Scale-free dynamics of global functional connectivity in the human brain

Higher brain functions depend upon the rapid creation and dissolution of ever changing synchronous cell assemblies. We examine the hypothesis that the dynamics of this process displays scale‐free, self‐similar properties. EEGs (19 channels, average reference, sample frequency 500 Hz) of 15 healthy s...

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Published inHuman brain mapping Vol. 22; no. 2; pp. 97 - 109
Main Authors Stam, Cornelis Jan, de Bruin, Eveline Astrid
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.06.2004
Wiley-Liss
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ISSN1065-9471
1097-0193
DOI10.1002/hbm.20016

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Abstract Higher brain functions depend upon the rapid creation and dissolution of ever changing synchronous cell assemblies. We examine the hypothesis that the dynamics of this process displays scale‐free, self‐similar properties. EEGs (19 channels, average reference, sample frequency 500 Hz) of 15 healthy subjects (10 men; mean age 22.5 years) were analyzed during eyes‐closed and eyes‐open no‐task conditions. Mean level of synchronization as a function of time was estimated with the synchronization likelihood for five frequency bands (0.5–4, 4–8, 8–13, 13–30, and 30–48 Hz). Scaling in these time series was investigated with detrended fluctuation analysis (DFA). DFA analysis of global synchronization time series showed scale‐free characteristics, suggesting neuronal dynamics do not necessarily have a characteristic time constant. The scaling exponent as determined with DFA differed significantly for different frequency bands and conditions. The exponent was close to 1.5 for low frequencies (δ, θ, and α) and close to 1 for β and γ bands. Eye opening decreased the exponent, in particular in α and β bands. Fluctuations of EEG synchronization in δ, θ, α, β, and γ bands exhibit scale‐free dynamics in eyes‐closed as well as eyes‐open no‐task states. The decrease in the scaling exponent following eye opening reflects a relative preponderance of rapid fluctuations with respect to slow changes in the mean synchronization level. The existence of scaling suggests that the underlying dynamics may display self‐organized criticality, possibly representing a near‐optimal state for information processing. Hum. Brain Mapping 22:99–111, 2004. © 2004 Wiley‐Liss, Inc.
AbstractList Higher brain functions depend upon the rapid creation and dissolution of ever changing synchronous cell assemblies. We examine the hypothesis that the dynamics of this process displays scale-free, self-similar properties. EEGs (19 channels, average reference, sample frequency 500 Hz) of 15 healthy subjects (10 men; mean age 22.5 years) were analyzed during eyes-closed and eyes-open no-task conditions. Mean level of synchronization as a function of time was estimated with the synchronization likelihood for five frequency bands (0.5-4, 4-8, 8-13, 13-30, and 30-48 Hz). Scaling in these time series was investigated with detrended fluctuation analysis (DFA). DFA analysis of global synchronization time series showed scale-free characteristics, suggesting neuronal dynamics do not necessarily have a characteristic time constant. The scaling exponent as determined with DFA differed significantly for different frequency bands and conditions. The exponent was close to 1.5 for low frequencies (, , and ) and close to 1 for and bands. Eye opening decreased the exponent, in particular in and bands. Fluctuations of EEG synchronization in , , , , and bands exhibit scale-free dynamics in eyes-closed as well as eyes-open no-task states. The decrease in the scaling exponent following eye opening reflects a relative preponderance of rapid fluctuations with respect to slow changes in the mean synchronization level. The existence of scaling suggests that the underlying dynamics may display self-organized criticality, possibly representing a near-optimal state for information processing. Hum. Brain Mapping 22:99-111, 2004.
