Comparison of early cortical networks in efficient and inefficient visual search: an event-related potential study.

Functional magnetic resonance imaging studies have indicated that efficient feature search (FS) and inefficient conjunction search (CS) activate partially distinct frontoparietal cortical networks. However, it remains a matter of debate whether the differences in these networks reflect differences in the early processing during FS and CS. In addition, the relationship between the differences in the networks and spatial shifts of attention also remains unknown. We examined these issues by applying a spatio-temporal analysis method to high-resolution visual event-related potentials (ERPs) and investigated how spatio-temporal activation patterns differ for FS and CS tasks. Within the first 450 msec after stimulus onset, scalp potential distributions (ERP maps) revealed 7 different electric field configurations for each search task. Configuration changes occurred simultaneously in the two tasks, suggesting that contributing processes were not significantly delayed in one task compared to the other. Despite this high spatial and temporal correlation, two ERP maps (120-190 and 250-300 msec) differed between the FS and CS. Lateralized distributions were observed only in the ERP map at 250-300 msec for the FS. This distribution corresponds to that previously described as the N2pc component (a negativity in the time range of the N2 complex over posterior electrodes of the hemisphere contralateral to the target hemifield), which has been associated with the focusing of attention onto potential target items in the search display. Thus, our results indicate that the cortical networks involved in feature and conjunction searching partially differ as early as 120 msec after stimulus onset and that the differences between the networks employed during the early stages of FS and CS are not necessarily caused by spatial attention shifts.

Auditory-visual multisensory interactions in humans: timing, topography, directionality, and sources.

Current models of brain organization include multisensory interactions at early processing stages and within low-level, including primary, cortices. Embracing this model with regard to auditory-visual (AV) interactions in humans remains problematic. Controversy surrounds the application of an additive model to the analysis of event-related potentials (ERPs), and conventional ERP analysis methods have yielded discordant latencies of effects and permitted limited neurophysiologic interpretability. While hemodynamic imaging and transcranial magnetic stimulation studies provide general support for the above model, the precise timing, superadditive/subadditive directionality, topographic stability, and sources remain unresolved. We recorded ERPs in humans to attended, but task-irrelevant stimuli that did not require an overt motor response, thereby circumventing paradigmatic caveats. We applied novel ERP signal analysis methods to provide details concerning the likely bases of AV interactions. First, nonlinear interactions occur at 60-95 ms after stimulus and are the consequence of topographic, rather than pure strength, modulations in the ERP. AV stimuli engage distinct configurations of intracranial generators, rather than simply modulating the amplitude of unisensory responses. Second, source estimations (and statistical analyses thereof) identified primary visual, primary auditory, and posterior superior temporal regions as mediating these effects. Finally, scalar values of current densities in all of these regions exhibited functionally coupled, subadditive nonlinear effects, a pattern increasingly consistent with the mounting evidence in nonhuman primates. In these ways, we demonstrate how neurophysiologic bases of multisensory interactions can be noninvasively identified in humans, allowing for a synthesis across imaging methods on the one hand and species on the other.

Propagation velocity kinetics and repolarization alternans in a free-behaving sheep model of pacing-induced atrial fibrillation.

AIMS: Experimental models have reported conflicting results regarding the role of dispersion of repolarization in promoting atrial fibrillation (AF). Repolarization alternans, a beat-to-beat alternation in action potential duration, enhances dispersion of repolarization when propagation velocity is involved. METHODS AND RESULTS: In this work, original electrophysiological parameters were analysed to study AF susceptibility in a chronic sheep model of pacing-induced AF. Two pacemakers were implanted, each with a single right atrial lead. Right atrial depolarization and repolarization waves were documented at 2-week intervals. A significant and gradual decrease in the propagation velocity at all pacing rates and in the right atrial effective refractory period (ERP) was observed during the weeks of burst pacing before sustained AF developed when compared with baseline conditions. Right atrial repolarization alternans was observed, but because of the development of 2/1 atrioventricular block with far-field ventricular interference, its threshold could not be precisely measured. Non-sustained AF was not observed at baseline, but appeared during the electrical remodelling in association with a decrease in both ERP and propagation velocity. CONCLUSION: We report here on the feasibility of measuring ERP, atrial repolarization alternans, and propagation velocity kinetics and their potential in predicting susceptibility to AF in a free-behaving model of pacing-induced AF using the standard pacemaker technology.

