Spatial variation in automated burst suppression detection in pharmacologically induced coma

Burst suppression is actively studied as a control signal to guide anesthetic dosing in patients undergoing medically induced coma. The ability to automatically identify periods of EEG suppression and compactly summarize the depth of coma using the burst suppression probability (BSP) is crucial to effective and safe monitoring and control of medical coma. Current literature however does not explicitly account for the potential variation in burst suppression parameters across different scalp locations. In this study we analyzed standard 19-channel EEG recordings from 8 patients with refractory status epilepticus who underwent pharmacologically induced burst suppression as medical treatment for refractory seizures. We found that although burst suppression is generally considered a global phenomenon, BSP obtained using a previously validated algorithm varies systematically across different channels. A global representation of information from individual channels is proposed that takes into account the burst suppression characteristics recorded at multiple electrodes. BSP computed from this representative burst suppression pattern may be more resilient to noise and a better representation of the brain state of patients. Multichannel data integration may enhance the reliability of estimates of the depth of medical coma.National Institutes of Health (U.S.) (Grant K23 NS090900)National Institute of Neurological Diseases and Stroke (U.S.) (Grant K23 NS090900)National Institutes of Health (U.S.) (Grant DP2-OD006454)National Institutes of Health (U.S.) (Grant TROI-GMI04948

Local cortical dynamics of burst suppression in the anaesthetized brain

Burst suppression is an electroencephalogram pattern that consists of a quasi-periodic alternation between isoelectric ‘suppressions’ lasting seconds or minutes, and high-voltage ‘bursts’. It is characteristic of a profoundly inactivated brain, occurring in conditions including hypothermia, deep general anaesthesia, infant encephalopathy and coma. It is also used in neurology as an electrophysiological endpoint in pharmacologically induced coma for brain protection after traumatic injury and during status epilepticus. Classically, burst suppression has been regarded as a ‘global’ state with synchronous activity throughout cortex. This assumption has influenced the clinical use of burst suppression as a way to broadly reduce neural activity. However, the extent of spatial homogeneity has not been fully explored due to the challenges in recording from multiple cortical sites simultaneously. The neurophysiological dynamics of large-scale cortical circuits during burst suppression are therefore not well understood. To address this question, we recorded intracranial electrocorticograms from patients who entered burst suppression while receiving propofol general anaesthesia. The electrodes were broadly distributed across cortex, enabling us to examine both the dynamics of burst suppression within local cortical regions and larger-scale network interactions. We found that in contrast to previous characterizations, bursts could be substantially asynchronous across the cortex. Furthermore, the state of burst suppression itself could occur in a limited cortical region while other areas exhibited ongoing continuous activity. In addition, we found a complex temporal structure within bursts, which recapitulated the spectral dynamics of the state preceding burst suppression, and evolved throughout the course of a single burst. Our observations imply that local cortical dynamics are not homogeneous, even during significant brain inactivation. Instead, cortical and, implicitly, subcortical circuits express seemingly different sensitivities to high doses of anaesthetics that suggest a hierarchy governing how the brain enters burst suppression, and emphasize the role of local dynamics in what has previously been regarded as a global state. These findings suggest a conceptual shift in how neurologists could assess the brain function of patients undergoing burst suppression. First, analysing spatial variation in burst suppression could provide insight into the circuit dysfunction underlying a given pathology, and could improve monitoring of medically-induced coma. Second, analysing the temporal dynamics within a burst could help assess the underlying brain state. This approach could be explored as a prognostic tool for recovery from coma, and for guiding treatment of status epilepticus. Overall, these results suggest new research directions and methods that could improve patient monitoring in clinical practice.Burroughs Wellcome Fund (Career Award at the Scientific Interface)National Institutes of Health (U.S.) (Director's Pioneer Award DP10D003646)National Institutes of Health (U.S.) (Transformative 1R01GM104948

Variability in pharmacologically-induced coma for treatment of refractory status epilepticus

