**5.1. Evaluating cortical connectivity**

in nonsurvivors [76]; therefore, rSO<sup>2</sup>

92 Current Topics in Intensive Care Medicine

as well [79].

regions of the brain.

ity is time-dependent [81].

it increases [84].

the case of resuscitated SCR patients, rSO<sup>2</sup>

**5. Cortical connectivity and coma**

links, such as synapses and neural fibers.

under 60% are associated with increased mortality. In

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

During coma states as during the anesthesia, there is a decrease in connectivity ("communication") between different cortical regions, or between cortical and subcortical regions, caused by a reduction of cerebral activity. The basis of cortical connectivity is made of structural

In clinical practice, the evaluation of connectivity is performed by analyzing the coherence/ correlation between biological signals (EEG, ECoG and local-field potentials) from different

*Functional connectivity* is based on biological signals analysis, which can be described as time series (such as the EEG) and can quantify cortical connectivity using statistical analysis (correlation) of the EEG signals from different cortical areas. The better the EEG signals are correlated (estimated by the correlation coefficient, XAppEn, mscohere), the more they are alike; therefore, there is a good connectivity between the cortical areas. Importantly, good statistical correlation of biological signals does not necessarily involve causality, and does not point out the direction the information moves [80]. Unlike structural connectivity, functional connectiv-

*Effective connectivity* may be regarded as a unit of structural and functional connectivity. It is the latest instrument trying to establish causal relations between neural network components [81]. Effective connectivity is calculated using complex mathematical algorithms (such as

The state of consciousness, according to Buzsaki (2007), is the consequence of the functional transformation of information contained by a neural network. Both posterior parietal and prefrontal association areas and frontoparietal network information integration were considered involved in the generation and maintenance of the state of consciousness [82, 83]. During sleep, which is a reversible modification of consciousness as well, there is a modification of cortical connectivity; therefore, during NREM sleep, it lowers and during REM sleep,

Cortical connectivity changes during anesthesia were first observed in lab animals, and then in humans. Thus, in 2005, the cortical connectivity changes, especially in the prefrontal cortex, during sevoflurane anesthesia of different concentrations, were described. Bouveroux et al. described the effects of propofol on cortical connectivity: during propofol anesthesia, corticocortical and thalamocortical connectivity decreases in frontal-parietal networks, while it is

Granger causality or transfer entropy), applied to time series.

in the first 24 hours was 68.2% for survivors and
