# What Do We Know about the Use of EEG Monitoring during Equine Anesthesia: A Review
## 4 Analysis of EEG and Its Usefulness in Equine General Anesthesia
More differences could be seen when comparing agents (such as isoflurane with halothane) to themselves and increasing levels of the inhalants. This also proved the fact that the analysis of raw EEG intraoperatively is not clinically useful in anesthesia depth assessment. Moreover, various intravenous agents and mixture of agents were  
Figure 1: Placing of electroencephalography (EEG) electrodes on the parietal part of the skull in a horse (**a**) during general anesthesia and (**b**) standing anesthesia. described (but in most cases with inhalant adjuvant, which means it was impossible to describe the effect of single intravenous agent at the time) [46; 47; 48; 49; 50; 53]. Another group of research focused on EEG measurement in different anesthesia schemes (based on the previous research describing EEG behavior in horses during anesthesia with use of specific agents) and during various surgical procedures characterized by different levels of amount of noxious stimuli [38; 43; 60]. During the research, three types of changes in the record were noticed:  
* A typical excitation pattern, characterized by increased frequency and reduced EEG amplitude, seen in horses and dogs [39; 45]
* Paradoxical excitation, in which the amplitude increased and the frequency of EEG decreased, seen in rats and sheep [61; 62]
* \"Burst suppression\" characterized by sudden flattening of the wave, depending on the dose of drugs and the species [63; 64]. As it was already known that the raw EEG cannot be evaluated intraoperatively, it was important to obtain the fast method of frequency and quality analysis, based on described changes during application of noxious stimuli. There are several frequency domains that are numerical parameters, deducted from the spectral analysis of EEG waves--total spectral power (measure of the overall signal variability), spectral power of four frequency bands (\(\alpha\), \(\beta\), \(\theta\), \(\delta\)), are given as a number of percentage of total power, which shows the contribution of each band to the variability of signal, spectral edge frequency (SEF), which can be counted as F95 (the frequency under which occurs 95% of total spectral power), F50 or mean frequency (under which occurs 50% of total spectral power), and other like F80 or F90 [28]. Until now, on the basis of the recent research, an increase in F50 and F80 has been observed during surgical stimuli in horses anesthetized with isoflurane [37; 61]. Similar results were obtained during total intravenous anesthesia with different combinations of drugs, provided that they had a documented analgesic effect [48; 53]. At the next stage of research development, a mathematical analysis of the recorder EEG waves was introduced, which compares records collected during the anesthesia to the experimental EEG that was saved for every depth level of anesthesia. This results in number reflecting the depth of anesthesia counted lively during surgery. However, when using those algorithms in animals the problem is the lack of species data collected from animals. Such library (collected measurements of EEG specific for different levels of anesthesia depth) was created only for people so far, and the adequacy of results obtained by algorithms to the clinical state of patient was proved. In the case of horses, research has been conducted on the bispectral index (BI) algorithm [40; 41], Narcotrend [42] and patient state index (PSI). Up to now, they were not confirmed to be accurate because of the differences in the activity of waves in humans and horses, and thus the lack of usefulness of human EEG records used for algorithms in horses only serves as study guidelines. The latest method for real-time EEG analysis introduced in humans a few decades ago [65] is the computer analysis of EEG signals in the form of power spectrum analysis (Figure 2). Nowadays it is a standard practice in human medicine, also in assessment of agent influence on brain [33].