**1. Introduction**

Coma is defined as a state of loss of consciousness and lack of response to external stimuli that occurs in pathological states and during anesthesia. The prognosis of coma patients is difficult to assess, as the mechanism through which coma occurs is not entirely understood. What we may do is evaluate cerebral function, through accurate and careful monitoring. Thus, the intensive care specialist requires one or several instruments to monitor the cerebral function of coma patients, as it is difficult to perform, even hourly, a clinical evaluation, taking into account the typical workload of the doctor.

In certain circumstances, a worsening neurological state does not manifest itself clinically an example being nonconvulsive status, which has negative prognostic value in the case of traumatic brain injury (TBI), and can only be diagnosed through continuous electroencephalographic monitoring (EEG).

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

functional connectivity of the claustrum with medial prefrontal cortex and mediodorsal thalamus decreased [2]. As for coma state, there are no definitive studies proving the role of the

Important Issues in Coma and Neuromonitoring http://dx.doi.org/10.5772/intechopen.79448 83

Regarding EEG activity, comas are different. The same coma state, defined by a lack of consciousness and of response to external pain stimuli may exhibit different EEG aspects. Thus, there are comas with prevalent alpha waves (alpha comas), beta waves (beta comas), theta waves (theta comas) or delta waves (delta comas). A common characteristic of these coma states is that if they are secondary to intoxication or metabolic encephalopathies, they have a positive prognosis, regardless of the EEG pattern, with response to external pain stimuli. If there are secondary to brain stem lesions or hypoxic ischemic encephalopathies and lacking

Comas secondary to TBI are caused by diffuse axonal injury (DAI) and by hemorrhages that compress the brain stem. Diffuse axonal injury occurs due to rapid (rotational) acceleration, which causes lacerations in the neuronal cytoskeleton and therefore block neuronal transport [4]. Hameroff and Penrose support the hypothesis that conscious processes are based in the microtubules of the neuronal cytoskeleton [5, 6]. Furthermore, it is known that volatile anesthetics interfere with the function of these microtubules. Nevertheless, if this theory proves true—that consciousness is based on and influenced by neuronal cytoskeleton microtubules—

Another etiology of coma is nonconvulsive status, defined as prolonged seizures there are not clinically manifested and associate altered mental status [7], secondary to TBI (8–16%), to stroke—HAS (3–31%) and craniotomy [8]. The mechanism of loss of consciousness during epilepsy is not entirely understood. Blumenfeld Hal et al. affirm that a common mechanism exists—a cortico-subcortical network dysfunction. Therefore, a decrease in cerebral blood flow (CBF) was noticed in frontoparietal association areas and the anterior and posterior interhemispheric regions with (CBF) increases in bilateral midline subcortical structures [9].

Besides, a loss of connectivity between medial and lateral frontoparietal association areas and upper brainstem/medial diencephalon was observed [10]. They state that these corticosubcortical connectivity malfunctions (occurring in generalized tonic-clonic seizures, complex partial seizures and temporal lobe seizures) are caused either by indirect inhibition or by

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

response to external pain stimuli, comas bring a negative prognosis [3].

that might explain loss of consciousness secondary to diffuse axon injury.

claustrum in its physiopathology.

convulsions initiated in these structures.

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

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

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 evaluate coma state—such as cortical connectivity and reactivity.
