Detecting Cortical Spreading Depolarization with Full Band Scalp Electroencephalography: An Illusion?

Real-Time Non-Invasive Imaging and Detection of Spreading Depolarizations through EEG: An Ultra-Light Explainable Deep Learning Approach

A core aim of neurocritical care is to prevent secondary brain injury. Spreading depolarizations (SDs) have been identified as an important independent cause of secondary brain injury. SDs are usually detected using invasive electrocorticography recorded at high sampling frequency. Recent pilot studies suggest a possible utility of scalp electrodes generated electroencephalogram (EEG) for non-invasive SD detection. However, noise and attenuation of EEG signals makes this detection task extremely challenging. Previous methods focus on detecting temporal power change of EEG over a fixed high-density map of scalp electrodes, which is not always clinically feasible. Having a specialized spectrogram as an input to the automatic SD detection model, this study is the first to transform SD identification problem from a detection task on a 1-D time-series wave to a task on a sequential 2-D rendered imaging. This study presented a novel ultra-light-weight multi-modal deep-learning network to fuse EEG spectrogram imaging and temporal power vectors to enhance SD identification accuracy over each single electrode, allowing flexible EEG map and paving the way for SD detection on ultra-low-density EEG with variable electrode positioning. Our proposed model has an ultra-fast processing speed (<0.3 sec). Compared to the conventional methods (2 hours), this is a huge advancement towards early SD detection and to facilitate instant brain injury prognosis. Seeing SDs with a new dimension - frequency on spectrograms, we demonstrated that such additional dimension could improve SD detection accuracy, providing preliminary evidence to support the hypothesis that SDs may show implicit features over the frequency profile.

Utility and rationale for continuous EEG monitoring: a primer for the general intensivist

This review offers a comprehensive guide for general intensivists on the utility of continuous EEG (cEEG) monitoring for critically ill patients. Beyond the primary role of EEG in detecting seizures, this review explores its utility in neuroprognostication, monitoring neurological deterioration, assessing treatment responses, and aiding rehabilitation in patients with encephalopathy, coma, or other consciousness disorders. Most seizures and status epilepticus (SE) events in the intensive care unit (ICU) setting are nonconvulsive or subtle, making cEEG essential for identifying these otherwise silent events. Imaging and invasive approaches can add to the diagnosis of seizures for specific populations, given that scalp electrodes may fail to identify seizures that may be detected by depth electrodes or electroradiologic findings. When cEEG identifies SE, the risk of secondary neuronal injury related to the time-intensity "burden" often prompts treatment with anti-seizure medications. Similarly, treatment may be administered for seizure-spectrum activity, such as periodic discharges or lateralized rhythmic delta slowing on the ictal-interictal continuum (IIC), even when frank seizures are not evident on the scalp. In this setting, cEEG is utilized empirically to monitor treatment response. Separately, cEEG has other versatile uses for neurotelemetry, including identifying the level of sedation or consciousness. Specific conditions such as sepsis, traumatic brain injury, subarachnoid hemorrhage, and cardiac arrest may each be associated with a unique application of cEEG; for example, predicting impending events of delayed cerebral ischemia, a feared complication in the first two weeks after subarachnoid hemorrhage. After brief training, non-neurophysiologists can learn to interpret quantitative EEG trends that summarize elements of EEG activity, enhancing clinical responsiveness in collaboration with clinical neurophysiologists. Intensivists and other healthcare professionals also play crucial roles in facilitating timely cEEG setup, preventing electrode-related skin injuries, and maintaining patient mobility during monitoring.

EEG Changes in Migraine-Can EEG Help to Monitor Attack Susceptibility?

Migraine is a highly prevalent brain condition with paroxysmal changes in brain excitability believed to contribute to the initiation of an attack. The attacks and their unpredictability have a major impact on the lives of patients. Clinical management is hampered by a lack of reliable predictors for upcoming attacks, which may help in understanding pathophysiological mechanisms to identify new treatment targets that may be positioned between the acute and preventive possibilities that are currently available. So far, a large range of studies using conventional hospital-based EEG recordings have provided contradictory results, with indications of both cortical hyper- as well as hypo-excitability. These heterogeneous findings may largely be because most studies were cross-sectional in design, providing only a snapshot in time of a patient's brain state without capturing day-to-day fluctuations. The scope of this narrative review is to (i) reflect on current knowledge on EEG changes in the context of migraine, the attack cycle, and underlying pathophysiology; (ii) consider the effects of migraine treatment on EEG features; (iii) outline challenges and opportunities in using EEG for monitoring attack susceptibility; and (iv) discuss future applications of EEG in home-based settings.

Signatures of migraine aura in high-density-EEG

OBJECTIVE

Cortical spreading depolarization is highly conserved among the species. It is easily detectable in direct cortical surface recordings and has been recorded in the cortex of humans with severe neurological disease. It is considered the pathophysiological correlate of human migraine aura, but direct electrophysiological evidence is still missing. As signatures of cortical spreading depolarization have been recognized in scalp EEG, we investigated typical spontaneous migraine aura, using full band high-density EEG (HD-EEG).

METHODS

In this prospective study, patients with migraine with aura were investigated during spontaneous migraine aura and interictally. Time compressed HD-EEG were analyzed for the presence of cortical spreading depolarization characterized by (a) slow potential changes below 0.05 Hz, (b) suppression of faster activity from 0.5 Hz - 45 Hz (c) spreading of these changes to neighboring regions during the aura phase. Further, topographical changes in alpha-power spectral density (8-14 Hz) during aura were analyzed.

