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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.


LZc, SCE and ACE computed as averages over multiple 10sec segments of EEG of the 7 subjects before and during anaesthesia.States shown are wakeful rest (WR) before propofol, mild sedation (MS), LOC and wakeful rest emerging from propofol sedation (WRa, not shown for single subject results). Measures are computed across 25 channels spread evenly across the whole cortex. The measures score highest for shuffled WR data, and consistently across subjects higher for WR as opposed to LOC. Error bars indicate standard error across segments, cyan horizontal lines are example thresholds for each of the measures, separating WR from LOC for all 7 subjects. For each single subject plot, the mean and standard error across its 7 values per state is displayed in the narrow plot to its right, with the title ‘mean’. For these mean values across subjects, significant differences between state pairs are shown by a double asterisk if p < 0.01 and a single asterisk if p < 0.05 (Wilcoxon rank sum test, FDR corrected for multiple comparison). See Table 1 for effect size comparison.
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pone.0133532.g007: LZc, SCE and ACE computed as averages over multiple 10sec segments of EEG of the 7 subjects before and during anaesthesia.States shown are wakeful rest (WR) before propofol, mild sedation (MS), LOC and wakeful rest emerging from propofol sedation (WRa, not shown for single subject results). Measures are computed across 25 channels spread evenly across the whole cortex. The measures score highest for shuffled WR data, and consistently across subjects higher for WR as opposed to LOC. Error bars indicate standard error across segments, cyan horizontal lines are example thresholds for each of the measures, separating WR from LOC for all 7 subjects. For each single subject plot, the mean and standard error across its 7 values per state is displayed in the narrow plot to its right, with the title ‘mean’. For these mean values across subjects, significant differences between state pairs are shown by a double asterisk if p < 0.01 and a single asterisk if p < 0.05 (Wilcoxon rank sum test, FDR corrected for multiple comparison). See Table 1 for effect size comparison.

Mentions: Fig 7 shows the mean values across 10sec segments of LZc, SCE and ACE during wakeful rest before sedation (WR), mild sedation (MS), LOC and shuffled data (in time domain shuffled WR) for each subject, computed for 25 EEG channels automatically selected to be spread evenly via k-medoids clustering across the whole cortex. For all subjects, the three measures LZc, SCE and ACE score higher for WR than for LOC, nearly all with high effect size (Cohen’s d > 0.8 for all measures and subjects except subject 1 for all measures and subject 3 for measure SCE, compare with Table 1.) Values for MS typically lie between those for WR or LOC, but the differences between MS vs. WR or LOC are less consistent than those between WR vs. LOC. For all three measures a single threshold can be drawn that separates WR from LOC across all subjects, as indicated by the cyan lines.


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, SCE and ACE computed as averages over multiple 10sec segments of EEG of the 7 subjects before and during anaesthesia.States shown are wakeful rest (WR) before propofol, mild sedation (MS), LOC and wakeful rest emerging from propofol sedation (WRa, not shown for single subject results). Measures are computed across 25 channels spread evenly across the whole cortex. The measures score highest for shuffled WR data, and consistently across subjects higher for WR as opposed to LOC. Error bars indicate standard error across segments, cyan horizontal lines are example thresholds for each of the measures, separating WR from LOC for all 7 subjects. For each single subject plot, the mean and standard error across its 7 values per state is displayed in the narrow plot to its right, with the title ‘mean’. For these mean values across subjects, significant differences between state pairs are shown by a double asterisk if p < 0.01 and a single asterisk if p < 0.05 (Wilcoxon rank sum test, FDR corrected for multiple comparison). See Table 1 for effect size comparison.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0133532.g007: LZc, SCE and ACE computed as averages over multiple 10sec segments of EEG of the 7 subjects before and during anaesthesia.States shown are wakeful rest (WR) before propofol, mild sedation (MS), LOC and wakeful rest emerging from propofol sedation (WRa, not shown for single subject results). Measures are computed across 25 channels spread evenly across the whole cortex. The measures score highest for shuffled WR data, and consistently across subjects higher for WR as opposed to LOC. Error bars indicate standard error across segments, cyan horizontal lines are example thresholds for each of the measures, separating WR from LOC for all 7 subjects. For each single subject plot, the mean and standard error across its 7 values per state is displayed in the narrow plot to its right, with the title ‘mean’. For these mean values across subjects, significant differences between state pairs are shown by a double asterisk if p < 0.01 and a single asterisk if p < 0.05 (Wilcoxon rank sum test, FDR corrected for multiple comparison). See Table 1 for effect size comparison.
Mentions: Fig 7 shows the mean values across 10sec segments of LZc, SCE and ACE during wakeful rest before sedation (WR), mild sedation (MS), LOC and shuffled data (in time domain shuffled WR) for each subject, computed for 25 EEG channels automatically selected to be spread evenly via k-medoids clustering across the whole cortex. For all subjects, the three measures LZc, SCE and ACE score higher for WR than for LOC, nearly all with high effect size (Cohen’s d > 0.8 for all measures and subjects except subject 1 for all measures and subject 3 for measure SCE, compare with Table 1.) Values for MS typically lie between those for WR or LOC, but the differences between MS vs. WR or LOC are less consistent than those between WR vs. LOC. For all three measures a single threshold can be drawn that separates WR from LOC across all subjects, as indicated by the cyan lines.

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.