Delayed Cyclic Activity Development on Early Amplitude-Integrated EEG in the Preterm Infant with Brain Lesions.

Background: Maturation of amplitude-integrated electroencephalogram (aEEG) activity is influenced by both gestational age (GA) and postmenstrual age. It is not fully known how this process is influenced by cerebral lesions. Objective: To compare early aEEG developmental changes between preterm newborns with different degrees of cerebral lesions on cranial ultrasound (cUS). Methods: Prospective cohort study on preterm newborns with GA <32.0 weeks, undergoing continuous aEEG recording during the first 84 h after birth. aEEG characteristics were qualitatively and quantitatively evaluated using pre-established criteria. Based on cUS findings three groups were formed: normal (n = 78), mild (n = 20), and severe cerebral lesions (n = 6). Linear mixed models for repeated measures were used to analyze aEEG maturational trajectories. Results: 104 newborns with a mean GA (range) 29.5 (24.4-31.7) weeks, and birth weight 1,220 (580-2,020) g were recruited. Newborns with severe brain lesions started with similar aEEG scores and tendentially lower aEEG amplitudes than newborns without brain lesions, and showed a slower development of the cyclic activity (p < 0.001), but a more rapid increase of the maximum and minimum aEEG amplitudes (p = 0.002 and p = 0.04). Conclusions: Preterm infants with severe cerebral lesions manifest a maturational delay in the aEEG cyclic activity already early after birth, but show a catch-up of aEEG amplitudes to that of newborns without cerebral lesions. Changes in the maturational aEEG pattern may be a marker of severe neurological lesions in the preterm infant.

Development of projections from auditory to visual areas in the cat.

In newborn kittens, cortical auditory areas (including AI and AII) send transitory projections to ipsi- and contralateral visual areas 17 and 18. These projections originate mainly from neurons in supragranular layers but also from a few in infragranular layers (Innocenti and Clarke: Dev. Brain Res. 14:143-148, '84; Clarke and Innocenti: J. Comp. Neurol. 251:1-22, '86). The postnatal development of these projections was studied with injections of anterograde tracers (wheat germ agglutinin-horseradish peroxidase [WGA-HRP]) in AI and AII and of retrograde tracers (WGA-HRP, fast blue, diamidino yellow, rhodamine-labeled latex beads) in areas 17 and 18. It was found that the projections are nearly completely eliminated in development, this, by the end of the first postnatal month. Until then, most of the transitory axons seem to remain confined to the white matter and the depth of layer VI; a few enter it further but do not appear to form terminal arbors. As for other transitory cortical projections the disappearance of the transitory axons seems not to involve death of their neurons of origin. In kittens older than 1 month and in normal adult cats, retrograde tracer injections restricted to, or including, areas 17 and 18 label only a few neurons in areas AI and AII. Unlike the situation in the kitten, nearly all of these are restricted to layers V and VI. A similar distribution of neurons projecting from auditory to visual areas is found in adult cats bilaterally enucleated at birth, which suggests that the postnatal elimination of the auditory-to-visual projection is independent of visual experience and more generally of information coming from the retina.

EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning ofEEGdata are then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9).

EEG-based functional networks in schizophrenia.

Schizophrenia is often considered as a dysconnection syndrome in which, abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. In this article we apply the graph theoretic measures to brain functional networks based on the resting EEGs of fourteen schizophrenic patients in comparison with those of fourteen matched control subjects. The networks were extracted from common-average-referenced EEG time-series through partial and unpartial cross-correlation methods. Unpartial correlation detects functional connectivity based on direct and/or indirect links, while partial correlation allows one to ignore indirect links. We quantified the network properties with the graph metrics, including mall-worldness, vulnerability, modularity, assortativity, and synchronizability. The schizophrenic patients showed method-specific and frequency-specific changes especially pronounced for modularity, assortativity, and synchronizability measures. However, the differences between schizophrenia patients and normal controls in terms of graph theory metrics were stronger for the unpartial correlation method.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

EEG signal analysis via a cleaning procedure based on multivariate empirical mode decomposition

Artifacts are present in most of the electroencephalography (EEG) recordings, making it difficult to interpret or analyze the data. In this paper a cleaning procedure based on a multivariate extension of empirical mode decomposition is used to improve the quality of the data. This is achieved by applying the cleaning method to raw EEG data. Then, a synchrony measure is applied on the raw and the clean data in order to compare the improvement of the classification rate. Two classifiers are used, linear discriminant analysis and neural networks. For both cases, the classification rate is improved about 20%.

