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AIM: Opioids might be harmful to the developing brain and dosing accuracy is important. We aimed at investigating fentanyl effects on cortical activity in infants using computational re-analysis of bedside recorded EEG signals. METHODS: Fifteen infants born at median 26.4 gestational weeks (range 23.3-34.1), with a birth weight 740 grams (530-1420) and postnatal age 7 days (5-11) received fentanyl 0.5 or 2 µg/kg intravenously before a skin-breaking procedure or tracheal intubation, respectively. Cortical activity was continuously recorded using amplitude-integrated electroencephalography (aEEG).  Analyses using three computational EEG features representing cortical synchrony and signal power, were conducted five minutes pre- and 10 minutes post the drug administration. RESULTS: Visual assessment of trends displayed from the EEG metrics did not indicate systematic changes. However, the magnitude of the changes in the parietal and right hemisphere signals after the dose was significantly correlated (ρ < -0.5, p < 0.05) to the EEG amplitude and frequency power level before drug administration. This effect started after 3-4 min. CONCLUSION: Fentanyl, even in small doses, may affect cortical activity in the preterm brain. The effect is robustly related to the state of cortical activity prior to drug treatment, which must be taken into account when analysing the effects of sedative drugs.

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Wearable in-ear electroencephalographic (EEG) devices hold significant promise for advancing brain monitoring technologies into everyday applications. However, despite the current availability of several in-ear EEG devices in the market, there remains a critical need for robust validation against established clinical-grade systems. In this study, we carried out a detailed examination of the signal performance of a mobile in-ear EEG device from Naox Technologies. Our investigation had two main goals: firstly, evaluating the hardware circuit's reliability through simulated EEG signal experiments and, secondly, conducting a thorough comparison between the in-ear EEG device and gold-standard EEG monitoring equipment. This comparison assesses correlation coefficients with recognized physiological patterns during wakefulness and sleep, including alpha rhythms, eye artifacts, slow waves, spindles, and sleep stages. Our findings support the feasibility of using this in-ear EEG device for brain activity monitoring, particularly in scenarios requiring enhanced comfort and user-friendliness in various clinical and research settings.

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OBJECTIVE: To evaluate the utility of a fully automated deep learning -based quantitative measure of EEG background, Brain State of the Newborn (BSN), for early prediction of clinical outcome at four years of age. METHODS: The EEG monitoring data from eighty consecutive newborns was analyzed using the automatically computed BSN trend. BSN levels during the first days of life (a of total 5427 hours) were compared to four clinical outcome categories: favorable, cerebral palsy (CP), CP with epilepsy, and death. The time dependent changes in BSN-based prediction for different outcomes were assessed by positive/negative predictive value (PPV/NPV) and by estimating the area under the receiver operating characteristic curve (AUC). RESULTS: The BSN values were closely aligned with four visually determined EEG categories (p < 0·001), as well as with respect to clinical milestones of EEG recovery in perinatal Hypoxic Ischemic Encephalopathy (HIE; p < 0·003). Favorable outcome was related to a rapid recovery of the BSN trend, while worse outcomes related to a slow BSN recovery. Outcome predictions with BSN were accurate from 6 to 48 hours of age: For the favorable outcome, the AUC ranged from 95 to 99% (peak at 12 hours), and for the poor outcome the AUC ranged from 96 to 99% (peak at 12 hours). The optimal BSN levels for each PPV/NPV estimate changed substantially during the first 48 hours, ranging from 20 to 80. CONCLUSIONS: We show that the BSN provides an automated, objective, and continuous measure of brain activity in newborns. SIGNIFICANCE: The BSN trend discloses the dynamic nature that exists in both cerebral recovery and outcome prediction, supports individualized patient care, rapid stratification and early prognosis.

