Evaluating the Electroencephalographic Signal Quality of an In-Ear Wearable Device.

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.

Linking and unlinking the paediatric brain: age-invariant neural correlates of general anaesthesia.

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.

Prognostic value of somatosensory-evoked potentials in the newborn with hypoxic-ischemic encephalopathy after the introduction of therapeutic hypothermia.

To establish the ability of somatosensory-evoked potentials (SEPs) to detect neurological damage in neonatal patients with hypoxic-ischemic encephalopathy (HIE) treated with therapeutic hypothermia (TH). Retrospective study including 84 neonates ≥ 36 weeks of gestational age with HIE and TH with SEPs performed in the first 14 days of life. SEPs from the median nerve were performed after completion of TH. Either unilateral or bilateral absence of N20, or unilateral or bilateral latency ≥ 36 ms, was considered pathological. All newborns underwent a cerebral resonance imaging (MRI) at between days 7 and 14 of life and a neurodevelopmental evaluation using the Brunet-Lezine test at two years of age; a global Brunet-Lezine test score < 70 was considered unfavorable. The risk of moderate-to-severe alteration on basal ganglia-thalamic (BGT) and/or white matter areas on MRI for pathological SEPs was as follows: odds ratio 95% IC: 23.1 (6.9-76.9), sensitivity 78.6%, specificity 86.3%, positive predictive value 75.9%, and negative predictive value 88%. The BGT and internal capsule were the areas with the greatest risk of lesion with an altered SEPs: odds ratio 95% IC 93.1 (11.1-777.8). The risk of neurodevelopmental impairment for pathological SEPs was odds ratio 95% IC: 38.5 (4.4-335.3), sensitivity 91.7%, specificity 77.8% positive predictive value 52.4%, and negative predictive value 97.2%. CONCLUSION: The present study demonstrates the good predictive capacity of SEPs performed in the first two weeks of life in newborns with HIE and TH to detect an increased risk of neuroimaging lesions and neurodevelopmental impairment at two years of age. WHAT IS KNOWN: • Bilateral absence of the N20 cortical component of somatosensory evoked potentials has been associated with poor neurological outcome in neonates with hypoxic-ischemic encephalopathy. WHAT IS NEW: • This work confirms the predictive capacity of SEPs by adding two important aspects: the value of latency when interpreting SEPs results and the absence of effect of the hypothermia method used on the results of SEPs.

Prolonged Automated Robotic TCD Monitoring in Acute Severe TBI: Study Design and Rationale.

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.

A Bedside Method for Measuring Effects of a Sedative Drug on Cerebral Function in Newborn Infants.

BACKGROUND: Data on the cerebral effects of analgesic and sedative drugs are needed for the development of safe and effective treatments during neonatal intensive care. Electroencephalography (EEG) is an objective, but interpreter-dependent method for monitoring cortical activity. Quantitative computerized analyses might reveal EEG changes otherwise not detectable. METHODS: EEG registrations were retrospectively collected from 21 infants (mean 38.7 gestational weeks; range 27-42) who received dexmedetomidine during neonatal care. The registrations were transformed into computational features and analyzed visually, and with two computational measures quantifying relative and absolute changes in power (range EEG; rEEG) and cortico-cortical synchrony (activation synchrony index; ASI), respectively. RESULTS: The visual assessment did not reveal any drug effects. In rEEG analyses, a negative correlation was found between the baseline and the referential frontal (rho = 0.612, p = 0.006) and parietal (rho = -0.489, p = 0.035) derivations. The change in ASI was negatively correlated to baseline values in the interhemispheric (rho = -0.753; p = 0.001) and frontal comparisons (rho = -0.496; p = 0.038). CONCLUSION: Cerebral effects of dexmedetomidine as determined by EEG in newborn infants are related to cortical activity prior to DEX administration, indicating that higher brain activity levels (higher rEEG) during baseline links to a more pronounced reduction by DEX. The computational measurements indicate drug effects on both overall cortical activity and cortico-cortical communication. These effects were not evident in visual analysis.

Design and Evaluation of a Lactate Microbiosensor: Toward Multianalyte Monitoring of Neurometabolic Markers In Vivo in the Brain.

