Literature DB >> 24973603

Dynamic functional connectivity of the default mode network tracks daydreaming.

Aaron Kucyi1, Karen D Davis2.   

Abstract

Humans spend much of their time engaged in stimulus-independent thoughts, colloquially known as "daydreaming" or "mind-wandering." A fundamental question concerns how awake, spontaneous brain activity represents the ongoing cognition of daydreaming versus unconscious processes characterized as "intrinsic." Since daydreaming involves brief cognitive events that spontaneously fluctuate, we tested the hypothesis that the dynamics of brain network functional connectivity (FC) are linked with daydreaming. We determined the general tendency to daydream in healthy adults based on a daydreaming frequency scale (DDF). Subjects then underwent both resting state functional magnetic resonance imaging (rs-fMRI) and fMRI during sensory stimulation with intermittent thought probes to determine the occurrences of mind-wandering events. Brain regions within the default mode network (DMN), purported to be involved in daydreaming, were assessed for 1) static FC across the entire fMRI scans, and 2) dynamic FC based on FC variability (FCV) across 30s progressively sliding windows of 2s increments within each scan. We found that during both resting and sensory stimulation states, individual differences in DDF were negatively correlated with static FC between the posterior cingulate cortex and a ventral DMN subsystem involved in future-oriented thought. Dynamic FC analysis revealed that DDF was positively correlated with FCV within the same DMN subsystem in the resting state but not during stimulation. However, dynamic but not static FC, in this subsystem, was positively correlated with an individual's degree of self-reported mind-wandering during sensory stimulation. These findings identify temporal aspects of spontaneous DMN activity that reflect conscious and unconscious processes.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Awareness; Brain dynamics; Consciousness; Spontaneous cognition; Stimulus-independent thought

Mesh:

Year:  2014        PMID: 24973603     DOI: 10.1016/j.neuroimage.2014.06.044

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


  112 in total

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Authors:  Carissa L Philippi; Joel Bruss; Aaron D Boes; Fatimah M Albazron; Carolina Deifelt Streese; Elisa Ciaramelli; David Rudrauf; Daniel Tranel
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2.  Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease.

Authors:  Biao Jie; Mingxia Liu; Dinggang Shen
Journal:  Med Image Anal       Date:  2018-04-04       Impact factor: 8.545

3.  When the brain takes a break: a model-based analysis of mind wandering.

Authors:  Matthias Mittner; Wouter Boekel; Adrienne M Tucker; Brandon M Turner; Andrew Heathcote; Birte U Forstmann
Journal:  J Neurosci       Date:  2014-12-03       Impact factor: 6.167

4.  Task-related modulation of functional connectivity variability and its behavioral correlations.

Authors:  Amanda Elton; Wei Gao
Journal:  Hum Brain Mapp       Date:  2015-05-26       Impact factor: 5.038

5.  Dynamic brain network configurations during rest and an attention task with frequent occurrence of mind wandering.

Authors:  Ekaterina Denkova; Jason S Nomi; Lucina Q Uddin; Amishi P Jha
Journal:  Hum Brain Mapp       Date:  2019-08-04       Impact factor: 5.038

6.  Spontaneous default network activity reflects behavioral variability independent of mind-wandering.

Authors:  Aaron Kucyi; Michael Esterman; Clay S Riley; Eve M Valera
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-15       Impact factor: 11.205

7.  Frequency-specific age-related decreased brain network diversity in cognitively healthy elderly: A whole-brain data-driven analysis.

Authors:  Wutao Lou; Defeng Wang; Adrian Wong; Winnie C W Chu; Vincent C T Mok; Lin Shi
Journal:  Hum Brain Mapp       Date:  2018-09-21       Impact factor: 5.038

8.  Wandering Minds with Wandering Brain Networks.

Authors:  Xinqi Zhou; Xu Lei
Journal:  Neurosci Bull       Date:  2018-08-22       Impact factor: 5.203

9.  Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

Authors:  Jin Liu; Xuhong Liao; Mingrui Xia; Yong He
Journal:  Hum Brain Mapp       Date:  2017-11-15       Impact factor: 5.038

10.  Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states.

Authors:  Sadia Shakil; Chin-Hui Lee; Shella Dawn Keilholz
Journal:  Neuroimage       Date:  2016-03-04       Impact factor: 6.556

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