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Alzheimer's disease (AD) has a detrimental impact on brain function, affecting various aspects such as cognition, memory, language, and motor skills. Previous research has dominantly used electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to individually measure brain signals or combine the two methods to target specific brain functions. However, comprehending Alzheimer's disease requires monitoring various brain functions rather than focusing on a single function. This paper presents a comprehensive research setup for a monitoring platform for AD. The platform incorporates a 32-channel dry electrode EEG, a custom-built four-channel fNIRS, and gait monitoring using a depth camera and pressure sensor. Various tasks are employed to target multiple brain functions. The paper introduced the detailed instrumentation of the fNIRS system, which measures the prefrontal cortex, outlines the experimental design targeting various brain functioning programmed in BCI2000 for visualizing EEG signals synchronized with experimental stimulation, and describes the gait monitoring hardware and software and protocol design. The ultimate goal of this platform is to develop an easy-to-perform brain and gait monitoring method for elderly individuals and patients with Alzheimer's disease. Supplementary Information: The online version contains supplementary material available at 10.1007/s13534-023-00306-7.

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BACKGROUND: Ultrafast cerebral Doppler ultrasound enables simultaneous quantification and visualization of cerebral blood flow velocity. The aim of this study is to compare the use of conventional and ultrafast spectral Doppler during anesthesia and their potential to show the effect of anesthesiologic procedures on cerebral blood flow velocities, in relation to blood pressure and cerebral oxygenation in infants undergoing inguinal hernia repair. METHODS: A single-center prospective observational cohort study in infants up to six months of age. We evaluated conventional and ultrafast spectral Doppler cerebral ultrasound measurements in terms of number of successful measurements during the induction of anesthesia, after sevoflurane induction, administration of caudal analgesia, a fluid bolus and emergence of anesthesia. Cerebral blood flow velocity was quantified in pial arteries using conventional spectral Doppler and in the cerebral cortex using ultrafast Doppler by peak systolic velocity, end diastolic velocity and resistivity index. RESULTS: Twenty infants were included with useable conventional spectral Doppler images in 72/100 measurements and ultrafast Doppler images in 51/100 measurements. Intraoperatively, the success rates were 53/60 (88.3%) and 41/60 (68.3%), respectively. Cerebral blood flow velocity increased after emergence for both conventional (end diastolic velocity, from 2.01 to 2.75 cm/s, p < 0.001) and ultrafast spectral Doppler (end diastolic velocity, from 0.59 to 0.94 cm/s), whereas cerebral oxygenation showed a reverse pattern with a decrease after the emergence of the infant (85% to 68%, p < 0.001). CONCLUSION: It is possible to quantify cortical blood flow velocity during general anesthesia using conventional and ultrafast spectral Doppler cerebral ultrasound. Cerebral blood flow velocity and blood pressure decreased, while regional cerebral oxygenation increased during general anesthesia. Ultrafast spectral Doppler ultrasound offers novel insights into perfusion within the cerebral cortex, unattainable through conventional spectral ultrasound. Yet, ultrafast Doppler is curtailed by a lower success rate and a more rigorous learning curve compared to conventional method.

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OBJECTIVES: To compare seizure burden between newborn infants treated with therapeutic hypothermia (TH) and those that were not and to compare the need for antiseizure medications (ASM) in a cohort of infants who were diagnosed with neonatal hypoxic-ischemic encephalopathy (HIE). METHODS: This was a retrospective cohort study on infants born after 35 weeks' gestation, diagnosed with moderate to severe HIE, monitored with amplitude-integrated electroencephalography (aEEG) and eligible for TH. Infants born before the implementation of TH in 2008 were compared with infants born thereafter who received TH. Seizure burden was assessed from aEEG as total time in minutes of seizures activity per hour of recording. Other clinical and demographic data were retrieved from a prospective local database of infants with HIE. RESULTS: Overall, 149 of 207 infants were included in the study: 112 exposed to TH and 37 not exposed. Cooled infants had a lower seizure burden overall (0.4 vs 2.3 min/h, P < 0.001) and were also less likely to be treated with ASM (74% vs 100%, P < 0.001). In multivariable regression models, not exposed to TH, having a depressed aEEG background, and having higher Apgar scores were associated with higher seizure burden (incidence rate ratio: 4.78 for noncooled infants, P < 0.001); also, not exposed to TH was associated with a higher likelihood of multidrug ASM (odds ratio: 4.83, P < 0.001). CONCLUSIONS: TH in infants with moderate to severe HIE is associated with significant reduction of seizure burden and ASM therapy.

