Magnetoencephalography in the study of brain dynamics

Functional Neurology

Volumn 29, Issue 4, 2014, Pages 241-253

  Pizzella, Vittorio ^a   Marzetti, Laura ^a   Penna, Stefania Della ^a   De Pasquale, Francesco ^a   Zappasodi, Filippo ^a   Romani, Gian Luca ^a  

^a UNIVERSITY OF CHIETI   (Italy)

Author keywords

Brain dynamics; Brain networks; Magnetoencephalography

Indexed keywords

ARTICLE; BOLD SIGNAL; BRAIN FUNCTION; CONNECTOME; ELECTROENCEPHALOGRAPHY; EVOKED RESPONSE; FUNCTIONAL ASSESSMENT; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; MAGNETOENCEPHALOGRAPHY; SIGNAL NOISE RATIO; SIGNAL PROCESSING; BRAIN; FUNCTIONAL NEUROIMAGING; NERVE CELL NETWORK; PHYSIOLOGY; PROCEDURES;

BRAIN; FUNCTIONAL NEUROIMAGING; HUMANS; MAGNETOENCEPHALOGRAPHY; NERVE NET;

EID: 84924864629     PISSN: 03935264     EISSN: 19713274     Source Type: Journal    
DOI: 10.11138/fneur/2014.29.4.241     Document Type: Article

References (81)

