Investigation of the modulation between EEG alpha waves and slow/fast delta waves in children in different depths of Desflurane anesthesia

Abstract Objectives Investigation of the amplitude modulation of alpha-band EEG oscillations (i.e., grouping of alpha-band activities) by delta-band EEG activities in various depths of anesthesia (DOA). Methods This modulation, which is a sort of phase dependent amplitude modulation, is studied in 10 children in various depths of Desflurane anesthesia. Two parameters are defined to quantify the modulation: strength of modulation (SOM) and phase of modulation (POM). SOM indicates to what extent delta and alpha activities are related to each other, and POM is the delta phase in which the alpha amplitude is maximal. These parameters are analyzed in different DOA for various formations of delta sub-bands. Results The ability of POM and SOM were explored to characterize mechanisms contributing to delta activities and their correlation with the level of anesthesia. These parameters are influenced by DOA and frequency intervals of delta sub-bands. SOM takes higher values around certain frequency ranges of delta band. According to this, delta band comprises three main sub-bands in various unconsciousness levels. Although boundaries of these sub-bands change with DOA, they are almost in [0.1–0.5] Hz (very slow delta), [0.7–1.7] Hz (slow delta) and [2–4] Hz (fast delta) intervals. POMs relating to slow and fast delta bands increase with consciousness level. This is an indication that delta waves differently modulate alpha EEG activities (in terms of phase lag) in different DOA. In deep anesthesia, POM relating to fast delta correlates with DOA better than POM relating to slow delta does. In light anesthesia this correlation is inversed. Investigation regarding to different formations of delta sub-bands shows that POM relating to [1.8–4] Hz is a proper choice for distinguishing deep, moderate and light anesthesia. Conclusion SOM allows separating mechanisms underlying delta band activities, and POM can be seen as a complementary neurophysiologic-based parameter for quantifying DOA.

[1]  M. Steriade,et al.  Network modulation of a slow intrinsic oscillation of cat thalamocortical neurons implicated in sleep delta waves: cortically induced synchronization and brainstem cholinergic suppression , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[2]  P. Achermann,et al.  Low-frequency (<1Hz) oscillations in the human sleep electroencephalogram , 1997, Neuroscience.

[3]  B. Antkowiak,et al.  Neocortex is the major target of sedative concentrations of volatile anaesthetics: strong depression of firing rates and increase of GABAA receptor‐mediated inhibition , 2005, The European journal of neuroscience.

[4]  Nassib G. Chamoun,et al.  An introduction to bispectral analysis for the electroencephalogram , 1994, Journal of Clinical Monitoring.

[5]  Odile Benoit,et al.  Slow (0.7–2 Hz) and fast (2–4 Hz) delta components are differently correlated to theta, alpha and beta frequency bands during NREM sleep , 2000, Clinical Neurophysiology.

[6]  M Steriade,et al.  Intracellular analysis of relations between the slow (< 1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[7]  M Steriade,et al.  Low-frequency rhythms in the thalamus of intact-cortex and decorticated cats. , 1996, Journal of neurophysiology.

[8]  D. Contreras,et al.  Synchronization of fast (30-40 Hz) spontaneous cortical rhythms during brain activation , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[9]  A. W. M. van den Enden,et al.  Discrete Time Signal Processing , 1989 .

[10]  M. Steriade,et al.  A novel slow (< 1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[11]  J. Palva,et al.  Infraslow oscillations modulate excitability and interictal epileptic activity in the human cortex during sleep. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[12]  L. Senhadji,et al.  An Investigation on Different EEG Patterns From Awake to Deep Anesthesia: Application to improve methods of determining depth of anesthesia , 2007 .

[13]  J. Reynolds,et al.  Characteristics of temporal fluctuations in the hyperpolarized state of the cortical slow oscillation. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  J. Born,et al.  Grouping of Spindle Activity during Slow Oscillations in Human Non-Rapid Eye Movement Sleep , 2002, The Journal of Neuroscience.

[15]  I. Rampil.  A Primer for EEG Signal Processing in Anesthesia , 1998, Anesthesiology.

[16]  Satoshi Hagihira,et al.  The Relationship Between Bispectral Index and Electroencephalographic Parameters During Isoflurane Anesthesia , 2004, Anesthesia and analgesia.

[17]  C. Elger,et al.  Brief Communication HUMAN SCALP RECORDED SIGMA ACTIVITY IS MODULATED BY SLOW EEG OSCILLATIONS DURING DEEP SLEEP , 2002, The International journal of neuroscience.

[18]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[19]  A. Hutt,et al.  Effects of the anesthetic agent propofol on neural populations , 2010, Cognitive Neurodynamics.

[20]  L Senhadji,et al.  The impact of age on bispectral index values and EEG bispectrum during anaesthesia with desflurane and halothane in children. , 2006, British journal of anaesthesia.

[21]  Thomas W. Bouillon,et al.  Bispectral Index (BIS) and Burst Suppression: Revealing a Part of the BIS Algorithm , 2004, Journal of Clinical Monitoring and Computing.

[22]  Ingo Bojak,et al.  Population based models of cortical drug response: insights from anaesthesia , 2008, Cognitive Neurodynamics.

[23]  W W Mapleson,et al.  Effect of age on MAC in humans: a meta-analysis. , 1996, British journal of anaesthesia.

[24]  R. Tibshirani,et al.  An introduction to the bootstrap , 1993 .

[25]  L. Senhadji,et al.  Brain activity modeling in general anesthesia: enhancing local mean-field models using a slow adaptive firing rate. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  J. Sleigh,et al.  Modelling general anaesthesia as a first-order phase transition in the cortex. , 2004, Progress in biophysics and molecular biology.

[27]  D. Liley,et al.  Modeling the effects of anesthesia on the electroencephalogram. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  I. Constant,et al.  Sevoflurane and epileptiform EEG changes , 2005, Paediatric anaesthesia.

[29]  M. Steriade.  Grouping of brain rhythms in corticothalamic systems , 2006, Neuroscience.

[30]  D. Contreras,et al.  The slow (< 1 Hz) oscillation in reticular thalamic and thalamocortical neurons: scenario of sleep rhythm generation in interacting thalamic and neocortical networks , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[31]  Ratko Magjarević,et al.  World Congress on Medical Physics and Biomedical Engineering 2006 , 2007 .

[32]  L. Senhadji,et al.  Monitoring approaches in general anesthesia: a survey. , 2002, Critical reviews in biomedical engineering.