Miika Koskinen

Aberrant temporal and spatial brain activity during rest in patients with chronic pain

In the absence of external stimuli, human hemodynamic brain activity displays slow intrinsic variations. To find out whether such fluctuations would be altered by persistent pain, we asked 10 patients with unrelenting chronic pain of different etiologies and 10 sex- and age-matched control subjects to rest with eyes open during 3-T functional MRI. Independent component analysis was used to identify functionally coupled brain networks. Time courses of an independent component comprising the insular cortices of both hemispheres showed stronger spectral power at 0.12 to 0.25 Hz in patients than in control subjects, with the largest difference at 0.16 Hz. A similar but weaker effect was seen in the anterior cingulate cortex, whereas activity of the precuneus and early visual cortex, used as a control site, did not differ between the groups. In the patient group, seed point-based correlation analysis revealed altered spatial connectivity between insulae and anterior cingulate cortex. The results imply both temporally and spatially aberrant activity of the affective pain-processing areas in patients suffering from chronic pain. The accentuated 0.12- to 0.25-Hz fluctuations in the patient group might be related to altered activity of the autonomic nervous system.

Automatic analysis and monitoring of burst suppression in anesthesia

Objective.We studied the spectral characteristics of the EEGburst suppression patterns (BSP) of two intravenous anesthetics,propofol and thiopental. Based on the obtained results, we developed amethod for automatic segmentation, classification and compactpresentation of burst suppression patterns. Methods.The spectralanalysis was performed with the short time Fourier transform and withautoregressive modeling to provide information of frequency contents ofbursts. This information was used when designing appropriate filters forsegmentation algorithms. The adaptive segmentation was carried out usingtwo different nonparametric methods. The first one was based on theabsolute values of amplitudes and is referred to as the ADIF method. Thesecond method used the absolute values of the Nonlinear Energy Operator(NLEO) and is referred to as the NLEO method. Both methods have beendescribed earlier but they were modified for the purposes of BSPdetection. The signal was classified to bursts, suppressions andartifacts. Automatic classification was compared with manualclassification. Results.The NLEO method was more accurate,especially in the detection of artifacts. NLEO method classifiedcorrectly 94.0% of the propofol data and 92.8% of thethiopental data. With the ADIF method, the results were 90.5% and88.1% respectively. Conclusions.Our results show thatburst suppression caused by the different anesthetics can be reliablydetected with our segmentation and classification methods. The analysisof normal and pathological EEG, however, should include information ofthe anesthetic used. Knowledge of the normal variation of the EEG isnecessary in order to detect the abnormal BSP of, for instance, seizurepatients.

Monotonicity of approximate entropy during transition from awareness to unresponsiveness due to propofol anesthetic induction

The ability to monitor the physiological effects of sedative medication accurately is of interest in clinical practice. During the anesthetic agent driven transition to unresponsiveness, nonstationary changes such as signal amplitude variations appear in electroencephalography. In this paper, it is studied whether the application of the approximate entropy (ApEn) method to electroencephalographic (EEG) signal produces a monotonic response curve during the transition from awareness to unresponsiveness. Data from fourteen patients, undergoing propofol anesthetic induction were studied. To optimize the ApEn performance, different parameter choices were carefully evaluated. It was assumed with our protocol, that the level of anesthesia changes monotonically with the elapsed induction time. The monotonicity of the ApEn change was assessed with the prediction probability statistic (P/sub K/). The monotonicity of the ApEn time-series depends on the parameters employed in the algorithm and the varying signal amplitude. Depending on the parameter values, the median P/sub K/ value ranged from 0.886 to 0.527. Thus, a good directionality and concordance was observed, but the nonstationarity of the signal affected the results. In conclusion, EEG-based ApEn measure shows a nonlinear response during propofol induction. With a judicious choice of parameters, a monotonic response is confirmed using P/sub K/ statistic.

