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How is information processed in the cerebral cortex? In most cases, recorded brain activity is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. However, the brain is obviously a single-trial processor. Thus, we here demonstrate that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial basis. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both extra-cellular neural recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Status epilepticus is characterized by persistent or repetitive seizures which, without successful treatment, can lead to neuronal damage, neurological deficits and death of the patient. While status epilepticus with motor symptoms can usually be clinically diagnosed, nonconvulsive status epilepticus is often clinically overlooked due to its ambiguous semiology, so that electroencephalography (EEG) recording is necessary. The treatment of status epilepticus is performed in four treatment steps, whereby a difficult to treat status epilepticus is present from the third step at the latest and intensive medical care of the patient is necessary. Timely initiation of treatment and sufficient dosage of anticonvulsive medication are decisive for the success of treatment. There is little evidence for the "late" stages of treatment. Intensive medical measures pose the risk of complications that worsen the prognosis. Especially in nonconvulsive status epilepticus, the use of anesthetics must be weighed against possible complications of mechanical ventilation. [ABSTRACT FROM AUTHOR]

Neurocritical patients suffer from a substantial risk of extubation failure. The aim of this prospective study was to analyze if quantitative EEG (qEEG) monitoring is able to predict successful extubation in these patients. We analyzed EEG-monitoring for at least six hours before extubation in patients receiving mechanical ventilation (MV) on our neurological intensive care unit (NICU) between November 2017 and May 2019. Patients were divided in 2 groups: patients with successful extubation (SE) versus patients with complications after MV withdrawal (failed extubation; FE), including reintubation, need for non-invasive ventilation (NIV) or death. Bipolar six channel EEG was applied. Unselected raw EEG signal underwent automated artefact rejection and Short Time Fast Fourier Transformation. The following relative proportions of global EEG spectrum were analyzed: relative beta (RB), alpha (RA), theta (RT), delta (RD) as well as the alpha delta ratio (ADR). Coefficient of variation (CV) was calculated as a measure of fluctuations in the different power bands. Mann–Whitney U test and logistic regression were applied to analyze group differences. 52 patients were included (26 male, mean age 65 ± 17 years, diagnosis: 40% seizures/status epilepticus, 37% ischemia, 13% intracranial hemorrhage, 10% others). Successful extubation was possible in 40 patients (77%), reintubation was necessary in 6 patients (12%), 5 patients (10%) required NIV, one patient died. In contrast to FE patients, SE patients showed more stable EEG power values (lower CV) considering all EEG channels (RB: p < 0.0005; RA: p = 0.045; RT: p = 0.045) with RB as an independent predictor of weaning success in logistic regression (p = 0.004). The proportion of the EEG frequency bands (RB, RA RT, RD) of the entire EEG power spectrum was not significantly different between SE and FE patients. Higher fluctuations in qEEG frequency bands, reflecting greater fluctuation in alertness, during the hours before cessation of MV were associated with a higher rate of complications after extubation in this cohort. The stability of qEEG power values may represent a non-invasive, examiner-independent parameter to facilitate weaning assessment in neurocritical patients. [ABSTRACT FROM AUTHOR]

Background: Patients in refractory status epilepticus (RSE) may require treatment with continuous intravenous anesthetic drugs (cIVADs) for seizure control. The use of cIVADs, however, was recently associated with poor outcome in status epilepticus (SE), raising the question of whether cIVAD therapy should be delayed for attempts to halt seizures with repeated non-anesthetic antiepileptic drugs. In this study, we aimed to determine the impact of differences in therapeutic approaches on RSE outcome using timing of cIVAD therapy as a surrogate for treatment aggressiveness.Methods: This was a retrospective cohort study over 14 years (n = 77) comparing patients with RSE treated with cIVADs within and after 48 h after RSE onset, and functional status at last follow-up was the primary outcome (good = return to premorbid baseline or modified Rankin Scale score of less than 3). Secondary outcomes included discharge functional status, in-hospital mortality, RSE termination, induction of burst suppression, use of thiopental, duration of RSE after initiation of cIVADs, duration of mechanical ventilation, and occurrence of super-refractory SE. Analysis was performed on the total cohort and on subgroups defined by RSE severity according to the Status Epilepticus Severity Score (STESS) and by the variables contained therein.Results: Fifty-three (68.8%) patients received cIVADs within the first 48 h. Early cIVAD treatment was independently associated with good outcome (adjusted risk ratio [aRR] 3.175, 95% confidence interval [CI] 1.273-7.918; P = 0.013) as well as lower chance of both induction of burst suppression (aRR 0.661, 95% CI 0.507-0.861; P = 0.002) and use of thiopental (aRR 0.446, 95% CI 0.205-0.874; P = 0.043). RSE duration after cIVAD initiation was shorter in the early cIVAD cohort (hazard ratio 1.796, 95% CI 1.047-3.081; P = 0.033). Timing of cIVAD use did not impact the remaining secondary outcomes. Subgroup analysis revealed early cIVAD impact on the primary outcome to be driven by patients with STESS of less than 3.Conclusions: Patients with RSE treated with cIVADs may benefit from early initiation of such therapy. [ABSTRACT FROM AUTHOR]

• Extent of alpha power decrease in qEEG moderately correlates with severity of vasospasm in transcranial ultrasound. • qEEG is able to differentiate between patients with and without development of cerebral infarction after subarachnoid haemorrhage. • Total duration of alpha power decrease in qEEG is an easy, non-invasive marker to survey treatment of delayed cerebral ischemia. In subarachnoid hemorrhage (SAH), transcranial Doppler/color-coded-duplex sonography (TCD/TCCS) is used to detect delayed cerebral ischemia (DCI). In previous studies, quantitative electroencephalography (qEEG) also predicted imminent DCI. This study aimed to compare and analyse the ability of qEEG and TCD/TCCS to early identify patients who will develop later manifest cerebral infarction. We analysed cohorts of two previous qEEG studies. Continuous six-channel-EEG with artefact rejection and a detrending procedure was applied. Alpha power decline of ≥ 40% for ≥ 5 hours compared to a 6-hour-baseline was defined as significant EEG event. Median reduction and duration of alpha power decrease in each channel was determined. Vasospasm was diagnosed by TCD/TCCS, identifying the maximum frequency and days of vasospasm in each territory. 34 patients were included (17 male, mean age 56 ± 11 years, Hunt and Hess grade: I–V, cerebral infarction: 9). Maximum frequencies in TCD/TCCS and alpha power reduction in qEEG were correlated (r = 0.43; p = 0.015). Patients with and without infarction significantly differed in qEEG parameters (maximum alpha power decrease: 78% vs 64%, p = 0.019; summed hours of alpha power decline: 236 hours vs 39 hours, p = 0.006) but showed no significant differences in TCD/TCCS parameters. There was a moderate correlation of TCD/TCCS frequencies and qEEG alpha power reduction but only qEEG differentiated between patients with and without cerebral infarction. qEEG represents a non-invasive, continuous tool to identify patients at risk of cerebral infarction. [ABSTRACT FROM AUTHOR]