Direct in vivo measurements of neurometabolic markers in the brain with high spatio-temporal resolution, sensitivity, and selectivity is highly important to understand neurometabolism. Electrochemical biosensors based on microelectrodes are very attractive analytical tools for continuous monitoring of neurometabolic markers, such as lactate and glucose in the brain extracellular space at resting and following neuronal activation. Here, we assess the merits of a platinized carbon fiber microelectrode (CFM/Pt) as a sensing platform for developing enzyme oxidase-based microbiosensors to measure extracellular lactate in the brain. Lactate oxidase was immobilized on the CFM/Pt surface by crosslinking with glutaraldehyde. The CFM/Pt-based lactate microbiosensor exhibited high sensitivity and selectivity, good operational stability, and low dependence on oxygen, temperature, and pH. An array consisting of a glucose and lactate microbiosensors, including a null sensor, was used for concurrent measurement of both neurometabolic substrates in vivo in the anesthetized rat brain. Rapid changes of lactate and glucose were observed in the cortex and hippocampus in response to local glucose and lactate application and upon insulin-induced fluctuations of systemic glucose. Overall, these results indicate that microbiosensors are a valuable tool to investigate neurometabolism and to better understand the role of major neurometabolic markers, such as lactate and glucose.

Offline comparison of processed electroencephalogram monitors for anaesthetic-induced electroencephalogram changes in older adults.

BACKGROUND: Several devices record and interpret patient brain activity via electroencephalogram (EEG) to aid physician assessment of anaesthetic effect. Few studies have compared EEG monitors on data from the same patient. Here, we describe a set-up to simultaneously compare the performance of three processed EEG monitors using pre-recorded EEG signals from older surgical patients. METHODS: A playback system was designed to replay EEG signals into three different commercially available EEG monitors. We could then simultaneously calculate indices from the SedLine® Root (Masimo Inc., Irvine, CA, USA; patient state index [PSI]), bilateral BIS VISTA™ (Medtronic Inc., Minneapolis, MN, USA; bispectral index [BIS]), and Datex Ohmeda S/5 monitor with the Entropy™ Module (GE Healthcare, Chicago, IL, USA; E-entropy index [Entropy]). We tested the ability of each system to distinguish activity before anaesthesia administration (pre-med) and before/after loss of responsiveness (LOR), and to detect suppression incidences in EEG recorded from older surgical patients receiving beta-adrenergic blockers. We show examples of processed EEG monitor output tested on 29 EEG recordings from older surgical patients. RESULTS: All monitors showed significantly different indices and high effect sizes between comparisons pre-med to after LOR and before/after LOR. Both PSI and BIS showed the highest percentage of deeply anaesthetised indices during periods with suppression ratios (SRs) > 25%. We observed significant negative correlations between percentage of suppression and indices for all monitors (at SR >5%). CONCLUSIONS: All monitors distinguished EEG changes occurring before anaesthesia administration and during LOR. The PSI and BIS best detected suppressed periods. Our results suggest that the PSI and BIS monitors might be preferable for older patients with risk factors for intraoperative awareness or increased sensitivity to anaesthesia.

Python-Embedded Plugin Implementation in ICM+: Novel Tools for Neuromonitoring Time Series Analysis with Examples Using CENTER-TBI Datasets.

With the appearance of publicly available, high-resolution, physiological datasets in neurocritical care, like Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI), there is a growing need for tools that could be used by clinical researchers to interrogate this information-rich data. The ICM+ software is widely used for processing data acquired from bedside monitors. Considering the growing popularity of scripting simple-syntax programming languages like Python, particularly among clinical researchers, we have developed an interface in ICM+ that provides a streamlined way of adding Python scripting functionality to the ICM+ calculation engine. The new interface imposes certain requirements on the scripts and needs an accompanying descriptor file that tells ICM+ about the functions implemented, so that they become available to the end user in the same way as native ICM+ functions. ICM+ also now includes a tool that eases the creation of Python functions to be imported. The Python extension works very efficiently, and any user with some degree of experience in scripting can use it to enrich capabilities of ICM+. Depending on the data analysed and calculations performed, Python functions are 15-60% slower than built-in ICM+ functions, which is a more-than-acceptable trade-off for empowering ICM+ with the unlimited analytical freedom offered by extensive Python libraries.

Development of an Integrated EEG/fNIRS Brain Function Monitoring System.

