Opportunities and methodological challenges in EEG and MEG resting state functional brain network research

被引:287
|
作者
van Diessen, E. [1 ]
Numan, T. [2 ]
van Dellen, E. [3 ,4 ,5 ]
van der Kooi, A. W. [2 ]
Boersma, M. [7 ]
Hofman, D. [7 ]
van Lutterveld, R. [6 ]
van Dijk, B. W. [4 ,5 ]
van Straaten, E. C. W. [4 ,5 ]
Hillebrand, A. [4 ,5 ]
Stam, C. J. [4 ,5 ]
机构
[1] Univ Med Ctr Utrecht, Brain Ctr Rudolf Magnus, Dept Pediat Neurol, NL-3508 AB Utrecht, Netherlands
[2] Univ Med Ctr Utrecht, Dept Intens Care, NL-3508 AB Utrecht, Netherlands
[3] Univ Med Ctr Utrecht, Brain Ctr Rudolf Magnus, Dept Psychiat, NL-3508 AB Utrecht, Netherlands
[4] Vrije Univ Amsterdam Med Ctr, Dept Clin Neurophysiol, Amsterdam, Netherlands
[5] Vrije Univ Amsterdam Med Ctr, MEG Ctr, Amsterdam, Netherlands
[6] Univ Massachusetts, Sch Med, Ctr Mindfulness, Worcester, MA USA
[7] Univ Utrecht, Dept Expt Psychol, NL-3508 TC Utrecht, Netherlands
关键词
Resting state; EEG; MEG; Functional connectivity; Functional networks; Graph analysis; Minimum spanning tree; GRAPH-THEORETICAL ANALYSIS; TEST-RETEST RELIABILITY; PHASE-LAG INDEX; VOLUME-CONDUCTION; DEFAULT MODE; EPILEPTOGENIC NETWORKS; EFFECTIVE CONNECTIVITY; GAMMA-OSCILLATIONS; DIRECTED COHERENCE; CORTICAL DYNAMICS;
D O I
10.1016/j.clinph.2014.11.018
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during resting state are increasingly used to study functional connectivity and network topology. Moreover, the number of different analysis approaches is expanding along with the rising interest in this research area. The comparison between studies can therefore be challenging and discussion is needed to underscore methodological opportunities and pitfalls in functional connectivity and network studies. In this overview we discuss methodological considerations throughout the analysis pipeline of recording and analyzing resting state EEG and MEG data, with a focus on functional connectivity and network analysis. We summarize current common practices with their advantages and disadvantages; provide practical tips, and suggestions for future research. Finally, we discuss how methodological choices in resting state research can affect the construction of functional networks. When taking advantage of current best practices and avoid the most obvious pitfalls, functional connectivity and network studies can be improved and enable a more accurate interpretation and comparison between studies. (c) 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:1468 / 1481
页数:14
相关论文
共 50 条
  • [41] Alterations of resting state functional network connectivity in the brain of nicotine and alcohol users
    Vergara, Victor M.
    Liu, Jingyu
    Claus, Eric D.
    Hutchison, Kent
    Calhou, Vince
    NEUROIMAGE, 2017, 151 : 45 - 54
  • [42] NETWORK ANALYSIS OF RESTING STATE FUNCTIONAL BRAIN CONNECTIVITY IN SPINAL CORD INJURY
    Oni-Orisan, Akinwunmi
    Kaushal, Mayank
    Chen, Gang
    Li, Wenjun
    Leschke, Jack
    Schmit, Brian
    Li, Shi-Jiang
    Muqeet, Vaishnavi
    Kurpad, Shekar
    JOURNAL OF NEUROTRAUMA, 2016, 33 (13) : A91 - A91
  • [43] Resting-state EEG and MEG biomarkers of pathological fatigue - A transdiagnostic systematic review
    Heitmann, Henrik
    Zebhauser, Paul Theo
    Hohn, Vanessa D.
    Henningsen, Peter
    Ploner, Markus
    NEUROIMAGE-CLINICAL, 2023, 39
  • [44] MEG and high-density EEG resting-state networks mapping in children
    Van Dyck, Dorine
    Coquelet, Nicolas
    Deconinck, Nicolas
    Aeby, Alec
    Baijot, Simon
    Goldman, Serge
    Urbain, Charline
    Trotta, Nicola
    Wens, Vincent
    De Tiege, Xavier
    CLINICAL NEUROPHYSIOLOGY, 2020, 131 (11) : 2713 - 2715
  • [45] Brain Network Analysis Based on Resting State Functional Magnetic Resonance Image
    Pan, Xin
    Jiang, Zhongyi
    Wang, Suhong
    Zou, Ling
    ADVANCED MANUFACTURING AND AUTOMATION VIII, 2019, 484 : 176 - 180
  • [46] Nodal properties of the resting-state brain functional network in childhood and adolescence
    Tian, Yu
    Xu, Gaoqiang
    Zhang, Jing
    Chen, Kuntao
    Liu, Songjiang
    JOURNAL OF NEUROIMAGING, 2023, 33 (06) : 1015 - 1023
  • [47] Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas
    Afnan, Jawata
    von Ellenrieder, Nicolas
    Lina, Jean-Marc
    Pellegrino, Giovanni
    Arcara, Giorgio
    Cai, Zhengchen
    Hedrich, Tanguy
    Abdallah, Chifaou
    Khajehpour, Hassan
    Frauscher, Birgit
    Gotman, Jean
    Grova, Christophe
    NEUROIMAGE, 2023, 274
  • [48] Exploring the brain network: A review on resting-state fMRI functional connectivity
    van den Heuvel, Martijn P.
    Pol, Hilleke E. Hulshoff
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2010, 20 (08) : 519 - 534
  • [49] Resting State Brain Network Modeling Based On Functional Magnetic Resonance Imaging
    Ke, Ming
    Li, Zhijing
    Cao, Zhao
    Yang, Xiaoping
    PROCEEDINGS OF THE 2015 JOINT INTERNATIONAL MECHANICAL, ELECTRONIC AND INFORMATION TECHNOLOGY CONFERENCE (JIMET 2015), 2015, 10 : 389 - 392
  • [50] Mobile EEG in research on neurodevelopmental disorders: Opportunities and challenges
    Lau-Zhu, Alex
    Lau, Michael P. H.
    McLoughlin, Grainne
    DEVELOPMENTAL COGNITIVE NEUROSCIENCE, 2019, 36