Higher brain functions depend upon the rapid creation and dissolution of ever changing synchronous cell assemblies. We examine the hypothesis that the dynamics of this process displays scale‐free, self‐similar properties. EEGs (19 channels, average reference, sample frequency 500 Hz) of 15 healthy subjects (10 men; mean age 22.5 years) were analyzed during eyes‐closed and eyes‐open no‐task conditions. Mean level of synchronization as a function of time was estimated with the synchronization likelihood for five frequency bands (0.5–4, 4–8, 8–13, 13–30, and 30–48 Hz). Scaling in these time series was investigated with detrended fluctuation analysis (DFA). DFA analysis of global synchronization time series showed scale‐free characteristics, suggesting neuronal dynamics do not necessarily have a characteristic time constant. The scaling exponent as determined with DFA differed significantly for different frequency bands and conditions. The exponent was close to 1.5 for low frequencies (δ, θ, and α) and close to 1 for β and γ bands. Eye opening decreased the exponent, in particular in α and β bands. Fluctuations of EEG synchronization in δ, θ, α, β, and γ bands exhibit scale‐free dynamics in eyes‐closed as well as eyes‐open no‐task states. The decrease in the scaling exponent following eye opening reflects a relative preponderance of rapid fluctuations with respect to slow changes in the mean synchronization level. The existence of scaling suggests that the underlying dynamics may display self‐organized criticality, possibly representing a near‐optimal state for information processing. Hum. Brain Mapping 22:99–111, 2004. © 2004 Wiley‐Liss, Inc.
Higher brain functions depend upon the rapid creation and dissolution of ever changing synchronous cell assemblies. We examine the hypothesis that the dynamics of this process displays scale-free, self-similar properties. EEGs (19 channels, average reference, sample frequency 500 Hz) of 15 healthy subjects (10 men; mean age 22.5 years) were analyzed during eyes-closed and eyes-open no-task conditions. Mean level of synchronization as a function of time was estimated with the synchronization likelihood for five frequency bands (0.5-4, 4-8, 8-13, 13-30, and 30-48 Hz). Scaling in these time series was investigated with detrended fluctuation analysis (DFA). DFA analysis of global synchronization time series showed scale-free characteristics, suggesting neuronal dynamics do not necessarily have a characteristic time constant. The scaling exponent as determined with DFA differed significantly for different frequency bands and conditions. The exponent was close to 1.5 for low frequencies (delta, theta, and alpha) and close to 1 for beta and gamma bands. Eye opening decreased the exponent, in particular in alpha and beta bands. Fluctuations of EEG synchronization in delta, theta, alpha, beta, and gamma bands exhibit scale-free dynamics in eyes-closed as well as eyes-open no-task states. The decrease in the scaling exponent following eye opening reflects a relative preponderance of rapid fluctuations with respect to slow changes in the mean synchronization level. The existence of scaling suggests that the underlying dynamics may display self-organized criticality, possibly representing a near-optimal state for information processing.
Higher brain functions depend upon the rapid creation and dissolution of ever changing synchronous cell assemblies. We examine the hypothesis that the dynamics of this process displays scale-free, self-similar properties. EEGs (19 channels, average reference, sample frequency 500 Hz) of 15 healthy subjects (10 men; mean age 22.5 years) were analyzed during eyes-closed and eyes-open no-task conditions. Mean level of synchronization as a function of time was estimated with the synchronization likelihood for five frequency bands (0.5-4, 4-8, 8-13, 13-30, and 30-48 Hz). Scaling in these time series was investigated with detrended fluctuation analysis (DFA). DFA analysis of global synchronization time series showed scale-free characteristics, suggesting neuronal dynamics do not necessarily have a characteristic time constant. The scaling exponent as determined with DFA differed significantly for different frequency bands and conditions. The exponent was close to 1.5 for low frequencies (delta, theta, and alpha) and close to 1 for beta and gamma bands. Eye opening decreased the exponent, in particular in alpha and beta bands. Fluctuations of EEG synchronization in delta, theta, alpha, beta, and gamma bands exhibit scale-free dynamics in eyes-closed