Literature DB >> 30953836

Mediation analysis of triple networks revealed functional feature of mindfulness from real-time fMRI neurofeedback.

Hyun-Chul Kim1, Marion Tegethoff2, Gunther Meinlschmidt3, Esther Stalujanis4, Angelo Belardi2, Sungman Jo1, Juhyeon Lee1, Dong-Youl Kim1, Seung-Schik Yoo5, Jong-Hwan Lee6.   

Abstract

The triple networks, namely the default-mode network (DMN), the central executive network (CEN), and the salience network (SN), play crucial roles in disorders of the brain, as well as in basic neuroscientific processes such as mindfulness. However, currently, there is no consensus on the underlying functional features of the triple networks associated with mindfulness. In this study, we tested the hypothesis that (a) the partial regression coefficient (i.e., slope): from the SN to the DMN, mediated by the CEN, would be one of the potential mindfulness features in the real-time functional magnetic resonance imaging (rtfMRI) neurofeedback (NF) setting, and (b) this slope level may be enhanced by rtfMRI-NF training. Sixty healthy mindfulness-naïve males participated in an MRI session consisting of two non-rtfMRI-runs, followed by two rtfMRI-NF runs and one transfer run. Once the regions-of-interest of each of the triple networks were defined using the non-rtfMRI-runs, the slope level was calculated by mediation analysis and used as neurofeedback information, in the form of a thermometer bar, to assist with participant mindfulness during the rtfMRI-NF runs. The participants were asked to increase the level of the thermometer bar while deploying a mindfulness strategy, which consisted of focusing attention on the physical sensations of breathing. rtfMRI-NF training was conducted as part of a randomized controlled trial design, in which participants were randomly assigned to either an experimental group or a control group. The participants in the experimental group received contingent neurofeedback information, which was obtained from their own brain signals, whereas the participants in the control group received non-contingent neurofeedback information that originated from matched participants in the experimental group. Our results indicated that the slope level from the SN to the DMN, mediated by the CEN, was associated with mindfulness score (rtfMRI-NF runs: r = 0.53, p = 0.007; p-value was corrected from 10,000 random permutations) and with task-performance feedback score (rtfMRI-NF run: r = 0.61, p = 0.001) in the experimental group only. In addition, during the rtfMRI-NF runs the level of the partial regression coefficient feature was substantially increased in the experimental group compared to the control group (p < 0.05 from the paired t-test; the p-value was corrected from 10,000 random permutations). To the best of our knowledge, this is the first study to demonstrate a partial regression coefficient feature of mindfulness in the rtfMRI-NF setting obtained by triple network mediation analysis, as well as the possibility of enhancement of the partial regression coefficient feature by rtfMRI-NF training.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Central executive network; Contemplative science; Default-mode network; Functional connectivity; Functional magnetic resonance imaging; Mediation analysis; Mindfulness; Real-time fMRI neurofeedback; Salience network

Year:  2019        PMID: 30953836     DOI: 10.1016/j.neuroimage.2019.03.066

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  7 in total

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Authors:  Tara Chand; Meng Li; Hamidreza Jamalabadi; Gerd Wagner; Anton Lord; Sarah Alizadeh; Lena V Danyeli; Luisa Herrmann; Martin Walter; Zumrut D Sen
Journal:  Front Neurosci       Date:  2020-07-02       Impact factor: 4.677

2.  Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture.

Authors:  Zohreh Doborjeh; Maryam Doborjeh; Mark Crook-Rumsey; Tamasin Taylor; Grace Y Wang; David Moreau; Christian Krägeloh; Wendy Wrapson; Richard J Siegert; Nikola Kasabov; Grant Searchfield; Alexander Sumich
Journal:  Sensors (Basel)       Date:  2020-12-21       Impact factor: 3.576

3.  Spectral dynamic causal modeling of mindfulness, mind-wandering, and resting-state in the triple network using fMRI.

Authors:  Hyun-Chul Kim; Jong-Hwan Lee
Journal:  Neuroreport       Date:  2022-03-23       Impact factor: 1.703

4.  Mixed-effects multilevel analysis followed by canonical correlation analysis is an effective fMRI tool for the investigation of idiosyncrasies.

Authors:  Sungman Jo; Hyun-Chul Kim; Niv Lustig; Gang Chen; Jong-Hwan Lee
Journal:  Hum Brain Mapp       Date:  2021-08-20       Impact factor: 5.038

5.  Electronic Cigarette Vaping Did Not Enhance the Neural Process of Working Memory for Regular Cigarette Smokers.

Authors:  Dong-Youl Kim; Yujin Jang; Da-Woon Heo; Sungman Jo; Hyun-Chul Kim; Jong-Hwan Lee
Journal:  Front Hum Neurosci       Date:  2022-02-18       Impact factor: 3.169

Review 6.  Underlying mechanisms of mindfulness meditation: Genomics, circuits, and networks.

Authors:  Ying-Qi Gu; Yi Zhu
Journal:  World J Psychiatry       Date:  2022-09-19

7.  Functional magnetic resonance imaging multivoxel pattern analysis reveals neuronal substrates for collaboration and competition with myopic and predictive strategic reasoning.

Authors:  Dong-Youl Kim; Eun Kyung Jung; Jun Zhang; Soo-Young Lee; Jong-Hwan Lee
Journal:  Hum Brain Mapp       Date:  2020-07-07       Impact factor: 5.399

  7 in total

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