Early EEG correlates of neuronal injury after brain anoxia.

OBJECTIVES: EEG and serum neuron-specific enolase (NSE) are used for outcome prognostication in patients with postanoxic coma; however, it is unclear if EEG abnormalities reflect transient neuronal dysfunction or neuronal death. To assess this question, EEG abnormalities were correlated with NSE. Moreover, NSE cutoff values and hypothermic EEG features related with poor outcome were explored.¦METHODS: In a prospective cohort of 61 adults treated with therapeutic hypothermia (TH) after cardiac arrest (CA), multichannel EEG recorded during TH was assessed for background reactivity and continuity, presence of epileptiform transients, and correlated with serum NSE collected at 24-48 hours after CA. Demographic, clinical, and functional outcome data (at 3 months) were collected and integrated in the analyses.¦RESULTS: In-hospital mortality was 41%, and 82% of survivors had good neurologic outcome at 3 months. Serum NSE and EEG findings were strongly correlated (Spearman rho = 0.45; p < 0.001). Median NSE peak values were higher in patients with unreactive EEG background (p < 0.001) and discontinuous patterns (p = 0.001). While all subjects with nonreactive EEG died, 5 survivors (3 with good outcome) had NSE levels >33 μg/L.¦CONCLUSION: The correlation between EEG during TH and serum NSE levels supports the hypothesis that early EEG alterations reflect permanent neuronal damage. Furthermore, this study confirms that absent EEG background reactivity and presence of epileptiform transients are robust predictors of poor outcome after CA, and that survival with good neurologic recovery is possible despite serum NSE levels> 33 μg/L. This underscores the importance of multimodal assessments in this setting.

Correlations between negative-induced cerebral dynamics and idiopathic intellectual disability: an EEG study

Intellectual disability has long been associated with deficits in socio-emotional processing. However, studies investigating brain dynamics of maladaptive socio-emotional skills associated with intellectual disability are scarce. Here, we compared differences in brain activity between low intelligence quotient (I.Q.<75, N=13) and normal controls (N=15) while evaluating their subjective emotions. Positive (P) and negative (N) valenced pictures were presented one at a time to participants of both groups, at a rate of ¾. The task required that each participant evaluate their subjective emotion and press a predefined push-button when done, alternatively P and N. Electroencephalographic (EEG) signals were continuously recorded, and the 1000ms time window following each picture was analyzed offline for power in frequency domain. Alpha low (8-10Hz) and upper (10-13Hz) frequency bands were then compared for both groups and for both P and N emotions in 12 distributed scalp electrodes. The qualitative evaluation of emotions was similar between both groups, with constant longer reaction times for the low IQ participants. The EEG signal comparison shows marked power decrease in upper alpha frequency range for N emotions in low intelligence group. Otherwise no significant difference was noticed between low and normal IQ. Main findings of the present study are (1) results do not support the hypothesis that impairment in developmental intelligence roots in maladaptive emotional processing; (2) the strong alpha power suppression during negative-induced emotions suggests the involvement of an extended neural network and more effortful inhibition processes than positive ones. We call for further studies with a larger sample.

Differential effects of GABAB receptor subtypes, {gamma}-hydroxybutyric Acid, and Baclofen on EEG activity and sleep regulation.

