Literature DB >> 28625875

Individual differences in functional connectivity during naturalistic viewing conditions.

Tamara Vanderwal1, Jeffrey Eilbott2, Emily S Finn2, R Cameron Craddock3, Adam Turnbull2, F Xavier Castellanos4.   

Abstract

Naturalistic viewing paradigms such as movies have been shown to reduce participant head motion and improve arousal during fMRI scanning relative to task-free rest, and have been used to study both functional connectivity and stimulus-evoked BOLD-signal changes. These task-based hemodynamic changes are synchronized across subjects and involve large areas of the cortex, and it is unclear whether individual differences in functional connectivity are enhanced or diminished under such naturalistic conditions. This work first aims to characterize variability in BOLD-signal based functional connectivity (FC) across 2 distinct movie conditions and eyes-open rest (n=31 healthy adults, 2 scan sessions each). We found that movies have higher within- and between-subject correlations in cluster-wise FC relative to rest. The anatomical distribution of inter-individual variability was similar across conditions, with higher variability occurring at the lateral prefrontal lobes and temporoparietal junctions. Second, we used an unsupervised test-retest matching algorithm that identifies individual subjects from within a group based on FC patterns, quantifying the accuracy of the algorithm across the three conditions. The movies and resting state all enabled identification of individual subjects based on FC matrices, with accuracies between 61% and 100%. Overall, pairings involving movies outperformed rest, and the social, faster-paced movie attained 100% accuracy. When the parcellation resolution, scan duration, and number of edges used were increased, accuracies improved across conditions, and the pattern of movies>rest was preserved. These results suggest that using dynamic stimuli such as movies enhances the detection of FC patterns that are unique at the individual level.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Identification algorithm; Inscapes; Movies; Naturalistic viewing; fMRI

Mesh:

Year:  2017        PMID: 28625875     DOI: 10.1016/j.neuroimage.2017.06.027

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


  51 in total

1.  Distinct modes of functional connectivity induced by movie-watching.

Authors:  Murat Demirtaş; Adrian Ponce-Alvarez; Matthieu Gilson; Patric Hagmann; Dante Mantini; Viviana Betti; Gian Luca Romani; Karl Friston; Maurizio Corbetta; Gustavo Deco
Journal:  Neuroimage       Date:  2018-09-17       Impact factor: 6.556

2.  Disentangled Intensive Triplet Autoencoder for Infant Functional Connectome Fingerprinting.

Authors:  Dan Hu; Fan Wang; Han Zhang; Zhengwang Wu; Li Wang; Weili Lin; Gang Li; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2020-09-29

Review 3.  Challenges and future directions for representations of functional brain organization.

Authors:  Janine Bijsterbosch; Samuel J Harrison; Saad Jbabdi; Mark Woolrich; Christian Beckmann; Stephen Smith; Eugene P Duff
Journal:  Nat Neurosci       Date:  2020-10-26       Impact factor: 24.884

Review 4.  Studying the visual brain in its natural rhythm.

Authors:  David A Leopold; Soo Hyun Park
Journal:  Neuroimage       Date:  2020-04-08       Impact factor: 6.556

5.  Inattentive Behavior in Boys with ADHD during Classroom Instruction: the Mediating Role of Working Memory Processes.

Authors:  Sarah A Orban; Mark D Rapport; Lauren M Friedman; Samuel J Eckrich; Michael J Kofler
Journal:  J Abnorm Child Psychol       Date:  2018-05

6.  Considering factors affecting the connectome-based identification process: Comment on Waller et al.

Authors:  Corey Horien; Stephanie Noble; Emily S Finn; Xilin Shen; Dustin Scheinost; R Todd Constable
Journal:  Neuroimage       Date:  2017-12-15       Impact factor: 6.556

7.  Temporal fluctuations in the brain's modular architecture during movie-watching.

Authors:  Richard F Betzel; Lisa Byrge; Farnaz Zamani Esfahlani; Daniel P Kennedy
Journal:  Neuroimage       Date:  2020-02-29       Impact factor: 6.556

8.  Combining multiple connectomes improves predictive modeling of phenotypic measures.

Authors:  Siyuan Gao; Abigail S Greene; R Todd Constable; Dustin Scheinost
Journal:  Neuroimage       Date:  2019-07-20       Impact factor: 6.556

9.  Task-evoked functional connectivity does not explain functional connectivity differences between rest and task conditions.

Authors:  Lauren K Lynch; Kun-Han Lu; Haiguang Wen; Yizhen Zhang; Andrew J Saykin; Zhongming Liu
Journal:  Hum Brain Mapp       Date:  2018-08-24       Impact factor: 5.038

10.  A naturalistic neuroimaging database for understanding the brain using ecological stimuli.

Authors:  Sarah Aliko; Jiawen Huang; Florin Gheorghiu; Stefanie Meliss; Jeremy I Skipper
Journal:  Sci Data       Date:  2020-10-13       Impact factor: 6.444

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