RESULTS

In total, 26 HD-EEGs were recorded in patients with migraine with aura, thereof 10 HD-EEGs during aura. Eight HD-EEGs were recorded in the same subject. During aura, no slow potentials were recorded, but alpha-power was significantly decreased in parieto-occipito-temporal location on the hemisphere contralateral to visual aura, lasting into the headache phase. Interictal alpha-power in patients with migraine with aura did not differ significantly from age- and sex-matched healthy controls.

CONCLUSIONS

Unequivocal signatures of spreading depolarization were not recorded with EEG on the intact scalp in migraine. The decrease in alpha-power contralateral to predominant visual symptoms is consistent with focal depression of spontaneous brain activity as a consequence of cortical spreading depolarization but is not specific thereof.

SIGNIFICANCE

Cortical spreading depolarization is relevant in migraine, other paroxysmal neurological disorders and neurointensive care.

Similarities in the Electrographic Patterns of Delayed Cerebral Infarction and Brain Death After Aneurysmal and Traumatic Subarachnoid Hemorrhage

While subarachnoid hemorrhage is the second most common hemorrhagic stroke in epidemiologic studies, the recent DISCHARGE-1 trial has shown that in reality, three-quarters of focal brain damage after subarachnoid hemorrhage is ischemic. Two-fifths of these ischemic infarctions occur early and three-fifths are delayed. The vast majority are cortical infarcts whose pathomorphology corresponds to anemic infarcts. Therefore, we propose in this review that subarachnoid hemorrhage as an ischemic-hemorrhagic stroke is rather a third, separate entity in addition to purely ischemic or hemorrhagic strokes. Cumulative focal brain damage, determined by neuroimaging after the first 2 weeks, is the strongest known predictor of patient outcome half a year after the initial hemorrhage. Because of the unique ability to implant neuromonitoring probes at the brain surface before stroke onset and to perform longitudinal MRI scans before and after stroke, delayed cerebral ischemia is currently the stroke variant in humans whose pathophysiological details are by far the best characterized. Optoelectrodes located directly over newly developing delayed infarcts have shown that, as mechanistic correlates of infarct development, spreading depolarizations trigger (1) spreading ischemia, (2) severe hypoxia, (3) persistent activity depression, and (4) transition from clustered spreading depolarizations to a negative ultraslow potential. Furthermore, traumatic brain injury and subarachnoid hemorrhage are the second and third most common etiologies of brain death during continued systemic circulation. Here, we use examples to illustrate that although the pathophysiological cascades associated with brain death are global, they closely resemble the local cascades associated with the development of delayed cerebral infarcts.

Cerebral Ischemic Reperfusion Injury: Preventative and Therapeutic Strategies

Acute ischemic stroke is a leading cause of morbidity and mortality in the United States. Treatment goals remain focused on restoring blood flow to compromised areas. However, a major concern arises after reperfusion occurs. Cerebral ischemic reperfusion injury is defined as damage to otherwise salvageable brain tissue occurring with the reestablishment of the vascular supply to that region. The pool of eligible patients for revascularization continues to grow, especially with the recently expanded endovascular therapeutic window. Neurointensivists should understand and manage complications of successful recanalization. In this review, we examine the pathophysiology, diagnosis, and potential management strategies in cerebral ischemic reperfusion injury.

Noninvasive and reliable automated detection of spreading depolarization in severe traumatic brain injury using scalp EEG

BACKGROUND

Spreading depolarizations (SDs) are a biomarker and a potentially treatable mechanism of worsening brain injury after traumatic brain injury (TBI). Noninvasive detection of SDs could transform critical care for brain injury patients but has remained elusive. Current methods to detect SDs are based on invasive intracranial recordings with limited spatial coverage. In this study, we establish the feasibility of automated SD detection through noninvasive scalp electroencephalography (EEG) for patients with severe TBI.

METHODS

Building on our recent WAVEFRONT algorithm, we designed an automated SD detection method. This algorithm, with learnable parameters and improved velocity estimation, extracts and tracks propagating power depressions using low-density EEG. The dataset for testing our algorithm contains 700 total SDs in 12 severe TBI patients who underwent decompressive hemicraniectomy (DHC), labeled using ground-truth intracranial EEG recordings. We utilize simultaneously recorded, continuous, low-density (19 electrodes) scalp EEG signals, to quantify the detection accuracy of WAVEFRONT in terms of true positive rate (TPR), false positive rate (FPR), as well as the accuracy of estimating SD frequency.

RESULTS

WAVEFRONT achieves the best average validation accuracy using Delta band EEG: 74% TPR with less than 1.5% FPR. Further, preliminary evidence suggests WAVEFRONT can estimate how frequently SDs may occur.

CONCLUSIONS

We establish the feasibility, and quantify the performance, of noninvasive SD detection after severe TBI using an automated algorithm. The algorithm, WAVEFRONT, can also potentially be used for diagnosis, monitoring, and tailoring treatments for worsening brain injury. Extension of these results to patients with intact skulls requires further study.

