Alternate Electrode Placements to Facilitate Frontal Electroencephalography Monitoring in Anesthetized and Critically Ill Patients.

BACKGROUND: Frontal electroencephalography (EEG) monitoring can be useful in guiding the titration of anesthetics, but it is not always feasible to place electrodes in the standard configuration in some circumstances, including during neurosurgery. This study compares 5 alternate configurations of the Masimo Sedline Sensor. METHODS: Ten stably sedated patients in the intensive care unit were recruited. Frontal EEG was monitored in the standard configuration (bifrontal upright) and 5 alternate configurations: bifrontal inverse, infraorbital, lateral upright, lateral inverse, and semilateral. Average power spectral densities (PSDs) with 95% CIs in the alternate configurations were compared to PSDs in the standard configuration. Two-one-sided-testing with Wilcoxon signed-rank tests assessed equivalence in the spectral edge frequency (SEF-95), EEG power, and relative delta (0.5 to 3.5 Hz), alpha (8 to 12 Hz), and beta (20 to 30 Hz) power between each alternate and standard configurations. RESULTS: After the removal of unanalyzable tracings, 7 patients were included for analysis in the infraorbital configuration and 9 in all other configurations. In the lateral upright and lateral inverse configurations, PSDs significantly differed from the standard configuration within the 15 to 20 Hz band. The greatest decrease in EEG power was in the lateral inverse configuration (median: -97 dB; IQR: -130, -62 dB). The largest change in frequency distribution of EEG power was in the infraorbital configuration; median SEF-95 change of -1.4 Hz (IQR: -2.8, 0.7 Hz), median relative delta power change of +7.3% (IQR: 1.4%, 7.9%), and median relative alpha power change of -0.6% (IQR: -5.7%, 0.0%). CONCLUSIONS: These 5 alternate Sedline electrode configurations are suitable options for monitoring frontal EEG when the standard configuration is not possible.

Telemetric electroencephalography recording in anesthetized mice-A novel system using minimally-invasive needle electrodes with a wireless OpenBCI™ Cyton Biosensing Board.

Telemetric electroencephalography (EEG) recording, using subdermal needle electrodes, is a minimally-invasive method to investigate mammalian neurophysiology during anesthesia. These inexpensive systems may streamline experiments examining global brain phenomena during surgical anesthesia or disease. We utilized the OpenBCI™ Cyton board with subdermal needle electrodes to extract EEG features in six C57BL/6J mice undergoing isoflurane anesthesia. Burst suppression ratio (BSR) and spectral features were compared for a verification of our method. Following an increase from 1.5% to 2.0% isoflurane, the BSR increased (Wilcoxon-signed-rank statistic; p = 0.0313). Furthermore, although the absolute EEG spectral power decreased, the relative spectral power remained comparable (Wilcoxon-Mann-Whitney U-Statistic; 95% CI exclusive AUC=0.5; p < 0.05). Compared to tethered systems, this method confers several improvements for anesthesia specific protocols: 1-Avoiding electrode implant surgical procedures, 2-Anatomical non-specificity for needle electrode placement to monitor global cortical activity representative of anesthetic state, 3-Facility to repeat recordings in the same animal, 4-User-friendly for non-experts, 5-Rapid set-up time, and 6-Lower costs.•Minimally-invasive telemetric EEG recording systems ergonomically improve tethered systems for anesthesia protocols.•Using this method, we verified that higher isoflurane concentrations resulted in an increased EEG burst suppression ratio and decreased EEG absolute spectral power, with no change in frequency distribution.

Frontal Electroencephalography Findings in Critically Ill COVID-19 Patients.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) negatively impacts the central nervous system, and studies using a full montage of electroencephalogram (EEG) electrodes have reported nonspecific EEG patterns associated with coronavirus disease 2019 (COVID-19) infection. The use of this technology is resource-intensive and limited in its implementation. In this descriptive pilot study, we report neurophysiological patterns and the potential prognostic capability of an abbreviated frontal EEG electrode montage in critically ill COVID-19 patients. MATERIALS AND METHODS: Patients receiving mechanical ventilation for SARS-CoV-2 respiratory failure were monitored with Sedline Root Devices using EEG electrodes were placed over the forehead. Qualitative EEG assessments were conducted daily. The primary outcome was mortality, and secondary outcomes were duration of endotracheal intubation and lengths of intensive care and hospitalization stay. RESULTS: Twenty-six patients were included in the study, and EEG discontinuity was identified in 22 (84.6%) patients. The limited sample size and patient heterogeneity precluded statistical analysis, but certain patterns were suggested by trends in the data. Survival was 100% (4/4) for those patients in which a discontinuous EEG pattern was not observed. The majority of patients (87.5%, 7/8) demonstrating activity in the low-moderate frequency range (7 to 17 Hz) survived compared with 61.1% (11/18) of those without this observation. CONCLUSIONS: The majority of COVID-19 patients showed signs of EEG discontinuity during monitoring with an abbreviated electrode montage. The trends towards worse survival among those with EEG discontinuity support the need for additional studies to investigate these associations in COVID-19 patients.