Objective To characterize the amount of EEG suppression achieved in refractory status epilepticus (RSE) patients treated with pharmacologically-induced coma (PIC). Methods We analyzed EEG recordings from 35 RSE patients between 21–84 years-old who received PIC that target burst suppression and quantified the amount of EEG suppression using the burst suppression probability (BSP). Then we measured the variability of BSPs with respect to a reference level of BSP 0.8 ± 0.15. Finally, we also measured the variability of BSPs with respect to the amount of intravenous anesthetic drugs (IVADs) received by the patients. Results Patients remained in the reference BSP range for only 8% (median, interquartile range IQR [0, 29] %) of the total time under treatment. The median time with BSP below the reference range was 84% (IQR [37, 100] %). BSPs in some patients drifted significantly over time despite constant infusion rates of IVADs. Similar weight-normalized infusion rates of IVADs in different patients nearly always resulted in distinct BSPs (probability 0.93 (IQR [0.82, 1.0]). Conclusion This study quantitatively identified high variability in the amount of EEG suppression achieved in clinical practice when treating RSE patients. While some of this variability may arise from clinicians purposefully deviating from clinical practice guidelines, our results show that the high variability also arises in part from significant inter- and intra- individual pharmacokinetic/pharmacodynamic variation. Our results indicate that the delicate balance between maintaining sufficient EEG suppression in RSE patients and minimizing IVAD exposure in clinical practice is challenging to achieve. This may affect patient outcomes and confound studies seeking to determine an optimal amount of EEG suppression for treatment of RSE. Therefore, our analysis points to the need for developing an alternative paradigm, such as vigilant anesthetic management as happens in operating rooms, or closed-loop anesthesia delivery, for investigating and providing induced-coma therapy to RSE patients

AN FMRI STUDY OF DEFAULT MODE NETWORK CONNECTIVITY IN COMATOSE PATIENTS

Functional connectivity within a resting state network of the brain, termed the default mode network (DMN), has been suggested to represent the neural correlate o f the stream of consciousness. Altered states of consciousness where awareness is thought to be absent could provide insight into the function o f the DMN. Here I examined the functional connectivity in the DMN in both reversible and irreversible coma using fMRI. Twelve healthy control subjects and thirteen comatose patients following cardiac arrest were included in the study. DMN connectivity was observed in healthy controls and two patients who regained consciousness. DMN connectivity was absent in the eleven patients who failed to regain consciousness. Functional connectivity in the DMN is preserved in the comatose patients who regained consciousness but absent in those who did not recover consciousness indicating that potentially the DMN is necessary but not sufficient to support consciousness

Advances in Clinical Neurophysiology

Including some of the newest advances in the field of neurophysiology, this book can be considered as one of the treasures that interested scientists would like to collect. It discusses many disciplines of clinical neurophysiology that are, currently, crucial in the practice as they explain methods and findings of techniques that help to improve diagnosis and to ensure better treatment. While trying to rely on evidence-based facts, this book presents some new ideas to be applied and tested in the clinical practice. Advances in Clinical Neurophysiology is important not only for the neurophysiologists but also for clinicians interested or working in wide range of specialties such as neurology, neurosurgery, intensive care units, pediatrics and so on. Generally, this book is written and designed to all those involved in, interpreting or requesting neurophysiologic tests

Study of the Term Neonatal Brain Injury with combined Diffuse Optical Tomography and Electroencephalography

