Figure 2.

Classification of PET-based diagnosis of consciousness based on heartbeat-evoked responses. A, Classification accuracy in sliding 200-ms-long time windows in a threefold cross-validation with HER amplitude and variance at each channel as features, using the consciousness diagnosis obtained from brain glucose metabolism measure with FDG-PET, in the training sample. Accuracy peaks in the 200–400 ms window. Accuracies have been normalized (posterior minimum-maximum normalization to unitary variance), one corresponding to the best accuracy across all time windows. B, ICA-EKG in MCS and UWS patients does not differ between 200 and 400 ms. C, HER topographies averaged between 200 and 400 ms, for MCS patients, UWS patients, and between-group difference in the training sample. The topographies markedly differ from the cardiac artifact (Fig. 1B) and indicate the neural origin of HERs. D, Topography of channel relevance in the training sample, based on both amplitude and variance of HERs, showing a larger contribution of left and right occipitotemporal electrodes as well as of right central and temporal electrodes. E, Group-averaged HERs in the training sample, averaged across right central channels, showing a sustained difference between 200 and 400 ms. F, HER-based consciousness scores in the independent validation sample, showing low HER-based consciousness scores, are more likely to correspond to nonbehavioral MCS than to behavioral MCS.