as well as eyes-open no-task states. The decrease in the scaling exponent following eye opening reflects a relative preponderance of rapid fluctuations with respect to slow changes in the mean synchronization level. The existence of scaling suggests that the underlying dynamics may display self-organized criticality, possibly representing a near-optimal state for information processing.Higher brain functions depend upon the rapid creation and dissolution of ever changing synchronous cell assemblies. We examine the hypothesis that the dynamics of this process displays scale-free, self-similar properties. EEGs (19 channels, average reference, sample frequency 500 Hz) of 15 healthy subjects (10 men; mean age 22.5 years) were analyzed during eyes-closed and eyes-open no-task conditions. Mean level of synchronization as a function of time was estimated with the synchronization likelihood for five frequency bands (0.5-4, 4-8, 8-13, 13-30, and 30-48 Hz). Scaling in these time series was investigated with detrended fluctuation analysis (DFA). DFA analysis of global synchronization time series showed scale-free characteristics, suggesting neuronal dynamics do not necessarily have a characteristic time constant. The scaling exponent as determined with DFA differed significantly for different frequency bands and conditions. The exponent was close to 1.5 for low frequencies (delta, theta, and alpha) and close to 1 for beta and gamma bands. Eye opening decreased the exponent, in particular in alpha and beta bands. Fluctuations of EEG synchronization in delta, theta, alpha, beta, and gamma bands exhibit scale-free dynamics in eyes-closed as well as eyes-open no-task states. The decrease in the scaling exponent following eye opening reflects a relative preponderance of rapid fluctuations with respect to slow changes in the mean synchronization level. The existence of scaling suggests that the underlying dynamics may display self-organized criticality, possibly representing a near-optimal state for information processing.
Author de Bruin, Eveline Astrid
Stam, Cornelis Jan
AuthorAffiliation 2 Department of Psychopharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
1 Department of Clinical Neurophysiology, VU University Medical Center, Amsterdam, The Netherlands
AuthorAffiliation_xml – name: 2 Department of Psychopharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
– name: 1 Department of Clinical Neurophysiology, VU University Medical Center, Amsterdam, The Netherlands
Author_xml – sequence: 1
  givenname: Cornelis Jan
  surname: Stam
  fullname: Stam, Cornelis Jan
  email: CJ.Stam@Vumc.nl
  organization: Department of Clinical Neurophysiology, VU University Medical Center, Amsterdam, The Netherlands
– sequence: 2
  givenname: Eveline Astrid
  surname: de Bruin
  fullname: de Bruin, Eveline Astrid
  organization: Department of Psychopharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
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Issue 2
Keywords Human
Fluctuations
Nervous system diseases
Radiodiagnosis
scale-free
EEG
Central nervous system
detrended fluctuation analysis
Electrophysiology
Electroencephalography
Synchronization
self-similar
Encephalon
self-organized criticality
Working memory
Language English
License http://onlinelibrary.wiley.com/termsAndConditions#vor
CC BY 4.0
Copyright 2004 Wiley-Liss, Inc.
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PublicationDate June 2004
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  text: June 2004
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PublicationTitle Human brain mapping
PublicationTitleAlternate Hum. Brain Mapp
PublicationYear 2004
Publisher Wiley Subscription Services, Inc., A Wiley Company
Wiley-Liss
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References Stam CJ, van Cappellen van Walsum AM, Pijnenburg YAL, Berendse HW, de Munck JC, Scheltens Ph, van Dijk BW (2002b): Generalized synchronization of MEG recordings in Alzheimer's disease: evidence for involvement of the γ band. J Clin Neurophysiol 19: 562-574.
Linkenkaer-Hansen K, Nikouline VV, Palva JM, Ilmoniemi RJ (2001): Long-range temporal correlations and scaling behavior in human brain oscillations. J Neurosci 21: 1370-1377.
Greicius MD, Krasnow B, Reiss AL, Menon V (2003): Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 100: 253-258.
Fell J, Klaver P, Elfadil H, Schaller C, Elger Ch E, Fernandez G (2003): Rhinal-hippocampal θ coherence during declarative memory formation: interaction with γ synchronization? Eur J Neurosci 17: 1082-1088.
