Background: Burst suppression occurs in the EEG during coma and under general anaesthesia. It has been assumed that burst suppression represents a deeper state of anaesthesia from which it is more difficult to recover. This has not been directly demonstrated, however. Here, we test this hypothesis directly by assessing relationships between EEG suppression in human volunteers and recovery of consciousness. Methods: We recorded the EEG of 27 healthy humans (nine women/18 men) anaesthetised with isoflurane 1.3 minimum alveolar concentration (MAC) for 3 h. Periods of EEG suppression and non-suppression were separated using principal component analysis of the spectrogram. After emergence, participants completed the digit symbol substitution test and the psychomotor vigilance test. Results: Volunteers demonstrated marked variability in multiple features of the suppressed EEG. In order to test the hypothesis that, for an individual subject, inclusion of features of suppression would improve accuracy of a model built to predict time of emergence, two types of models were constructed: one with a suppression-related feature included and one without. Contrary to our hypothesis, Akaike information criterion demonstrated that the addition of a suppression-related feature did not improve the ability of the model to predict time to emergence. Furthermore, the amounts of EEG suppression and decrements in cognitive task performance relative to pre-anaesthesia baseline were not significantly correlated. Conclusions: These findings suggest that, in contrast to current assumptions, EEG suppression in and of itself is not an important determinant of recovery time or the degree of cognitive impairment upon emergence from anaesthesia in healthy adults.

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Raters differed in competency ratings. Implications for potential use and adaptation of CBT competency measurement methods to enhance training and implementation are discussed.

IntroductionDelirium is a potentially preventable disorder characterised by acute disturbances in attention and cognition with fluctuating severity. Postoperative delirium is associated with prolonged intensive care unit and hospital stay, cognitive decline and mortality. The development of biomarkers for tracking delirium could potentially aid in the early detection, mitigation and assessment of response to interventions. Because sleep disruption has been posited as a contributor to the development of this syndrome, expression of abnormal electroencephalography (EEG) patterns during sleep and wakefulness may be informative. Here we hypothesise that abnormal EEG patterns of sleep and wakefulness may serve as predictive and diagnostic markers for postoperative delirium. Such abnormal EEG patterns would mechanistically link disrupted thalamocortical connectivity to this important clinical syndrome.Methods and analysisP-DROWS-E (Prognosticating Delirium Recovery Outcomes Using Wakefulness and Sleep Electroencephalography) is a 220-patient prospective observational study. Patient eligibility criteria include those who are English-speaking, age 60 years or older and undergoing elective cardiac surgery requiring cardiopulmonary bypass. EEG acquisition will occur 1–2 nights preoperatively, intraoperatively, and up to 7 days postoperatively. Concurrent with EEG recordings, two times per day postoperative Confusion Assessment Method (CAM) evaluations will quantify the presence and severity of delirium. EEG slow wave activity, sleep spindle density and peak frequency of the posterior dominant rhythm will be quantified. Linear mixed-effects models will be used to evaluate the relationships between delirium severity/duration and EEG measures as a function of time.Ethics and disseminationP-DROWS-E is approved by the ethics board at Washington University in St. Louis. Recruitment began in October 2018. Dissemination plans include presentations at scientific conferences, scientific publications and mass media.Trial registration numberNCT03291626.

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Electroconvulsive therapy (ECT) relies on the electrical induction of generalized seizures to treat major depressive disorder and other psychiatric illnesses. These planned procedures provide a clinically relevant model system for studying neurophysiologic characteristics of generalized seizures. We recently described novel central-positive complexes (CPCs), which were observed during ECT-induced seizures as generalized, high-amplitude waveforms with maximum positive voltage over the vertex. Here, we performed a systematic characterization of 6,928 CPC ictal waveforms recorded in 11 patients undergoing right unilateral (RUL) ECT. Analyses of high-density 65-electrode EEG recordings during these 50 seizures allowed evaluation of these CPCs across temporal, spatial, and spectral domains. Peak-amplitude CPC scalp topology was consistent across seizures, showing maximal positive polarity over the midline fronto-central region and maximal negative polarity over the suborbital regions. Total duration of CPCs positively correlated with the time required for return of responsiveness after ECT treatment (r = 0.39, p = 0.005). The rate of CPCs showed a frequency decline consistent with an exponential decay (median 0.032 (IQR 0.053) complexes/second). Gamma band (30-80 Hz) oscillations correlated with the peak amplitude of CPCs, which was also reproducible across seizures, with band power declining over time (r = -0.32, p < 10-7). The sources of these peak potentials were localized to the bilateral medial thalamus and cingulate cortical regions. Our findings demonstrated CPC characteristics that were invariant to participant, stimulus charge, time, and agent used to induce general anesthesia during the procedure. Consistent with ictal waveforms of other generalized epilepsy syndromes, CPCs showed topographic distribution over the fronto-central regions, predictable intra-seizure frequency decline, and correlation with gamma-range frequencies. Furthermore, source localization to the medial thalamus was consistent with underlying thalamocortical pathophysiology, as established in generalized epilepsy syndromes. The consistency and reproducibility of CPCs offers a new avenue for studying the dynamics of seizure activity and thalamocortical networks.

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