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Objective: This research aims to evaluate the possible association between pulsatile near infrared spectroscopic waveform features and induced changes in intracranial pressure in healthy volunteers. Methods: An optical intracranial pressure sensor was attached to the forehead of 16 healthy volunteers. Pulsatile near infrared spectroscopic signals were acquired from the forehead during body position changes and Valsalva manoeuvers. Features were extracted from the pulsatile signals and analyses were carried out to investigate the presence of statistical differences in the features when intracranial pressure changes were induced. Classification models were developed utilizing the features extracted from the pulsatile near-infrared spectroscopic signals to classify between different body positions and Valsalva manoeuvre. Results: The presence of significant differences in the majority of the analyzed features (p < 0.05) indicates the technique's ability to distinguish between variations in intracranial pressure. Furthermore, the disparities observed in the optical signal features captured by the proximal and distal photodetectors support the hypothesis that alterations in back-scattered light directly correspond to brain-related changes. Further research is required to subtract distal and proximal signals and construct predictive models employing a gold standard measurement for non-invasive, continuous monitoring of intracranial pressure. Conclusion: The study investigated the use of pulsatile near infrared spectroscopic signals to detect changes in intracranial pressure in healthy volunteers. The results revealed significant differences in the features extracted from these signals, demonstrating a correlation with ICP changes induced by positional changes and Valsalva manoeuvre. Classification models were capable of identifying changes in ICP using features from optical signals from the brain, with a sensitivity ranging from 63.07% to 80% and specificity ranging from 60.23% to 70% respectively. These findings underscored the potential of these features to effectively identify alterations in ICP. Significance: The study's results demonstrate the feasibility of using features extracted from optical signals from the brain to detect changes in ICP induced by positional changes and Valsalva manoeuvre in healthy volunteers. This represents a first step towards the non-invasive monitoring of intracranial pressure.

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Resumen: Los monitores de profundidad anestésica permiten guiar el estado hipnótico del paciente durante la anestesia general. Debido a su sencillez, tradicionalmente se han empleado índices de profundidad anestésica, obtenidos a través del procesamiento del electroencefalograma mediante algoritmos matemáticos, para orientar la monitorización del nivel de consciencia. Sus beneficios han sido ampliamente recogidos en la literatura científica; sin embargo, no están exentos de importantes limitaciones. No todos los anestésicos actúan en las mismas dianas moleculares ni dichos índices tienen en cuenta las características propias del paciente (comorbilidades, edades extremas, etcétera). Estas limitaciones podrían reducirse si interpretamos directamente toda la información que nos ofrecen los monitores. Presentamos una revisión que describe los conceptos básicos necesarios para su valoración directa, así como su correlación con los estados de profundidad anestésica del paciente.

Abstract: Anesthesia depth monitors allow to guide the patient's hypnotic state during general anesthesia. Traditionally, anesthetic depth indices have been used due to their simplicity to guide the monitoring of the level of consciousness. They have been obtained by processing the electroencephalogram using mathematical algorithms and their benefits have been widely reported in the scientific literature. However, they are not exempt from important limitations. Neither all anesthetics act on the same molecular targets, nor these mentioned indices take into account the patient's own characteristics (comorbidities, extreme ages, etc.). These limitations could be far reduced if we are able to understand all the information provided by the monitors. We present a review describing the basic concepts necessary for its direct assessment, as well as their correlation with the patient's anesthetic depth states.

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Severe physical injuries and associated traumatic brain injury and/or hemorrhagic shock (HS) remain leading causes of death worldwide, aggravated by accompanying extensive inflammation. Retrospective clinical data indicated an association between mild hyperoxemia and improved survival and outcome. However, corresponding prospective clinical data, including long-term resuscutation, are scarce. Therefore, the present study explored the effect of mild hyperoxemia for 24 hours in a prospective randomized controlled trial in a long-term resuscitated model of combined acute subdural hematoma (ASDH) and HS. ASDH was induced by injecting 0.1 ml × kg-1 autologous blood into the subdural space and HS was triggered by passive removal of blood. After 2 hours, the animals received full resuscitation, including retransfusion of the shed blood and vasopressor support. During the first 24 hours, the animals underwent targeted hyperoxemia (PaO2 = 200 - 250 mmHg) or normoxemia (PaO2 = 80 - 120 mmHg) with a total observation period of 55 hours after the initiation of ASDH and HS. Survival, cardiocirculatory stability, and demand for vasopressor support were comparable between both groups. Likewise, humoral markers of brain injury and systemic inflammation were similar. Multimodal brain monitoring, including microdialysis and partial pressure of O2 in brain tissue, did not show significant differences either, despite a significantly better outcome regarding the modified Glasgow Coma Scale 24 hours after shock that favors hyperoxemia. In summary, the present study reports no deleterious and few beneficial effects of mild targeted hyperoxemia in a clinically relevant model of ASDH and HS with long-term resuscitation in otherwise healthy pigs. Further beneficial effects on neurological function were probably missed due to the high mortality in both experimental groups. The present study remains exploratory due to the unavailability of an a priori power calculation resulting from the lack of necessary data.