Nunez PL, Srinivasan R, Westdorp AF, Wijesinghe RS, Tucker DM, Silberstein RB, Cadusch PJ (1992): EEG coherency I: statistics, reference electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scales. Electroenceph Clin Neurophysiol 103: 499-515.
Stam CJ, van der Made Y, Pijnenburg YAL, Scheltens Ph (2003b): EEG synchronization in mild cognitive impairment and Alzheimer's disease. Acta Neurol Scand 108: 90-96.
Gong P, Nikolaev AR, van Leeuwen C (2003): Scale-invariant fluctuations of the dynamical synchronization in human brain electrical activity. Neurosci Lett 336: 33-36.
Bullock TH, McClune MC, Achimowicz JZ, Iragui-Madoz VJ, Duckrow RB, Spencer SS (1995): Temporal fluctuations in coherence of brain waves. Proc Natl Acad Sci USA 92: 11568-11572.
Friston KJ (2000): The labile brain. I. Neuronal transients and nonlinear coupling. Phil Trans R Soc Lond B 355: 215-236.
Engel AK, Singer W (2001): Temporal binding and the neural correlates of sensory awareness. Trends Cognit Sci 5: 16-25.
Schack B, Vath N, Petsche H, Geissler H-G, Moller E (2002): Phase-coupling of θ-γ EEG rhythms during short-term memory processing. Int J Psychophysiol 44: 143-163.
Van Putten MJAM (2003): Proposed link rates in the human brain. J Neurosci Methods 127: 1-10.
Stam CJ, van Dijk BW (2002): Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets. Physica D 163: 236-241.
Hopfield JJ, Brody CD (2001): What is a moment? Transient synchrony as a collective mechanism for spatiotemporal integration. PNAS 98: 1282-1287.
Lee J-M, Kim D-J, Kim I-Y, Park K-S, Kim SI (2002): Detrended fluctuation analysis of EEG in sleep apnea using MIT/BIG polysomnography data. Comput Biol Med 32: 37-47.
Stam CJ, Pijn JPM, Suffczynski P, Lopes da Silva FH (1999): Dynamics of the human α rhythm: evidence for non-linearity? Clin Neurophysiol 110: 1801-1813.
Hwa R, Ferree ThC (2002): Scaling properties of fluctations in the human electroencephalogram. Phys Rev E 66: 021901.
Breakspear M, Terry JR, Friston KJ (2003): Modulation of excitatory synaptic coupling facilitates synchronization and complex dynamics in a biophysiocal model of neuronal dynamics. Network: Comput Neural Syst 14: 703-732.
Peng CK, Havlin S, Stanley HE, Goldbergeer AL (1995): Quantification of scaling exponents and crossover phenomena in nonstationary hearbeat time series. Chaos 5: 82-87.
Leopold DA, Murayama Y, Logothetis NK (2003): ) Very slow activity fluctuations in monkey visuual cortex: implications for functional brain imaging. Cereb Cort 13: 422-433.
Freeman WJ, Rogers LJ (2002): Fine temporal resolution of analytic phase reveals episodic synchronization by state transitions in γ EEGs. J Neurophysiol 87: 937-945.
Sarnthein J, Petsche H, Rappelsberger P, Shaw GL, von Stein A (1998): Synchronization between prefrontal and posterior association cortex during human working memory. Proc Natl Acad Sci USA 95: 7092-7096.
Bressler SL, Kelso JAS (2001): Cortical coordination dynamics and cognition. Trends Cognit Neurosci 5: 26-36.
Freeman WJ, Burke BC, Holmes MD (2003): Aperiodic phase-resetting in scalp EEG of β-γ oscillations by state transitions at α-θ rates. Hum Brain Mapping 19: 248-272.
Gilden DL, Thornton T, Mallon MW (1995): 1/f Noise in human cognition. Science 267: 1837-1839.
