Classifying four-category visual objects using multiple ERP components in single-trial ERP.

Categorization of images containing visual objects can be successfully recognized using single-trial electroencephalograph (EEG) measured when subjects view images. Previous studies have shown that task-related information contained in event-related potential (ERP) components could discriminate two or three categories of object images. In this study, we investigated whether four categories of objects (human faces, buildings, cats and cars) could be mutually discriminated using single-trial EEG data. Here, the EEG waveforms acquired while subjects were viewing four categories of object images were segmented into several ERP components (P1, N1, P2a and P2b), and then Fisher linear discriminant analysis (Fisher-LDA) was used to classify EEG features extracted from ERP components. Firstly, we compared the classification results using features from single ERP components, and identified that the N1 component achieved the highest classification accuracies. Secondly, we discriminated four categories of objects using combining features from multiple ERP components, and showed that combination of ERP components improved four-category classification accuracies by utilizing the complementarity of discriminative information in ERP components. These findings confirmed that four categories of object images could be discriminated with single-trial EEG and could direct us to select effective EEG features for classifying visual objects.

To clarify the functional significance of Go event-related potential (ERP) components, this study aimed to explore stimulus- and response-locked ERP averaging effects on the series of ERP components elicited during an auditory Go/NoGo task. Go stimulus- and response-locked ERP data from 126 healthy young adults (Mage =20.3, SD=2.8years, 83 female) were decomposed using temporal principal components analysis (PCA). The extracted components were then identified as stimulus-specific, response-specific, or common to both stimulus- and response-locked data. MANOVAs were then used to test for stimulus- versus response-locked averaging effects on common component amplitudes to determine their primary functional significance (i.e., stimulus- or response-related). Go stimulus- and response-related component amplitudes were then entered into stepwise linear regressions predicting the reaction time (RT), RT variability, and omission errors. Nine ERP components were extracted from the stimulus- and response-locked data, including N1-1, processing negativity (PN), P2, response-related N2 (RN2), motor potential (MP), P3b, P420, and two slow wave components; SW1 and SW2. N1-1, PN, and P2 were stimulus-specific, whereas, RN2, MP, and P420 were response-specific; P3b, SW1, and SW2 were common to both data sets. P3b, SW1, and SW2 were significantly larger in the response-locked data, indicating that they were primarily response-related. RT, RT variability, and omission errors were predicted by various stimulus- and response-related components, providing further insight into ERP markers of auditory information processing and cognitive control. Further, the results of this study indicate the utility of quantifying some common components (i.e., Go P3b, SW1, and SW2) using the response-locked ERP.

Sedative-hypnotic drugs not only increase sedation, but also impair memory as serum concentration increases. These drugs also produce profound changes in the auditory event-related potential (ERP). The ability of various ERP components to predict changes in sedation and memory produced by various drugs was tested. Sixty-five healthy volunteers randomly received intravenous placebo, midazolam, propofol, thiopental, fentanyl with ondansetron, or ondansetron alone at five different stable target concentrations (three increasing, two decreasing) using a computer-controlled infusion pump to produce varying degrees of sedation without loss of consciousness. ERPs were recorded while volunteer participants detected a deviant auditory stimulus and made a button-press response to a target tone (standard oddball paradigm, 80:20 ratio, to elicit a P3 response). At each target concentration, volunteers learned a list of 16 words. The predictive probabilities (Pk) of various ERP components were determined for word recognition at the end of the day (memory) and log reaction time to the deviant stimulus (sedation). The N2 latency of the ERP consistently predicted log reaction time in all groups (Pk +/- SE from 0.58 +/- 0.04 to 0.71 +/- 0.04). The N2P3 amplitude of the ERP was the best predictor of memory performance for midazolam (Pk, 0.63 +/- 0.04), propofol (Pk, 0.62 +/- 0.05), and thiopental (Pk, 0.66 +/- 0.04). There was a differential ability to predict memory performance from sedation for midazolam and propofol. Midazolam and propofol affect memory differentially from their sedative effects, and these are indexed by specific components of the auditory ERP. These components of the ERP are associated with specific, but not necessarily unique, neuroanatomic structures. Thus, these drugs act by additional mechanisms beyond general central nervous system depression to produce the effects of sedation and memory impairment.