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Significance: Dementia presents a global healthcare crisis, and neuroimaging is the main method for developing effective diagnoses and treatments. Yet currently, there is a lack of sensitive, portable, and low-cost neuroimaging tools. As dementia is associated with vascular and metabolic dysfunction, near-infrared spectroscopy (NIRS) has the potential to fill this gap. Aim: This future perspective aims to briefly review the use of NIRS in dementia to date and identify the challenges involved in realizing the full impact of NIRS for dementia research, including device development, study design, and data analysis approaches. Approach: We briefly appraised the current literature to assess the challenges, giving a critical analysis of the methods used. To assess the sensitivity of different NIRS device configurations to the brain with atrophy (as is common in most forms of dementia), we performed an optical modeling analysis to compare their cortical sensitivity. Results: The first NIRS dementia study was published in 1996, and the number of studies has increased over time. In general, these studies identified diminished hemodynamic responses in the frontal lobe and altered functional connectivity in dementia. Our analysis showed that traditional (low-density) NIRS arrays are sensitive to the brain with atrophy (although we see a mean decrease of 22% in the relative brain sensitivity with respect to the healthy brain), but there is a significant improvement (a factor of 50 sensitivity increase) with high-density arrays. Conclusions: NIRS has a bright future in dementia research. Advances in technology - high-density devices and intelligent data analysis-will allow new, naturalistic task designs that may have more clinical relevance and increased reproducibility for longitudinal studies. The portable and low-cost nature of NIRS provides the potential for use in clinical and screening tests.

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There is no single electroencephalographic metric for general anaesthesia that is validated for both children and adults. This is, in part, because of the changing electroencephalographic features associated with development. Here, we discuss how alterations in correlated brain activity during general anaesthesia advance our understanding of anaesthetic monitoring and the neurobiology of consciousness.

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ABSTRACT Objective: To evaluate the association between different intensive care units and levels of brain monitoring with outcomes in acute brain injury. Methods: Patients with traumatic brain injury and subarachnoid hemorrhage admitted to intensive care units were included. Neurocritical care unit management was compared to general intensive care unit management. Patients managed with multimodal brain monitoring and optimal cerebral perfusion pressure were compared with general management patients. A good outcome was defined as a Glasgow outcome scale score of 4 or 5. Results: Among 389 patients, 237 were admitted to the neurocritical care unit, and 152 were admitted to the general intensive care unit. Neurocritical care unit management patients had a lower risk of poor outcome (OR = 0.228). A subgroup of 69 patients with multimodal brain monitoring (G1) was compared with the remaining patients (G2). In the G1 and G2 groups, 59% versus 23% of patients, respectively, had a good outcome at intensive care unit discharge; 64% versus 31% had a good outcome at 28 days; 76% versus 50% had a good outcome at 3 months (p < 0.001); and 77% versus 58% had a good outcome at 6 months (p = 0.005). When outcomes were adjusted by SAPS II severity score, using good outcome as the dependent variable, the results were as follows: for G1 compared to G2, the OR was 4.607 at intensive care unit discharge (p < 0.001), 4.22 at 28 days (p = 0.001), 3.250 at 3 months (p = 0.001) and 2.529 at 6 months (p = 0.006). Patients with optimal cerebral perfusion pressure management (n = 127) had a better outcome at all points of evaluation. Mortality for those patients was significantly lower at 28 days (p = 0.001), 3 months (p < 0.001) and 6 months (p = 0.001). Conclusion: Multimodal brain monitoring with autoregulation and neurocritical care unit management were associated with better outcomes and should be considered after severe acute brain injury.

