Self-paced Movement Intention Detection from Human Brain Signals: Invasive and Non-invasive EEG

Neural signatures of humans' movement intention can be exploited by future neuroprosthesis. We propose a method for detecting self-paced upper limb movement intention from brain signals acquired with both invasive and noninvasive methods. In the first study with scalp electroencephalograph (EEG) signals from healthy controls, we report single trial detection of movement intention using movement related potentials (MRPs) in a frequency range between 0.1 to 1 Hz. Movement intention can be detected above chance level (p<0.05) on average 460 ms before the movement onset with low detection rate during the on-movement intention period. Using intracranial EEG (iEEG) from one epileptic subject, we detect movement intention as early as 1500 ms before movement onset with accuracy above 90% using electrodes implanted in the bilateral supplementary motor area (SMA). The coherent results obtained with non-invasive and invasive method and its generalization capabilities across different days of recording, strengthened the theory that self-paced movement intention can be detected before movement initiation for the advancement in robot-assisted neurorehabilitation.

Clinical outcome after a reactive hypothermic EEG following cardiac arrest.

BACKGROUND: Reactive electroencephalography (EEG) background during therapeutic hypothermia (TH) is related to favorable prognosis after cardiac arrest (CA), but its predictive value is not 100 %. The aim of this study was to investigate outcome predictors after a first reactive EEG recorded during TH after CA. METHODS: We studied a cohort of consecutive comatose adults admitted between February 2008 and November 2012, after successful resuscitation from CA, selecting patients with reactive EEG during TH. Outcome was assessed at three months, and categorized as survivors and non-survivors (no patient was in vegetative state). Demographics, clinical variables, EEG features, serum neuron-specific enolase (NSE) and procalcitonin, were compared using uni- and multivariable analyses. RESULTS: A total of 290 patients were treated with TH after cardiac arrest; 146 had an EEG during TH, which proved reactive in 90 of them; 77 (86 %) survived and 13 (14 %) died (without recovery from coma). The group of non-survivors had a higher occurrence of discontinuous EEG (p = 0.006; multivariate analysis p = 0.026), and a higher serum NSE peak (p = 0.021; multivariate analysis p = 0.014); conversely, demographics, and other clinical variables including serum procalcitonin did not differ. CONCLUSIONS: A discontinuous EEG and high serum NSE are associated with mortality after CA in patients with poor outcome despite a reactive hypothermic EEG. This suggests more severe cerebral damage, but not to higher extent of systemic disease.

Homeostatic and circadian contribution to EEG and molecular state variables of sleep regulation.

STUDY OBJECTIVES: Besides their well-established role in circadian rhythms, our findings that the forebrain expression of the clock-genes Per2 and Dbp increases and decreases, respectively, in relation to time spent awake suggest they also play a role in the homeostatic aspect of sleep regulation. Here, we determined whether time of day modulates the effects of elevated sleep pressure on clock-gene expression. Time of day effects were assessed also for recognized electrophysiological (EEG delta power) and molecular (Homer1a) markers of sleep homeostasis. DESIGN: EEG and qPCR data were obtained for baseline and recovery from 6-h sleep deprivation starting at ZT0, -6, -12, or -18. SETTING: Mouse sleep laboratory. PARTICIPANTS: Male mice. INTERVENTIONS: Sleep deprivation. RESULTS: The sleep-deprivation induced changes in Per2 and Dbp expression importantly varied with time of day, such that Per2 could even decrease during sleep deprivations occurring at the decreasing phase in baseline. Dbp showed similar, albeit opposite dynamics. These unexpected results could be reliably predicted assuming that these transcripts behave according to a driven damped harmonic oscillator. As expected, the sleep-wake distribution accounted for a large degree of the changes in EEG delta power and Homer1a. Nevertheless, the sleep deprivation-induced increase in delta power varied also with time of day with higher than expected levels when recovery sleep started at dark onset. CONCLUSIONS: Per2 and delta power are widely used as exclusive state variables of the circadian and homeostatic process, respectively. Our findings demonstrate a considerable cross-talk between these two processes. As Per2 in the brain responds to both sleep loss and time of day, this molecule is well positioned to keep track of and to anticipate homeostatic sleep need. CITATION: Curie T; Mongrain V; Dorsaz S; Mang GM; Emmenegger Y; Franken P. Homeostatic and circadian contribution to EEG and molecular state variables of sleep regulation. SLEEP 2013;36(3):311-323.

