35Monitoring the hypnotic component of anesthesia during surgeries is critical to prevent 36 intraoperative awareness and reduce adverse side effects. For this purpose, 37 electroencephalographic methods complementing measures of autonomic functions and 38 behavioral responses are in use in clinical practice. However, in human neonates and 39 infants existing methods may be unreliable and the correlation between brain activity 40 and anesthetic depth is still poorly understood. Here, we characterize the effects of 41 different anesthetics on activity of several brain areas in neonatal mice and develop 42 machine learning approaches to identify electrophysiological features predicting inspired 43 or end-tidal anesthetic concentration as a proxy for anesthetic depth. We show that 44 similar features from electroencephalographic recordings can be applied to predict 45 anesthetic concentration in neonatal mice, and human neonates and infants. These 46 results might support a novel strategy to monitor anesthetic depth in human newborns. 47 49 Reliable monitoring of anesthesia depth is critical during surgery. It allows for loss 50 of consciousness, analgesia and immobility without incurring the risk of side effects and 51 complications due to anesthetic misdosing. Typically used measures to monitor 52 anesthesia depth are inspired and end-tidal anesthetic concentrations as well as 53 physiologic parameters, including respiratory rate and depth (in the absence of 54 neuromuscular blockade or controlled ventilation), heart rate, blood pressure, and 55 responses to noxious stimuli (1). These measures all respond to spinal and brainstem 56 reflexes and are not specific for arousal or cortical responses to noxious events. 57 Anesthesia-induced changes in brain activity can be measured with 58 electroencephalographic (EEG) recordings. Specific algorithms have been developed to 59 predict anesthesia depth in adults (2-4). The most commonly used of such methods, the 60 Bispectral Index, has been shown to significantly reduce intraoperative awareness, 61 amount of anesthetic used, recovery time and post-anesthesia care unit stay in a recent 62Cochrane meta-analysis (5), but see (6, 7). However, evidence of similar benefits in 63 infants and younger children is sparse, as recently shown (8-10). EEG in anesthetized 64 infants changes dramatically depending on postnatal age (8,(11)(12)(13)(14). 65 EEG recordings mainly monitor neocortical activity. Converging evidence from 66 animal and human studies has shown that most anesthetics slow 67 electroencephalographic oscillations (15)(16)(17). While power at high frequency oscillations 68 is reduced (>40 Hz), power at slower frequencies (<15 Hz) is enhanced (15). The 69 computations underling proprietary indexes such as the Bispectral index or Narcotrend 70 are thought to take advantage of these phenomena (18). However, in preterm and term 71 neonates for the first weeks of life, EEG during sleep-wake cycles is weakly correlated 72 Anesthesia and network dynamics during deve...