The role of GABA(B) receptors in sleep is still poorly understood. GHB (γ-hydroxybutyric acid) targets these receptors and is the only drug approved to treat the sleep disorder narcolepsy. GABA(B) receptors are obligate dimers comprised of the GABA(B2) subunit and either one of the two GABA(B1) subunit isoforms, GABA(B1a) and GABA(B1b). To better understand the role of GABA(B) receptors in sleep regulation, we performed electroencephalogram (EEG) recordings in mice devoid of functional GABA(B) receptors (1(-/-) and 2(-/-)) or lacking one of the subunit 1 isoforms (1a(-/-) and 1b(-/-)). The distribution of sleep over the day was profoundly altered in 1(-/-) and 2(-/-) mice, suggesting a role for GABA(B) receptors in the circadian organization of sleep. Several other sleep and EEG phenotypes pointed to a more prominent role for GABA(B1a) compared with the GABA(B1b) isoform. Moreover, we found that GABA(B1a) protects against the spontaneous seizure activity observed in 1(-/-) and 2(-/-) mice. We also evaluated the effects of the GHB-prodrug GBL (γ-butyrolactone) and of baclofen (BAC), a high-affinity GABA(B) receptor agonist. Both drugs induced a state distinct from physiological sleep that was not observed in 1(-/-) and 2(-/-) mice. Subsequent sleep was not affected by GBL whereas BAC was followed by a delayed hypersomnia even in 1(-/-) and 2(-/-) mice. The differential effects of GBL and BAC might be attributed to differences in GABA(B)-receptor affinity. These results also indicate that all GBL effects are mediated through GABA(B) receptors, although these receptors do not seem to be involved in mediating the BAC-induced hypersomnia.

Auditory spatio-temporal brain dynamics and their consequences for multisensory interactions in humans.

Recent multisensory research has emphasized the occurrence of early, low-level interactions in humans. As such, it is proving increasingly necessary to also consider the kinds of information likely extracted from the unisensory signals that are available at the time and location of these interaction effects. This review addresses current evidence regarding how the spatio-temporal brain dynamics of auditory information processing likely curtails the information content of multisensory interactions observable in humans at a given latency and within a given brain region. First, we consider the time course of signal propagation as a limitation on when auditory information (of any kind) can impact the responsiveness of a given brain region. Next, we overview the dual pathway model for the treatment of auditory spatial and object information ranging from rudimentary to complex environmental stimuli. These dual pathways are considered an intrinsic feature of auditory information processing, which are not only partially distinct in their associated brain networks, but also (and perhaps more importantly) manifest only after several tens of milliseconds of cortical signal processing. This architecture of auditory functioning would thus pose a constraint on when and in which brain regions specific spatial and object information are available for multisensory interactions. We then separately consider evidence regarding mechanisms and dynamics of spatial and object processing with a particular emphasis on when discriminations along either dimension are likely performed by specific brain regions. We conclude by discussing open issues and directions for future research.

Auditory localisation and recognition after left inferior collicular lesion: effects of work load on cortical activation patterns (fMRI study)

Evidence from neuropsychological and activation studies (Clarke et al., 2oo0, Maeder et al., 2000) suggests that sound recognitionand localisation are processed by two anatomically and functionally distinct cortical networks. We report here on a case of a patientthat had an interruption of auditory information and we show: i) the effects of this interruption on cortical auditory processing; ii)the effect of the workload on activation pattern.A 36 year old man suffered from a small left mesencephalic haemotrhage, due to cavernous angioma; the let% inferior colliculuswas resected in the surgical approach of the vascular malformation. In the acute stage, the patient complained of auditoryhallucinations and of auditory loss in right ear, while tonal audiometry was normal. At 12 months, auditory recognition, auditorylocalisation (assessed by lTD and IID cues) and auditory motion perception were normal (Clarke et al., 2000), while verbal dichoticlistening was deficient on the right side.Sound recognition and sound localisation activation patterns were investigated with fMRI, using a passive and an activeparadigm. In normal subjects, distinct cortical networks were involved in sound recognition and localisation, both in passive andactive paradigm (Maeder et al., 2OOOa, 2000b).Passive listening of environmental and spatial stimuli as compared to rest strongly activated right auditory cortex, but failed toactivate left primary auditory cortex. The specialised networks for sound recognition and localisation could not be visual&d onthe right and only minimally on the left convexity. A very different activation pattern was obtained in the active condition wherea motor response was required. Workload not only increased the activation of the right auditory cortex, but also allowed theactivation of the left primary auditory cortex. The specialised networks for sound recognition and localisation were almostcompletely present in both hemispheres.These results show that increasing the workload can i) help to recruit cortical region in the auditory deafferented hemisphere;and ii) lead to processing auditory information within specific cortical networks.References:Clarke et al. (2000). Neuropsychologia 38: 797-807.Mae.der et al. (2OOOa), Neuroimage 11: S52.Maeder et al. (2OOOb), Neuroimage 11: S33