Event-related potential analyses via single-subject topographic classification.

Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research.

Alu expression in human cell lines and their retrotranspositional potential.

BACKGROUND: The vast majority of the 1.1 million Alu elements are retrotranspositionally inactive, where only a few loci referred to as 'source elements' can generate new Alu insertions. The first step in identifying the active Alu sources is to determine the loci transcribed by RNA polymerase III (pol III). Previous genome-wide analyses from normal and transformed cell lines identified multiple Alu loci occupied by pol III factors, making them candidate source elements. FINDINGS: Analysis of the data from these genome-wide studies determined that the majority of pol III-bound Alus belonged to the older subfamilies Alu S and Alu J, which varied between cell lines from 62.5% to 98.7% of the identified loci. The pol III-bound Alus were further scored for estimated retrotransposition potential (ERP) based on the absence or presence of selected sequence features associated with Alu retrotransposition capability. Our analyses indicate that most of the pol III-bound Alu loci candidates identified lack the sequence characteristics important for retrotransposition. CONCLUSIONS: These data suggest that Alu expression likely varies by cell type, growth conditions and transformation state. This variation could extend to where the same cell lines in different laboratories present different Alu expression patterns. The vast majority of Alu loci potentially transcribed by RNA pol III lack important sequence features for retrotransposition and the majority of potentially active Alu loci in the genome (scored high ERP) belong to young Alu subfamilies. Our observations suggest that in an in vivo scenario, the contribution of Alu activity on somatic genetic damage may significantly vary between individuals and tissues.

Aging effects on selective attention-related electroencephalographic patterns during face encoding.

Previous electrophysiological studies revealed that human faces elicit an early visual event-related potential (ERP) within the occipito-temporal cortex, the N170 component. Although face perception has been proposed to rely on automatic processing, the impact of selective attention on N170 remains controversial both in young and elderly individuals. Using early visual ERP and alpha power analysis, we assessed the influence of aging on selective attention to faces during delayed-recognition tasks for face and letter stimuli, examining 36 elderly and 20 young adults with preserved cognition. Face recognition performance worsened with age. Aging induced a latency delay of the N1 component for faces and letters, as well as of the face N170 component. Contrasting with letters, ignored faces elicited larger N1 and N170 components than attended faces in both age groups. This counterintuitive attention effect on face processing persisted when scenes replaced letters. In contrast with young, elderly subjects failed to suppress irrelevant letters when attending faces. Whereas attended stimuli induced a parietal alpha band desynchronization within 300-1000 ms post-stimulus with bilateral-to-right distribution for faces and left lateralization for letters, ignored and passively viewed stimuli elicited a central alpha synchronization larger on the right hemisphere. Aging delayed the latency of this alpha synchronization for both face and letter stimuli, and reduced its amplitude for ignored letters. These results suggest that due to their social relevance, human faces may cause paradoxical attention effects on early visual ERP components, but they still undergo classical top-down control as a function of endogenous selective attention. Aging does not affect the face bottom-up alerting mechanism but reduces the top-down suppression of distracting letters, possibly impinging upon face recognition, and more generally delays the top-down suppression of task-irrelevant information.

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.

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.

Attention-related potentials allow for a highly accurate discrimination of mild cognitive impairment subtypes.

