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Complexity of Multi-Dimensional Spontaneous EEG Decreases during Propofol Induced General Anaesthesia.

Schartner M, Seth A, Noirhomme Q, Boly M, Bruno MA, Laureys S, Barrett A - PLoS ONE (2015)

Bottom Line: Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions).In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation.We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels.

View Article: PubMed Central - PubMed

Affiliation: Sackler Centre for Consciousness Science, Department of Informatics, University of Sussex, Brighton, United Kingdom.

ABSTRACT
Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct 'flavours' of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia.

No MeSH data available.


Related in: MedlinePlus

LZc, ACE and SCE for Kuramoto model.The data were obtained by varying phase-lags for inter-community interactions. A small value of βext corresponds to a large phase lag and leads to little inter-community synchrony (as measured by phase synchrony, PhaseSync—indicated as green discs, see text for its computation) whereas larger values of βext correspond to smaller phase lags and lead to greater inter-community synchrony. See main text for details. LZc and ACE show similar dependence on βext whereas SCE peaks where the former two have a minimum.
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pone.0133532.g006: LZc, ACE and SCE for Kuramoto model.The data were obtained by varying phase-lags for inter-community interactions. A small value of βext corresponds to a large phase lag and leads to little inter-community synchrony (as measured by phase synchrony, PhaseSync—indicated as green discs, see text for its computation) whereas larger values of βext correspond to smaller phase lags and lead to greater inter-community synchrony. See main text for details. LZc and ACE show similar dependence on βext whereas SCE peaks where the former two have a minimum.

Mentions: Secondly, we computed the three measures for simulated continuous data created with a Kuramoto model (see Methods, Section ‘Kuramoto model’), a model known to display rich dynamics [37, 49]. Fig 6 shows the results for the Kuramoto simulations, plotting LZc, ACE and SCE against the phase-lag parameter βext. In addition a measure of phase synchrony is plotted (PhaseSync), being the mean of over all observations t and channels i, as described in the definition of SCE. This plot illustrates (i) the similarity of LZc and ACE, which are both based on the diversity of the dynamics of amplitude fluctuations, and (ii) that SCE is a distinct measure of complexity to LZc and ACE, by virtue of being based on diversity in synchrony patterns. For all values of βext, fluctuations in the amplitude of each community propagate to different communities, and this leads to diversity in relative amplitude reflected in the high values of LZc and ACE. In contrast, SCE is (i) low for small values of βext (large phase lag) since there is little synchrony between communities, (ii) low for large values of βext (small phase lag) since there is almost total synchrony between communities, (iii) high for intermediate values of βext in which synchrony between communities is able to fluctuate. Also note that LZc and ACE have a minimum at βext = 0.15 whereas SCE has a maximum there.


Complexity of Multi-Dimensional Spontaneous EEG Decreases during Propofol Induced General Anaesthesia.

Schartner M, Seth A, Noirhomme Q, Boly M, Bruno MA, Laureys S, Barrett A - PLoS ONE (2015)

LZc, ACE and SCE for Kuramoto model.The data were obtained by varying phase-lags for inter-community interactions. A small value of βext corresponds to a large phase lag and leads to little inter-community synchrony (as measured by phase synchrony, PhaseSync—indicated as green discs, see text for its computation) whereas larger values of βext correspond to smaller phase lags and lead to greater inter-community synchrony. See main text for details. LZc and ACE show similar dependence on βext whereas SCE peaks where the former two have a minimum.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4529106&req=5

pone.0133532.g006: LZc, ACE and SCE for Kuramoto model.The data were obtained by varying phase-lags for inter-community interactions. A small value of βext corresponds to a large phase lag and leads to little inter-community synchrony (as measured by phase synchrony, PhaseSync—indicated as green discs, see text for its computation) whereas larger values of βext correspond to smaller phase lags and lead to greater inter-community synchrony. See main text for details. LZc and ACE show similar dependence on βext whereas SCE peaks where the former two have a minimum.
Mentions: Secondly, we computed the three measures for simulated continuous data created with a Kuramoto model (see Methods, Section ‘Kuramoto model’), a model known to display rich dynamics [37, 49]. Fig 6 shows the results for the Kuramoto simulations, plotting LZc, ACE and SCE against the phase-lag parameter βext. In addition a measure of phase synchrony is plotted (PhaseSync), being the mean of over all observations t and channels i, as described in the definition of SCE. This plot illustrates (i) the similarity of LZc and ACE, which are both based on the diversity of the dynamics of amplitude fluctuations, and (ii) that SCE is a distinct measure of complexity to LZc and ACE, by virtue of being based on diversity in synchrony patterns. For all values of βext, fluctuations in the amplitude of each community propagate to different communities, and this leads to diversity in relative amplitude reflected in the high values of LZc and ACE. In contrast, SCE is (i) low for small values of βext (large phase lag) since there is little synchrony between communities, (ii) low for large values of βext (small phase lag) since there is almost total synchrony between communities, (iii) high for intermediate values of βext in which synchrony between communities is able to fluctuate. Also note that LZc and ACE have a minimum at βext = 0.15 whereas SCE has a maximum there.

Bottom Line: Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions).In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation.We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels.

View Article: PubMed Central - PubMed

Affiliation: Sackler Centre for Consciousness Science, Department of Informatics, University of Sussex, Brighton, United Kingdom.

ABSTRACT
Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct 'flavours' of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia.

No MeSH data available.


Related in: MedlinePlus