Cross-frequency coupling in EEG revealed by adaptive oscillation tracking.

Introduction: Neuronal oscillations have been the focus of increasing interest in the neuroscientific community, in part because they have been considered as a possible integrating mechanism through which internal states can influence stimulus processing in a top-down way (Engel et al., 2001). Moreover, increasing evidence indicates that oscillations in different frequency bands interact with one other through coupling mechanisms (Jensen and Colgin, 2007). The existence and the importance of these cross-frequency couplings during various tasks have been verified by recent studies (Canolty et al., 2006; Lakatos et al., 2007). In this study, we measure the strength and directionality of two types of couplings - phase-amplitude couplings and phase-phase couplings - between various bands in EEG data recorded during an illusory contour experiment that were identified using a recently-proposed adaptive frequency tracking algorithm (Van Zaen et al., 2010). Methods: The data used in this study have been taken from a previously published study examining the spatiotemporal mechanisms of illusory contour processing (Murray et al., 2002). The EEG in the present study were from a subset of nine subjects. Each stimulus was composed of 'pac-man' inducers presented in two orientations: IC, when an illusory contour was present, and NC, when no contour could be detected. The signals recorded by the electrodes P2, P4, P6, PO4 and PO6 were averaged, and filtered into the following bands: 4-8Hz, 8-12Hz, 15-25Hz, 35-45Hz, 45-55Hz, 55-65Hz and 65-75Hz. An adaptive frequency tracking algorithm (Van Zaen et al., 2010) was then applied in each band in order to extract the main oscillation and estimate its frequency. This additional step ensures that clean phase information is obtained when taking the Hilbert transform. The frequency estimated by the tracker was averaged over sliding windows and then used to compare the two conditions. Two types of cross-frequency couplings were considered: phase-amplitude couplings and phase-phase couplings. Both types were measured with the phase locking value (PLV, Lachaux et al., 1999) over sliding windows. The phase-amplitude couplings were computed with the phase of the low frequency oscillation and the phase of the amplitude of the high frequency one. Different coupling coefficients were used when measuring phase-phase couplings in order to estimate different m:n synchronizations (4:3, 3:2, 2:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1 and 9:1) and to take into account the frequency differences across bands. Moreover, the direction of coupling was estimated with a directionality index (Bahraminasab et al., 2008). Finally, the two conditions IC and NC were compared with ANOVAs with 'subject' as a random effect and 'condition' as a fixed effect. Before computing the statistical tests, the PLV values were transformed into approximately normal variables (Penny et al., 2008). Results: When comparing the mean estimated frequency across conditions, a significant difference was found only in the 4-8Hz band, such that the frequency within this band was significantly higher for IC than NC stimuli starting at ~250ms post-stimulus onset (Fig. 1; solid line shows IC and dashed line NC). Significant differences in phase-amplitude couplings were obtained only when the 4-8 Hz band was taken as the low frequency band. Moreover, in all significant situations, the coupling strength is higher for the NC than IC condition. An example of significant difference between conditions is shown in Fig. 2 for the phase-amplitude coupling between the 4-8Hz and 55-65Hz bands (p-value in top panel and mean PLV values in the bottom panel). A decrease in coupling strength was observed shortly after stimulus onset for both conditions and was greater for the condition IC. This phenomenon was observed with all other frequency bands. The results obtained for the phase-phase couplings were more complex. As for the phase-amplitude couplings, all significant differences were obtained when the 4-8Hz band was considered as the low frequency band. The stimulus condition exhibiting the higher coupling strength depended on the ratio of the coupling coefficients. When this ratio was small, the IC condition exhibited the higher phase-phase coupling strength. When this ratio was large, the NC condition exhibited the higher coupling strength. Fig. 3 shows the phase-phase couplings between the 4-8Hz and 35-45Hz bands for the coupling coefficient 6:1, and the coupling strength was significantly higher for the IC than NC condition. By contrast, for the coupling coefficient 9:1 the NC condition gave the higher coupling strength (Fig. 4). Control analyses verified that it is not a consequence of the frequency difference between the two conditions in the 4-8Hz band. The directionality measures indicated a transfer of information from the low frequency components towards the high frequency ones. Conclusions: Adaptive tracking is a feasible method for EEG analyses, revealing information both about stimulus-related differences and coupling patterns across frequencies. Theta oscillations play a central role in illusory shape processing and more generally in visual processing. The presence vs. absence of illusory shapes was paralleled by faster theta oscillations. Phase-amplitude couplings were decreased more for IC than NC and might be due to a resetting mechanism. The complex patterns in phase-phase coupling between theta and beta/gamma suggest that the contribution of these oscillations to visual binding and stimulus processing are not as straightforward as conventionally held. Causality analyses further suggest that theta oscillations drive beta/gamma oscillations (see also Schroeder and Lakatos, 2009). The present findings highlight the need for applying more sophisticated signal analyses in order to establish a fuller understanding of the functional role of neural oscillations.