A Spatial-Temporal Graph Attention Network for Automated Detection and Width Estimation of Cortical Spreading Depression Using Scalp EEG

We present an end-to-end Spatial-Temporal Graph Attention Network (STGAT) for non-invasive detection and width estimation of Cortical Spreading Depressions (CSDs) on scalp electroencephalography (EEG). Our algorithm, that we refer to as CSD Spatial-temporal graph attention network or CSD-STGAT, is trained and tested on simulated CSDs with varying width and speed ranges. Using high-density EEG, CSD-STGAT achieves less than 10.96% normalized width estimation error for narrow CSDs, with an average normalized error of 6.35%±3.08% across all widths, enabling non-invasive and automated estimation of the width of CSDs for the first time. In addition, CSD-STGAT learns the temporal and spatial features of CSDs simultaneously, which improves the "spatio-temporal tracking accuracy" (i.e., the defined detection performance metric at each electrode) of the narrow CSDs by up to 14%, compared to the state-of-the-art CSD-SpArC algorithm, with only one-tenth of the network size. CSD-STGAT achieves the best spatio-temporal tracking accuracy of 86.27%±0.53% for wide CSDs using high-density EEG, which is comparable to the performance of CSD-SpArC with less than 0.38% performance reduction. We further stitch the detections across all electrodes and over time to evaluate the "temporal accuracy". Our algorithm achieves less than 0.7% false positive rate in the simulated dataset with inter-CSD intervals ranging from 5 to 60 minutes. The lightweight architecture of CSD-STGAT paves the way towards real-time detection and parameter estimation of these waves in the brain, with significant clinical impact.

Neurological and psychiatric comorbidities of migraine: Concepts and future perspectives

BACKGROUND

This narrative review aims to discuss several common neurological and psychiatric disorders that show comorbidity with migraine. Not only can we gain pathophysiological insights by studying these disorders, comorbidities also have important implications for treating migraine patients in clinical practice.

METHODS

A literature search on PubMed and Embase was conducted with the keywords "comorbidity", "migraine disorders", "migraine with aura", "migraine without aura", "depression", "depressive disorders", "epilepsy", "stroke", "patent foramen ovale", "sleep wake disorders", "restless legs syndrome", "genetics", "therapeutics".

RESULTS

Several common neurological and psychiatric disorders show comorbidity with migraine. Major depression and migraine show bidirectional causality and have shared genetic factors. Dysregulation of both hypothalamic and thalamic pathways have been implicated as a possibly cause. The increased risk of ischaemic stroke in migraine likely involves spreading depolarizations. Epilepsy is not only bidirectionally related to migraine, but is also co-occurring in monogenic migraine syndromes. Neuronal hyperexcitability is an important overlapping mechanism between these conditions. Hypothalamic dysfunction is suggested as the underlying mechanism for comorbidity between sleep disorders and migraine and might explain altered circadian timing in migraine.

CONCLUSION

These comorbid conditions in migraine with distinct pathophysiological mechanisms have important implications for best treatment choices and may provide clues for future approaches.

Oxyhemoglobin and Cerebral Blood Flow Transients Detect Infarction in Rat Focal Brain Ischemia

Spreading depolarizations (SD) refer to the near-complete depolarization of neurons that is associated with brain injuries such as ischemic stroke. The present gold standard for SD monitoring in humans is invasive electrocorticography (ECoG). A promising non-invasive alternative to ECoG is diffuse optical monitoring of SD-related flow and hemoglobin transients. To investigate the clinical utility of flow and hemoglobin transients, we analyzed their association with infarction in rat focal brain ischemia. Optical images of flow, oxy-hemoglobin, and deoxy-hemoglobin were continuously acquired with Laser Speckle and Optical Intrinsic Signal imaging for 2 h after photochemically induced distal middle cerebral artery occlusion in Sprague-Dawley rats (n = 10). Imaging was performed through a 6 × 6 mm window centered 3 mm posterior and 4 mm lateral to Bregma. Rats were sacrificed after 24 h, and the brain slices were stained for assessment of infarction. We mapped the infarcted area onto the imaging data and used nine circular regions of interest (ROI) to distinguish infarcted from non-infarcted tissue. Transients propagating through each ROI were characterized with six parameters (negative, positive, and total amplitude; negative and positive slope; duration). Transients were also classified into three morphology types (positive monophasic, biphasic, negative monophasic). Flow transient morphology, positive amplitude, positive slope, and total amplitude were all strongly associated with infarction (p < 0.001). Associations with infarction were also observed for oxy-hemoglobin morphology, oxy-hemoglobin positive amplitude and slope, and deoxy-hemoglobin positive slope and duration (all p < 0.01). These results suggest that flow and hemoglobin transients accompanying SD have value for detecting infarction.

Less-invasive subdural electrocorticography for investigation of spreading depolarizations in patients with subarachnoid hemorrhage

Introduction

Wyler-strip electrodes for subdural electrocorticography (ECoG) are the gold standard for continuous bed-side monitoring of pathological cortical network events, such as spreading depolarizations (SD) and electrographic seizures. Recently, SD associated parameters were shown to be (1) a marker of early brain damage after aneurysmal subarachnoid hemorrhage (aSAH), (2) the strongest real-time predictor of delayed cerebral ischemia currently known, and (3) the second strongest predictor of patient outcome at 7 months. The strongest predictor of patient outcome at 7 months was focal brain damage segmented on neuroimaging 2 weeks after the initial hemorrhage, whereas the initial focal brain damage was inferior to the SD variables as a predictor for patient outcome. However, the implantation of Wyler-strip electrodes typically requires either a craniotomy or an enlarged burr hole. Neuromonitoring via an enlarged burr hole has been performed in only about 10% of the total patients monitored.

