The efficacy of an online learning tool in improving EEG analysis and interpretation skills of Technologists, Neurology Registrars and Neurologists

Background Scalp electroencephalography (EEG) remains an invaluable neurophysiological tool in supporting the diagnosis and management of epilepsy and encephalopathy, however, most sub-Saharan countries have very few neurologists per population for EEG analysis and training. Web-based, distance learning programs may provide effective electroencephalogram (EEG) training in resource-poor settings. EEGonline is an interactive, web-based, 6-month multi-modality, learning program designed to teach basic principles and clinical application of EEG. This study aimed to determine the effectiveness of EEGonline in improving EEG analysis and interpretation skills for neurologists, neurology residents and technologists, particularly in resource-limited settings. Methods Between June 2017 and November 2018, 179 learners were registered on the EEGonline course. Of these, 128 learners originating from 20 African countries, Europe, the UK and USA participated in the study. Pre- and post-course multiplechoice question (MCQ) test results and EEGonline user logs were analyzed. Differences in pre- and post-test performance were correlated with quantified exposure to various EEGonline learning modalities. Participants' impressions of EEGonline efficacy and usefulness were assessed through pre- and post-course perception surveys. Results Ninety-one participants attempted both pre- and post-course tests. Mean scores improved from 46.7% ± 17.6% to 64.1% ± 18% respectively (p< 0.001, Cohen's d 0.974). Almost all participants improved regardless of the amount of course material used, however those who used more, tended to have higher scores. The largest percentage-improvement was in the correct identification of normal features (43.2% to 59.1%, p< 0.001, Cohen's d 0.664) and artefacts (43.3% to 61.6%, p< 0.001, Cohen's d 0.836). Improvement in competence was associated with improvement in subjective confidence in EEG analysis. Overall confidence among 72 survey respondents improved significantly from 25.3% to 64.8% (p< 0.001). Lecture notes, end-of-module self-assessment quizzes and discussion forums were the most utilised learning modalities. The majority of survey respondents (97.2%) concluded that EEGonline was a useful learning tool and 93% recommended that similar courses should be included in EEG training curricula. Discussion Almost all participants showed significant improvement in EEG analysis competence (MCQ test scores) and confidence (survey responses) following the educational intervention, regardless of the amount of course material used. Improved identification of normal features and artefacts is particularly useful as it reduces the risk of misdiagnosis which can cause harm. The EEGonline course employed several learning techniques, through its multi-modality format, that may have contributed to the improvement observed, including, self-directed learning, cognitivism, collaborative learning, contextual learning and reflective learning. Subjective confidence likely correlates with competence and may be useful to gauge learners' needs and levels of understanding about a subject. Learning preferences vary among adult learners, it is unclear if one learning modality (that is, video, audio, lecture notes, epoch activities, discussion forums) is superior to others, but it seems as though a multi-modal approach may be the most sensible. Conclusions This study demonstrated that a multi-modal, online EEG teaching tool was effective in improving EEG analysis and interpretation skills and may be a useful supplement for EEG teaching especially in resource-poor settings. Given the optimistic findings of this study, we encourage the development and evaluation of further online neurology teaching tools

Clinical Applications of Neuromonitoring Following Acute Brain Injury

Various invasive and non-invasive cranial monitoring techniques can be applied clinically to describe the extent to which cerebral hemodynamics and subsequently, patient outcome, have been impacted following acute brain injury (ABI). This Ph.D. thesis examines both prospective and retrospective patient data in both neurocritical and general intensive care patients. Thirty neurotrauma patients and forty general intensive care patients with neurological complications were prospectively monitored after ABI. Retrospective patient data was harvested from a database of 1,023 traumatic brain injury (TBI) patients with invasive intracranial pressure (ICP), arterial blood pressure (ABP), and transcranial Doppler ultrasonography (TCD) recordings. Data analysis focused on ICP microsensor accuracy, compensatory reserve, the pulsatility of brain signals (ICP and TCD), and cerebral arterial blood volume (CaBV) based on TCD. The main results are summarized below: I. Intracranial hypertension has a profound negative influence on cerebrovascular parameters and patient outcome. II. ICP microsensor accuracy is limited, with an average error of approximately ± 6.0 mm Hg. III. ICP weighted with the compensatory reserve better predicts outcome than mean ICP alone. IV. ICP and TCD pulsatility are functions of mean ICP and cerebral perfusion pressure (CPP). V. Continuous blood flow forward (CFF) and pulsatile blood flow forward (PFF) models can approximate CaBV with derived TCD signals; CFF best models TCD pulsatility. VI. The pressure reactivity index (PRx) and the pulse amplitude index (PAx) can be estimated non-invasively using slow waves of TCD estimated by CaBV with similar outcome-predictive power. VII. Multi-parametric TCD-based monitoring of general intensive care patients is clinically feasible; the joint estimation of autoregulation, dysautonomia, non-invasive ICP, and critical closing pressure is possible. The culmination of these projects should have an impact on current monitoring practices in ABI patients, emphasizing the continued validation and refinement of TCD methodology in clinical neurosciences