Singer W (2001): Consciousness and the binding problem. Ann NY Acad Sci 929: 123-146.
Varela F, Lachaux J-P, Rodriguez E, Martinerie J (2001): The brainweb: phase synchronization and large-scale integration. Nature Rev Neurosci 2: 229-239.
Rodriguez E, George N, Lachaux JP, Martinerie J, Renault B, Varela FJ (1999): Perception's shadow: long-distance synchronization of human brain activity. Nature 397: 430-433.
Bak P, Tang Ch, Wiesenfeld K (1987): Self-organized criticality: an explanation of 1/f noise. Phys Rev Lett 59: 381-384.
Shen Y, Olbrich E, Achermann P, Meier PF (2003): Dimensional complexity and spectral properties of the human sleep EEG. Clin Neurophysiol 114: 199-209.
Stam CJ, van Cappellen van Walsum AM, Micheloyannis S (2002a): Variability of EEG synchronization during a working memory task in healthy subjects. Int J Psychophysiol 46: 53-66.
Corral A, Perez J, Diaz-Guilera A, Arenas A (1995): Self-organized criticality and synchronization in a lattice model of integrate-and-fire oscillators. Phys Rev Lett 74: 118-121.
Stam CJ, Breakspear M, van Cappellen van Walsum AM, van Dijk BW (2003a): Nonlinear synchronization in EEG and whole-head MEG recordings of healthy subjects. Hum Brain Mapping 19: 63-78.
Basar E, Basar-Eroglu C, Karakas S, Schurmann M (2001): Gamma, α, δ, and θ oscillations govern cognitive processes. Int J Psychophysiol 39: 241-248.
Takens F (1981): Detecting strange attractors in turbulence. Lecture Notes in Mathematics 898: 366-381.
Burgess AP, Ali L (2002): Functional connectivity of γ EEG activity is modulated at low frequency during conscious recollection. Int J Psychophysiol 46: 91-100.
Le van Quyen, M (2003): Disentangling the dynamic core: a research program for a neurodynamics at the large-scale. Biol Res 36: 67-88.
Lisman JE, Idiart MAP (1995): Storage of 7 ± 2 short-term memories in oscillatory subcycles. Science 267: 1512-1515.
Peng CK, Buldyrev SV, Goldberger AL, Havlin S, Sciortino F, Simons M, Stanley HE (1992): Long-range correlations in nucleotide sequences. Nature 356: 168-170.
Pfurtscheller G, Aranibar A (1997): Event-related cortical desynchronization detected by power measurements of scalp EEG. Electroenceph Clin Neurophysiol 42: 817-826.
1995; 74
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2003; 336
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2002; 32
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2002a; 46
2002; 87
1992; 356
2002; 66
2002; 44
1999; 110
1981; 898
1995; 267
2001; 2
2001; 39
1999; 397
1998; 95
2003; 100
2001; 98
2003b; 108
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References_xml – reference: Bressler SL, Kelso JAS (2001): Cortical coordination dynamics and cognition. Trends Cognit Neurosci 5: 26-36.
– reference: Stam CJ, van der Made Y, Pijnenburg YAL, Scheltens Ph (2003b): EEG synchronization in mild cognitive impairment and Alzheimer's disease. Acta Neurol Scand 108: 90-96.
– reference: Sarnthein J, Petsche H, Rappelsberger P, Shaw GL, von Stein A (1998): Synchronization between prefrontal and posterior association cortex during human working memory. Proc Natl Acad Sci USA 95: 7092-7096.
– reference: Rodriguez E, George N, Lachaux JP, Martinerie J, Renault B, Varela FJ (1999): Perception's shadow: long-distance synchronization of human brain activity. Nature 397: 430-433.
– reference: Lee J-M, Kim D-J, Kim I-Y, Park K-S, Kim SI (2002): Detrended fluctuation analysis of EEG in sleep apnea using MIT/BIG polysomnography data. Comput Biol Med 32: 37-47.
