**4. Near-infrared spectroscopy (NIRS)**

Jobsis first noticed in 1977 [72] that tissues are transparent for a wavelength of light of 700–950 nm. Based on this, the concentration of oxyhemoglobin, deoxyhemoglobin and cytochrome C oxidase can be measured (only the first two are used in clinical practice).

Starting from the oxyHb and deoxyHb concentrations, one can estimate regional saturation of oxygen (rSO<sup>2</sup> ) in a tissue. Furthermore, the regional changes of blood flow can be assessed, by evaluating the changes of total hemoglobin (HbT). Monitors for cerebral oxygenation, that are based on the NIRS technology, use a sensor placed above the tissue, whose oxygenation is to be measured. The sensor is made of emitting and detecting diodes, placed within 4–8 cm of each other. Detecting diodes will detect the infrared light reflected by the tissue. In the case of cerebral tissue, the infrared light can penetrate up to a depth of 0.6–1 centimeters [73]. Thus, cerebral oxygenation through this method is underestimated, compared with jugular vein saturation (SjVO<sup>2</sup> ) [74]. Among the benefits of this method are the noninvasive character and the ease of use at the bedside.

In the case of the brain, rSO<sup>2</sup> values are closer to the venous saturation than to arterial saturation because 70% of cerebral blood is in the veins and capillaries, and thus, normal cerebral rSO<sup>2</sup> values are between 60 and 80%. Using NIRS in the current clinical practice began in the 1980s, with the first studies on monitoring cerebral function in the adult and neonate. More recent studies are focused upon evaluating prehospital coma gravity. For example, Peters et al. [75] observed in a study including 25 patients that NIRS has a sensitivity of 93.3% and a specificity of 78.6% over CT scans in detecting intracranial hematoma.

Additionally, NIRS values have prognostic value in TBI patients. The values of rSO<sup>2</sup> at hospital admission were 74.7 ± 1.5% in the case of surviving patients and 61.9 ± 19.4% in nonsurvivors [76]; therefore, rSO<sup>2</sup> under 60% are associated with increased mortality. In the case of resuscitated SCR patients, rSO<sup>2</sup> in the first 24 hours was 68.2% for survivors and 62.9% for nonsurvivors [77]. As for blood flow variation monitoring, it was noticed that the cerebral oximetry index (Cox), determined through NIRS, is a good substitute of the mean velocity index (Mx)—determined through transcranial Doppler echography (TCD) [78]. NIRS is also useful in detecting vasospasm in subarachnoid hemorrhage (SAH) patients as well [79].

maintained in the visual and auditory cortex [85]. Mhuircheartaigh et al. regard the lack of response to auditory and pain stimuli during propofol anesthesia as a consequence of putamencortex connectivity decreases, while thalamocortical connectivity remains unchanged [86]. Ferrarelli et al. notice as well the frontal intracortical connectivity decreases, during transcranial magnetic stimulation, under midazolam sedation [87]. Cortical connectivity is disrupted in several pathological states, such as brain trauma, vegetative state and memory or attention loss. During mild brain trauma, there have been described frontal and occipital cortical connectivity changes, a decrease of intercortical connectivity over longer distances and an increase of cortical connectivity over shorter distances [88]. The vegetative state is defined as the abolishing of consciousness, while excitatory external factors are present. While in vegetative state, there is a decrease of cortical connectivity in several areas: prefrontal and premotor cortex, temporal-parietal association areas and posterior cingulate cortex. Furthermore, there is an altered connectivity between prefrontal and premotor cortical areas and posterior cingulate cortex [89]. Subcortical cerebrovascular accidents alter cortical connectivity between the two hemispheres: between supplementary motor areas and between ipsilateral supplementary motor area and lateral premotor area. These neural connectivity modifications, both under physiological and under pathological conditions, make cortical connectivity, if not the most

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*Functional cortical connectivity* may be estimated by calculating the correlation coefficient between signals of different regions, the covariance or the coherence of two or several signals. The disadvantage of these algorithms is the inability to determine the direction of data

*Effective cortical connectivity* is estimated with the direct transfer function (DTF), based on Granger causality. Named after Clive Granger, econometrician awarded the Nobel Memorial Prize in Economic Sciences in 2003, the Granger linear systems causality states that for two time series (such as two EEG channels) with a unidirectional data exchange from the Y series to the X series, the modifications from the Y series will be found after a certain amount of time in the X series, or that analyzing Y series data can better predict X series modifications. By evaluating effective connectivity through DTF, we may analyze several time series/ EEG channels. This algorithm

BSMART is a cortical connectivity analysis software package that can run on the MATLAB

Cortical connectivity can also be evaluated through imagistic methods (such as MRI) or elec-

High-density electroencephalography (64–256 electrodes) can provide information on intercortical connectivity, and is based on EEG signal analysis of different cortical regions. It has the advantage of being usable bedside, and data analysis can be performed more quickly than

was developed by Polish mathematicians Kaminski and Blinowska in 1991 [90].

sensitive, among the most sensitive parameters of nervous function.

*5.1.1. Mathematical algorithms to estimate cortical connectivity*

exchange between cortical and subcortical areas.

**5.1. Evaluating cortical connectivity**

program.

trophysiological methods (EEG).

in the case of imagistic methods [91, 92].