In this study, a fully integrated electroencephalogram/functional near-infrared spectroscopy (EEG/fNIRS) brain monitoring system was designed to fulfill the demand for a miniaturized, light-weight, low-power-consumption, and low-cost brain monitoring system as a potential tool with which to screen for brain diseases. The system is based on the ADS1298IPAG Analog Front-End (AFE) and can simultaneously acquire two-channel EEG signals with a sampling rate of 250 SPS and six-channel fNIRS signals with a sampling rate of 8 SPS. AFE is controlled by Teensy 3.2 and powered by a lithium polymer battery connected to two protection circuits and regulators. The acquired EEG and fNIRS signals are monitored and stored using a Graphical User Interface (GUI). The system was evaluated by implementing several tests to verify its ability to simultaneously acquire EEG and fNIRS signals. The implemented system can acquire EEG and fNIRS signals with a CMRR of -115 dB, power consumption of 0.75 mW/ch, system weight of 70.5 g, probe weight of 3.1 g, and a total cost of USD 130. The results proved that this system can be qualified as a low-cost, light-weight, low-power-consumption, and fully integrated EEG/fNIRS brain monitoring system.

Cortical responses to tactile stimuli in preterm infants.

The conventional assessment of preterm somatosensory functions using averaged cortical responses to electrical stimulation ignores the characteristic components of preterm somatosensory evoked responses (SERs). Our study aimed to systematically evaluate the occurrence and development of SERs after tactile stimulus in preterm infants. We analysed SERs performed during 45 electroencephalograms (EEGs) from 29 infants at the mean post-menstrual age of 30.7 weeks. Altogether 2,087 SERs were identified visually at single-trial level from unfiltered signals capturing also their slowest components. We observed salient SERs with a high-amplitude slow component at a high success rate after hand (95%) and foot (83%) stimuli. There was a clear developmental change in both the slow wave and the higher-frequency components of the SERs. Infants with intraventricular haemorrhage (IVH; eleven infants) had initially normal SERs, but those with bilateral IVH later showed a developmental decrease in the ipsilateral SER occurrence after 30 weeks of post-menstrual age. Our study shows that tactile stimulus applied at bedside elicits salient SERs with a large slow component and an overriding fast oscillation, which are specific to the preterm period. Prior experimental research indicates that such SERs allow studying both subplate and cortical functions. Our present findings further suggest that they might offer a window to the emergence of neurodevelopmental sequelae after major structural brain lesions and, hence, an additional tool for both research and clinical neurophysiological evaluation of infants before term age.

Traumatic brain injury neuroelectrochemical monitoring: behind-the-ear micro-instrument and cloud application.

BACKGROUND: Traumatic Brain Injury (TBI) is a leading cause of fatality and disability worldwide, partly due to the occurrence of secondary injury and late interventions. Correct diagnosis and timely monitoring ensure effective medical intervention aimed at improving clinical outcome. However, due to the limitations in size and cost of current ambulatory bioinstruments, they cannot be used to monitor patients who may still be at risk of secondary injury outside the ICU. METHODS: We propose a complete system consisting of a wearable wireless bioinstrument and a cloud-based application for real-time TBI monitoring. The bioinstrument can simultaneously record up to ten channels including both ECoG biopotential and neurochemicals (e.g. potassium, glucose and lactate), and supports various electrochemical methods including potentiometry, amperometry and cyclic voltammetry. All channels support variable gain programming to automatically tune the input dynamic range and address biosensors' falling sensitivity. The instrument is flexible and can be folded to occupy a small space behind the ear. A Bluetooth Low-Energy (BLE) receiver is used to wirelessly connect the instrument to a cloud application where the recorded data is stored, processed and visualised in real-time. Bench testing has been used to validate device performance. RESULTS: The instrument successfully monitored spreading depolarisations (SDs) - reproduced using a signal generator - with an SNR of 29.07 dB and NF of 0.26 dB. The potentiostat generates a wide voltage range from -1.65V to +1.65V with a resolution of 0.8mV and the sensitivity of the amperometric AFE was verified by recording 5 pA currents. Different potassium, glucose and lactate concentrations prepared in lab were accurately measured and their respective working curves were constructed. Finally,the instrument achieved a maximum sampling rate of 1.25 ksps/channel with a throughput of 105 kbps. All measurements were successfully received at the cloud. CONCLUSION: The proposed instrument uniquely positions itself by presenting an aggressive optimisation of size and cost while maintaining high measurement accuracy. The system can effectively extend neuroelectrochemical monitoring to all TBI patients including those who are mobile and those who are outside the ICU. Finally, data recorded in the cloud application could be used to help diagnosis and guide rehabilitation.

