Using electroencephalography to explore neurocognitive correlates of procedural proficiency: A pilot study to compare experts and novices during simulated endotracheal intubation.

The objective of this study was to explore the use of EEG as a measure of neurocognitive engagement during a procedural task. In this observational study, self-reported cognitive load, observed performance, and EEG signatures in experts and novices were compared during simulated endotracheal intubation. Twelve medical students (novices) and eight senior anesthesiology trainees (experts) were included in the study. Experts reported significantly lower cognitive load (P < 0.001) and outperformed novices based on the observational checklist (P < 0.001). EEG signatures differed significantly between the experts and novices. Experts showed a greater increase in delta and theta band amplitudes, especially in temporal and frontal locations and in right occipital areas for delta. A machine learning algorithm showed 83.3 % accuracy for expert-novice skill classification using the selected EEG features. Performance scores were positively correlated (P < 0.05) with event-related amplitudes for delta and theta bands at locations where experts and novices showed significant differences. Increased delta and frontal/midline theta oscillations on EEG suggested that experts had better attentional control than novices. This pilot study provides initial evidence that EEG may be a useful, noninvasive measure of neurocognitive engagement in operational settings and that it has the potential to complement traditional clinical skills assessment.

An EEG Signature of MCH Neuron Activities Predicts Cocaine Seeking.

Background: Identifying biomarkers that predict substance use disorder (SUD) propensity may better strategize anti-addiction treatment. The melanin-concentrating hormone (MCH) neurons in the lateral hypothalamus (LH) critically mediates interactions between sleep and substance use; however, their activities are largely obscured in surface electroencephalogram (EEG) measures, hindering the development of biomarkers. Methods: Surface EEG signals and real-time Ca2+ activities of LH MCH neurons (Ca2+MCH) were simultaneously recorded in male and female adult rats. Mathematical modeling and machine learning were then applied to predict Ca2+MCH using EEG derivatives. The robustness of the predictions was tested across sex and treatment conditions. Finally, features extracted from the EEG-predicted Ca2+MCH either before or after cocaine experience were used to predict future drug-seeking behaviors. Results: An EEG waveform derivative - a modified theta-to-delta ratio (EEG Ratio) - accurately tracks real-time Ca2+MCH in rats. The prediction was robust during rapid eye movement sleep (REMS), persisted through REMS manipulations, wakefulness, circadian phases, and was consistent across sex. Moreover, cocaine self-administration and long-term withdrawal altered EEG Ratio suggesting shortening and circadian redistribution of synchronous MCH neuron activities. In addition, features of EEG Ratio indicative of prolonged synchronous MCH neuron activities predicted lower subsequent cocaine seeking. EEG Ratio also exhibited advantages over conventional REMS measures for the predictions. Conclusions: The identified EEG Ratio may serve as a non-invasive measure for assessing MCH neuron activities in vivo and evaluating REMS; it may also serve as a potential biomarker predicting drug use propensity.

An Electroencephalogram Signature of Melanin-Concentrating Hormone Neuron Activities Predicts Cocaine Seeking.

BACKGROUND: Identifying biomarkers that predict substance use disorder propensity may better strategize antiaddiction treatment. Melanin-concentrating hormone (MCH) neurons in the lateral hypothalamus critically mediate interactions between sleep and substance use; however, their activities are largely obscured in surface electroencephalogram (EEG) measures, hindering the development of biomarkers. METHODS: Surface EEG signals and real-time calcium (Ca2+) activities of lateral hypothalamus MCH neurons (Ca2+MCH) were simultaneously recorded in male and female adult rats. Mathematical modeling and machine learning were then applied to predict Ca2+MCH using EEG derivatives. The robustness of the predictions was tested across sex and treatment conditions. Finally, features extracted from the EEG-predicted Ca2+MCH either before or after cocaine experience were used to predict future drug-seeking behaviors. RESULTS: An EEG waveform derivative-a modified theta-delta-theta peak ratio (EEGTDT ratio)-accurately tracked real-time Ca2+MCH in rats. The prediction was robust during rapid eye movement sleep (REMS), persisted through vigilance states, sleep manipulations, and circadian phases, and was consistent across sex. Moreover, cocaine self-administration and long-term withdrawal altered EEGTDT ratio, suggesting shortening and circadian redistribution of synchronous MCH neuron activities. In addition, features of EEGTDT ratio indicative of prolonged synchronous MCH neuron activities predicted lower subsequent cocaine seeking. EEGTDT ratio also exhibited advantages over conventional REMS measures for the predictions. CONCLUSIONS: The identified EEGTDT ratio may serve as a noninvasive measure for assessing MCH neuron activities in vivo and evaluating REMS; it may also serve as a potential biomarker for predicting drug use propensity.

Neurocognitive Correlates of Clinical Decision Making: A Pilot Study Using Electroencephalography.