Effects of Remifentanil on the Spectrum and Quantitative Parameters of Electroencephalogram in Propofol Anesthesia

Background:A high dose of opioids associated with a low dose of propofol has become a popular anesthetic technique. However, the influence of opioids on the electroencephalographic phenomenon related to induction of anesthesia and, thereby, on the quantitative parameters used in the depth-of-anesthesia estimation is not well known. Methods:Twenty-seven patients were divided into three groups to receive saline, low-dose remifentanil (7.5 μg · kg−1 · h−1) or high-dose remifentanil (30 μg · kg−1 · h−1) during induction of anesthesia with propofol (30 mg · kg−1 · h−1). Electroencephalogram was recorded from Fz electrode, and its time-frequency properties in the patient groups were analyzed from the induction of anesthesia to the occurrence of burst suppression pattern. The group differences in 14 quantitative spectral parameters used in the depth-of-anesthesia estimation were examined as well. Results:The time-frequency properties of electroencephalogram were different between groups. The high-frequency (greater than 14 Hz) activity during light anesthesia was decreased in remifentanil groups; whereas, increased activity in extended alpha band (7–14 Hz) and decreased activity in delta band (0.5–4 Hz) was observed during deep anesthesia. This resulted in statistically significant changes in all 14 quantitative parameters. Conclusions:The effect of remifentanil on the spectrum and quantitative parameters of electroencephalogram is significant and strongly dependent on the level of anesthesia. Coadministration of opioids therefore challenges the reliability of the spectral properties of electroencephalogram in the depth-of-anesthesia estimation by using a frontal montage. Furthermore, the finding has implications for design of opioid coadministration studies.

Propofol anesthesia induces phase synchronization changes in EEG

OBJECTIVE Phase coupling between EEG channel pairs in various frequency bands was evaluated during propofol anesthetic induction and recovery periods. METHODS Twenty-three patients participated in the study. Phase synchronization indices based on the Hilbert transform were investigated on frequency bands 0.05-1 Hz, 1-4 Hz, 4-8 Hz, 8-12 Hz and 12-16 Hz for all pairs of the 9 EEG channels covering midline and frontal areas. A straight line was used to approximate the index values as a function of time and the Sign Test statistics were applied to the slope parameters. RESULTS Systematic phase synchronization changes were detected. Generally, phase synchronization in the sub-delta band decreased during the induction and increased during the recovery, while the directions were reversed in the alpha band. The changes were dependent on the channel pair. In the delta, theta and beta bands, the changes were aligned more irregularly than in the sub-delta or in the alpha bands. Highly asymmetric behavior between the induction and the recovery periods was also observed in these bands. CONCLUSIONS Induction and recovery from propofol anesthesia changes the phase synchronization between the EEG channels. The passband and location-specific behavior of these changes reveals the effects of the anesthetic to the different neural mechanisms.

Relation of EEG spectrum progression to loss of responsiveness during induction of anesthesia with propofol.

OBJECTIVE Our purpose is to find out whether the Loss of obeying a Verbal Command (LVC) and the preceding progression of the EEG frequency patterns are mutually related during an anesthetic induction. METHODS EEG was analyzed from sixteen patients, anesthetized with a fixed rate infusion of propofol (30 mg/kg/h). An artifact-purified EEG from electrode Fz referenced to the average of mastoid signals was filtered to consecutive 4 Hz frequency passbands with a filter bank. Signal envelope time-series were computed for all the passbands and studied as a function of the elapsed induction time t and as a function of the relative time r, which is t divided by the time of the LVC. RESULTS A frequency band specific biphasic activity pattern progressed from high towards low frequencies systematically and uniformly in the population studied when presented on the relative time scale r, irrespective of individual responses to the dosage. CONCLUSIONS The grouping of the individual progression patterns on the r scale indicates a strong relation between the EEG spectral behavior and the LVC. SIGNIFICANCE EEG may provide phenomenological grounds for a continuous control variable of a sedative drug effect, even in between the discrete clinical end-points.

EEG Frequency Progression during Induction of Anesthesia: from Start of Infusion to Onset of Burst Suppression Pattern

The anesthetic infusion with propofol influences EEG activity rather smoothly by changing the amplitude activity in different frequency bands. This results in a frequency progression pattern (FPP) which can be related to the depth of anesthesia. An iterative algorithm is proposed for the estimation of the shape of this pattern. The presented method is applied to the data recorded from the start of the propofol anesthetic infusion to the onset of the burst suppression pattern (BSP) with nine patients. The results reveal the underlying FPP and how the onset of the BSP is related to it. The proposed method offers potential for the development of automatic assessment systems for the depth of anesthesia.