Fiberless, Multi-Channel fNIRS-EEG System Based on Silicon Photomultipliers: Towards Sensitive and Ecological Mapping of Brain Activity and Neurovascular Coupling.

Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together with neurovascular coupling. An innovative fNIRS-EEG system is here presented. The system integrated a novel continuous-wave fNIRS component and a modified commercial EEG device. fNIRS probing relied on fiberless technology based on light emitting diodes and silicon photomultipliers (SiPMs). SiPMs are sensitive semiconductor detectors, whose large detection area maximizes photon harvesting from the scalp and overcomes limitations of fiberless technology. To optimize the signal-to-noise ratio and avoid fNIRS-EEG interference, a digital lock-in was implemented for fNIRS signal acquisition. A benchtop characterization of the fNIRS component showed its high performances with a noise equivalent power below 1 pW. Moreover, the fNIRS-EEG device was tested in vivo during tasks stimulating visual, motor and pre-frontal cortices. Finally, the capabilities to perform ecological recordings were assessed in clinical settings on one Alzheimer's Disease patient during long-lasting cognitive tests. The system can pave the way to portable technologies for accurate evaluation of multimodal brain activity, allowing their extensive employment in ecological environments and clinical practice.

EEG-Brain Activity Monitoring and Predictive Analysis of Signals Using Artificial Neural Networks.

Predictive observation and real-time analysis of the values of biomedical signals and automatic detection of epileptic seizures before onset are beneficial for the development of warning systems for patients because the patient, once informed that an epilepsy seizure is about to start, can take safety measures in useful time. In this article, Daubechies discrete wavelet transform (DWT) was used, coupled with analysis of the correlations between biomedical signals that measure the electrical activity in the brain by electroencephalogram (EEG), electrical currents generated in muscles by electromyogram (EMG), and heart rate monitoring by photoplethysmography (PPG). In addition, we used artificial neural networks (ANN) for automatic detection of epileptic seizures before onset. We analyzed 30 EEG recordings 10 min before a seizure and during the seizure for 30 patients with epilepsy. In this work, we investigated the ANN dimensions of 10, 50, 100, and 150 neurons, and we found that using an ANN with 150 neurons generates an excellent performance in comparison to a 10-neuron-based ANN. However, this analyzes requests in an increased amount of time in comparison with an ANN with a lower neuron number. For real-time monitoring, the neurons number should be correlated with the response time and power consumption used in wearable devices.

A Practical Approach to Cerebro-Somatic Near-Infrared Spectroscopy and Whole-Body Ultrasound.

Near-infrared spectroscopy (NIRS) is an emerging noninvasive monitoring modality based on chromophore absorption of infrared light. Because NIRS provides instantaneous information on cerebral and somatic tissue oxygenation, it becomes mandatory to identify rapidly the etiology of impaired regional oxygenation and thus perfusion. To do so, the use of whole-body ultrasound (WHOBUS) represents a significant advance in the management of patients experiencing cerebral or somatic desaturation. This narrative review describes the authors' experience since 2002 in the use of combined NIRS and WHOBUS. A practical approach in the use of both modalities and their respective limitations is described.

Multimodal Regional Brain Monitoring of Tissue Ischemia in Severe Cerebral Venous Sinus Thrombosis.