Methods

In the present pilot study, we investigated the feasibility of ECoG monitoring via a less invasive burrhole approach using a Spencer-type electrode array, which was implanted subdurally rather than in the depth of the parenchyma. Seven aSAH patients requiring extraventricular drainage (EVD) were included. For electrode placement, the burr hole over which the EVD was simultaneously placed, was used in all cases. After electrode implantation, continuous, direct current (DC)/alternating current (AC)-ECoG monitoring was performed at bedside in our Neurointensive Care unit. ECoGs were analyzed following the recommendations of the Co-Operative Studies on Brain Injury Depolarizations (COSBID).

Results

Subdural Spencer-type electrode arrays permitted high-quality ECoG recording. During a cumulative monitoring period of 1,194.5 hours and a median monitoring period of 201.3 (interquartile range: 126.1-209.4) hours per patient, 84 SDs were identified. Numbers of SDs, isoelectric SDs and clustered SDs per recording day, and peak total SD-induced depression duration of a recording day were not significantly different from the previously reported results of the prospective, observational, multicenter, cohort, diagnostic phase III trial, DISCHARGE-1. No adverse events related to electrode implantation were noted.

Discussion

In conclusion, our findings support the safety and feasibility of less-invasive subdural electrode implantation for reliable SD-monitoring.

Multiscale Computer Modeling of Spreading Depolarization in Brain Slices

Spreading depolarization (SD) is a slow-moving wave of neuronal depolarization accompanied by a breakdown of ion concentration homeostasis, followed by long periods of neuronal silence (spreading depression), and is associated with several neurologic conditions. We developed multiscale (ions to tissue slice) computer models of SD in brain slices using the NEURON simulator: 36,000 neurons (two voltage-gated ion channels; three leak channels; three ion exchangers/pumps) in the extracellular space (ECS) of a slice (1 mm sides, varying thicknesses) with ion (K+, Cl-, Na+) and O2 diffusion and equilibration with a surrounding bath. Glia and neurons cleared K+ from the ECS via Na+/K+ pumps. SD propagated through the slices at realistic speeds of 2-4 mm/min, which increased by as much as 50% in models incorporating the effects of hypoxia or propionate. In both cases, the speedup was mediated principally by ECS shrinkage. Our model allows us to make testable predictions, including the following: (1) SD can be inhibited by enlarging ECS volume; (2) SD velocity will be greater in areas with greater neuronal density, total neuronal volume, or larger/more dendrites; (3) SD is all-or-none: initiating K+ bolus properties have little impact on SD speed; (4) Slice thickness influences SD because of relative hypoxia in the slice core, exacerbated by SD in a pathologic cycle; and (5) SD and high neuronal spike rates will be observed in the core of the slice. Cells in the periphery of the slice near an oxygenated bath will resist SD.

Ictal neural oscillatory alterations precede sudden unexpected death in epilepsy

Sudden unexpected death in epilepsy is the most catastrophic outcome of epilepsy. Each year there are as many as 1.65 cases of such death for every 1000 individuals with epilepsy. Currently, there are no methods to predict or prevent this tragic event, due in part to a poor understanding of the pathologic cascade that leads to death following seizures. We recently identified enhanced seizure-induced mortality in four inbred strains from the genetically diverse Collaborative Cross mouse population. These mouse models of sudden unexpected death in epilepsy provide a unique tool to systematically examine the physiological alterations during fatal seizures, which can be studied in a controlled environment and with consideration of genetic complexity. Here, we monitored the brain oscillations and heart functions before, during, and after non-fatal and fatal seizures using a flurothyl-induced seizure model in freely moving mice. Compared with mice that survived seizures, non-survivors exhibited significant suppression of brainstem neural oscillations that coincided with cortical epileptic activities and tachycardia during the ictal phase of a fatal seizure. Non-survivors also exhibited suppressed delta (0.5-4 Hz)/gamma (30-200 Hz) phase-amplitude coupling in cortex but not in brainstem. A connectivity analysis revealed elevated synchronization of cortex and brainstem oscillations in the delta band during fatal seizures compared with non-fatal seizures. The dynamic ictal oscillatory and connectivity features of fatal seizures provide insights into sudden unexpected death in epilepsy and may suggest biomarkers and eventual therapeutic targets.

Cortical Spreading Depolarizations in Aneurysmal Subarachnoid Hemorrhage: An Overview of Current Knowledge and Future Perspectives

Despite significant advances in the management of aneurysmal subarachnoid hemorrhage (SAH), morbidity and mortality remain devastating particularly for high-grade SAH. Poor functional outcome usually results from delayed cerebral ischemia (DCI). The pathogenesis of DCI during aneurysmal SAH has historically been attributed to cerebral vasospasm, but spreading depolarizations (SDs) are now considered to play a central role in DCI. During SAH, SDs may produce an inverse hemodynamic response leading to spreading ischemia. Several animal models have contributed to a better understanding of the pathogenesis of SDs during aneurysmal SAH and provided new therapeutic approaches including N-methyl-D-aspartate receptor antagonists and phosphodiesterase inhibitors. Herein we review the current knowledge in the field of SDs' pathogenesis and we detail the key experimental and clinical studies that have opened interesting new therapeutic approaches to prevent DCI in aneurysmal SAH.

