An end-to-end framework for real-time automatic sleep stage classification.

Sleep staging is a fundamental but time consuming process in any sleep laboratory. To greatly speed up sleep staging without compromising accuracy, we developed a novel framework for performing real-time automatic sleep stage classification. The client-server architecture adopted here provides an end-to-end solution for anonymizing and efficiently transporting polysomnography data from the client to the server and for receiving sleep stages in an interoperable fashion. The framework intelligently partitions the sleep staging task between the client and server in a way that multiple low-end clients can work with one server, and can be deployed both locally as well as over the cloud. The framework was tested on four datasets comprising ≈1700 polysomnography records (≈12000 hr of recordings) collected from adolescents, young, and old adults, involving healthy persons as well as those with medical conditions. We used two independent validation datasets: one comprising patients from a sleep disorders clinic and the other incorporating patients with Parkinson's disease. Using this system, an entire night's sleep was staged with an accuracy on par with expert human scorers but much faster (≈5 s compared with 30-60 min). To illustrate the utility of such real-time sleep staging, we used it to facilitate the automatic delivery of acoustic stimuli at targeted phase of slow-sleep oscillations to enhance slow-wave sleep

EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications.

Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact with the environment. Recent advancements in technology and machine learning algorithms have increased interest in electroencephalographic (EEG)-based BCI applications. EEG-based intelligent BCI systems can facilitate continuous monitoring of fluctuations in human cognitive states under monotonous tasks, which is both beneficial for people in need of healthcare support and general researchers in different domain areas. In this review, we survey the recent literature on EEG signal sensing technologies and computational intelligence approaches in BCI applications, compensating for the gaps in the systematic summary of the past five years. Specifically, we first review the current status of BCI and signal sensing technologies for collecting reliable EEG signals. Then, we demonstrate state-of-the-art computational intelligence techniques, including fuzzy models and transfer learning in machine learning and deep learning algorithms, to detect, monitor, and maintain human cognitive states and task performance in prevalent applications. Finally, we present a couple of innovative BCI-inspired healthcare applications and discuss future research directions in EEG-based BCI research

Focal lesions induce large-scale percolation of sleep-like intracerebral activity in awake humans.

Focal cortical lesions are known to result in large-scale functional alterations involving distant areas; however, little is known about the electrophysiological mechanisms underlying these network effects. Here, we addressed this issue by analysing the short and long distance intracranial effects of controlled structural lesions in humans. The changes in Stereo-Electroencephalographic (SEEG) activity after Radiofrequency-Thermocoagulation (RFTC) recorded in 21 epileptic subjects were assessed with respect to baseline resting wakefulness and sleep activity. In addition, Cortico-Cortical Evoked Potentials (CCEPs) recorded before the lesion were employed to interpret these changes with respect to individual long-range connectivity patterns. We found that small structural ablations lead to the generation and large-scale propagation of sleep-like slow waves within the awake brain. These slow waves match those recorded in the same subjects during sleep, are prevalent in perilesional areas, but can percolate up to distances of 60 mm through specific long-range connections, as predicted by CCEPs. Given the known impact of slow waves on information processing and cortical plasticity, demonstrating their intrusion and percolation within the awake brain add key elements to our understanding of network dysfunction after cortical injuries

Multimodal neuroimaging in patients with disorders of consciousness showing "functional hemispherectomy".

Beside behavioral assessment of patients with disorders of consciousness, neuroimaging modalities may offer objective paraclinical markers important for diagnosis and prognosis. They provide information on the structural location and extent of brain lesions (e.g., morphometric MRI and diffusion tensor imaging (DTI-MRI) assessing structural connectivity) but also their functional impact (e.g., metabolic FDG-PET, hemodynamic fMRI, and EEG measurements obtained in "resting state" conditions). We here illustrate the role of multimodal imaging in severe brain injury, presenting a patient in unresponsive wakefulness syndrome (UWS; i.e., vegetative state, VS) and in a "fluctuating" minimally conscious state (MCS). In both cases, resting state FDG-PET, fMRI, and EEG showed a functionally preserved right hemisphere, while DTI showed underlying differences in structural connectivity highlighting the complementarities of these neuroimaging methods in the study of disorders of consciousness.Peer reviewe