Automated analysis of background EEG and reactivity during therapeutic hypothermia in comatose patients after cardiac arrest.

Visual analysis of electroencephalography (EEG) background and reactivity during therapeutic hypothermia provides important outcome information, but is time-consuming and not always consistent between reviewers. Automated EEG analysis may help quantify the brain damage. Forty-six comatose patients in therapeutic hypothermia, after cardiac arrest, were included in the study. EEG background was quantified with burst-suppression ratio (BSR) and approximate entropy, both used to monitor anesthesia. Reactivity was detected through change in the power spectrum of signal before and after stimulation. Automatic results obtained almost perfect agreement (discontinuity) to substantial agreement (background reactivity) with a visual score from EEG-certified neurologists. Burst-suppression ratio was more suited to distinguish continuous EEG background from burst-suppression than approximate entropy in this specific population. Automatic EEG background and reactivity measures were significantly related to good and poor outcome. We conclude that quantitative EEG measurements can provide promising information regarding current state of the patient and clinical outcome, but further work is needed before routine application in a clinical setting.

Attenuated asymmetry of functional connectivity in schizophrenia: a high-resolution EEG study.

The interhemispheric asymmetries that originate from connectivity-related structuring of the cortex are compromised in schizophrenia (SZ). Under the assumption that such abnormalities affect functional connectivity, we analyzed its correlate-EEG synchronization-in SZ patients and matched controls. We applied multivariate synchronization measures based on Laplacian EEG and tuned to various spatial scales. Compared to the controls who had rightward asymmetry at a local level (EEG power), rightward anterior and leftward posterior asymmetries at an intraregional level (1st and 2nd order S-estimator), and rightward global asymmetry (hemispheric S-estimator), SZ patients showed generally attenuated asymmetry, the effect being strongest for intraregional synchronization in the alpha and beta bands. The abnormalities of asymmetry increased with the duration of the disease and correlated with the negative symptoms. We discuss the tentative links between these findings and gross anatomical asymmetries, including the cerebral torque and gyrification pattern, in normal subjects and SZ patients.

Decoding stimulus-related information from single-trial EEG responses based on voltage topographies

Neuroimaging studies typically compare experimental conditions using average brain responses, thereby overlooking the stimulus-related information conveyed by distributed spatio-temporal patterns of single-trial responses. Here, we take advantage of this rich information at a single-trial level to decode stimulus-related signals in two event-related potential (ERP) studies. Our method models the statistical distribution of the voltage topographies with a Gaussian Mixture Model (GMM), which reduces the dataset to a number of representative voltage topographies. The degree of presence of these topographies across trials at specific latencies is then used to classify experimental conditions. We tested the algorithm using a cross-validation procedure in two independent EEG datasets. In the first ERP study, we classified left- versus right-hemifield checkerboard stimuli for upper and lower visual hemifields. In a second ERP study, when functional differences cannot be assumed, we classified initial versus repeated presentations of visual objects. With minimal a priori information, the GMM model provides neurophysiologically interpretable features - vis à vis voltage topographies - as well as dynamic information about brain function. This method can in principle be applied to any ERP dataset testing the functional relevance of specific time periods for stimulus processing, the predictability of subject's behavior and cognitive states, and the discrimination between healthy and clinical populations.

Proposition: Limbic encephalitis may represent limbic status epilepticus. A review of clinical and EEG characteristics.

Limbic encephalitis (LE) with waxing and waning neuropsychiatric manifestations including behavioral, personality, psychiatric, and memory changes can evolve over days to months. Many features of LE show remarkable overlap with the characteristics of mesial-temporal (limbic) status epilepticus (MTLSE or LSE). With LE, these prolonged impaired states are assumed not to be due to ongoing epileptic activity or MTLSE, because scalp EEGs usually show no epileptiform spike-wave activity; cycling behavioral and motor changes are attributed to LE; there may be little immediate improvement with antiepileptic drugs (AEDs); and of course, implanted electrodes are rarely used. Conversely, it is known that in pre-surgical patients with refractory limbic epilepsy, implanted electrodes have revealed limbic seizures that cannot be seen at the scalp. This paper assembles a chain of inferences to advance the proposition that refractory LE might represent LSE more often than is thought, and that implanted electrodes should be considered in some cases. We present two cases that suggest that LE was also LSE, one of which warranted implanted electrodes (case 1).