Attentional selection of a target presented among distractors can be indexed with an event-related potential (ERP) component known as the N2pc. Theoretical interpretation of the N2pc has suggested that it reflects a fundamental mechanism of attention that shelters the cortical representation of targets by suppressing neural activity stemming from distractors. Results from fields other than human electrophysiology, however, suggest that attention does not act solely through distractor suppression; rather, it modulates the processing of both target and distractors. We conducted four ERP experiments designed to investigate whether the N2pc reflects multiple attentional mechanisms. Our goal was to reconcile ostensibly conflicting outcomes obtained in electrophysiological studies of attention with those obtained using other methodologies. Participants viewed visual search arrays containing one target and one distractor. In Experiments 1 through 3, the distractor was isoluminant with the background, and therefore, did not elicit early lateralized ERP activity. This work revealed a novel contralateral ERP component that appears to reflect direct suppression of the cortical representation of the distractor. We accordingly name this component the distractor positivity (P(D)). In Experiment 4, an ERP component associated with target processing was additionally isolated. We refer to this component as the target negativity (N(T)). We believe that the N2pc reflects the summation of the P(D) and N(T), and that these discrete components may have been confounded in earlier electrophysiological studies. Overall, this study demonstrates that attention acts on both target and distractor representations, and that this can be indexed in the visual ERP.

Crowding occurs when an easily identified isolated stimulus is surrounded by stimuli with similar properties, making it very difficult to identify. Crowding is suggested as a mechanism that creates a bottleneck in object recognition and awareness. Recently, we showed that brief presentation times at the fovea resulted in a significant crowding effect on target identification, impaired the target's color awareness, and resulted in a slower reaction time. However, when tagging the target with a red letter, the crowding effect is abolished. Crowding is widely considered a grouping; hence, it is pre-attentive. An event-related potential (ERP) study that investigated the spatial-temporal properties of crowding suggested the involvement of higher-level visual processing. Here, we investigated whether ERP's components may be affected by crowding and tagging, and whether the temporal advantage of ERP can be utilized to gain further information about the crowding mechanism. The participants reported target identification using our standard foveal crowing paradigm. It is assumed that crowding occurs due to a suppressive effect; thus, it can be probed by changes in perceptual (N1, ~160 ms) and attentive (P3 ~300-400 ms) components. We found a suppression effect (less negative ERP magnitude) in N1 under foveal crowding, which was recovered under tagging conditions. ERP's amplitude components (N1 and P3) and the behavioral proportion correct are highly correlated. These findings suggest that crowding is an early grouping mechanism that may be combined with later processing involving the segmentation mechanism.

The purpose of this study was to apply recurrence plots and recurrence quantification analysis (RQA) on event related potentials (ERPs) recorded during memory recognition tests. Data recorded during memory retrieval in four scalp region was used. Tow most important ERP's components corresponding to memory retrieval, FN400 and LPC, were detected in recurrence plots computed for single-trial EEGs. In addition, the RQA was used to quantify changes in signal dynamic structure during memory retrieval, and measures of complexity as RQA variables were computed. Given the stimulus, amplitude of the RQA variables increases around 400ms, corresponding to dimension reduction of system. Furthermore, after 800ms these amplitudes decreased which can be as a consequence of an increase in system dimension and back to its basic state. The mean amplitude of Old items was more than New one. Using this method, we found its ability to detect memory components of EEG signals and do a distinction between Old/ New items. In contrast with linear techniques recurrence plots and RQA do not need large number of recorded trials, and they can indicate changes in even single-trial EEGs. RQA can also show differences between old and new events in a memory process.

Event-related potentials (ERPs) evoked by key stimuli informing a subject about the forthcoming recognition of the global or local level of a hierarchical test figure were analyzed in 7-year-old children with different levels of maturity of the regulatory brain systems. Differences in both the initial ERP components P1, N1, and P2 (which reflect the analysis of the sensory characteristics and significance of a key stimulus) and the late components N3, Pc, and Nc (which reflect the preparation for the recognition of a subsequent test figure) were found. It was shown that, in children with frontal-thalamic regulatory system immaturity (FTRSI), the amplitude of the ERP component N1 is decreased in the caudal areas. In children with an immature bottom-up activation system, a decrease in the amplitude of initial ERP components in the caudal areas was observed in a broader time interval in components P1, N1, and P2. As compared to the control groups of children, in children with immature frontal-thalamic structures, components N3, Pc, and Nc were different in both the caudal and precentral areas. In children with immature lower brainstem activation structures, the late ERP components were different, predominantly, in the parietal and temporo-parieto-occipital areas. Comparison of ERPs in response to global and local key stimuli in children of the control group demonstrated a clear-cut temporal and topographical organization in the period of preparation for subsequent recognition of a prescribed level of the test stimulus: the earlier preparation stages were associated with component N3 in the parietal and temporo-parieto-occipital areas, whereas later stages were associated with Pc changes in the frontal areas. In children with FTRSI, changes in the late components in the caudal areas were poorly expressed and their topographical organization (characteristic of the control group) was absent; the involvement of the frontal areas in the late stages of the key stimulus analysis was restricted. These findings may give grounds to suggest the significance of the frontal-thalamic system in the organization of the response to an expected stimulus. In children with immature lower brainstem activation structures, the type of the key stimulus was reflected in the late ERP components in a diffuse way.