The three most frequent forms of mild cognitive impairment (MCI) are single-domain amnestic MCI (sd-aMCI), single-domain dysexecutive MCI (sd-dMCI) and multiple-domain amnestic MCI (md-aMCI). Brain imaging differences among single domain subgroups of MCI were recently reported supporting the idea that electroencephalography (EEG) functional hallmarks can be used to differentiate these subgroups. We performed event-related potential (ERP) measures and independent component analysis in 18 sd-aMCI, 13 sd-dMCI and 35 md-aMCI cases during the successful performance of the Attentional Network Test. Sensitivity and specificity analyses of ERP for the discrimination of MCI subgroups were also made. In center-cue and spatial-cue warning stimuli, contingent negative variation (CNV) was elicited in all MCI subgroups. Two independent components (ICA1 and 2) were superimposed in the time range on the CNV. The ICA2 was strongly reduced in sd-dMCI compared to sd-aMCI and md-aMCI (4.3 vs. 7.5% and 10.9% of the CNV component). The parietal P300 ERP latency increased significantly in sd-dMCI compared to md-aMCI and sd-aMCI for both congruent and incongruent conditions. This latency for incongruent targets allowed for a highly accurate separation of sd-dMCI from both sd-aMCI and md-aMCI with correct classification rates of 90 and 81%, respectively. This EEG parameter alone performed much better than neuropsychological testing in distinguishing sd-dMCI from md-aMCI. Our data reveal qualitative changes in the composition of the neural generators of CNV in sd-dMCI. In addition, they document an increased latency of the executive P300 component that may represent a highly accurate hallmark for the discrimination of this MCI subgroup in routine clinical settings.

Event-related potentials and changes of brain rhythm oscillations during working memory activation in patients with first-episode psychosis.

Background: Earlier contributions have documented significant changes in sensory, attention-related endogenous event-related potential (ERP) components and θ band oscillatory responses during working memory activation in patients with schizophrenia. In patients with first-episode psychosis, such studies are still scarce and mostly focused on auditory sensory processing. The present study aimed to explore whether subtle deficits of cortical activation are present in these patients before the decline of working memory performance. Methods: We assessed exogenous and endogenous ERPs and frontal θ event-related synchronization (ERS) in patients with first-episode psychosis and healthy controls who successfully performed an adapted 2-back working memory task, including 2 visual n-backworking memory tasks as well as oddball detection and passive fixation tasks. Results: We included 15 patients with first-episode psychosis and 18 controls in this study. Compared with controls, patients with first-episode psychosis displayed increased latencies of early visual ERPs and phasic θ ERS culmination peak in all conditions. However, they also showed a rapid recruitment of working memory-related neural generators, even in pure attention tasks, as indicated by the decreased N200 latency and increased amplitude of sustained θ ERS in detection compared with controls. Limitations: Owing to the limited sample size, no distinction was made between patients with first-episode psychosis with positive and negative symptoms. Although we controlled for the global load of neuroleptics, medication effect cannot be totally ruled out. Conclusion: The present findings support the concept of a blunted electroencephalographic response in patients with first-episode psychosis who recruit the maximum neural generators in simple attention conditions without being able to modulate their brain activation with increased complexity of working memory tasks.

Cost-effectiveness of temozolomide for the treatment of newly diagnosed glioblastoma multiforme.

AIM: To perform a systematic review on the costs and cost-effectiveness of concomitant and adjuvant temozolomide with radiotherapy for the treatment of newly diagnosed glioblastoma compared with initial radiotherapy alone. METHODS: Electronic databases were searched for relevant publications on costs and cost-effectiveness until October 2008. RESULTS: We found four relevant clinical trials, one cost study and two economic models. The mean survival benefit in the radiotherapy plus temozolomide group varied between 0.21 and 0.25 life-years. Treatment costs were between 27,365 euros and 39,092 euros. The costs of temozolomide amounted to approximately 40% of the total treatment costs. The incremental cost-effectiveness ratios found in the literature were 37,361 euros per life-year gained and 42,912 euros per quality-adjusted life-year gained. However, the models are not comparable because different outcomes are used (i.e., life-years and quality-adjusted life-years). CONCLUSION: Although the models are not comparable according to outcome, the incremental cost-effectiveness ratios found are within acceptable ranges. We concluded that despite the high temozolomide acquisition costs, the costs per life-year gained and the costs per quality-adjusted life-year gained are comparable with other accepted first-line treatments with chemotherapy in patients with cancer.

Separating mismatch negativity (MMN) response from auditory obligatory brain responses in school-aged children.