– reference: Bak P, Tang Ch, Wiesenfeld K (1987): Self-organized criticality: an explanation of 1/f noise. Phys Rev Lett 59: 381-384.
– reference: Fell J, Klaver P, Elfadil H, Schaller C, Elger Ch E, Fernandez G (2003): Rhinal-hippocampal θ coherence during declarative memory formation: interaction with γ synchronization? Eur J Neurosci 17: 1082-1088.
– reference: Peng CK, Havlin S, Stanley HE, Goldbergeer AL (1995): Quantification of scaling exponents and crossover phenomena in nonstationary hearbeat time series. Chaos 5: 82-87.
– reference: Freeman WJ, Burke BC, Holmes MD (2003): Aperiodic phase-resetting in scalp EEG of β-γ oscillations by state transitions at α-θ rates. Hum Brain Mapping 19: 248-272.
– reference: Stam CJ, van Cappellen van Walsum AM, Pijnenburg YAL, Berendse HW, de Munck JC, Scheltens Ph, van Dijk BW (2002b): Generalized synchronization of MEG recordings in Alzheimer's disease: evidence for involvement of the γ band. J Clin Neurophysiol 19: 562-574.
– reference: Stam CJ, van Cappellen van Walsum AM, Micheloyannis S (2002a): Variability of EEG synchronization during a working memory task in healthy subjects. Int J Psychophysiol 46: 53-66.
– reference: Hopfield JJ, Brody CD (2001): What is a moment? Transient synchrony as a collective mechanism for spatiotemporal integration. PNAS 98: 1282-1287.
– reference: Breakspear M, Terry JR, Friston KJ (2003): Modulation of excitatory synaptic coupling facilitates synchronization and complex dynamics in a biophysiocal model of neuronal dynamics. Network: Comput Neural Syst 14: 703-732.
– reference: Pfurtscheller G, Aranibar A (1997): Event-related cortical desynchronization detected by power measurements of scalp EEG. Electroenceph Clin Neurophysiol 42: 817-826.
– reference: Stam CJ, van Dijk BW (2002): Synchronization likelihood: an unbiased measure of generalized synchronization in multivariate data sets. Physica D 163: 236-241.
– reference: Burgess AP, Ali L (2002): Functional connectivity of γ EEG activity is modulated at low frequency during conscious recollection. Int J Psychophysiol 46: 91-100.
– reference: Bullock TH, McClune MC, Achimowicz JZ, Iragui-Madoz VJ, Duckrow RB, Spencer SS (1995): Temporal fluctuations in coherence of brain waves. Proc Natl Acad Sci USA 92: 11568-11572.
– reference: Linkenkaer-Hansen K, Nikouline VV, Palva JM, Ilmoniemi RJ (2001): Long-range temporal correlations and scaling behavior in human brain oscillations. J Neurosci 21: 1370-1377.
– reference: Leopold DA, Murayama Y, Logothetis NK (2003): ) Very slow activity fluctuations in monkey visuual cortex: implications for functional brain imaging. Cereb Cort 13: 422-433.
– reference: Greicius MD, Krasnow B, Reiss AL, Menon V (2003): Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 100: 253-258.
– reference: Hwa R, Ferree ThC (2002): Scaling properties of fluctations in the human electroencephalogram. Phys Rev E 66: 021901.
– reference: Nunez PL, Srinivasan R, Westdorp AF, Wijesinghe RS, Tucker DM, Silberstein RB, Cadusch PJ (1992): EEG coherency I: statistics, reference electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scales. Electroenceph Clin Neurophysiol 103: 499-515.
– reference: Schack B, Vath N, Petsche H, Geissler H-G, Moller E (2002): Phase-coupling of θ-γ EEG rhythms during short-term memory processing. Int J Psychophysiol 44: 143-163.
– reference: Varela F, Lachaux J-P, Rodriguez E, Martinerie J (2001): The brainweb: phase synchronization and large-scale integration. Nature Rev Neurosci 2: 229-239.