This thesis describes the application of combined diffuse optical tomography (DOT) and electroencephalography (EEG) in the investigation of neonatal term brain injury. With hypoxic ischaemic encephalopathy (HIE) and perinatal stroke being the most frequent contributors to brain injury in the term neonatal population, the first part of the thesis focuses on the description and ongoing requirement for their further investigation. In continuation to that, the characteristics and unique properties of both DOT and EEG are described and explored. The combination of these two modalities was utilised in elucidating the relationship between neuronal activity and cerebral haemodynamics both in physiological processes as well as in disease, by the infant’s cot side. This work differs to previous studies using near-infrared technologies and EEG, as a denser whole head array was used, offering the potential of 3-dimensional image reconstruction of the cortical haemodynamic events in relation to electro-cortical activity. These methods were applied in the study of critically ill infants presenting with seizures in the first few days of life. The relevant results are presented in three separate chapters of the thesis. Distinct neurophysiological phenomena such as seizures and burst suppression were detected and studied in association to underlying HIE. On the grounds of a pre-existing pilot study of our research group, distinct prolonged de-oxygenated cortical areas were identified following electrical seizure activity. Further exploration of infants with seizures provided limited supporting evidence. The investigation of burst suppression in HIE led to the first ever identification of repeated, waveform, cortical haemodynamic events in response to bursts of electrical activity with some spatial correlation to regions of brain injury. Further analysis of the low frequencies within the diffuse optical signal in cases of perinatal stroke, showed a consistent interhemispheric difference between the healthy and stroke-affected brain regions. The limitations, prospects and conclusions are presented in the final chapter. The use of simultaneous DOT and EEG offers a unique neuro-monitoring and neuro-investigating tool in the neonatal intensive care environment, which is safe, portable, and cost-effective, Ongoing research is required for the exploration and development of the methodology and its potential diagnostic properties

Spatiotemporal brain dynamics induced by propofol and ketamine in humans

Human brain dynamics are radically altered under the influence of anaesthetics. However, despite their widespread clinical use, the whole-brain mechanisms by which anaesthetics alter consciousness are still not fully understood and clinical translation of existing insights is limited. This thesis presents several lines of investigation aimed to improve our understanding of spatiotemporal brain states under the anaesthetics propofol and ketamine. First, slow-wave activity saturation (SWAS) was studied across the brain and in relation to existing depth of anaesthesia markers. Local propofol concentration needed to achieve SWAS in healthy volunteers correlated with GABA-A receptor density (Spearman ρ=-0.69, P=0.0018), providing more evidence for the importance of the neurophysiological state of SWAS. The average Bispectral Index at SWAS across volunteers was 49±4, but its value varied significantly over time. Second, relevant cortico-cardiac interactions were studied. A slow propofol infusion increased heart rate in a dose-dependent manner (increase of +4.2±1.5 bpm / (μg ml-1), P<0.001). Individual cortical slow waves were coupled to the heartbeat (P<0.001), with heartbeat incidence peaking about 450ms before slow-wave onset. A ketamine case study showed decreased amplitude of heartbeat-evoked potentials, suggesting impaired interoceptive signalling may have a part in dissociative phenomenology. Third, novel methodology was developed, validated, and applied throughout the thesis. Iterated Masking Empirical Mode Decomposition was used to identify three types of low-frequency propofol waves with different spatiotemporal maps and dose-responses. Hidden Markov Modelling of propofol showed a shift to anterior alpha states and a reduced switching rate (P<0.01); with ketamine states exhibiting low alpha power and decreased connectivity became more prominent (P<0.001). Fourth, the potential of translating electroencephalographic markers from high- to low- density montages was studied. Posterior montages were best at capturing the reduced state switching under propofol. A patient study of antidepressant ketamine treatment demonstrated reduced temporal lobe alpha and theta power were associated with dissociation (P=0.0109)

State Transitions Within The Cortex Are Strongly Influenced By Local Interactions Under General Anesthesia

