**2.2. Burst suppression (BS) state**

Continuous EEG monitoring and cerebral oximetry monitoring—through the NIRS (nearinfrared spectroscopy) technique—are useful instruments that provide the doctor with real-time, vital information on the coma patient. These techniques have the advantage of noninvasivity, ease of use and they can provide the doctor with easily quantifiable scores. Perhaps most importantly, they can be made available continuously at the bedside (**Figure 1**). Unfortunately, there is not one single standard monitor at this moment to accurately estimate what occurs in the brain of a coma patient. Therefore, in this chapter, we shall start with a brief exposition on coma physiopathology, insisting on burst suppression (BS) state, and we shall continue with the characteristics of the main coma states we might encounter in the intensive care unit (ICU). We will continue with the devices used to monitor anesthesia depth, which are used to monitor coma depth as well. These devices are based on EEG signal analysis. The main drawback of EEG signal analysis is noise: how shall we define and remove noise on an EEG? A definitive answer is difficult to find, that is why "noise-resistant" mathematical algorithms have been developed. Thus, this chapter focuses on the mathematical algorithms used to interpret EEG signal, as it is important to know the basis of parameters and scores we receive from the devices we use. In the end, we describe new theories that might be standardized to

**Figure 1.** Continuous BIS (bispectral index) and NIRS (near-infrared spectroscopy) monitoring during anesthesia.

Coma is defined as a state of unconsciousness and lack of response to noxious stimuli. The physiopathology of consciousness and coma state is not entirely understood. It is not clear if a "coma center" exists or if the diverse pathological states that induce coma do so through different mechanisms. From this perspective, coma is similar to the anesthetic state, which is caused by several pharmacological agents, with different chemical structures. It is also unclear if a common center, on which all anesthetics act, exists. Based on histology and physiology, Sir Francis Crick postulated that the claustrum has a central role in maintaining consciousness (as it is connected with nearly all cerebral structures), like the conductor of an orchestra [1]. Recent studies have shown that during isoflurane anesthesia on the rat,

evaluate coma state—such as cortical connectivity and reactivity.

**2. Coma state**

**2.1. Coma—definition and theories**

82 Current Topics in Intensive Care Medicine

Burst suppression is a cortical electrical activity defined by the existence of high-amplitude and variable frequency waves discharge, followed by a period of electrical activity suppression. BS is an intermediate state between slow waves EEG pattern and an isoelectric line. This BS pattern is present in several conditions, such as Ohtahara syndrome, TBI, hypoglycemia, hypoxia, hypothermia and anesthesia [11]. As for anesthesia bursts, they have a wave morphology specific to each anesthetic compound, and a different duration as well. In addition, the length of the burst decreases as the anesthesia depth increases [12]. Not only is the burst length variable, but so is its structure, according to its length. Thus, we have noticed [13] that for isoflurane anesthesia in rat, 4-seconds bursts and 1-second bursts have different aspects

is based on the fact that BS states correlate with low metabolism states (with low metabolic rate), such as hypothermia, anesthesia and hypoglycemia. The link between the electrical and the metabolic activity is the KATP channels, so during the burst, ATP concentration decreased which induces an increase in the conductance of KATP and thus a neuronal membrane hyperpolarization occurs (flat-line EEG). The theory of Amzica [16] states that BS activity is modulated by extracellular calcium concentration variations, thus the depletion of the extracellular cortical calcium during the burst is responsible for the EEG silence (flat line) after that. The basis of this phenomenon is unclear as well. It is regarded that bursts are caused by internal input, modulated by neural networks. On the other hand, the cortex has been proven to

Important Issues in Coma and Neuromonitoring http://dx.doi.org/10.5772/intechopen.79448 85

In the clinical practice, finding BS patterns in coma patients presents a negative prognostic value, if the BS ratio (BSR = suppression time/epoch duration \* 100) is over 20–23% [18].

Continuous EEG monitoring is the most used and, perhaps, the most efficient method of evaluating coma patients in the ICU. The advantage is the electrode placing: it is noninvasive (or minimally invasive), can be easily applied on the scalp of the patient and requires a minimal qualification of the ICU staff. Most EEG recording devices include software for

The acquisition system 10–20, that is classically used, provides an overview of the main cortical areas. Placing the electrodes and fastening them with a specialized helmet may facilitate CT or MRI transportation, in order to obtain a complex imagistic and electroencephalographic representation. Standard EEG monitoring provides information on the onset of epileptic seizures, is useful in detecting nonconvulsive status and in detecting early and late ischemia, secondary to subarachnoid hemorrhage. Furthermore, it provides useful information (based

on prevailing EEG patterns and reactivity) for the prognostic of the coma patient [19].

The following chapter will describe the main mathematical algorithms that are used in analyzing EEG signal, as well as the devices used for monitoring coma and anesthesia depth.

Spectral analysis of EEG signal is based on the fast Fourier transformation (FFT), which decomposes the signal according to the mean amplitude of each frequency in the signal. By applying second-order FFT, the result is the spectral power graphic, which decomposes the

Median frequency (MEF) represents the value of frequency whose perpendicular meets Ox in

/Hz). Analyzing this graphic pro-

signal based on amplitude squared/frequency (microvolts<sup>2</sup>

vides very important parameters to estimate the depth of sedation/anesthesia.

the point that splits equally the area under the spectral power graphic.

exhibit BS activity, without the intervention of subcortical structures [17].

mathematically processing the signal, and generating scores or frequencies.

**3. EEG monitoring and interpretation**

**3.1. Continuous EEG monitoring**

**3.2. EEG signal analysis**

*3.2.1. Spectral analysis*

**Figure 2.** Burst aspects according to its length (local-field potential—LFP—recording). The first burst lasts almost 4 seconds and presents high-frequency waves at the beginning followed by slow waves. The second burst is short (almost 1 second) and presents slow waves.

(**Figure 2**). Long bursts start with high-frequency high-amplitude waves, followed by lowfrequency high-amplitude waves, while short bursts present low-frequency high-amplitude waves as it is seen on power spectral density graphics (**Figure 3**).

Even though a BS presenting coma state is considered deep, BS is deemed a state of hyperexcitability, as bursts can be evoked by subliminal stimuli [14] and BS electrical activity is correlated with cerebral blood flow changes as well [15].

The mechanism supporting this phenomenon remains incompletely explained. We have two theories attempting an explanation at the moment. The metabolic theory of Emery Brown [11]

**Figure 3.** Power spectral density during the long burst versus the short burst. Two peaks of frequencies can be observed in the long burst.

is based on the fact that BS states correlate with low metabolism states (with low metabolic rate), such as hypothermia, anesthesia and hypoglycemia. The link between the electrical and the metabolic activity is the KATP channels, so during the burst, ATP concentration decreased which induces an increase in the conductance of KATP and thus a neuronal membrane hyperpolarization occurs (flat-line EEG). The theory of Amzica [16] states that BS activity is modulated by extracellular calcium concentration variations, thus the depletion of the extracellular cortical calcium during the burst is responsible for the EEG silence (flat line) after that. The basis of this phenomenon is unclear as well. It is regarded that bursts are caused by internal input, modulated by neural networks. On the other hand, the cortex has been proven to exhibit BS activity, without the intervention of subcortical structures [17].

In the clinical practice, finding BS patterns in coma patients presents a negative prognostic value, if the BS ratio (BSR = suppression time/epoch duration \* 100) is over 20–23% [18].
