Editing Computational neuroscience (section)

=== Predictive computational neuroscience ===
Predictive computational neuroscience is a recent field that combines signal processing, neuroscience, clinical data and machine learning to predict the brain during coma <ref>{{Cite journal |last1=Floyrac |first1=Aymeric |last2=Doumergue |first2=Adrien |last3=Legriel |first3=Stéphane |last4=Deye |first4=Nicolas |last5=Megarbane |first5=Bruno |last6=Richard |first6=Alexandra |last7=Meppiel |first7=Elodie |last8=Masmoudi |first8=Sana |last9=Lozeron |first9=Pierre |last10=Vicaut |first10=Eric |last11=Kubis |first11=Nathalie |last12=Holcman |first12=David |date=2023 |title=Predicting neurological outcome after cardiac arrest by combining computational parameters extracted from standard and deviant responses from auditory evoked potentials |journal=Frontiers in Neuroscience |volume=17 |page=988394 |doi=10.3389/fnins.2023.988394 |pmid=36875664 |pmc=9975713 |issn=1662-453X|doi-access=free }}</ref> or anesthesia.<ref>{{Cite journal |last1=Sun |first1=Christophe |last2=Holcman |first2=David |date=2022-08-01 |title=Combining transient statistical markers from the EEG signal to predict brain sensitivity to general anesthesia |url=https://www.sciencedirect.com/science/article/pii/S174680942200235X |journal=Biomedical Signal Processing and Control |language=en |volume=77 |pages=103713 |doi=10.1016/j.bspc.2022.103713 |s2cid=248488365 |issn=1746-8094}}</ref> For example, it is possible to anticipate deep brain states using the EEG signal. These states can be used to anticipate hypnotic concentration to administrate to the patient.