Dissociable endogenous and exogenous attention in disorders of consciousness

Recent research suggests that despite the seeming inability of patients in vegetative and minimally conscious states to generate consistent behaviour, some might possess covert awareness detectable with functional neuroimaging. These findings motivate further research into the cognitive mechanisms that might support the existence of consciousness in these states of profound neurological dysfunction. One of the key questions in this regard relates to the nature and capabilities of attention in patients, known to be related to but distinct from consciousness. Previous assays of the electroencephalographic P300 marker of attention have demonstrated its presence and potential clinical value. Here we analysed data from 21 patients and 8 healthy volunteers collected during an experimental task designed to engender exogenous or endogenous attention, indexed by the P3a and P3b components, respectively, in response to a pair of word stimuli presented amongst distractors. Remarkably, we found that the early, bottom-up P3a and the late, top-down P3b could in fact be dissociated in a patient who fitted the behavioural criteria for the vegetative state. In juxtaposition with healthy volunteers, the patient's responses suggested the presence of a relatively high level of attentional abilities despite the absence of any behavioural indications thereof. Furthermore, we found independent evidence of covert command following in the patient, as measured by functional neuroimaging during tennis imagery. Three other minimally conscious patients evidenced non-discriminatory bottom-up orienting, but no top-down engagement of selective attentional control. Our findings present a persuasive case for dissociable attentional processing in behaviourally unresponsive patients, adding to our understanding of the possible levels and applications of consequent conscious awareness

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

EEG revealed improved vigilance regulation after stress exposure under Nx4: A randomized, placebo-controlled, double-blind, cross-over trial

ObjectivesVigilance is characterized by alertness and sustained attention. The hyper-vigilance states are indicators of stress experience in the resting brain. Neurexan (Nx4) has been shown to modulate the neuroendocrine stress response. Here, we hypothesized that the intake of Nx4 would alter brain vigilance states at rest.MethodIn this post-hoc analysis of the NEURIM study, EEG recordings of three, 12 min resting-state conditions in 39 healthy male volunteers were examined in a randomized, placebo-controlled, double-blind, cross-over clinical trial. EEG was recorded at three resting-state sessions: at baseline (RS0), after single-dose treatment with Nx4 or placebo (RS1), and subsequently after a psychosocial stress task (RS2). During each resting-state session, each 2-s segment of the consecutive EEG epochs was classified into one of seven different brain states along a wake-sleep continuum using the VIGALL 2.1 algorithm.ResultsIn the post-stress resting-state, subjects exhibited a hyper-stable vigilance regulation characterized by an increase in the mean vigilance level and by more rigidity in the higher vigilance states for a longer period of time. Importantly, Nx4-treated participants exhibited significantly lower mean vigilance level compared to placebo-treated ones. Also, Nx4- compared to placebo-treated participants spent comparably less time in higher vigilance states and more time in lower vigilance states in the post-stress resting-state.ConclusionStudy participants showed a significantly lower mean vigilance level in the post-stress resting-state condition and tended to stay longer in lower vigilance states after treatment with Nx4. These findings support the known stress attenuation effect of Nx4

Circadian Preference Modulates the Neural Substrate of Conflict Processing across the Day

Human morning and evening chronotypes differ in their preferred timing for sleep and wakefulness, as well as in optimal daytime periods to cope with cognitive challenges. Recent evidence suggests that these preferences are not a simple by-product of socio-professional timing constraints, but can be driven by inter-individual differences in the expression of circadian and homeostatic sleep-wake promoting signals. Chronotypes thus constitute a unique tool to access the interplay between those processes under normally entrained day-night conditions, and to investigate how they impinge onto higher cognitive control processes. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on conflict processing-related cerebral activity throughout a normal waking day. Sixteen morning and 15 evening types were recorded at two individually adapted time points (1.5 versus 10.5 hours spent awake) while performing the Stroop paradigm. Results show that interference-related hemodynamic responses are maintained or even increased in evening types from the subjective morning to the subjective evening in a set of brain areas playing a pivotal role in successful inhibitory functioning, whereas they decreased in morning types under the same conditions. Furthermore, during the evening hours, activity in a posterior hypothalamic region putatively involved in sleep-wake regulation correlated in a chronotype-specific manner with slow wave activity at the beginning of the night, an index of accumulated homeostatic sleep pressure. These results shed light into the cerebral mechanisms underlying inter-individual differences of higher-order cognitive state maintenance under normally entrained day-night conditions