Migraine Visual Aura and Cortical Spreading Depression-Linking Mathematical Models to Empirical Evidence

This review describes the subjective experience of visual aura in migraine, outlines theoretical models of this phenomenon, and explores how these may be linked to neurochemical, electrophysiological, and psychophysical differences in sensory processing that have been reported in migraine with aura. Reaction-diffusion models have been used to model the hallucinations thought to arise from cortical spreading depolarisation and depression in migraine aura. One aim of this review is to make the underlying principles of these models accessible to a general readership. Cortical spreading depolarisation and depression in these models depends on the balance of the diffusion rate between excitation and inhibition and the occurrence of a large spike in activity to initiate spontaneous pattern formation. We review experimental evidence, including recordings of brain activity made during the aura and attack phase, self-reported triggers of migraine, and psychophysical studies of visual processing in migraine with aura, and how these might relate to mechanisms of excitability that make some people susceptible to aura. Increased cortical excitability, increased neural noise, and fluctuations in oscillatory activity across the migraine cycle are all factors that are likely to contribute to the occurrence of migraine aura. There remain many outstanding questions relating to the current limitations of both models and experimental evidence. Nevertheless, reaction-diffusion models, by providing an integrative theoretical framework, support the generation of testable experimental hypotheses to guide future research.

Ketamine for empiric treatment of cortical spreading depolarization after subdural hematoma evacuation

BACKGROUND

It is widely known that some patients surgically treated for subdural hematoma (SDH) experience neurologic deficits not clearly explained by the acute brain injury or known sequelae like seizures. There is increasing evidence that cortical spreading depolarization (CSD) may be the cause. A recent article demonstrated that CSD occurred at a rate of 15 % and was associated with neurological deterioration in a subset of patients following chronic subdural hematoma evacuation. Furthermore, CSD can lead to ischemia leading to worsening neurologic deficits. CSD is usually detected on electrocorticography (ECoG) and needs cortical strip electrode placement with equipment and expertise that may not be readily available.

CASE DESCRIPTION

We report three cases of patients with subdural hematoma (SDH) not undergoing ECoG in whom CSD was suspected to be the cause of their neurologic deficits post evacuation. Extensive workup including neuroimaging and electroencephalography (EEG) were inconclusive. Patients were subsequently treated with ketamine infusion and had resultant neurological recovery.

CONCLUSIONS

Ketamine infusion can help reverse neurologic deficits in patients with SDH in whom the deficits are not explained by neuroimaging or electrographic seizure. CSD is a known phenomenon that can result in neurological injury and must remain in the differential diagnosis of such patients. Though only limited cases are discussed (n = 3), this small case series provides the basis for conducting clinical trials evaluating the efficacy of ketamine in improving functional outcome in brain-injured patients demonstrating evidence of CSD.

Is Spreading Depolarization a Risk Factor for Late Epilepsy? A Prospective Study in Patients with Traumatic Brain Injury and Malignant Ischemic Stroke Undergoing Decompressive Craniectomy

OBJECTIVE

Spreading depolarizations (SDs) have been described in patients with ischemic and haemorrhagic stroke, traumatic brain injury, and migraine with aura, among other conditions. The exact pathophysiological mechanism of SDs is not yet fully established. Our aim in this study was to evaluate the relationship between the electrocorticography (ECoG) findings of SDs and/or epileptiform activity and subsequent epilepsy and electroclinical outcome.

METHODS

This was a prospective observational study of 39 adults, 17 with malignant middle cerebral artery infarction (MMCAI) and 22 with traumatic brain injury, who underwent decompressive craniectomy and multimodal neuromonitoring including ECoG in penumbral tissue. Serial electroencephalography (EEG) recordings were obtained for all surviving patients. Functional disability at 6 and 12 months after injury were assessed using the Barthel, modified Rankin (mRS), and Extended Glasgow Outcome (GOS-E) scales.

RESULTS

SDs were recorded in 58.9% of patients, being more common-particularly those of isoelectric type-in patients with MMCAI (p < 0.04). At follow-up, 74.7% of patients had epileptiform abnormalities on EEG and/or seizures. A significant correlation was observed between the degree of preserved brain activity on EEG and disability severity (R [mRS]: + 0.7, R [GOS-E, Barthel]: - 0.6, p < 0.001), and between the presence of multifocal epileptiform abnormalities on EEG and more severe disability on the GOS-E at 6 months (R: - 0.3, p = 0.03) and 12 months (R: - 0.3, p = 0.05). Patients with more SDs and higher depression ratios scored worse on the GOS-E (R: - 0.4 at 6 and 12 months) and Barthel (R: - 0.4 at 6 and 12 months) disability scales (p < 0.05). The number of SDs (p = 0.064) and the depression ratio (p = 0.1) on ECoG did not show a statistically significant correlation with late epilepsy.

CONCLUSIONS

SDs are common in the cortex of ischemic or traumatic penumbra. Our study suggests an association between the presence of SDs in the acute phase and worse long-term outcome, although no association with subsequent epilepsy was found. More comprehensive studies, involving ECoG and EEG could help determine their association with epileptogenesis.

IRIS: A Modular Platform for Continuous Monitoring and Caretaker Notification in the Intensive Care Unit

OBJECTIVE

New approaches are needed to interpret large amounts of physiologic data continuously recorded in the ICU. We developed and prospectively validated a versatile platform (IRIS) for real-time ICU physiologic monitoring, clinical decision making, and caretaker notification.

