The Cortical Network of Emotion Regulation: Insights From Advanced EEG-fMRI Integration Analysis

被引:43
|
作者
Thinh Nguyen [1 ]
Zhou, Tiantong [2 ]
Potter, Thomas [1 ]
Zou, Ling [2 ]
Zhang, Yinchun [1 ]
机构
[1] Univ Houston, Dept Biomed Engn, Houston, TX 77204 USA
[2] Changzhou Univ, Sch Informat Sci & Engn, Changzhou 213164, Peoples R China
关键词
Functional magnetic resonance imaging; Electroencephalography; Spatiotemporal phenomena; Image reconstruction; Brain modeling; Visualization; functional magnetic resonance imaging; neuroimaging; source localization; emotion; causal brain network; POSTERIOR PARIETAL CORTEX; GENERAL LINEAR-MODEL; COGNITIVE REAPPRAISAL; ASYMMETRY; BRAIN; CHILDREN; MEG; ACTIVATION; ATTENTION; COHERENCE;
D O I
10.1109/TMI.2019.2900978
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The ability to perceive and regulate emotion is a key component of cognition that is often disrupted by disease. Current neuroimaging studies regarding emotion regulation have implicated a number of cortical regions and identified several EEG features of interest, including the late positive potential and frontal asymmetry. Unfortunately, currently applied methods generally lack in the resolution necessary to capture focal cortical activity and explore the causal interactions between brain regions. In this paper, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data were simultaneously recorded from 20 subjects undergoing emotion processing and regulation tasks. Cortical activity with high-spatiotemporal resolution and accuracy was reconstructed using a novel multimodal EEG/fMRI integration method. A detailed causal brain network associated with emotion processing and regulation was then identified, and the network changes that facilitate different emotion conditions were investigated. The cortical activity of the ventrolateral prefrontal (VLPFC) and posterior parietal cortices depicted conditionally-sensitive spike and wave patterns evidenced in inter-regional communication. The VLPFC was found to behave as a main network source, with conditionally-specific interactions supporting emotional shifts. The results provide unique insight into the cortical activity that supports emotional perception and regulation, the origins of known EEG phenomena, and the manner in which brain regions coordinate to affect behavior.
引用
收藏
页码:2423 / 2433
页数:11
相关论文
共 50 条
  • [1] Source localization and functional network analysis in emotion cognitive reappraisal with EEG-fMRI integration
    Li, Wenjie
    Zhang, Wei
    Jiang, Zhongyi
    Zhou, Tiantong
    Xu, Shoukun
    Zou, Ling
    FRONTIERS IN HUMAN NEUROSCIENCE, 2022, 16
  • [2] A personalized history of EEG-fMRI integration
    Laufs, Helmut
    NEUROIMAGE, 2012, 62 (02) : 1056 - 1067
  • [3] Dynamic functional connectivity estimation for neurofeedback emotion regulation paradigm with simultaneous EEG-fMRI analysis
    Mosayebi, Raziyeh
    Dehghani, Amin
    Hossein-Zadeh, Gholam-Ali
    FRONTIERS IN HUMAN NEUROSCIENCE, 2022, 16
  • [4] The benefits of simultaneous EEG-fMRI for EEG analysis
    Debener, Stefan
    De Vos, Maarten
    CLINICAL NEUROPHYSIOLOGY, 2011, 122 (02) : 217 - 218
  • [5] A multilayered approach to studying cortical malformations EEG-fMRI
    Detre, JA
    Crino, PB
    NEUROLOGY, 2005, 64 (07) : 1108 - 1110
  • [6] EEG-FMRI IN SEIZURES: IMAGING THE EPILEPTIC NETWORK
    Thornton, R.
    Rodionov, R.
    Laufs, H.
    Vulliemoz, Serge
    Carmichael, D. W.
    Mcevoy, A. W.
    Scott, C.
    Smith, S. M.
    Walker, M. C.
    Lhatoo, S. D.
    Guye, M.
    Bartolomei, F.
    Chauvel, Patrick
    Duncan, John S.
    Lemieux, L.
    EPILEPSIA, 2008, 49 : 402 - 402
  • [7] The dynamics of contour integration: A simultaneous EEG-fMRI study
    Mijovic, Bogdan
    De Vos, Maarten
    Vanderperren, Katrien
    Machilsen, Bart
    Sunaert, Stefan
    Van Huffel, Sabine
    Wagemans, Johan
    NEUROIMAGE, 2014, 88 : 10 - 21
  • [8] Probing the cortical network underlying the psychological refractory period: A combined EEG-fMRI study
    Hesselmann, G.
    Flandin, G.
    Dehaene, S.
    NEUROIMAGE, 2011, 56 (03) : 1608 - 1621
  • [9] EEG-fMRI integration for the study of human brain function
    Jorge, Joao
    van der Zwaag, Wietske
    Figueiredo, Patricia
    NEUROIMAGE, 2014, 102 : 24 - 34
  • [10] EEG-fMRI INTEGRATION: A CRITICAL REVIEW OF BIOPHYSICAL MODELING AND DATA ANALYSIS APPROACHES
    Rosa, M. J.
    Daunizeau, J.
    Friston, K. J.
    JOURNAL OF INTEGRATIVE NEUROSCIENCE, 2010, 9 (04) : 453 - 476