– reference: Engel AK, Singer W (2001): Temporal binding and the neural correlates of sensory awareness. Trends Cognit Sci 5: 16-25.
– reference: Le van Quyen, M (2003): Disentangling the dynamic core: a research program for a neurodynamics at the large-scale. Biol Res 36: 67-88.
– reference: Friston KJ (2000): The labile brain. I. Neuronal transients and nonlinear coupling. Phil Trans R Soc Lond B 355: 215-236.
– reference: Stam CJ, Breakspear M, van Cappellen van Walsum AM, van Dijk BW (2003a): Nonlinear synchronization in EEG and whole-head MEG recordings of healthy subjects. Hum Brain Mapping 19: 63-78.
– reference: Shen Y, Olbrich E, Achermann P, Meier PF (2003): Dimensional complexity and spectral properties of the human sleep EEG. Clin Neurophysiol 114: 199-209.
– reference: Corral A, Perez J, Diaz-Guilera A, Arenas A (1995): Self-organized criticality and synchronization in a lattice model of integrate-and-fire oscillators. Phys Rev Lett 74: 118-121.
– reference: Gilden DL, Thornton T, Mallon MW (1995): 1/f Noise in human cognition. Science 267: 1837-1839.
– reference: Stam CJ, Pijn JPM, Suffczynski P, Lopes da Silva FH (1999): Dynamics of the human α rhythm: evidence for non-linearity? Clin Neurophysiol 110: 1801-1813.
– reference: Basar E, Basar-Eroglu C, Karakas S, Schurmann M (2001): Gamma, α, δ, and θ oscillations govern cognitive processes. Int J Psychophysiol 39: 241-248.
– reference: Freeman WJ, Rogers LJ (2002): Fine temporal resolution of analytic phase reveals episodic synchronization by state transitions in γ EEGs. J Neurophysiol 87: 937-945.
– reference: Van Putten MJAM (2003): Proposed link rates in the human brain. J Neurosci Methods 127: 1-10.
– reference: Peng CK, Buldyrev SV, Goldberger AL, Havlin S, Sciortino F, Simons M, Stanley HE (1992): Long-range correlations in nucleotide sequences. Nature 356: 168-170.
– reference: Takens F (1981): Detecting strange attractors in turbulence. Lecture Notes in Mathematics 898: 366-381.
– reference: Lisman JE, Idiart MAP (1995): Storage of 7 ± 2 short-term memories in oscillatory subcycles. Science 267: 1512-1515.
– reference: Singer W (2001): Consciousness and the binding problem. Ann NY Acad Sci 929: 123-146.
– reference: Gong P, Nikolaev AR, van Leeuwen C (2003): Scale-invariant fluctuations of the dynamical synchronization in human brain electrical activity. Neurosci Lett 336: 33-36.
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Snippet Higher brain functions depend upon the rapid creation and dissolution of ever changing synchronous cell assemblies. We examine the hypothesis that the dynamics...
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StartPage 97
SubjectTerms Adolescent
Adult
Biological and medical sciences
Brain - physiology
Brain Mapping
Cortical Synchronization
detrended fluctuation analysis
EEG
Electroencephalography
Evoked Potentials, Visual - physiology
Female
Humans
Investigative techniques, diagnostic techniques (general aspects)
Male
Medical sciences
Nervous system
Radiodiagnosis. Nmr imagery. Nmr spectrometry
scale-free
self-organized criticality
self-similar
synchronization
working memory
Title Scale-free dynamics of global functional connectivity in the human brain
URI https://api.istex.fr/ark:/67375/WNG-QTHPT08Z-N/fulltext.pdf
https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fhbm.20016
https://www.ncbi.nlm.nih.gov/pubmed/15108297
https://www.proquest.com/docview/20473076
https://www.proquest.com/docview/71869452
https://pubmed.ncbi.nlm.nih.gov/PMC6871799
Volume 22
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