Auditory stimulation does not induce implicit memory during anaesthesia

Background and aim of the study: Formation of implicit memory during general anaesthesia is still debated. Perceptual learning is the ability to learn to perceive. In this study, an auditory perceptual learning paradigm, using frequency discrimination, was performed to investigate the implicit memory. It was hypothesized that auditory stimulation would successfully induce perceptual learning. Thus, initial thresholds of the frequency discrimination postoperative task should be lower for the stimulated group (group S) compared to the control group (group C). Material and method: Eighty-seven patients ASA I-III undergoing visceral and orthopaedic surgery during general anaesthesia lasting more than 60 minutes were recruited. The anaesthesia procedure was standardized (BISR monitoring included). Group S received auditory stimulation (2000 pure tones applied for 45 minutes) during the surgery. Twenty-four hours after the operation, both groups performed ten blocks of the frequency discrimination task. Mean of the thresholds for the first three blocks (T1) were compared between groups. Results: Mean age and BIS value of group S and group C are respectively 40 } 11 vs 42 } 11 years (p = 0,49) and 42 } 6 vs 41 } 8 (p = 0.87). T1 is respectively 31 } 33 vs 28 } 34 (p = 0.72) in group S and C. Conclusion: In our study, no implicit memory during general anaesthesia was demonstrated. This may be explained by a modulation of the auditory evoked potentials caused by the anaesthesia, or by an insufficient longer time of repetitive stimulation to induce perceptual learning.

Bilateral transitory projection to visual areas from auditory cortex in kittens.

A transitory projection from primary and secondary auditory areas to the contralateral and ipsilateral areas 17 and 18 exists in newborn kittens. Distinct neuronal populations project to ipsilateral areas 17-18, contralateral areas 17-18 and contralateral auditory cortex; they are at different depth in layers II, III, and IV. By postnatal day 38 the auditory to visual projections have been lost, apparently by elimination of axons rather than by neuronal death. While it was previously reported that the elimination of transitory axons is responsible for focusing the origin of callosal connections to restricted portions of sensory areas it now appears that similar events play a more general role in the organization of cortico-cortical networks. Indeed, the elimination of juvenile projections is largely responsible for determining which areas will be connected in the adult.