1. Ahlfors SP, Simpson GV, Dale AM, et al (1999). Spatiotemporal activity of a cortical network for processing visual motion revealed by MEG and fMRI. J Neurophysiol 82:2545-2555.
2. Baillet S, Mosher JC, Leahy RM (2001). Electromagnetic brain mapping. IEEE Signal Processing Magazine 18:14-30.
3. Beggs JM, Plenz D (2003) Neuronal avalanches in neocortical circuits. J Neurosci 23:11167-11177.
4. Betti V, Della Penna S, de Pasquale F, et al (2013). Natural scenes viewing alters the dynamics of functional connectivity in the human brain. Neuron 79:782-797.
5. Biswal B, Yetkin FZ, Haughton VM, et al (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34:537-541.
6. Brancucci A, Franciotti R, D’Anselmo A, et al (2011). The sound of consciousness: neural underpinnings of auditory perception. J Neurosci 31:16611-16618.
7. Brookes MJ, Hale JR, Zumer JM, et al (2011a). Measuring functional connectivity using MEG: methodology and comparison with fcMRI. Neuroimage 56:1082-1104.
8. Brookes MJ, Woolrich M, Luckhoo H, et al (2011b). Investigating the electrophysiological basis of resting state networks using magnetoencephalography. Proc Natl Acad Sci USA 108:16783-16788.
9. Brookes MJ, Woolrich MW, Barnes GR (2012). Measuring functional connectivity in MEG: a multivariate approach insensitive to linear source leakage. Neuroimage 63:910-920.
10. Brunetti M, Della Penna S, Ferretti A, et al (2008). A frontoparietal network for the spatial attention reorienting in the auditory domain: A human fMRI/MEG study of functional and temporal dynamics. Cereb Cortex 18:1139-1147.
11. Brunetti M, Zappasodi F, Marzetti L, et al (2014). Do you know what I mean? Brain oscillations and the understanding of communicative intentions. Front Hum Neurosci 8:36.
12. Buzsáki G (2006). Rhythms of the Brain. New York, Oxford University Press.
13. Buzsáki G, Draguhn A (2004). Neuronal oscillations in cortical networks. Science 304:1926-1929.
14. Chella F, Marzetti L, Pizzella V, et al (2014). Third order spectral analysis robust to mixing artifacts for mapping crossfrequency interactions in EEG/MEG. Neuroimage 91:146-161.
15. Cichy RM, Pantazis D, Oliva A (2014). Resolving human object recognition in space and time. Nat Neurosci 17:455-462.
16. Clarke J, Braginski A (Eds) (2006). The SQUID Handbook Vol. 1 & 2. New York, Wiley.
17. Dale AM, Fischl B, Sereno MI (1999). Cortical surface-based analysis. I. segmentation and surface reconstruction. Neuroimage 9:179-194.
18. Deco G, Corbetta M (2011). The dynamical balance of the brain at rest. Neuroscientist 17:107-123.
19. Deco G, Jirsa VK (2012). Ongoing cortical activity at rest: criticality, multistability, and ghost attractors. J Neurosci 32: 3366-3375.
20. Del Gratta C, Della Penna S, Ferretti A, et al (2002). Topographic organization of the human primary and secondary somatosensory cortices: comparison of fMRI and MEG findings. Neuroimage 17:1373-1383.
21. Della Penna S, Brancucci A, Babiloni C, et al (2007). Lateralization of dichotic speech stimuli is based on specific auditory pathway interactions: neuromagnetic evidence. Cereb Cortex 17:2303-2311.
22. Della Penna S, Pizzella V, Romani GL (2014). Impact of SQUIDs on functional imaging in neuroscience. Superconductor Science and Technology 27:044004.
23. de Pasquale F, Della Penna S, Snyder AZ, et al (2010). Temporal dynamics of spontaneous MEG activity in brain networks. Proc Natl Acad Sci USA 107:6040-6045.
24. de Pasquale F, Della Penna S, Snyder AZ, et al (2012). A cortical core for dynamic integration of functional networks in the resting human brain. Neuron 74:753-764.
25. Di Lanzo C, Marzetti L, Zappasodi F, et al (2012). Redundancy as a graph-based index of frequency specific MEG functional connectivity. Comput Math Methods Med 2012: 207305.
26. Donner TH, Siegel M, Fries P, et al (2009). Buildup of choicepredictive activity in human motor cortex during perceptual decision making. Curr Biol 19:1581-1585.
27. Dymond S, Lawrence NS, Dunkley BT, et al (2014). Almost winning: induced MEG theta power in insula and orbitofrontal cortex increases during gambling near-misses and is associated with BOLD signal and gambling severity. Neuroimage 91:210-219.
28. Engel AK, Fries P (2010). Beta-band oscillations—signalling the status quo? Curr Opin Neurobiol 20:156-165.
29. Engel AK, Gerloff C, Hilgetag CC, et al (2013). Intrinsic coupling modes: multiscale interactions in ongoing brain activity. Neuron 80:867-886.
30. Ewald A, Marzetti L, Zappasodi F, et al (2012). Estimating true brain connectivity from EEG/MEG data invariant to linear and static transformations in sensor space. Neuroimage. 60:476-488.
31. Friston KJ (2011). Functional and effective connectivity: a review. Brain Connect 1:13-36.
32. Fuchs M, Drenckhahn R, Wischmann HA, et al (1998). An improved boundary element method for realistic volumeconductor modeling. IEEE Trans Biomed Eng 45:980-997.
33. Hämäläinen M, Hari R, Ilmoniemi R, et al (1993). Magneto - encephalography: theory, instrumentation and applications to the noninvasive study of human brain function. Review of Modern Physics 65:413-497.
34. Hauk O, Stenroos M (2014). A framework for the design of flexible cross-talk functions for spatial filtering of EEG/MEG data: DeFleCT. Hum Brain Mapp 35:1642-1653.
35. He BJ (2014). Scale-free brain activity: past, present, and future. Trends Cogn Sci 18:480-487.
36. Hillebrand A, Barnes GR, Bosboom JL, et al (2012). Frequency-dependent functional connectivity within resting- state networks: an atlas-based MEG beamformer solution. Neuroimage 59:3909-3921.
37. Hipp JF, Hawellek DJ, Corbetta M, et al (2012). Large-scale cortical correlation structure of spontaneous oscillatory activity. Nat Neurosci 15:884-890.
38. Horwitz B (2003). The elusive concept of brain connectivity. Neuroimage 19:466-470.
39. Huettel SA, Song AW, McCarthy G (2009). Functional Magnetic Resonance Imaging. Massachusetts, Sinauer.
40. Hutchison RM, Womelsdorf T, Allen EA, et al (2013). Dynamic functional connectivity: promise, issues, and interpretations. Neuroimage 80:360-378.
41. Jung P, Klein JC, Wibral M, et al (2012). Spatiotemporal dynamics of bimanual integration in human somatosensory cortex and their relevance to bimanual object manipulation. J Neurosci 32:5667-5677.
42. Lang EW, Tomé AM, Keck IR, et al (2012). Brain connectivity analysis: a short survey. Comput Intell Neurosci 2012: 412512.
