Time-evolving dynamics in brain networks forecast responses to health messaging

被引:14
|
作者
Cooper, Nicole [1 ,2 ]
Garcia, Javier O. [2 ,3 ]
Tompson, Steven H. [2 ,3 ]
O'Donnell, Matthew B. [1 ]
Falk, Emily B. [1 ]
Vettel, Jean M. [2 ,3 ,4 ]
机构
[1] Univ Penn, Annenberg Sch Commun, Philadelphia, PA 19104 USA
[2] US Army Res Lab, Aberdeen, MD USA
[3] Univ Penn, Dept Bioengn, Philadelphia, PA 19104 USA
[4] Univ Calif Santa Barbara, Dept Psychol & Brain Sci, Santa Barbara, CA 93106 USA
来源
NETWORK NEUROSCIENCE | 2018年 / 3卷 / 01期
基金
美国国家卫生研究院;
关键词
Functional MRI (fMRI); Neuroimaging; Functional connectivity; Behavior change; Smoking; LARGE-SCALE BRAIN; SELF-REPORTED SMOKING; FUNCTIONAL CONNECTIVITY; DEFAULT MODE; ANTISMOKING MESSAGES; DORSAL ATTENTION; BEHAVIOR-CHANGE; AFFIRMATION; ARCHITECTURE; COTININE;
D O I
10.1162/netn_a_00058
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Neuroimaging measures have been used to forecast complex behaviors, including how individuals change decisions about their health in response to persuasive communications, but have rarely incorporated metrics of brain network dynamics. How do functional dynamics within and between brain networks relate to the processes of persuasion and behavior change? To address this question, we scanned 45 adult smokers by using functional magnetic resonance imaging while they viewed anti-smoking images. Participants reported their smoking behavior and intentions to quit smoking before the scan and 1 month later. We focused on regions within four atlas-defined networks and examined whether they formed consistent network communities during this task (measured as allegiance). Smokers who showed reduced allegiance among regions within the default mode and fronto-parietal networks also demonstrated larger increases in their intentions to quit smoking 1 month later. We further examined dynamics of the ventromedial prefrontal cortex (vmPFC), as activation in this region has been frequently related to behavior change. The degree to which vmPFC changed its community assignment over time (measured as flexibility) was positively associated with smoking reduction. These data highlight the value in considering brain network dynamics for understanding message effectiveness and social processes more broadly.
引用
收藏
页码:138 / 156
页数:19
相关论文
共 50 条
  • [31] TEMPI: probabilistic modeling time-evolving differential PPI networks with multiPle information
    Kim, Yongsoo
    Jang, Jin-Hyeok
    Choi, Seungjin
    Hwang, Daehee
    BIOINFORMATICS, 2014, 30 (17) : I453 - I460
  • [32] WINTENDED: WINdowed TENsor decomposition for Densification Event Detection in time-evolving networks
    Sofia Fernandes
    Hadi Fanaee-T
    João Gama
    Leo Tišljarić
    Tomislav Šmuc
    Machine Learning, 2023, 112 : 459 - 481
  • [33] WINTENDED: WINdowed TENsor decomposition for Densification Event Detection in time-evolving networks
    Fernandes, Sofia
    Fanaee-T, Hadi
    Gama, Joao
    Tisljaric, Leo
    Smuc, Tomislav
    MACHINE LEARNING, 2023, 112 (02) : 459 - 481
  • [34] Brittleness Analysis and Important Nodes Discovery in Large Time-Evolving Complex Networks
    张红
    胡昌振
    王小军
    Journal of Shanghai Jiaotong University(Science), 2017, 22 (01) : 50 - 54
  • [35] Brittleness analysis and important nodes discovery in large time-evolving complex networks
    Zhang H.
    Hu C.
    Wang X.
    Zhang, Hong (GraceZXKL@126.com), 2017, Shanghai Jiaotong University (22): : 50 - 54
  • [36] Multityped Community Discovery in Time-Evolving Heterogeneous Information Networks Based on Tensor Decomposition
    Wu, Jibing
    Yu, Lianfei
    Zhang, Qun
    Shi, Peiteng
    Liu, Lihua
    Deng, Su
    Huang, Hongbin
    COMPLEXITY, 2018,
  • [37] Efficient Topology Design for Load Balancing in Time-Evolving Delay-Tolerant Networks
    Yan, Dawei
    Liu, Cong
    You, Peng
    Yong, Shaowei
    2018 8TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION (ICEIEC), 2018, : 103 - 107
  • [38] Statistical Consistency for Change Point Detection and Community Estimation in Time-Evolving Dynamic Networks
    Xu, Cong
    Lee, Thomas C. M.
    IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 2022, 8 : 215 - 227
  • [39] Smurf-Based Anti-money Laundering in Time-Evolving Transaction Networks
    Starnini, Michele
    Tsourakakis, Charalampos E.
    Zamanipour, Maryam
    Panisson, Andre
    Allasia, Walter
    Fornasiero, Marco
    Li Puma, Laura
    Ricci, Valeria
    Ronchiadin, Silvia
    Ugrinoska, Angela
    Varetto, Marco
    Moncalvo, Dario
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2021: APPLIED DATA SCIENCE TRACK, PT IV, 2021, 12978 : 171 - 186
  • [40] Reliable Topology Design in Time-Evolving Delay-Tolerant Networks with Unreliable Links
    Li, Fan
    Chen, Siyuan
    Huang, Minsu
    Yin, Zhiyuan
    Zhang, Chao
    Wang, Yu
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2015, 14 (06) : 1301 - 1314