U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions

BACKGROUND: Shedding light on the neuroscientific mechanisms of human upper limb motor control, in both healthy and disease conditions (e.g., after a stroke), can help to devise effective tools for a quantitative evaluation of the impaired conditions, and to properly inform the rehabilitative process. Furthermore, the design and control of mechatronic devices can also benefit from such neuroscientific outcomes, with important implications for assistive and rehabilitation robotics and advanced human-machine interaction. To reach these goals, we believe that an exhaustive data collection on human behavior is a mandatory step. For this reason, we release U-Limb, a large, multi-modal, multi-center data collection on human upper limb movements, with the aim of fostering trans-disciplinary cross-fertilization. CONTRIBUTION: This collection of signals consists of data from 91 able-bodied and 65 post-stroke participants and is organized at 3 levels: (i) upper limb daily living activities, during which kinematic and physiological signals (electromyography, electro-encephalography, and electrocardiography) were recorded; (ii) force-kinematic behavior during precise manipulation tasks with a haptic device; and (iii) brain activity during hand control using functional magnetic resonance imaging

Quantitative MRI correlates of hippocampal and neocortical pathology in intractable temporal lobe epilepsy

Intractable or drug-resistant epilepsy occurs in over 30% of epilepsy patients, with many of these patients undergoing surgical excision of the affected brain region to achieve seizure control. Advances in MRI have the potential to improve surgical treatment of epilepsy through improved identification and delineation of lesions. However, validation is currently needed to investigate histopathological correlates of these new imaging techniques. The purpose of this work is to investigate histopathological correlates of quantitative relaxometry and DTI from hippocampal and neocortical specimens of intractable TLE patients. To achieve this goal I developed and evaluated a pipeline for histology to in-vivo MRI image registration, which finds dense spatial correspondence between both modalities. This protocol was divided in two steps whereby sparsely sectioned histology from temporal lobe specimens was first registered to the intermediate ex-vivo MRI which is then registered to the in-vivo MRI, completing a pipeline for histology to in-vivo MRI registration. When correlating relaxometry and DTI with neuronal density and morphology in the temporal lobe neocortex, I found T1 to be a predictor of neuronal density in the neocortical GM and demonstrated that employing multi-parametric MRI (combining T1 and FA together) provided a significantly better fit than each parameter alone in predicting density of neurons. This work was the first to relate in-vivo T1 and FA values to the proportion of neurons in GM. When investigating these quantitative multimodal parameters with histological features within the hippocampal subfields, I demonstrated that MD correlates with neuronal density and size, and can act as a marker for neuron integrity within the hippocampus. More importantly, this work was the first to highlight the potential of subfield relaxometry and diffusion parameters (mainly T2 and MD) as well as volumetry in predicting the extent of cell loss per subfield pre-operatively, with a precision so far unachievable. These results suggest that high-resolution quantitative MRI sequences could impact clinical practice for pre-operative evaluation and prediction of surgical outcomes of intractable epilepsy

Intraoperative Neurophysiological Monitoring for Endoscopic Endonasal Approaches to the Skull Base: A Technical Guide.

Intraoperative neurophysiological monitoring during endoscopic, endonasal approaches to the skull base is both feasible and safe. Numerous reports have recently emerged from the literature evaluating the efficacy of different neuromonitoring tests during endonasal procedures, making them relatively well-studied. The authors report on a comprehensive, multimodality approach to monitoring the functional integrity of at risk nervous system structures, including the cerebral cortex, brainstem, cranial nerves, corticospinal tract, corticobulbar tract, and the thalamocortical somatosensory system during endonasal surgery of the skull base. The modalities employed include electroencephalography, somatosensory evoked potentials, free-running and electrically triggered electromyography, transcranial electric motor evoked potentials, and auditory evoked potentials. Methodological considerations as well as benefits and limitations are discussed. The authors argue that, while individual modalities have their limitations, multimodality neuromonitoring provides a real-time, comprehensive assessment of nervous system function and allows for safer, more aggressive management of skull base tumors via the endonasal route