Effects of exercise on the sleep microarchitecture in the aging brain: A study on a sedentary sample.

Having a healthy sleep pattern plays a vital role in one's overall health. Sleep in the elderly is characterized by decreased slow-wave sleep and an increase of REM sleep. Furthermore, quantitative electroencephalographic (qEEG) studies have shown an age-related attenuation of total EEG power in sleep. However, exercise has been shown to improve sleep across all age groups. In this study, we used the Sleep Profiler™ EEG Sleep Monitor to observe EEG changes occurring during sleep following an aerobic exercise intervention. This study was done on older adults (N = 18, with only five subjects containing both pre- and post-data of sufficient quality for analysis) with an age range 60-85 years. The aerobics regimen was performed three times weekly for 12-weeks commencing with 20-min sessions. The time of each session progressed by 1-2 min/session as needed to a maximum time of 45 min per session. The macro-architecture (sleep stages) and microarchitecture (EEG) results were analyzed using MATLAB. For the microarchitecture, our results showed more deep sleep following the aerobic exercise regimen. Furthermore, for the microarchitecture, out results shows an increase in total EEG power post-exercise in both light (N1 and L1) and deep sleep (N2 and N3). These preliminary changes in sleep the microarchitecture suggest that non-pharmacologic methods might mitigate age-related EEG changes with potential implications for neurocognitive health.

Raspberry Pi-Based Data Archival System for Electroencephalogram Signals From the SedLine Root Device.

BACKGROUND: The retrospective analysis of electroencephalogram (EEG) signals acquired from patients under general anesthesia is crucial in understanding the patient's unconscious brain's state. However, the creation of such database is often tedious and cumbersome and involves human labor. Hence, we developed a Raspberry Pi-based system for archiving EEG signals recorded from patients under anesthesia in operating rooms (ORs) with minimal human involvement. METHODS: Using this system, we archived patient EEG signals from over 500 unique surgeries at the Emory University Orthopaedics and Spine Hospital, Atlanta, for about 18 months. For this, we developed a software package that runs on a Raspberry Pi and archives patient EEG signals from a SedLine Root EEG Monitor (Masimo) to a secure Health Insurance Portability and Accountability Act (HIPAA) compliant cloud storage. The OR number corresponding to each surgery was archived along with the EEG signal to facilitate retrospective EEG analysis. We retrospectively processed the archived EEG signals and performed signal quality checks. We also proposed a formula to compute the proportion of true EEG signal and calculated the corresponding statistics. Further, we curated and interleaved patient medical record information with the corresponding EEG signals. RESULTS: We retrospectively processed the EEG signals to demonstrate a statistically significant negative correlation between the relative alpha power (8-12 Hz) of the EEG signal captured under anesthesia and the patient's age. CONCLUSIONS: Our system is a standalone EEG archiver developed using low cost and readily available hardware. We demonstrated that one could create a large-scale EEG database with minimal human involvement. Moreover, we showed that the captured EEG signal is of good quality for retrospective analysis and combined the EEG signal with the patient medical records. This project's software has been released under an open-source license to enable others to use and contribute.

Autistic traits moderate relations between cardiac autonomic activity, interoceptive accuracy, and emotion processing in college students.

The autonomic nervous system (ANS) plays a key role in maintaining physiological homeostasis, and research with neurotypical and autistic individuals has found relations between cardiac autonomic responses, as well as awareness of one's cardiac responses, and social and emotional processing. The current study examined relations between cardiac autonomic activity, heartbeat perception, emotion processing, and levels of autistic traits in a group of college students. Cardiac ANS at baseline and during an emotional picture task was measured, and a heartbeat perception task was used to assess interoceptive accuracy (IA). Questionnaires then assessed autistic traits, alexithymia (difficulties processing one's own emotions), and emotion recognition. Consistent with past work, greatest heart rate deceleration was seen in response to negative images. In the overall sample, no correlations were found between cardiac ANS, IA, autistic traits, and aspects of emotion processing, but when examining individuals high and low on autistic traits separately, distinct associations were found. Within the group of participants with elevated autistic traits, greater baseline respiratory sinus arrhythmia (RSA) was predictive of lower levels of alexithymia and autistic traits, as well as higher IA, but these associations were not seen in participants low on autistic traits. These findings suggest that variability in autistic traits in a non-autistic sample can lead to differential relations between cardiac autonomic responses, awareness of one's cardiac responses, and emotion processing.