METHODS

IRIS was implemented in the neurointensive care unit to stream multimodal time series data, including EEG, intracranial pressure (ICP), and brain tissue oxygenation (PbtO2), from ICU monitors to an analysis server. IRIS was applied for 364 patients undergoing continuous EEG, 26 patients undergoing burst suppression monitoring, and four patients undergoing intracranial pressure and brain tissue oxygen monitoring. Custom algorithms were used to identify periods of elevated ICP, compute burst suppression ratios (BSRs), and detect faulty or disconnected EEG electrodes. Hospital staff were notified of clinically relevant events using our secure API to route alerts through a password-protected smartphone application.

RESULTS

Sustained increases in ICP and concordant decreases in PbtO2 were reliably detected using user-defined thresholds and alert throttling. BSR trends computed by the platform correlated highly with manual neurologist markings (r2 0.633-0.781; p < 0.0001). The platform identified EEG electrodes with poor signal quality with 95% positive predictive value, and reduced latency of technician response by 93%.

CONCLUSION

This study validates a flexible real-time platform for monitoring and interpreting ICU data and notifying caretakers of actionable results, with potential to reduce the manual burden of continuous monitoring services on care providers.

SIGNIFICANCE

This work represents an important step toward facilitating translational medical data analytics to improve patient care and reduce health care costs.

[Scalp-recorded cortical spreading depolarizations (CSDs) of EEG with time constant of 2 seconds in a patient with acute traumatic brain injury]

An 82-year-old female suffered from head trauma, and developed acute consciousness disturbance 6 days after the event. Head CT showed the acute subdural hematoma in the left temporooccipital area and the patient underwent emergency hematoma evacuation and decompression. However, her consciousness disturbance became worse after surgery. Intermittent large negative infraslow shifts (lasting longer than 40 seconds) were recorded in the right posterior quadrant by scalp EEG with TC of 2 sec, that was defined as cortical spreading depolarizations (CSDs). Clinically consciousness disturbance sustained poor until 1 month after surgery in spite of treatment by anti-epileptic drugs. CSDs were observed on the right side where head injury most likely occurred. It may explain the sustained consciousness disturbance associated with significant prolonged ischemia. Once scalp EEG could record CSDs in this particular patient, the degree and its prognosis of traumatic head injury were estimated.

A Machine Learning Enabled Wireless Intracranial Brain Deformation Sensing System

A leading cause of traumatic brain injury (TBI) is intracranial brain deformation due to mechanical impact. This deformation is viscoelastic and differs from a traditional rigid transformation. In this paper, we describe a machine learning enabled wireless sensing system that predicts the trajectory of intracranial brain deformation. The sensing system consists of an implantable soft magnet and an external magnetic sensor array with a sensing volume of 12 × 12 × 4 mm³. Machine learning algorithm predicts the brain deformation by interpreting the magnetic sensor outputs created by the change in position of the implanted soft magnet. Three different machine learning models were trained on calibration data: (1) random forests, (2) k-nearest neighbors, and (3) a multi-layer perceptron-based neural network. These models were validated using both in vitro (a needle inserted into PVC gel) and in vivo (blast exposure to live and dead rat brains) experiments. The in vitro gel deformation predicted by these machine learning models showed excellent agreement with the camera measurements and had absolute error = 138 μm, Fréchet distance = 372 μm with normalized Procrustes disparity = 0.034. The in vivo brain deformation predicted by these models had absolute error = 50 μm, Fréchet distance = 95 μm with normalized Procrustes disparity = 0.055 for dead animal and absolute error = 125 μm, Fréchet distance = 289 μm with normalized Procrustes disparity = 0.2 for live animal respectively. These results suggest that the proposed machine learning enabled sensor system can be an effective tool for measuring in situ brain deformation.

Self-health monitoring and wearable neurotechnologies

Brain-computer interfaces and wearable neurotechnologies are now used to measure real-time neural and physiologic signals from the human body and hold immense potential for advancements in medical diagnostics, prevention, and intervention. Given the future role that wearable neurotechnologies will likely serve in the health sector, a critical state-of-the-art assessment is necessary to gain a better understanding of their current strengths and limitations. In this chapter we present wearable electroencephalography systems that reflect groundbreaking innovations and improvements in real-time data collection and health monitoring. We focus on specifications reflecting technical advantages and disadvantages, discuss their use in fundamental and clinical research, their current applications, limitations, and future directions. While many methodological and ethical challenges remain, these systems host the potential to facilitate large-scale data collection far beyond the reach of traditional research laboratory settings.

Severely Disturbed Sleep in Patients With Acute Ischemic Stroke on Stroke Units: A Pilot Study

Introduction: Previous studies revealed a high prevalence of sleep-wake disturbances in subacute and chronic stroke. We analyzed sleep quantity and quality in patients with hyperacute ischemic stroke on stroke units.

Methods: We categorized sleep stages as N1, N2, N3, and REM according to the 2017 criteria of the American Academy of Sleep Medicine in 23 continuous, overnight EEG registrations from 18 patients, starting within 48 h since the onset of cortical ischemic stroke. Associations between presence and duration of sleep stages, and secondary deterioration or functional outcome were analyzed.