RESUMO Objetivo: Avaliar a associação entre diferentes tipos de unidades de cuidados intensivos e os níveis de monitorização cerebral com desfechos na lesão cerebral aguda. Métodos: Foram incluídos doentes com traumatismo craniencefálico e hemorragia subaracnoide internados em unidades de cuidados intensivos. A abordagem na unidade de cuidados neurocríticos foi comparada à abordagem na unidade de cuidados intensivos polivalente geral. Os doentes com monitorização cerebral multimodal e pressão de perfusão cerebral ótima foram comparados aos que passaram por tratamento geral. Um bom desfecho foi definido como pontuação de 4 ou 5 na Glasgow outcome scale. Resultados: Dos 389 doentes, 237 foram admitidos na unidade de cuidados neurocríticos e 152 na unidade de cuidados intensivos geral. Doentes com abordagem em unidades de cuidados neurocríticos apresentaram menor risco de um mau desfecho (Odds ratio = 0,228). Um subgrupo de 69 doentes com monitorização cerebral multimodal (G1) foi comparado aos demais doentes (G2). Em G1 e G2, respectivamente, 59% e 23% dos doentes apresentaram bom desfecho na alta da unidade de cuidados intensivos; 64% e 31% apresentaram bom desfecho aos 28 dias; 76% e 50% apresentaram bom desfecho aos 3 meses (p < 0,001); e 77% e 58% apresentaram bom desfecho aos 6 meses (p = 0,005). Quando os desfechos foram ajustados para o escore de gravidade do SAPS II, usando o bom desfecho como variável dependente, os resultados foram os seguintes: para o G1, em comparação ao G2, a odds ratio foi de 4,607 na alta da unidade de cuidados intensivos (p < 0,001), 4,22 aos 28 dias (p = 0,001), 3,250 aos 3 meses (p = 0,001) e 2,529 aos 6 meses (p = 0,006). Os doentes com abordagem da pressão de perfusão cerebral ótima (n = 127) apresentaram melhor desfecho em todos os momentos de avaliação. A mortalidade desses doentes foi significativamente menor aos 28 dias (p = 0,001), aos 3 meses (p < 0,001) e aos 6 meses (p = 0,001). Conclusão: A monitorização cerebral multimodal com autorregulação e abordagem na unidade de cuidados neurocríticos foi associado a melhores desfechos e deve ser levado em consideração após lesão cerebral aguda grave.

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Abstract Objective: Amplitude-integrated electroencephalography (aEEG) is a simplified bedside neurophysiology tool that has been implemented in the neonatal intensive care unit and studied in an extensive range of clinical applications in the past decade. This critical review aimed to evaluate a variety of clinical applications of aEEG monitoring in diagnosis, clinical management, and prognosis assessment in critically ill neonates. Sources: The databases of Pubmed, SciELO, Lilacs, and Cochrane, books, and other online resources were consulted, as well as sources of professional experiences. Summary of findings: The clinical use of aEEG to access real-time brain function, background activity, and utility in seizures detection has been described. A critical review was realized considering the authors' professional experience. Newborns with hypoxic-ischemic encephalopathy and seizures screening represent the most common studied population. However, several studies have shown interesting applications on preterm infants, newborns with congenital heart disease, and other clinical situations of high risk of injury to the developing brain. Conclusion: The aEEG has shown to be a useful non-invasive bedside monitor that aids in evaluating brain function, background activity, and cyclicity. aEEG findings have also demonstrated good prognostic value in a group of critically ill neonates. The aEEG seizure diagnosis capability has limitations, which have been already well established. The use of neonatal brain monitoring such as aEEG was shown to give valuable information in several high-risk clinical situations.