Single-trial topographic analysis of human EEG: A new image of event-related potentials

We present a novel approach for analyzing single-trial electroencephalography (EEG) data, using topographic information. The method allows for visualizing event-related potentials using all the electrodes of recordings overcoming the problem of previous approaches that required electrode selection and waveforms filtering. We apply this method to EEG data from an auditory object recognition experiment that we have previously analyzed at an ERP level. Temporally structured periods were statistically identified wherein a given topography predominated without any prior information about the temporal behavior. In addition to providing novel methods for EEG analysis, the data indicate that ERPs are reliably observable at a single-trial level when examined topographically.

EEG alpha activity reflects motor preparation rather than the mode of action selection

Alpha-band activity (8-13 Hz) is not only suppressed by sensory stimulation and movements, but also modulated by attention, working memory and mental tasks, and could be sensitive to higher motor control functions. The aim of the present study was to examine alpha oscillatory activity during the preparation of simple left or right finger movements, contrasting the external and internal mode of action selection. Three preparation conditions were examined using a precueing paradigm with S1 as the preparatory and S2 as the imperative cue: Full, laterality instructed by S1; Free, laterality freely selected and None, laterality instructed by S2. Time-frequency (TF) analysis was performed in the alpha frequency range during the S1-S2 interval, and alpha motor-related amplitude asymmetries (MRAA) were also calculated. The significant MRAA during the Full and Free conditions indicated effective external and internal motor response preparation. In the absence of specific motor preparation (None), a posterior alpha event-related desynchronization (ERD) dominated, reflecting the main engagement of attentional resources. In Full and Free motor preparation, posterior alpha ERD was accompanied by a midparietal alpha event-related synchronization (ERS), suggesting a concomitant inhibition of task-irrelevant visual activity. In both Full and Free motor preparation, analysis of alpha power according to MRAA amplitude revealed two types of functional activation patterns: (1) a motor alpha pattern, with predominantly midparietal alpha ERS and large MRAA corresponding to lateralized motor activation/visual inhibition and (2) an attentional alpha pattern, with dominating right posterior alpha ERD and small MRAA reflecting visuospatial attention. The present results suggest that alpha oscillatory patterns do not resolve the selection mode of action, but rather distinguish separate functional strategies of motor preparation.

Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design.

BACKGROUND: Electroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations. METHODS/DESIGN: In the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented. DISCUSSION: A well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool. TRIAL REGISTRATION: The TTM-trial is registered at ClinicalTrials.gov (NCT01020916).

EEG Patterns and Imaging Correlations in Encephalopathy: Encephalopathy Part II.

SUMMARY:: The EEG patterns seen with encephalopathies can be correlated to cerebral imaging findings including head computerized tomography and MRI. Background slowing without slow-wave intrusion is seen with acute and chronic cortical impairments that spare subcortical white matter. Subcortical/white matter structural abnormalities or hydrocephalus may produce projected slow-wave activity, while clinical entities involving both cortical and subcortical regions (diffuse cerebral abnormalities) engender both background slowing and slow-wave activity. Triphasic waves are seen with hepatic and renal insufficiency or medication toxicities (e.g., lithium, baclofen) in the absence of a significant cerebral imaging abnormality, Conversely, subcortical/white matter abnormalities may facilitate the appearance of triphasic waves without significant hepatic, renal, or toxic comorbidities. More specific syndromes, such as Jakob-Creutzfeldt disease, autoimmune limbic encephalitis, autoimmune corticosteroid-responsive encephalopathy with thyroid autoimmunity, sepsis-associated encephalopathy, and acute disseminated encephalomyelitis, have imaging/EEG changes that are variable but which may include slowing and epileptiform activity. This overview highlighting EEG-imaging correlations may help the treating physician in the diagnosis, and hence the appropriate treatment, of patients with encephalopathy.