Results: Physiological sleep cycles were seen in none of the patients. Otherwise, sleep stages alternated chaotically, both during day- and during nighttime, with a sleep efficiency of 30% and 10.5 ± 4.4 (mean ± SD) awakenings per hour of sleep. We cannot differentiate between stroke related and external factors. Only few interruptions could be related to planned nightly wake up calls, but turbulence on stroke units may have played a role. Six patients (seven nights) did not reach deep sleep (N3), 10 patients (13 nights) did not reach REM sleep. If reached, the mean durations of deep and REM sleep were short, with 37 (standard deviation (SD) 25) and 18 (SD15) minutes, respectively. Patients with secondary deterioration more often lacked deep sleep (N3) than patients without secondary deterioration [4 (57%) vs. 2 (25%)], but without statistical significance (p = 0.12).

Conclusion: We show that sleep is severely disturbed in patients with acute ischemic stroke admitted to stroke units. Larger studies are needed to clarify associations between deprivation of deep sleep and secondary deterioration.

Current understanding of cortical structure and function in migraine

OBJECTIVE

To review and discuss the literature on the role of cortical structure and function in migraine.

DISCUSSION

Structural and functional findings suggest that changes in cortical morphology and function contribute to migraine susceptibility by modulating dynamic interactions across cortical and subcortical networks. The involvement of the cortex in migraine is well established for the aura phase with the underlying phenomenon of cortical spreading depolarization, while increasing evidence suggests an important role for the cortex in perception of head pain and associated sensations. As part of trigeminovascular pain and sensory processing networks, cortical dysfunction is likely to also affect initiation of attacks.

CONCLUSION

Morphological and functional changes identified across cortical regions are likely to contribute to initiation, cyclic recurrence and chronification of migraine. Future studies are needed to address underlying mechanisms, including interactions between cortical and subcortical regions and effects of internal (e.g. genetics, gender) and external (e.g. sensory inputs, stress) modifying factors, as well as possible clinical and therapeutic implications.

Correlates of Spreading Depolarization, Spreading Depression, and Negative Ultraslow Potential in Epidural Versus Subdural Electrocorticography

Spreading depolarizations (SDs) are characterized by near-complete breakdown of the transmembrane ion gradients, neuronal oedema and activity loss (=depression). The SD extreme in ischemic tissue, termed ‘terminal SD,’ shows prolonged depolarization, in addition to a slow baseline variation called ‘negative ultraslow potential’ (NUP). The NUP is the largest bioelectrical signal ever recorded from the human brain and is thought to reflect the progressive recruitment of neurons into death in the wake of SD. However, it is unclear whether the NUP is a field potential or results from contaminating sensitivities of platinum electrodes. In contrast to Ag/AgCl-based electrodes in animals, platinum/iridium electrodes are the gold standard for intracranial direct current (DC) recordings in humans. Here, we investigated the full continuum including short-lasting SDs under normoxia, long-lasting SDs under systemic hypoxia, and terminal SD under severe global ischemia using platinum/iridium electrodes in rats to better understand their recording characteristics. Sensitivities for detecting SDs or NUPs were 100% for both electrode types. Nonetheless, the platinum/iridium-recorded NUP was 10 times smaller in rats than humans. The SD continuum was then further investigated by comparing subdural platinum/iridium and epidural titanium peg electrodes in patients. In seven patients with either aneurysmal subarachnoid hemorrhage or malignant hemispheric stroke, two epidural peg electrodes were placed 10 mm from a subdural strip. We found that 31/67 SDs (46%) on the subdural strip were also detected epidurally. SDs that had longer negative DC shifts and spread more widely across the subdural strip were more likely to be observed in epidural recordings. One patient displayed an SD-initiated NUP while undergoing brain death despite continued circulatory function. The NUP’s amplitude was -150 mV subdurally and -67 mV epidurally. This suggests that the human NUP is a bioelectrical field potential rather than an artifact of electrode sensitivity to other factors, since the dura separates the epidural from the subdural compartment and the epidural microenvironment was unlikely changed, given that ventilation, arterial pressure and peripheral oxygen saturation remained constant during the NUP. Our data provide further evidence for the clinical value of invasive electrocorticographic monitoring, highlighting important possibilities as well as limitations of less invasive recording techniques.

An Algorithm for Automated, Noninvasive Detection of Cortical Spreading Depolarizations Based on EEG Simulations

OBJECTIVE

We present a novel signal processing algorithm for automated, noninvasive detection of cortical spreading depolarizations (CSDs) using electroencephalography (EEG) signals and validate the algorithm on simulated EEG signals. CSDs are waves of neurochemical changes that suppress the neuronal activity as they propagate across the brain's cortical surface. CSDs are believed to mediate secondary brain damage after brain trauma and cerebrovascular diseases like stroke. We address the following two key challenges in detecting CSDs from EEG signals: i) attenuation and loss of high spatial resolution information; and ii) cortical folds, which complicate tracking CSD waves.

METHODS

Our algorithm detects and tracks "wavefronts" of a CSD wave, and stitch together data across space and time to make a detection. To test our algorithm, we provide different models of CSD waves, including different widths of CSD suppressions and different patterns, and use them to simulate scalp EEG signals using head models of four subjects.

RESULTS AND CONCLUSION

Our results suggest that low-density EEG grids (40 electrodes) can detect CSD widths of 1.1 cm on average, while higher density EEG grids (340 electrodes) can detect CSD patterns as thin as 0.43 cm (less than minimum widths reported in prior works), among which single-gyrus CSDs are the hardest to detect because of their small suppression area.