General anesthetics are a class of drugs with diverse molecular mechanisms that cause a state of unconsciousness. Generally, anesthetics are thought to exert this effect by co- opting endogenous sleep pathways within the brain, and activity patterns recorded during anesthesia resemble those recorded during natural sleep. Monitors of anesthetic depth take advantage of the relationship between brain activity patterns and anesthetic concentration to define a depth of exposure. Recovery from anesthetic-induced unconsciousness is typically assumed to be a passive, linear process that relies upon elimination of drug from the body. However, it has been shown that activity patterns undergo discrete transitions between several distinct brain states under anesthesia. Furthermore, the brain exhibits a resistance to recovery of consciousness during emergence from anesthesia. Together, these results show that emergence cannot be explained by drug elimination alone. In this dissertation, we present evidence to suggest that stochastic fluctuations between distinct brain states account for this resistance to emergence. Furthermore, we show evidence to suggest that local cortical interactions are the principal organizing mechanism that gives rise to the brain states and state transitions recorded under general anesthesia. This mechanism is distinct from those known to drive state transitions during natural sleep. During sleep, broadly projecting modulatory pathways engage neurons throughout the thalamocortical network in coherent activity patterns and state transitions. Here, we demonstrate local heterogeneity in activity patterns and transition times within the cortex. Furthermore, our results indicate that, despite there being only weak coupling between activity patterns and transition times between different cortical regions, this coupling is sufficient to give rise to global brain states. Altogether, the work presented in this dissertation indicates that the nature of oscillations within the cortex is strongly influenced by local interactions. This finding suggests that the mechanisms thought to give rise to state transitions during sleep are not the same as those that give rise to transitions under anesthesia. This finding that local interactions are potentially a stronger organizing mechanism for cortical activity than previously appreciated has important implications for anesthetic monitoring, clinical sleep disorders, and our basic understanding of thalamocortical activity patterns

Deep Learning for Electrophysiological Investigation and Estimation of Anesthetic-Induced Unconsciousness

Neuroscience has made a number of advances in the search for the neural correlates of consciousness, but our understanding of the neurophysiological markers remains incomplete. In this work, we apply deep learning techniques to resting-state electroencephalographic (EEG) measures of healthy participants under general anesthesia, for the investigation and estimation of altered states of consciousness. Specifically, we focus on states characterized by different levels of unconsciousness and anesthetic depths, based on definitions and metrics from contemporary clinical practice. Our experiments begin by exploring the ability of deep learning to extract relevant electrophysiological features, under a cross-subject decoding task. As there is no state-of-theart model for EEG analysis, we compare two widely used deep learning architectures - convolutional neural networks (cNNs) and multilayer perceptrons (MLPs) - and show that cNNs perform effectively, using only one second of the raw EEG signals. Relying on cNNs, we derive a novel 3D architecture design and a standard preprocessing pipeline, which allows us to exploit the spatio-temporal structure of the EEG, as well as to integrate different acquisition systems and datasets under a common methodology. We then focus on the nature of different predictive tasks, by investigating classification and regression algorithms under a variety of clinical ground-truths, based on behavioral, pharmacological, and psychometrical evidence for consciousness. Our findings provide several insights regarding the interaction across the anesthetic states, the electrophysiological signatures, and the temporal dynamics of the models. We also reveal an optimal training strategy, based on which we can detect progressive changes in levels of unconsciousness, with higher granularity than current clinical methods. Finally, we test the generalizability of our deep learning-based EEG framework, across subjects, experimental designs, and anesthetic agents (propofol, ketamine and xenon). Our results highlight the capacity of our model to acquire appropriate, task-related, cross-study features, and the potential to discover common cross-drug features of unconsciousness. This work has broader significance for discovering generalized electrophysiological markers that index states of consciousness, using a data-driven analysis approach. It also provides a basis for the development of automated, machine-learning driven, non-invasive EEG systems for real-time monitoring of the depth of anesthesia, which can advance patients' comfort and safety

Anesthetic-induced unresponsiveness: Electroencephalographic correlates and subjective experiences