The development of sound clinical reasoning, while essential for optimal patient care, can be quite an elusive process. Researchers typically rely on a self-report or observational measures to study decision making, but clinicians' reasoning processes may not be apparent to themselves or outside observers. This study explored electroencephalography (EEG) to examine neurocognitive correlates of clinical decision making during a simulated American Board of Anesthesiology-style standardized oral exam. Eight novice anesthesiology residents and eight fellows who had recently passed their board exams were included in the study. Measures included EEG recordings from each participant, demographic information, self-reported cognitive load, and observed performance. To examine neurocognitive correlates of clinical decision making, power spectral density (PSD) and functional connectivity between pairs of EEG channels were analyzed. Although both groups reported similar cognitive load (p = 0.840), fellows outperformed novices based on performance scores (p < 0.001). PSD showed no significant differences between the groups. Several coherence features showed significant differences between fellows and residents, mostly related to the channels within the frontal, between the frontal and parietal, and between the frontal and temporal areas. The functional connectivity patterns found in this study could provide some clues for future hypothesis-driven studies in examining the underlying cognitive processes that lead to better clinical reasoning.

A Multimodal Evaluation of Podcast Learning, Retention, and Electroencephalographically Measured Attention in Medical Trainees.

INTRODUCTION: Podcasts have become popular among medical trainees. However, it is unclear how well learners retain information from podcasts compared to traditional educational modalities, and whether multitasking affects the learner's ability to pay attention and learn. This study attempted to examine the effectiveness of podcast learning by using electroencephalography (EEG) to measure learner attention, in addition to test performance, task load, and preferences. METHODS: The study used a repeated measures design with three conditions: podcast listening on a treadmill, podcast listening seated, and textbook reading seated. Participants were anesthesiology residents and medical students at a large United States academic medical center. Three topics were chosen: allergic response, liver physiology, and statistics. Each participant studied all three topics that were randomly assigned to one of three learning conditions - in random order. Participants completed a knowledge test at baseline, after each condition, and at four-week follow-up, and reported preferred learning modality and task load under each modality. Activation levels in alerting, orienting, and executive attentional networks were examined using EEG.  Results: Sixty-one participants (11 anesthesiology residents and 50 medical students) were included in the study. Of the 61, six were excluded from the EEG analyses due to corrupted recordings. EEG results showed that mean attention network activation scores did not differ between the study conditions. Trainees preferred podcast learning over reading for all three topics. When compared to textbook reading, podcast learning (seated or on a treadmill) produced significantly better learning gain, and equivalent retention for two of the three topics. CONCLUSIONS: Our study is the first to use neurocognitive data, self-reported satisfaction, and knowledge test performance to demonstrate that podcasts are at least equivalent to textbooks for maintaining attention, immediate learning, and retention - even while exercising.

Rapid Eye Movement Sleep Engages Melanin-Concentrating Hormone Neurons to Reduce Cocaine Seeking.

BACKGROUND: Persistent sleep disruptions following withdrawal from abused drugs may hold keys to battle drug relapse. It is posited that there may be sleep signatures that predict relapse propensity, identifying which may open new avenues for treating substance use disorders. METHODS: We trained male rats (approximately postnatal day 56) to self-administer cocaine. After long-term drug withdrawal (approximately postnatal day 100), we examined the correlations between the intensity of cocaine seeking and key sleep features. To test for causal relationships, we then used behavioral, chemogenetic, or optogenetic methods to selectively increase rapid eye movement sleep (REMS) and measured behavioral and electrophysiological outcomes to probe for cellular and circuit mechanisms underlying REMS-mediated regulation of cocaine seeking. RESULTS: A selective set of REMS features was preferentially associated with the intensity of cue-induced cocaine seeking after drug withdrawal. Moreover, selectively increasing REMS time and continuity by environmental warming attenuated a withdrawal time-dependent intensification of cocaine seeking, or incubation of cocaine craving, suggesting that REMS may benefit withdrawal. Warming increased the activity of lateral hypothalamic melanin-concentrating hormone (MCH) neurons selectively during prolonged REMS episodes and counteracted cocaine-induced synaptic accumulation of calcium-permeable AMPA receptors in the nucleus accumbens-a critical substrate for incubation. Finally, the warming effects were partly mimicked by chemogenetic or optogenetic stimulations of MCH neurons during sleep, or intra-accumbens infusions of MCH peptide during the rat's inactive phase. CONCLUSIONS: REMS may encode individual vulnerability to relapse, and MCH neuron activities can be selectively targeted during REMS to reduce drug relapse.

Pencil back-projection method for SAR imaging.

We present a high-resolution method for spotlight mode SAR imaging that utilizes parametric modeling of projected target reflectivity density function and tomographic reconstruction. The method requires no polar-to-cartesian interpolation in spectral domain. Utilization of forward-backward total least squares bandpass matrix pencil method allows super resolution to be achieved in range for a single imaging angle. Hence, the quality of the image reconstructed by convolution back-projection is also improved. It is shown that the method is very resistant to noise and can generate images down to very low SNR values. Direct formulation in terms of physical quantities such as electric field and current density is another contribution of this paper.