Diagnostic yield of short-term video-EEG monitoring for epilepsy and PNESs: a European assessment.

INTRODUCTION: Although long-term video-EEG monitoring (LVEM) is routinely used to investigate paroxysmal events, short-term video-EEG monitoring (SVEM) lasting <24 h is increasingly recognized as a cost-effective tool. Since, however, relatively few studies addressed the yield of SVEM among different diagnostic groups, we undertook the present study to investigate this aspect. METHODS: We retrospectively analyzed 226 consecutive SVEM recordings over 6 years. All patients were referred because routine EEGs were inconclusive. Patients were classified into 3 suspected diagnostic groups: (1) group with epileptic seizures, (2) group with psychogenic nonepileptic seizures (PNESs), and (3) group with other or undetermined diagnoses. We assessed recording lengths, interictal epileptiform discharges, epileptic seizures, PNESs, and the definitive diagnoses obtained after SVEM. RESULTS: The mean age was 34 (±18.7) years, and the median recording length was 18.6 h. Among the 226 patients, 127 referred for suspected epilepsy - 73 had a diagnosis of epilepsy, none had a diagnosis of PNESs, and 54 had other or undetermined diagnoses post-SVEM. Of the 24 patients with pre-SVEM suspected PNESs, 1 had epilepsy, 12 had PNESs, and 11 had other or undetermined diagnoses. Of the 75 patients with other diagnoses pre-SVEM, 17 had epilepsy, 11 had PNESs, and 47 had other or undetermined diagnoses. After SVEM, 15 patients had definite diagnoses other than epilepsy or PNESs, while in 96 patients, diagnosis remained unclear. Overall, a definitive diagnosis could be reached in 129/226 (57%) patients. CONCLUSIONS: This study demonstrates that in nearly 3/5 patients without a definitive diagnosis after routine EEG, SVEM allowed us to reach a diagnosis. This procedure should be encouraged in this setting, given its time-effectiveness compared with LVEM.

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Binding under Conflict Conditions: State-Space Analysis of Multivariate EEG Synchronization.

Real-world objects are often endowed with features that violate Gestalt principles. In our experiment, we examined the neural correlates of binding under conflict conditions in terms of the binding-by-synchronization hypothesis. We presented an ambiguous stimulus ("diamond illusion") to 12 observers. The display consisted of four oblique gratings drifting within circular apertures. Its interpretation fluctuates between bound ("diamond") and unbound (component gratings) percepts. To model a situation in which Gestalt-driven analysis contradicts the perceptually explicit bound interpretation, we modified the original diamond (OD) stimulus by speeding up one grating. Using OD and modified diamond (MD) stimuli, we managed to dissociate the neural correlates of Gestalt-related (OD vs. MD) and perception-related (bound vs. unbound) factors. Their interaction was expected to reveal the neural networks synchronized specifically in the conflict situation. The synchronization topography of EEG was analyzed with the multivariate S-estimator technique. We found that good Gestalt (OD vs. MD) was associated with a higher posterior synchronization in the beta-gamma band. The effect of perception manifested itself as reciprocal modulations over the posterior and anterior regions (theta/beta-gamma bands). Specifically, higher posterior and lower anterior synchronization supported the bound percept, and the opposite was true for the unbound percept. The interaction showed that binding under challenging perceptual conditions is sustained by enhanced parietal synchronization. We argue that this distributed pattern of synchronization relates to the processes of multistage integration ranging from early grouping operations in the visual areas to maintaining representations in the frontal networks of sensory memory.

Robust discrimination between EEG responses to categories of environmental sounds in early coma.

Humans can recognize categories of environmental sounds, including vocalizations produced by humans and animals and the sounds of man-made objects. Most neuroimaging investigations of environmental sound discrimination have studied subjects while consciously perceiving and often explicitly recognizing the stimuli. Consequently, it remains unclear to what extent auditory object processing occurs independently of task demands and consciousness. Studies in animal models have shown that environmental sound discrimination at a neural level persists even in anesthetized preparations, whereas data from anesthetized humans has thus far provided null results. Here, we studied comatose patients as a model of environmental sound discrimination capacities during unconsciousness. We included 19 comatose patients treated with therapeutic hypothermia (TH) during the first 2 days of coma, while recording nineteen-channel electroencephalography (EEG). At the level of each individual patient, we applied a decoding algorithm to quantify the differential EEG responses to human vs. animal vocalizations as well as to sounds of living vocalizations vs. man-made objects. Discrimination between vocalization types was accurate in 11 patients and discrimination between sounds from living and man-made sources in 10 patients. At the group level, the results were significant only for the comparison between vocalization types. These results lay the groundwork for disentangling truly preferential activations in response to auditory categories, and the contribution of awareness to auditory category discrimination.

