Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement

被引:2
|
作者
Sorrentino, Pierpaolo [1 ,2 ]
Ambrosanio, Michele [3 ]
Rucco, Rosaria [2 ]
Cabral, Joana [4 ,5 ]
Gollo, Leonardo L. [6 ,7 ]
Breakspear, Michael [7 ,8 ]
Baselice, Fabio [3 ]
机构
[1] Syst Neurosci Inst, Marseille, France
[2] Hermitage Capodimonte Hosp, Naples, Italy
[3] Univ Naples Parthenope, Egineering Dept, Naples, Italy
[4] Univ Minho, Life & Hlth Sci Res Inst ICVS, Braga, Portugal
[5] Univ Oxford, Dept Psychiat, Oxford, England
[6] Monash Univ, Turner Inst Brain & Mental Hlth, Melbourne, Vic, Australia
[7] QIMR Berghofer Med Res Inst, Brisbane, Qld, Australia
[8] Hunter Med Res Inst, Newcastle, NSW, Australia
关键词
cross frequency coupling; brain network; brain functional connectivity; phase coupling; phase linearity measurement; PLM; NEURONAL OSCILLATIONS; SYNCHRONIZATION; AMPLITUDE; CORTEX; MEG; CONNECTIVITY; NETWORKS; RHYTHMS; REAL; LEAD;
D O I
10.3389/fnins.2022.846623
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The current paper proposes a method to estimate phase to phase cross-frequency coupling between brain areas, applied to broadband signals, without any a priori hypothesis about the frequency of the synchronized components. N:m synchronization is the only form of cross-frequency synchronization that allows the exchange of information at the time resolution of the faster signal, hence likely to play a fundamental role in large-scale coordination of brain activity. The proposed method, named cross-frequency phase linearity measurement (CF-PLM), builds and expands upon the phase linearity measurement, an iso-frequency connectivity metrics previously published by our group. The main idea lies in using the shape of the interferometric spectrum of the two analyzed signals in order to estimate the strength of cross-frequency coupling. We first provide a theoretical explanation of the metrics. Then, we test the proposed metric on simulated data from coupled oscillators synchronized in iso- and cross-frequency (using both Rossler and Kuramoto oscillator models), and subsequently apply it on real data from brain activity. Results show that the method is useful to estimate n:m synchronization, based solely on the phase of the signals (independently of the amplitude), and no a-priori hypothesis is available about the expected frequencies.
引用
下载
收藏
页数:14
相关论文
共 50 条
  • [31] DETECTION OF CONDITION-BASED CHANGES IN CROSS-FREQUENCY COUPLING WITH MEG
    Soto, Juan L. P.
    Jerbi, Karim
    2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015, : 355 - 358
  • [32] Sample-Based Cross-Frequency Coupling Analysis with CFAR Detection
    Creusere, Charles D.
    Mcrae, Nathan
    Davis, Philip
    CONFERENCE RECORD OF THE 2014 FORTY-EIGHTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2014, : 179 - 183
  • [33] A critical note on the definition of phase-amplitude cross-frequency coupling
    Ozkurt, Tolga Esat
    Schnitzler, Alfons
    JOURNAL OF NEUROSCIENCE METHODS, 2011, 201 (02) : 438 - 443
  • [34] Cross-frequency coupling in real and simulated data
    Mueller, V.
    Jirsa, V.
    Lindenberger, U.
    INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 2012, 85 (03) : 382 - 383
  • [35] Cross-Frequency Brain Network Dynamics Support Pitch Change Detection
    Samiee, Soheila
    Vuvan, Dominique
    Florin, Esther
    Albouy, Philippe
    Peretz, Isabelle
    Baillet, Sylvain
    JOURNAL OF NEUROSCIENCE, 2022, 42 (18): : 3823 - 3835
  • [36] An information theoretic measure of cross-frequency coupling
    Silvia C Ardila-Jimenez
    Jiaying Tang
    Simon R Schultz
    BMC Neuroscience, 16 (Suppl 1)
  • [37] Comparison of Brain Network Models using Cross-Frequency Coupling and Attack Strategies
    Antonakakis, Marios
    Dimitriadis, Stavros I.
    Zervakis, Michalis
    Rezaie, Roozbeh
    Babajani-Feremi, Abbas
    Micheloyannis, Sifis
    Zouridakis, George
    Papanicolaou, Andrew C.
    2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2015, : 7426 - 7429
  • [38] Effective deep brain stimulation co-modulate cross-frequency coupling
    Muthuraman, M.
    Groppa, S.
    Glaser, M.
    Koirala, N.
    Bange, M.
    MOVEMENT DISORDERS, 2019, 34 : S816 - S816
  • [39] Corticothalamic phase synchrony and cross-frequency coupling predict human memory formation
    Sweeney-Reed, Catherine M.
    Zaehle, Tino
    Voges, Juergen
    Schmitt, Friedhelm C.
    Buentjen, Lars
    Kopitzki, Klaus
    Esslinger, Christine
    Hinrichs, Hermann
    Heinze, Hans-Jochen
    Knight, Robert T.
    Richardson-Klavehn, Alan
    ELIFE, 2014, 3 : e05352
  • [40] Cross-frequency coupling of brain oscillations indicates the success in visual motion discrimination
    Haendel, Barbara
    Haarmeier, Thomas
    NEUROIMAGE, 2009, 45 (03) : 1040 - 1046