Yield of intermittent versus continuous EEG in comatose survivors of cardiac arrest treated with hypothermia.

INTRODUCTION: Electroencephalography (EEG) has a central role in the outcome prognostication in subjects with anoxic/hypoxic encephalopathy following a cardiac arrest (CA). Continuous EEG monitoring (cEEG) has been consistently developed and studied; however, its yield as compared to repeated standard EEG (sEEG) is unknown. METHODS: We studied a prospective cohort of comatose adults treated with therapeutic hypothermia (TH) after a CA. cEEG data regarding background activity and epileptiform components were compared to two 20 minute sEEG extracted from the cEEG recording (one during TH, and one in early normothermia). RESULTS: In this cohort, 34 recordings were studied. During TH, the agreement between cEEG and sEEG was 97.1% (95% CI: 84.6 - 99.9%) for background discontinuity and reactivity evaluation, while it was 94.1% (95% CI 80.3 - 99.2%) regarding epileptiform activity. In early normothermia, we did not find any discrepancies. Thus, concordance was very good during TH (kappa 0.83), and optimal during normothermia (kappa=1). The median delay between CA and the first EEG reactivity testing was 18 hours (range: 4.75 - 25) for patients with perfect agreement and 10 hours (range: 5.75 - 10.5) for the three patients in whom there were discordant findings (P=0.02, Wilcoxon). CONCLUSION: Standard intermittent EEG has comparable performance than continuous EEG both for variables important for outcome prognostication (EEG reactivity) and identification of epileptiform transients in this relatively small sample of comatose survivors of CA. This finding has an important practical implication, especially for centers where EEG resources are limited.

Synchronizability of EEG-Based Functional Networks in Early Alzheimer's Disease.

Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy control subjects at no-task, eyes-closed condition. The cross-correlation of artifact-free EEGs was used to construct brain functional networks. The extracted networks were then tested for their synchronization properties by calculating the eigenratio of the Laplacian matrix of the connection graph, i.e., the largest eigenvalue divided by the second smallest one. In AD patients, we found an increase in the eigenratio, i.e., a decrease in the synchronizability of brain networks across delta, alpha, beta, and gamma EEG frequencies within the wide range of network costs. The finding indicates the destruction of functional brain networks in early AD.

Prognostic value of continuous eeg monitoring during therapeutic hypothermia in patients with coma after cardiac arrest

INTRODUCTION: Continuous EEG (cEEG) is increasingly used to monitor brain function in neuro-ICU patients. However, its value in patients with coma after cardiac arrest (CA), particularly in the setting of therapeutic hypothermia (TH), is only beginning to be elucidated. The aim of this study was to examine whether cEEG performed during TH may predict outcome. METHODS: From April 2009 to April 2010, we prospectively studied 34 consecutive comatose patients treated with TH after CA who were monitored with cEEG, initiated during hypothermia and maintained after rewarming. EEG background reactivity to painful stimulation was tested. We analyzed the association between cEEG findings and neurologic outcome, assessed at 2 months with the Glasgow-Pittsburgh Cerebral Performance Categories (CPC). RESULTS: Continuous EEG recording was started 12 ± 6 hours after CA and lasted 30 ± 11 hours. Nonreactive cEEG background (12 of 15 (75%) among nonsurvivors versus none of 19 (0) survivors; P < 0.001) and prolonged discontinuous "burst-suppression" activity (11 of 15 (73%) versus none of 19; P < 0.001) were significantly associated with mortality. EEG seizures with absent background reactivity also differed significantly (seven of 15 (47%) versus none of 12 (0); P = 0.001). In patients with nonreactive background or seizures/epileptiform discharges on cEEG, no improvement was seen after TH. Nonreactive cEEG background during TH had a positive predictive value of 100% (95% confidence interval (CI), 74 to 100%) and a false-positive rate of 0 (95% CI, 0 to 18%) for mortality. All survivors had cEEG background reactivity, and the majority of them (14 (74%) of 19) had a favorable outcome (CPC 1 or 2). CONCLUSIONS: Continuous EEG monitoring showing a nonreactive or discontinuous background during TH is strongly associated with unfavorable outcome in patients with coma after CA. These data warrant larger studies to confirm the value of continuous EEG monitoring in predicting prognosis after CA and TH.