BACKGROUND: Comatose critically ill patients with severe diffuse cerebral venous thrombosis (CVT) are at high risk of secondary hypoxic/ischemic insults, which may considerably worsen neurological recovery. Multimodal brain monitoring (MBM) may therefore improve patient care in this setting, yet no data are available in the literature. METHODS: We report two patients with coma following severe diffuse CVT who underwent emergent invasive MBM with intracranial pressure (ICP), brain tissue oximetry (PbtO2), and cerebral microdialysis (CMD). Therapy of CVT consisted of intravenous unfractionated heparin (UFH), followed by endovascular mechanical thrombectomy (EMT). EMT efficacy was assessed continuously at the bedside using MBM. RESULTS: Despite effective therapeutic UFH (aPTT two times baseline levels in the two subjects), average CMD levels of lactate and glucose in the 6 h prior to EMT displayed evidence of regional brain ischemia. The EMT procedure was associated with a rapid (within 6 h) improvement in both CMD lactate (6.42 ± 0.61 4.89 ± 0.55 mmol/L, p = 0.02) and glucose (0.49 ± 0.17 vs. 0.96 ± 0.32 mmol/L, p = 0.0005). EMT was also associated with a significant increase in PbtO2 (22.9 ± 7.5 vs. 30.1 ± 3.6 mmHg, p = 0.0003) and a decrease in CMD glutamate (12.69 ± 1.06 vs. 5.73 ± 1.76 µmol/L, p = 0.017) and intracranial pressure (ICP) (13 ± 4 vs. 11 ± 4 mmHg (p = 004). Patients did not require surgical decompression, regained consciousness, and were discharged from the hospital with a good neurological outcome (modified Rankin score 3 and 4). CONCLUSIONS: This study illustrates the potential utility of continuous bedside MBM in patients with coma after severe brain injury, irrespective of the primary acute cerebral condition. Despite adequate ICP and PbtO2 control, the presence of CMD signs of regional brain cell ischemia triggered emergent EMT to treat CVT, which was associated with a significant and clinically relevant improvement of intracerebral physiology.

Ultrasound-tagged near-infrared spectroscopy does not disclose absent cerebral circulation in brain-dead adults.

BACKGROUND: Near-infrared spectroscopy, a non-invasive technique for monitoring cerebral oxygenation, is widely used, but its accuracy is questioned because of the possibility of extra-cranial contamination. Ultrasound-tagged near-infrared spectroscopy (UT-NIRS) has been proposed as an improvement over previous methods. We investigated UT-NIRS in healthy volunteers and in brain-dead patients. METHODS: We studied 20 healthy volunteers and 20 brain-dead patients with two UT-NIRS devices, CerOx™ and c-FLOW™ (Ornim Medical, Kfar Saba, Israel), which measure cerebral flow index (CFI), a parameter related to changes in cerebral blood flow (CBF). Monitoring started after the patients had been declared brain dead for a median of 34 (range: 11-300) min. In 11 cases, we obtained further demonstration of absent CBF. RESULTS: In healthy volunteers, CFI was markedly different in the two hemispheres in the same subject, with wide variability amongst subjects. In brain-dead patients (median age: 64 yr old, 45% female; 20% traumatic brain injury, 40% subarachnoid haemorrhage, and 40% intracranial haemorrhage), the median (inter-quartile range) CFI was 41 (36-47), significantly higher than in volunteers (33; 27-36). CONCLUSIONS: In brain-dead patients, where CBF is absent, the UT-NIRS findings can indicate an apparently perfused brain. This might reflect an insufficient separation of signals from extra-cranial structures from a genuine appraisal of cerebral perfusion. For non-invasive assessment of CBF-related parameters, the near-infrared spectroscopy still needs substantial improvement.

Occurrence of CPPopt Values in Uncorrelated ICP and ABP Time Series.

OBJECTIVES: Optimal cerebral perfusion pressure (CPPopt) is a concept that uses the pressure reactivity (PRx)-CPP relationship over a given period to find a value of CPP at which PRx shows best autoregulation. It has been proposed that this relationship be modelled by a U-shaped curve, where the minimum is interpreted as being the CPP value that corresponds to the strongest autoregulation. Owing to the nature of the calculation and the signals involved in it, the occurrence of CPPopt curves generated by non-physiological variations of intracranial pressure (ICP) and arterial blood pressure (ABP), termed here "false positives", is possible. Such random occurrences would artificially increase the yield of CPPopt values and decrease the reliability of the methodology.In this work, we studied the probability of the random occurrence of false-positives and we compared the effect of the parameters used for CPPopt calculation on this probability. MATERIALS AND METHODS: To simulate the occurrence of false-positives, uncorrelated ICP and ABP time series were generated by destroying the relationship between the waves in real recordings. The CPPopt algorithm was then applied to these new series and the number of false-positives was counted for different values of the algorithm's parameters. RESULTS: The percentage of CPPopt curves generated from uncorrelated data was demonstrated to be 11.5%. CONCLUSION: This value can be minimised by tuning some of the calculation parameters, such as increasing the calculation window and increasing the minimum PRx span accepted on the curve.

Effect of Mild Hypocapnia on Critical Closing Pressure and Other Mechanoelastic Parameters of the Cerebrospinal System.

