Fig. 2

Examples of the Predictive (A) and Native (B) curves. The horizontal axis is a time scale (s), and the vertical axis is a Probability Value scale (from 0 to 1). (A) The Predictive curve graph was played back using data from the seventh session of Patient A. In this example, the classification model was trained using the 1.5–14 Hz range. The curve was smoothed by the Moving epoch average (Immediate) function. The number of 4-s epochs with an overlap of 0.5 s used for averaging was 50. This curve was obtained by feeding the real-time patient’s EEG during the seventh session to the model trained on data from the first session and represents the changing probability of a deep hypnotic state over the session. “Supplements C” contain a detailed case-related analysis of how it could potentially describe session dynamics. (B) The Native curve of the seventh session with Patient A. The band and the smoothing features are the same as in the Predictive curve. This curve was obtained after this (seventh) session by training a model (auxiliary) on data from the same session and then feeding this EEG recording to this model. Thus, this curve, which could only be constructed after the session was over, reflects the changes in the probability of deep hypnosis with very high accuracy