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OBJECTIVE: This study evaluated the accuracy of neonatal amplitude-integrated electroencephalography (aEEG) brain monitoring for predicting development of postneonatal epilepsy after perinatal hypoxic ischemic encephalopathy (HIE). METHODS: We studied a population-based cohort of 85 consecutive neonates with moderate-to-severe HIE that had aEEG started <12 hours postnatally. We marked electrographic seizures and graded each hour of the aEEG background as inactive, burst-suppression, or continuous without or with sleep cycling. These aEEG parameters were compared to outcome at 4-years age (deceased, epilepsy, cerebral palsy without epilepsy, favorable), which was available for 80 children. RESULTS: At group level, total seizure burden (p = 0.003), maximum hourly seizure burden (p = 0.007), and aEEG background recovery (p < 0.001) were all significantly associated with outcome. At individual level six children developed epilepsy, and the most accurate predictors for later epilepsy were inactive aEEG at 24 hours (accuracy 97%, positive predictive value 100%, two false negatives) and inactive aEEG at the onset of seizures (accuracy 97%, sensitivity of 100%, one false positive). CONCLUSIONS: At individual level aEEG background recovery was a better predictor for later epilepsy than neonatal seizures, although both were associated with epilepsy at group level. SIGNIFICANCE: Poor aEEG background recovery predicts development of epilepsy after perinatal HIE at individual level.

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OBJECTIVE: To develop and validate an automated method for bedside monitoring of sleep state fluctuations in neonatal intensive care units. METHODS: A deep learning-based algorithm was designed and trained using 53 EEG recordings from a long-term (a)EEG monitoring in 30 near-term neonates. The results were validated using an independent dataset from 30 polysomnography recordings. In addition, we constructed Sleep State Trend (SST), a bedside-ready means for visualizing classifier outputs. RESULTS: The accuracy of quiet sleep detection in the training data was 90%, and the accuracy was comparable (85-86 %) in all bipolar derivations available from the 4-electrode recordings. The algorithm generalized well to a polysomnography dataset, showing 81% overall accuracy despite different signal derivations. SST allowed an intuitive, clear visualization of the classifier output. CONCLUSIONS: Fluctuations in sleep states can be detected at high fidelity from a single EEG channel, and the results can be visualized as a transparent and intuitive trend in the bedside monitors. SIGNIFICANCE: The Sleep State Trend (SST) may provide caregivers and clinical studies a real-time view of sleep state fluctuations and its cyclicity.

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Controversial evidence is available regarding suitable targets for the arterial O2 tension (PaO2) after traumatic brain injury and/or hemorrhagic shock (HS). We previously demonstrated that hyperoxia during resuscitation from hemorrhagic shock attenuated cardiac injury and renal dysfunction in swine with coronary artery disease. Therefore, this study investigated the impact of targeted hyperoxemia in a long-term, resuscitated model of combined acute subdural hematoma (ASDH)-induced brain injury and HS. The prospective randomized, controlled, resuscitated animal investigation consisted of 15 adult pigs. Combined ASDH plus HS was induced by injection of 0.1 ml/kg autologous blood into the subdural space followed by controlled passive removal of blood. Two hours later, resuscitation was initiated comprising re-transfusion of shed blood, fluids, continuous i.v. noradrenaline, and either hyperoxemia (target PaO2 200 - 250 mmHg) or normoxemia (target PaO2 80 - 120 mmHg) during the first 24 h of the total of 54 h of intensive care. Systemic hemodynamics, intracranial and cerebral perfusion pressures, parameters of brain microdialysis and blood biomarkers of brain injury did not significantly differ between the two groups. According to the experimental protocol, PaO2 was significantly higher in the hyperoxemia group at the end of the intervention period, i.e., at 24 h of resuscitation, which coincided with a higher brain tissue PO2. The latter persisted until the end of observation period. While neurological function as assessed using the veterinary Modified Glasgow Coma Score progressively deteriorated in the control group, it remained unaffected in the hyperoxemia animals, however, without significant intergroup difference. Survival times did not significantly differ in the hyperoxemia and control groups either. Despite being associated with higher brain tissue PO2 levels, which were sustained beyond the intervention period, targeted hyperoxemia exerted neither significantly beneficial nor deleterious effects after combined ASDH and HS in swine with pre-existing coronary artery disease. The unavailability of a power calculation and, thus, the limited number of animals included, are the limitations of the study.