OBJECTIVE: Brain arterial critical closing pressure (CrCP) has been studied in several diseases such as traumatic brain injury (TBI), subarachnoid haemorrhage, hydrocephalus, and in various physiological scenarios: intracranial hypertension, decreased cerebral perfusion pressure, hypercapnia, etc. Little or nothing so far has been demonstrated to characterise change in CrCP during mild hypocapnia. METHOD: We retrospectively analysed recordings of intracranial pressure (ICP), arterial blood pressure (ABP) and blood flow velocity from 27 severe TBI patients (mean 39.5 ± 3.4 years, 6 women) in whom a ventilation increase (20% increase in respiratory minute volume) was performed over 50 min as part of a standard clinical CO2 reactivity test. CrCP was calculated using the Windkessel model of cerebral arterial flow. Arteriolar wall tension (WT) was calculated as a difference between CrCP and ICP. The compartmental compliances arterial (C a ) and cerebrospinal fluid space (C i ) were also evaluated. RESULTS: During hypocapnia, ICP decreased from 17±6.8 to 13.2±6.6 mmHg (p < 0.000001). Wall tension increased from 14.5 ± 9.9 to 21.7±9.1 mmHg (p < 0.0002). CrCP, being a sum of WT + ICP, changed significantly from 31.5 ± 11.9 mmHg to 34.9±11.1 mmHg (p < 0.002), and the closing margin (ABP-CrCP) remained constant at an average value of 60 mmHg. C a decreased significantly during hypocapnia by 30% (p < 0.00001) and C i increased by 26% (p < 0.003). CONCLUSION: During hypocapnia in TBI patients, ICP decreases and WT increases. CrCP increases slightly as the rise in wall tension outweighs the decrease in ICP. The closing margin remained unchanged, suggesting that the risk of hypocapnia-induced ischemia might not be increased.

Neonatal somatosensory evoked potentials persist during hypothermia.

AIM: Treatment with therapeutic hypothermia has challenged the use of amplitude-integrated electroencephalography in predicting outcomes after perinatal asphyxia. In this study, we assessed the feasibility and gain of somatosensory evoked potentials (SEP) during hypothermia. METHODS: This retrospective study comprised neonates from 35 + 6 to 42 + 2 gestational weeks and treated for asphyxia or hypoxic-ischaemic encephalopathy at Helsinki University Hospital between 14 February 2007 and 23 December 2009. This period was partly before the introduction of routine therapeutic hypothermia, which enabled us to include normothermic neonates who would these days receive hypothermia treatment. We analysed SEPs from 47 asphyxiated neonates and compared the results between 23 normothermic and 24 hypothermic neonates. RESULTS: Our data showed that hypothermia led to SEP latencies lengthening by a few milliseconds, but the essential gain for predicting outcomes by SEPs was preserved during hypothermia. Of the 24 hypothermic neonates, bilaterally absent SEPs were associated with poor outcome in 2/2 neonates, normal SEPs were associated with good outcomes in 13/15 neonates and 5/7 neonates with unilaterally absent or grossly delayed SEPs had a poor outcome. CONCLUSION: Our findings indicated that SEPs were a reliable tool for evaluating the somatosensory system in asphyxiated neonates in both normothermic and hypothermic conditions.

Cortical burst dynamics predict clinical outcome early in extremely preterm infants.

Intermittent bursts of electrical activity are a ubiquitous signature of very early brain activity. Previous studies have largely focused on assessing the amplitudes of these transient cortical bursts or the intervals between them. Recent advances in basic neuroscience have identified the presence of scale-free 'avalanche' processes in bursting patterns of cortical activity in other clinical contexts. Here, we hypothesize that cortical bursts in human preterm infants also exhibit scale-free properties, providing new insights into the nature, temporal evolution, and prognostic value of spontaneous brain activity in the days immediately following preterm birth. We examined electroencephalographic recordings from 43 extremely preterm infants (gestational age 22-28 weeks) and demonstrated that their cortical bursts exhibit scale-free properties as early as 12 h after birth. The scaling relationships of cortical bursts correlate significantly with later mental development-particularly within the first 12 h of life. These findings show that early preterm brain activity is characterized by scale-free dynamics which carry developmental significance, hence offering novel means for rapid and early clinical prediction of neurodevelopmental outcomes.