strength of expression of all networks, whereas Bifidobacterium was associated with the default mode and frontoparietal-attention networks.We provide the first exploratory evidence for multivariate associative patterns between the gut microbiota and brain network connectivity in healthy humans, taking into account the complexity of both systems.

scholarly journals Brain Network Organization During Mindful Acceptance of Emotions

2020 ◽  
Author(s):  
Matthew Luke Dixon ◽  
Manesh Girn ◽  
Kalina Christoff
Keyword(s):  
Information Flow ◽  
Large Scale ◽  
Network Connectivity ◽  
Brain Network ◽  
Global Network ◽  
Default Network ◽  
Present Moment ◽  
Network Organization ◽  
Attentional Scope ◽  
Narrative Evaluation

AbstractIndividuals use various strategies to cope with challenging emotions such as anxiety. Mindful acceptance involves broadening attentional scope and fully experiencing present moment sensory feelings (whether pleasant or unpleasant) without judgment or elaboration. In contrast, narrative-evaluation involves focusing on a narrow band of sensory experience and generating an elaborate narrative about the meaning and desirability of one’s emotional feelings. The current study examined brain network organization during these strategies using graph theoretic analyses. We used a naturalistic task paradigm in which participants reflected on an anxiety-provoking issue from their personal lives and adopted each strategy in different blocks. Compared to narrative-evaluation, mindful acceptance was associated with: (i) increased global network connectivity; (ii) greater integration of interoceptive regions (mid and posterior insula) into large-scale networks; (iii) reorganization of motivational circuits including a shift in the striatum’s network assignment from the default network to the salience network; and (iv) a shift from default network to frontoparietal control network (FPCN) regions as central hubs that coordinate information flow. Functional connectivity patterns within the left FPCN were associated with acceptance reports. Thus, broadening attentional scope during mindful acceptance is supported by a more globally interconnected neural landscape, as well as greater information flow through FPCN regions that underlie metacognitive awareness and cognitive control.

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