Mismatch negativity (MMN) overlaps with other auditory event-related potential (ERP) components. We examined the ERPs of 50 9- to 11-year-old children for vowels /i/, /y/ and equivalent complex tones. The goal was to separate MMN from obligatory ERP components using principal component analysis and equal probability control condition. In addition to the contrast of the deviant minus standard response, we employed the contrast of the deviant minus control response, to see whether the obligatory processing contributes to MMN in children. When looking for differences in speech deviant minus standard contrast, MMN starts around 112 ms. However, when both contrasts are examined, MMN emerges for speech at 160 ms whereas for nonspeech MMN is observed at 112 ms regardless of contrast. We argue that this discriminative response to speech stimuli at 112 ms is obligatory in nature rather than reflecting change detection processing.

Different colors of light lead to different adaptation and activation as determined by high-density EEG.

Light adaptation is crucial for coping with the varying levels of ambient light. Using high-density electroencephalography (EEG), we investigated how adaptation to light of different colors affects brain responsiveness. In a within-subject design, sixteen young participants were adapted first to dim white light and then to blue, green, red, or white bright light (one color per session in a randomized order). Immediately after both dim and bright light adaptation, we presented brief light pulses and recorded event-related potentials (ERPs). We analyzed ERP response strengths and brain topographies and determined the underlying sources using electrical source imaging. Between 150 and 261ms after stimulus onset, the global field power (GFP) was higher after dim than bright light adaptation. This effect was most pronounced with red light and localized in the frontal lobe, the fusiform gyrus, the occipital lobe and the cerebellum. After bright light adaptation, within the first 100ms after light onset, stronger responses were found than after dim light adaptation for all colors except for red light. Differences between conditions were localized in the frontal lobe, the cingulate gyrus, and the cerebellum. These results indicate that very short-term EEG brain responses are influenced by prior light adaptation and the spectral quality of the light stimulus. We show that the early EEG responses are differently affected by adaptation to different colors of light which may contribute to known differences in performance and reaction times in cognitive tests.

Kinetics of atrial repolarization alternans in a free-behaving ovine model.

Kinetics of Atrial Repolarization Alternans. INTRODUCTION: Repolarization alternans (Re-ALT), a beat-to-beat alternation in action potential repolarization, promotes dispersion of repolarization, wavebreaks, and reentry. Recently, Re-ALT has been shown to play an important role in the transition from rapid pacing to atrial fibrillation (AF) in humans. The detailed kinetics of atrial Re-ALT, however, has not been reported so far. We developed a chronic free-behaving ovine pacing model to study the kinetics of atrial Re-ALT as a function of pacing rate. METHODS: Thirteen sheep were chronically implanted with 2 pacemakers for the recording of broadband right atrial unipolar electrograms and delivery of rapid pacing protocols. Beat-to-beat differences in the atrial T-wave apex amplitude as a measure of Re-ALT and activation time were analyzed at incremental pacing rates until the effective refractory period (ERP) defined as stable 2:1 capture. RESULTS: Atrial Re-ALT appeared intermittently but without periodicity, and increased in amplitude as a function of pacing rate until ERP. Intermittent 2:1 atrial capture was observed at pacing cycle lengths 40 ms above ERP, and increased in duration as a function of pacing rate. Episodes of rapid pacing-induced AF were rare, and were preceded by Re-ALT or complex oscillations of atrial repolarization, but without intermittent capture. CONCLUSION: We show in vivo that atrial Re-ALT developed and increased in magnitude with rate until stable 2:1 capture. In rare instances where capture failure did not occur, Re-ALT and complex oscillations of repolarization surged and preceded AF initiation. (J Cardiovasc Electrophysiol, Vol. 23, pp. 1003-1012, September 2012).

A tutorial review of electrical neuroimaging from group-average to single-trial event-related potentials.

This tutorial review details some of the recent advances in signal analyses applied to event-related potential (ERP) data. These "electrical neuroimaging" analyses provide reference-independent measurements of response strength and response topography that circumvent statistical and interpretational caveats of canonical ERP analysis methods while also taking advantage of the greater information provided by high-density electrode montages. Electrical neuroimaging can be applied across scales ranging from group-averaged ERPs to single-subject and single-trial datasets. We illustrate these methods with a tutorial dataset and place particular emphasis on their suitability for studies of clinical and/or developmental populations.