Removal of imaging artifacts in EEG during simultaneous EEG/fMRI recording: Reconstruction of a high-precision artifact template

Functional magnetic resonance imaging (fMRI) induces coarse electromagnetic artifacts into the simultaneously recorded electroencephalogram (EEG). The problem in the signal processing framework is to model the underlying artifact, which is time-continuous, as a discretely sampled waveform. To build up an artifact template, the EEG sampling in relation to the phase of the imaging artifacts should be known. If the MR scanner and EEG sampling are not synchronized, this relation is not constant and a time adjustment of the template with the individual slice artifacts becomes essential. However, lack of synchrony opens up the possibility for approximating a high-precision and continuous artifact template by using the samples acquired from slightly different phases of the induced artifact. In this work, methodology for reconstructing such a template was developed using EEG data recorded simultaneously with fMRI at 3 T. A time-continuous cubic spline approximation was used as the slice artifact model. To overcome the problem of non-synchronized clocks, two methods were proposed to find the starting times of the slice artifacts at sub-sample precision. This approach yielded efficient imaging artifact reduction: the amplitude at the dominant frequency was attenuated by 55-70 dB (the median values over EEG channels) and the residual signal, at its best, was practically free from sharp transients even with 5000 Hz sampling frequency and without further residual artifact reduction algorithms. The presented methods may reduce the need for post-processing of the residual signal after the template subtraction and may help to preserve the EEG bandwidth.

Time-frequency properties of electroencephalogram during induction of anesthesia.

A method for detailed description of the time-frequency characteristics of electroencephalogram during induction of anesthesia is proposed. The method, based on averaging of time-normalized smoothed pseudo-Wigner-Ville distributions, is applied to data recorded from nine patients undergoing propofol anesthesia. An extensive representation of the frequency progression pattern related to the induction of anesthesia is given and the time-frequency characteristics that are consistent/not consistent between patients are determined. It is also illustrated how four different clinical end-points, generally used in the assessment of the depth of anesthesia, can be related to different phases of the frequency progression pattern. The method presented has importance in providing information about the neurophysiological phenomenon during induction of anesthesia and can therefore be used in the development of new monitoring algorithms.

Remifentanil Modifies the Relation of Electroencephalographic Spectral Changes and Clinical Endpoints in Propofol Anesthesia

Background:Depth-of-anesthesia monitoring with the electroencephalogram has become widely used in anesthesia practice. Generally, the methods presented are based on the spectral changes of the electroencephalogram. In this study, the authors evaluate the influence of remifentanil on the relation of timely occurrence of clinical endpoints and the spectral behavior of the electroencephalogram. Methods:Twenty-seven patients scheduled to undergo a surgical procedure were randomly assigned to three groups. Patients blindly received equal volumes of saline or remifentanil (7.5 or 30 &mgr;g · kg−1 · h−1) 1 min before induction of anesthesia with infusion of propofol (30 mg · kg−1 · h−1). The occurrence of loss of counting, loss of obeying verbal command, and loss of reaction to tetanic stimulation was assessed. The electroencephalogram was recorded from electrode Fz referenced to the common average, and an iterative algorithm was applied to solve the underlying frequency progression pattern. The positions of the clinical endpoints on the pattern were analyzed. Results:The administration of remifentanil during induction of anesthesia with propofol led to an earlier occurrence of the clinical endpoints on the frequency progression pattern. A significant difference (P < 0.05) was observed between the saline and high-dose patient groups in all three endpoints. The effect of remifentanil was proportional to the infusion rate. Conclusions:The infusion of remifentanil during propofol anesthesia significantly modifies the mutual relations of the electroencephalographic spectral characteristics and the endpoints in a predictable and quantifiable manner. This finding suggests that the electroencephalographic phenomena and the endpoints may not be identical but rather to some extent separate manifestations of hypnotic drug effect.