Drug refractory epilepsy in brain damage: effect of dextromethorphan on EEG in four patients.

High doses of dextromethorphan (20-42 mg/kg/day) were given to four critically ill children with seizures and frequent epileptiform abnormalities in the EEG that were refractory to antiepileptic drugs. Their acute diseases (hypoxia, head trauma and hypoxia, neurodegenerative disease, hypoglycaemia) were thought to be due in part to N-methyl-D-aspartate (NMDA) receptor mediated processes. Treatment with dextromethorphan, an NMDA receptor antagonist, was started between 48 hours and 14 days after the critical incident. In three patients the EEG improved considerably within 48 hours and seizures ceased within 72 hours. In the patient with neurodegenerative disease the effect on the EEG was impressive, but the seizures were not controlled. Despite the improvement of the EEG the clinical outcome was poor in all children: three died in the critical period or due to the progressing disease; the patient with hypoglycaemia survived with severe neurological sequelae. Plasma concentrations of dextromethorphan varied between 74-1730 ng/ml and its metabolite dextrorphan varied between 349-3790 ng/ml. In one patient corresponding concentrations in CSF were lower than those in plasma. The suppression of epileptic discharges by the doses of dextromethorphan given suggests that such doses are sufficient to block NMDA receptors.

Sleep EEG changes after middle cerebral artery infarcts in mice: different effects of striatal and cortical lesions.

STUDY OBJECTIVES: Hemispheric stroke in humans is associated with sleep-wake disturbances and sleep electroencephalogram (EEG) changes. The correlation between these changes and stroke extent remains unclear. In the absence of experimental data, we assessed sleep EEG changes after focal cerebral ischemia of different extensions in mice. DESIGN: Following electrode implantation and baseline sleep-wake EEG recordings, mice were submitted to sham surgery (control group), 30 minutes of intraluminal middle cerebral artery (MCA) occlusion (striatal stroke), or distal MCA electrocoagulation (cortical stroke). One and 12 days after stroke, sleep-wake EEG recordings were repeated. The EEG recorded from the healthy hemisphere was analyzed visually and automatically (fast Fourier analysis) according to established criteria. MEASUREMENTS AND RESULTS: Striatal stroke induced an increase in non-rapid eye movement (NREM) sleep and a reduction of rapid eye movement sleep. These changes were detectable both during the light and the dark phase at day 1 and persisted until day 12 after stroke. Cortical stroke induced a less-marked increase in NREM sleep, which was present only at day 1 and during the dark phase. In cortical stroke, the increase in NREM sleep was associated in the wake EEG power spectra, with an increase in the theta and a reduction in the beta activity. CONCLUSION: Cortical and striatal stroke lead to different sleep-wake EEG changes in mice, which probably reflect variable effects on sleep-promoting and wakefulness-maintaining neuronal networks.

Visual stimulus-dependent changes in interhemispheric EEG coherence in humans.

We analyzed the coherence of electroencephalographic (EEG) signals recorded symmetrically from the two hemispheres, while subjects (n = 9) were viewing visual stimuli. Considering the many common features of the callosal connectivity in mammals, we expected that, as in our animal studies, interhemispheric coherence (ICoh) would increase only with bilateral iso-oriented gratings located close to the vertical meridian of the visual field, or extending across it. Indeed, a single grating that extended across the vertical meridian significantly increased the EEG ICoh in normal adult subjects. These ICoh responses were obtained from occipital and parietal derivations and were restricted to the gamma frequency band. They were detectable with different EEG references and were robust across and within subjects. Other unilateral and bilateral stimuli, including identical gratings that were effective in anesthetized animals, did not affect ICoh in humans. This fact suggests the existence of regulatory influences, possibly of a top-down kind, on the pattern of callosal activation in conscious human subjects. In addition to establishing the validity of EEG coherence analysis for assaying cortico-cortical connectivity, this study extends to the human brain the finding that visual stimuli cause interhemispheric synchronization, particularly in frequencies of the gamma band. It also indicates that the synchronization is carried out by cortico-cortical connection and suggests similarities in the organization of visual callosal connections in animals and in man.