43. Larson-Prior LJ, Oostenveld R, Della Penna S, et al (2013). Adding dynamics to the Human Connectome Project with MEG. Neuroimage 80:190-201.
44. Le Bihan D (2003). Looking into the functional architecture of the brain with diffusion MRI. Nat Rev Neurosci 4:469-480.
45. Leonard MK, Ferjan-Ramirez N, Torres C, et al (2012). Signed words in the congenitally deaf evoke typical late lexicosemantic responses with no early visual responses in left superior temporal cortex. J Neurosci 32:9700-9705.
46. Liu Z, Fukunaga M, de Zwart JA, et al (2010). Large-scale spontaneous fluctuations and correlations in brain electrical activity observed with magnetoencephalography. Neuroimage 51:102-111.
47. Marzetti L, Nolte G, Perrucci MG, et al (2007). The use of standardized infinity reference in EEG coherency studies. Neuroimage 36:48-63.
48. Marzetti L, Del Gratta C, Nolte G (2008). Understanding brain connectivity from EEG data by identifying systems composed of interacting sources. Neuroimage 42:87-98.
49. Marzetti L, Della Penna S, Snyder AZ, et al (2013). Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure. Neuroimage 79:172-183.
50. Marzetti L, Di Lanzo C, Zappasodi F, et al (2014). Magneto - encephalographic alpha band connectivity reveals differential default mode network interactions during focused attention and open monitoring meditation. Front Hum Neurosci 8:832.
51. Nolte G, Fieseler T, Curio G (2001). Perturbative analytical solutions of the magnetic forward problem for realistic volume conductors. Journal of Applied Physics 89:2360-2368.
52. Nolte G, Bai O, Wheaton L, et al (2004). Identifying true brain interaction from EEG data using the imaginary part of coherency. Clin Neurophysiol 115:2292-2307.
53. Nolte G, Marzetti L, Valdes Sosa P (2009). Minimum overlap component analysis (MOCA) of EEG/MEG data for more than two sources. J Neurosci Methods 183:72-76.
54. Nolte G, Marzetti L (2014). Methods to estimate functional and effective brain connectivity from MEG data robust to artifacts of volume conduction. In S Supek S, CJ Aine (Eds), MEG: From signal to Dynamic cortical networks, Springer, Berlin.
55. Palva S, Palva JM (2007). New vistas for a-frequency band oscillations. Trends Neurosci 30:150-158.
56. Palva JM, Palva S (2012). Infra-slow fluctuations in electrophysiological recordings, blood-oxygenation-level-dependent signals, and psychophysical time series. Neuroimage 62: 2201-2211.
57. Palva JM, Zhigalov A, Hirvonen J, et al (2013). Neuronal longrange temporal correlations and avalanche dynamics are correlated with behavioral scaling laws. Proc Natl Acad Sci U S A 110:3585-3590.
58. Petermann T, Thiagarajan TC, Lebedev MA, et al (2009) Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc Natl Acad Sci U S A 106:15921-15926.
59. Pfurtscheller G, Lopes da Silva FH (1999). Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 110:1842-1857.
60. Pizzella V, Della Penna S, Del Gratta C, et al (2001). SQUID systems for biomagnetic imaging. Superconductor Science and Technology 14:R79-R114.
61. Raichle ME (2010). Two views of brain function. Trends Cogn Sci 14:180-190.
62. Rouhinen S, Panula J, Palva JM, et al (2013). Load dependence of β and γ oscillations predicts individual capacity of visual attention. J Neurosci 33:19023-19033.
63. Sakkalis V (2011). Review of advanced techniques for the estimation of brain connectivity measured with EEG/MEG. Comput Biol Med 41:1110-1117.
64. Sarvas J (1987). Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. Phys Med Biol 32:11-22.
65. Schoffelen JM, Gross J (2009). Source connectivity analysis with MEG and EEG. Hum Brain Mapp 30:1857-1865.
66. Sekihara K, Owen JP, Trisno S, et al (2011). Removal of spurious coherence in MEG source-space coherence analysis. IEEE Trans Biomed Eng 58:3121-3129.
67. Stam CJ (2010). Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders. J Neurol Sci 289:128-234.
68. Stam CJ, van Straaten EC (2012). Go with the flow: use of a directed phase lag index (dPLI) to characterize patterns of phase relations in a large-scale model of brain dynamics. Neuroimage 62:1415-1428.
69. Stenroos M, Hunold A, Haueisen J (2014). Comparison of three-shell and simplified volume conductor models in magnetoencephalography. Neuroimage 94:337-348.
70. Stufflebeam SM, Tanaka N, Ahlfors SP (2009). Clinical applications of magnetoencephalography. Hum Brain Mapp 30: 1813-1823.
71. Tarantola A (2004). Inverse problem theory and methods for model parameter estimation. Philadelphia, USA, SIAM.
72. Tetzlaff C, Okujeni S, Egert U, et al (2010). Self-organized criticality in developing neuronal networks. PLoS Comput Biol 6:e1001013.
73. Torquati K, Pizzella V, Babiloni C, et al (2005). Nociceptive and non-nociceptive sub-regions in human secondary somatosensory cortex: an MEG study using fMRI constraints. Neuroimage 26:48-56.
74. Torquati K, Pizzella V, Della Penna S, et al (2003). “Gating” effects of simultaneous peripheral electrical stimulations on human secondary somatosensory cortex: a whole-head MEG study. Neuroimage 20:1704-1713.
75. van Dijk H, van der Werf J, Mazaheri A, et al (2010). Modulations in oscillatory activity with amplitude asymmetry can produce cognitively relevant event-related responses. Proc Natl Acad Sci U S A 107:900-905.
76. Vanni S, Tanskanen T, Seppä M, et al (2001). Coinciding early activation of human primary visual cortex and anteromedial cuneus. Proc Natl Acad Sci USA 98:2776-2780
77. Varela F, Lachaux JP, Rodriguez E, et al (2001). The brainweb: phase synchronization and large-scale integration. Nat Rev Neurosci 2:229-239.
78. Waldert S, Preissl H, Demandt E, et al (2008). Hand movement direction decoded from MEG and EEG. J Neurosci 28: 1000-1008.
79. Weisz N, Müller N, Jatzev S, et al (2014). Oscillatory alpha modulations in right auditory regions reflect the validity of acoustic cues in an auditory spatial attention task. Cereb Cortex 24:2579-2590.
80. Wolters CH, Anwander A, Tricoche X, et al (2006). Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: a simulation and visualization study using high-resolution finite element modeling. Neuroimage 30:813-826.
81. Zappasodi F, Olejarczyk E, Marzetti L, et al (2014). Fractal dimension of EEG activity senses neuronal impairment in acute stroke. PLoS One 9:e100199.