Anesthetic drugs can induce reversible alterations in responsiveness, connectedness and consciousness. The measures based on electroencephalogram (EEG) have marked potential for monitoring the anesthetized state because of their relatively easy use in the operating room. In this study, 79 healthy young men participated in an awake experiment, and 47 participants continued to an anesthesia experiment where they received either dexmedetomidine or propofol as target-controlled infusion with stepwise increments until the loss of responsiveness. The participants were roused during the constant drug infusion and interviewed. The drug dose was increased to 1.5-fold to achieve a deeper unresponsive state. After regaining responsiveness, the participants were interviewed. EEG was measured throughout the experiment and the N400 event-related potential component and functional and directed connectivity were studied. Prefrontal-frontal connectivity in the alpha frequency band discriminated the states that differed with respect to responsiveness or drug concentration. The net direction of connectivity was frontal-to-prefrontal during unresponsiveness and reversed back to prefrontal-to-frontal upon return of responsiveness. The understanding of the meaning of spoken language, as measured with the N400 effect, was lost along with responsiveness but, in the dexmedetomidine group, the N400 component was preserved suggesting partial preservation of the processing of words during anesthetic-induced unresponsiveness. However, the N400 effect could not be detected in all the awake participants and the choice of analysis method had marked impact on its detection rate at the individual-level. Subjective experiences were common during unresponsiveness induced by dexmedetomidine and propofol but the experiences most often suggested disconnectedness from the environment. In conclusion, the doses of dexmedetomidine or propofol minimally sufficient to induce unresponsiveness do not render the participants unconscious and dexmedetomidine does not completely abolish the processing of semantic stimuli. The local anterior EEG connectivity in the alpha frequency band may have potential in monitoring the depth of dexmedetomidine- and propofol-induced anesthesia.Anesteettien aiheuttama vastauskyvyttömyys: aivosähkökäyräpohjaiset korrelaatit ja subjektiiviset kokemukset Anestesialääkkeillä voidaan saada aikaan palautuvia muutoksia vastauskykyisyydessä, kytkeytyneisyydessä ja tajunnassa. Aivosähkökäyrään (EEG) pohjautuvat menetelmät tarjoavat lupaavia mahdollisuuksia mitata anestesian vaikutusta aivoissa, sillä niitä on suhteellisen helppo käyttää leikkaussalissa. Tässä tutkimuksessa 79 tervettä nuorta miestä osallistui valvekokeeseen ja 47 heistä jatkoi anestesiakokeeseen. Anestesiakokeessa koehenkilöille annettiin joko deksmedetomidiinia tai propofolia tavoiteohjattuna infuusiona nousevia annosportaita käyttäen, kunnes he menettivät vastauskykynsä. Koehenkilöt herätettiin tasaisen lääkeinfuusion aikana ja haastateltiin. Koko kokeen ajan mitattiin EEG:tä, josta tutkittiin N400-herätevastetta sekä toiminnallista ja suunnattua konnektiivisuutta. Prefrontaali-frontaalivälillä mitattu konnektiivisuus alfa-taajuuskaistassa erotteli toisistaan tilat, jotka erosivat vastauskykyisyyden tai lääkepitoisuuden suhteen. Konnektiivisuuden vallitseva suunta oli frontaalialueilta prefrontaalialueille vastauskyvyttömyyden aikana, mutta se kääntyi takaisin prefrontaalisesta frontaaliseen kulkevaksi koehenkilöiden vastauskyvyn palatessa. N400-efektillä mitattu puhutun kielen ymmärtäminen katosi vastauskyvyn menettämisen myötä. Deksmedetomidiiniryhmässä N400-komponentti säilyi, mikä viittaa siihen, että anesteettien aiheuttaman vastauskyvyttömyyden aikana sanojen prosessointi voi säilyä osittain. Yksilötasolla N400-efektiä ei kuitenkaan havaittu edes kaikilla hereillä olevilla henkilöillä, ja analyysimenetelmän valinnalla oli suuri vaikutus herätevasteen havaitsemiseen. Subjektiiviset kokemukset olivat yleisiä deksmedetomidiinin ja propofolin aiheuttaman vastauskyvyttömyyden aikana, mutta kokemukset olivat usein ympäristöstä irtikytkeytyneitä. Yhteenvetona voidaan todeta, että deksmedetomidiini- ja propofoliannokset, jotka juuri ja juuri riittävät aikaansaamaan vastauskyvyttömyyden, eivät aiheuta tajuttomuutta. Deksmedetomidiini ei myöskään täysin estä merkityssisällöllisten ärsykkeiden käsittelyä. Frontaalialueen sisällä EEG:llä mitattu konnektiivisuus alfataajuuskaistassa saattaa olla tulevaisuudessa hyödyllinen menetelmä deksmedetomidiini- ja propofolianestesian syvyyden mittaamiseksi