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Deep brain stimulation (DBS) is a revolutionary treatment for movement disorders. Measuring DBS-induced hemodynamic responses may be useful for surgical guidance of DBS electrode implantation as well as to study the mechanism and assess therapeutic effects of DBS. In this study, we evaluated the performance of a single fiber spectroscopic (SFS) system for measuring hemodynamic response in different cortical layers in a DBS animal model. We showed that SFS is capable of measuring minute relative changes in oxygen saturation and blood volume fraction in-vivo at a sampling rate of 22-33 Hz. During stimulation, blood volume fraction increased, while oxygen saturation showed both increases and decreases at different cortical depths across animals. In addition, we showed the potential of using SFS for measuring other physiological parameters, for example, heart rate, and respiratory rate.

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Extended exposure to radiation, microgravity, and isolation during space exploration has significant physiological, structural, and psychosocial effects on astronauts, and particularly their central nervous system. To date, the use of brain monitoring techniques adopted on Earth in pre/post-spaceflight experimental protocols has proven to be valuable for investigating the effects of space travel on the brain. However, future (longer) deep space travel would require some brain function monitoring equipment to be also available for evaluating and monitoring brain health during spaceflight. Here, we describe the impact of spaceflight on the brain, the basic principles behind six brain function analysis technologies, their current use associated with spaceflight, and their potential for utilization during deep space exploration. We suggest that, while the use of magnetic resonance imaging (MRI), positron emission tomography (PET), and computerized tomography (CT) is limited to analog and pre/post-spaceflight studies on Earth, electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and ultrasound are good candidates to be adapted for utilization in the context of deep space exploration.

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BACKGROUND: Transcranial Doppler ultrasonography (TCD) is a portable, bedside, noninvasive diagnostic tool used for the real-time assessment of cerebral hemodynamics. Despite the evident utility of TCD and the ability of this technique to function as a stethoscope to the brain, its use has been limited to specialized centers because of the dearth of technical and clinical expertise required to acquire and interpret the cerebrovascular parameters. Additionally, the conventional pragmatic episodic TCD monitoring protocols lack dynamic real-time feedback to guide time-critical clinical interventions. Fortunately, with the recent advent of automated robotic TCD technology in conjunction with the automated software for TCD data processing, we now have the technology to automatically acquire TCD data and obtain clinically relevant information in real-time. By obviating the need for highly trained clinical personnel, this technology shows great promise toward a future of widespread noninvasive monitoring to guide clinical care in patients with acute brain injury. METHODS: Here, we describe a proposal for a prospective observational multicenter clinical trial to evaluate the safety and feasibility of prolonged automated robotic TCD monitoring in patients with severe acute traumatic brain injury (TBI). We will enroll patients with severe non-penetrating TBI with concomitant invasive multimodal monitoring including, intracranial pressure, brain tissue oxygenation, and brain temperature monitoring as part of standard of care in centers with varying degrees of TCD availability and experience. Additionally, we propose to evaluate the correlation of pertinent TCD-based cerebral autoregulation indices such as the critical closing pressure, and the pressure reactivity index with the brain tissue oxygenation values obtained invasively. CONCLUSIONS: The overarching goal of this study is to establish safety and feasibility of prolonged automated TCD monitoring for patients with TBI in the intensive care unit and identify clinically meaningful and pragmatic noninvasive targets for future interventions.

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OBJECTIVE: We analyze a slow electrographic pattern, Macroperiodic Oscillations (MOs), in the EEG from a cohort of young critical care patients (n = 43) with continuous EEG monitoring. We construct novel quantitative methods to quantify and understand MOs. METHODS: We applied a nonparametric bilevel spectral analysis to identify MOs, a millihertz (0.004-0.01 Hz) modulation of 5-15 Hz activity in two separate ICU patient cohorts (n = 195 total). We also developed a rigorous measure to quantify MOs strength and spatial expression, which was validated against surrogate noise data. RESULTS: Strong or spatially widespread MOs appear in both high clinical suspicion and a general ICU population. In the former, patients with strong or spatially widespread MOs tended to have worse clinical outcomes. Intracranial pressure and heart rate data from one patient provide insight into a potential broader physiological mechanism for MOs. CONCLUSIONS: We quantified millihertz EEG modulation (MOs) in cohorts of critically ill pediatric patients. We demonstrated high incidence in two patient populations. In a high suspicion cohort, MOs are associated with poor outcome, suggesting future potential as a diagnostic and prognostic aid. SIGNIFICANCE: These results support the existence of EEG dynamics across disparate time-scales and may provide insight into brain injury physiology in young children.

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