SIGNIFICANCE

The proposed algorithm is a first step toward noninvasive, automated detection of CSDs, which can help in reducing secondary brain damages.

An update on EEG in migraine

Introduction: In the past few years, brain functional analysis has provided scientific evidence supporting the neuronal basis of migraine. The role of electroencephalography (EEG) in detecting subtle dysfunctions in sensory temporal processing has been fully re-evaluated, thanks to advances in methods of quantitative analysis. However, the diagnostic value of EEG in migraine is very low, and migraine diagnosis is completely based on clinical criteria, while the utility of EEG in migraine pathophysiology has only been confirmed in more recent applications. Areas covered: The present review focuses on the few situations in which EEG may provide diagnostic utility, and on the numerous and intriguing applications of novel analysis, based on time-related changes in neuronal network oscillations and functional connectivity. Expert opinion: Although routine EEG is not particularly useful for the clinical assessment of migraine, novel methods of analysis, mostly based on functional connectivity, could improve knowledge of the migraine brain. The application is worthy of promotion and improvement in support of neuroimaging data to shed light on migraine mechanisms and support the rationale for therapeutic approaches.

High-resolution mapping of infraslow cortical brain activity enabled by graphene microtransistors

Recording infraslow brain signals (<0.1 Hz) with microelectrodes is severely hampered by current microelectrode materials, primarily due to limitations resulting from voltage drift and high electrode impedance. Hence, most recording systems include high-pass filters that solve saturation issues but come hand in hand with loss of physiological and pathological information. In this work, we use flexible epicortical and intracortical arrays of graphene solution-gated field-effect transistors (gSGFETs) to map cortical spreading depression in rats and demonstrate that gSGFETs are able to record, with high fidelity, infraslow signals together with signals in the typical local field potential bandwidth. The wide recording bandwidth results from the direct field-effect coupling of the active transistor, in contrast to standard passive electrodes, as well as from the electrochemical inertness of graphene. Taking advantage of such functionality, we envision broad applications of gSGFET technology for monitoring infraslow brain activity both in research and in the clinic.

Cortical Spreading Depolarization (CSD) Recorded from Intact Skin, from Surface of Dura Mater or Cortex: Comparison with Intracortical Recordings in the Neocortex of Adult Rats

In cerebral cortex of anesthetized rats single waves of spreading depolarization (CSD) were elicited by needle prick. CSD-related changes of DC (direct current) potentials were either recorded from the intact skin or together with concomitant changes of potassium concentration with K⁺-selective microelectrodes simultaneously at the surface of the dura mater or of the cortex ([K⁺]_s) and in the extracellular space at a cortical depth of 1200 µm. At the intact skin CSD-related DC-shifts had amplitudes of less than 1 mV and had only in a minority of cases the typical CSD-like shape. In the majority these DC-shifts rose and recovered very slowly and were difficult to identify without further indicators. At dura surface CSD-related DC shifts were significantly smaller and rose and recovered slower than intracortically recorded CSD. Concomitant increases in [K⁺]_s were delayed and reached maximal values of about 5 mM from a baseline of 3 mM. They rose and recovered slower than simultaneously recorded intracortical changes in extracellular potassium concentration ([K⁺]_e) that were up to 65 mM. The results suggest that extracellular potassium during CSD is diffusing through the subarachnoid space and across the dura mater. In a few cases CSD was either absent at the dura or at a depth of 1200 µm. Even full blown CSDs in this cortical depth could remain without concomitant deflections at the dura. Our data confirmed in principle the possibility of non-invasive recordings of CSD-related DC-shifts. For a use in clinical routine sensitivity and specificity will have to be improved.

Design and Methodology of a Pilot Randomized Controlled Trial of Transcranial Direct Current Stimulation in Acute Middle Cerebral Artery Stroke (STICA)

Background: Stroke is a major cause of death and disability worldwide. The related burden is expected to further increase due to aging populations, calling for more efficient treatment. Ischemic stroke results from a focal reduction in cerebral blood flow due to the sudden occlusion of a brain artery. Ischemic brain injury results from a sequence of pathophysiological events that evolve over time and space. This cascade includes excitotoxicity and peri-infarct depolarizations (PIDs). Focal impairment of cerebral blood flow restricts the delivery of energetics substrates and impairs ionic gradients. Membrane potential is eventually lost, and neurons depolarize. Although recanalization therapies target the ischemic penumbra, they can only rescue the penumbra still present at the time of reperfusion. A promising novel approach is to "freeze" the penumbra until reperfusion occurs. Transcranial direct current stimulation (tDCS) is a non-invasive method of neuromodulation. Based on preclinical evidence, we propose to test the penumbra freezing concept in a clinical phase IIa trial assessing whether cathodal tDCS-shown in rodents to reduce infarction volume-prevents early infarct growth in human acute Middle Cerebral Artery (MCA) stroke, in adjunction to conventional revascularization methods. Methods: This is a monocentric randomized, double-blind, and placebo-controlled trial performed in patients with acute MCA stroke eligible to revascularization procedures. Primary outcome is infarct volume growth on diffusion weighted imaging (DWI) at day 1 relative to baseline. Secondary outcomes include safety and clinical efficacy. Significance: Results from this clinical trial are expected to provide rationale for a phase III study. Clinical trial registration-EUDRACT: 2016-A00160-51.