Imaging EEG synchronization in schizophrenia patients with S-estimator

Recently a new measure of the cooperative behavior of simultaneous time series was introduced (Carmeli et al. NeuroImage 2005). This measure called S-estimator is defined from the embedding dimension in a state space. S-estimator quantifies the amount of synchronization within a data set by comparing the actual dimensionality of the set with the expected full dimensionality of the asynchronous set. It has the advantage of being a multivariate measure over traditionally used in systems neuroscience bivariate measures of synchronization. Multivariate measures of synchronization are of particular interest for applications in the field of modern multichannel EEG research, since they easily allow mapping of local and/or regional synchronization and are compatible with other imaging techniques. We applied Sestimator to the analysis of EEG synchronization in schizophrenia patients vs. matched controls. The whole-head mapping with S-estimator revealed a specific pattern of local synchronization in schizophrenia patients. The differences in the landscape of synchronization included decreased local synchronization in the territories over occipital and midline areas and increased synchronization over temporal areas. In frontal areas, the S-estimator revealed a tendency for an asymmetry: decreased S-values over the left hemisphere were adjacent to increased values over the right hemisphere. Separate calculations showed reproducibility of this pattern across the main EEG frequency bands. The maintenance of the same synchronization landscape across EEG frequencies probably implies the structural changes in the cortical circuitry of schizophrenia patients. These changes are regionally specific and suggest that schizophrenia is a misconnectivity rather than hypo- or hyper-connectivity disorder.

Adaptive filtering methods for identifying cross-frequency couplings in human EEG.

Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.

Age differences in the EEG N2 and P3 components during an interference task

The age-related increase in interference susceptibility has been well documented and largely attributed to a deficit in inhibition. In the present study, event-related potentials were used to investigate EEG correlates of inhibitory processing in an interference "Arrow" task. A specific interest was addressed to theN2 and P3 components that respectively refers to conflict monitoring and to efficiency of inhibition processes (Anguera et al,. 2011). Younger (N=10, Mage=24.6) and older (N=10, Mage=65.5) participants were invited to perform a task consisting in deciding, as fast and accurately as possible, whether an arrow presented on a computer screen points to the left or the right, irrespective of its position on the screen (left, middle or right). Responses were provided by key-presses using the left and right indexes. Three conditions were considered: congruent (arrow pointing to the same direction as that of the side of the screen on which it appears), incongruent (arrow pointing to the opposite direction), and neutral (arrow presented at the center of the screen). A total of 56 trials per conditions were performed. Behaviorally, the results showed that in the incongruent condition the percent of correct responses significantly decreased in both groups. After adjustment with simple RT (additional control task), the increased RTs obtained in the old group were significantly more pronounced in the incongruent condition. With respect to electrophysiological data, results showed that frontal site (Fz), the N2 amplitude was significantly larger for the younger as compared to the older (- 2.55 μV vs. -0.62 μV respectively) whatever the condition. At central site (Cz), the P3 amplitude significantly decreased in the older compared to the younger in the incongruent condition only. Our findings suggest that the increased RTs observed in older participants during the incongruent condition is more specifically linked to late cognitive resources involved in inhibiting prepotent response tendencies rather than associated with earlier stages of treatment dedicated to conflict monitoring.

Influence of quinidine on the pharmacokinetics of trimipramine and on its effect on the waking EEG of healthy volunteers. A pilot study on two subjects.

The pharmacokinetics and pharmacodynamics (waking EEG) of 75 mg trimipramine taken orally were determined in two healthy volunteers on two separate occasions, once without and once after comedication with 2 x 50 mg quinidine. Quinidine, a potent cytochrome P-450IID6 inhibitor, is used as a pharmacological tool to mimic a lack of this enzyme in man. In this study, it markedly altered the pharmacokinetics of trimipramine, almost doubling its plasma half-life and decreasing its apparent clearance and volume of distribution. These results strongly suggest that trimipramine is a substrate of cytochrome P-450IID6. These modifications of trimipramine metabolism were accompanied by measurable changes in some EEG variables, most notably with regard to the relative power in the alpha and theta bands, which showed higher and longer-lasting effects of trimipramine. Since cytochrome P-450IID6 is deficient in 5-10% of Caucasian subjects, this may have consequences in trimipramine-treated subjects, especially with regard to the effects of the drug on the EEG.

Towards the utilization of EEG as a brain imaging tool.

Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications.

Synchronization of EEG: bivariate and multivariate measures.

Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs.We found widespread correlations between BM and MM, which were almost frequency-independent for all the measures except coherence. The analysis of the behavior of synchronization measures in simulated settings with variable coupling strength, connection probability, and parameter mismatch showed that some of them, including S-estimator, S-Renyi, omega, and coherence, aremore sensitive to linear interdependences,while others, like mutual information and phase locking value, are more responsive to nonlinear effects. Onemust consider these properties together with the fact thatMM are computationally less expensive and, therefore, more efficient for the large-scale data sets than BM while choosing a synchronization measure for EEG analysis.