The present study investigated the role of proficiency in late second-language (L2) processing using comparable stimuli in German and Italian. Both sets of stimuli consisted of simple active sentences including a word category violation, a morphosyntactic agreement violation, or a combination of the two. Four experiments were conducted to study high- and low-proficiency L2 learners of German as well as high- and low-proficiency L2 learners of Italian. High-proficiency L2 learners in both languages showed the same event-related potential (ERP) components as native speakers for all syntactic violations. For the word category violation, they displayed an early anterior negativity (ELAN), an additional negativity reflecting reference-related processes, and a late P600 evidencing processes of reanalysis. For the processing of the morphosyntactic error, an anterior negativity (LAN) and a P600 were observed, whereas for the combined violation, the same ERP components were found as in the pure category violation. In high-proficiency L2 learners, the timing of the processing steps was equivalent to that of native speakers, although some amplitude differences were present. Low-proficiency L2 learners, however, showed qualitative differences in the agreement violation characterized by the absence of the LAN and quantitative differences reflected in a delayed P600 in every violation condition. These findings emphasize that with a high proficiency, late L2 learners can indeed show native-like neural responses with the timing approximating that of native speakers. This challenges the idea that there are fundamental differences in language processing in the brain between natives and late L2 learners.

Objective. Single-trial electroencephalography (EEG) classification is of great importance in the rapid serial visual presentation (RSVP) task. Convolutional neural networks (CNNs), as one of the mainstream deep learning methods, have been proven to be effective in extracting RSVP EEG features. However, most existing CNN models for EEG classification do not consider the phase-locked characteristic of event-related potential (ERP) components very well in the architecture design. Here, we propose a novel CNN model to make better use of the phase-locked characteristic to extract spatiotemporal features for single-trial RSVP EEG classification. Based on the phase-locked characteristic, the spatial distributions of the main ERP component in different periods can be learned separately. Approach. In this work, we propose a novel CNN model to achieve superior performance on single-trial RSVP EEG classification. We introduce the combination of the standard convolutional layer, the permute layer and the depthwise convolutional layer to separately operate the spatial convolution in different periods, which more fully utilizes the phase-locked characteristic of ERPs for classification. We compare our model with several traditional and deep-learning methods in the classification performance. Moreover, we use spatial topography and saliency map to visually analyze the ERP features extracted by our model. Main results. The results show that our model obtains better classification performance than those of reference methods. The spatial topographies of each subject exhibit the typical ERP spatial distribution in different time periods. And the saliency map of each subject illustrates the discriminant electrodes and the meaningful temporal features. Significance. Our model is designed with better consideration of the phase-locked ERP characteristic and reaches excellent performance on single-trial RSVP EEG classification.

Time effects on event-related brain potentials and vigilance performance

A wavelet based algorithm for the identification of oscillatory event-related potential components.

Event-related potential correlates of color selection and lexical decision: hierarchical processing or late selection?

The complex multidimensional visual patterns of facial expression is particularly well suited for studying perception and the processes underlying perceptual integration of component parts into a meaningful whole. With the high resolution in milliseconds, event-related potential (ERP) may be an excellent technique to track the time course of cognitive processing for facial emotions. Facial affective stimuli elicit particular ERP components involved in early processing of facial expressions, including: early sensory processing of visual stimuli: the P100; early structural encoding of facial features: the N170; second-order sustained activities necessary for consequent deeper processing: the posterior P2 and decoding of facial features to identify emotional content: the N250. We reviewed above mentioned ERP components respectively, in order to add the knowledge about ERP components as indicators of neural dynamics of facial emotion processing, and to provide a point of reference for further exploration on facial emotion processing that may be useful for understanding human cognition development and pathology. Key words: Face; Emotion; ERP; P100; N170; P2; N250

Combined effects of transcranial direct current stimulation and aerobic exercise on inhibitory control function in healthy young adults: An event-related potential study

Error-related negativity (ERN) is one of the electroencephalographical (EEG) traces related to the subject perception of erroneous responses. Methods for detecting the ERN from EEG signals have been widely investigated. Many known techniques use the ERN component of event-related potentials (ERP) by extracting relevant features and feeding those features to a classifier. In these approaches, feature extraction becomes the key point. In this paper, we used the t-CWT method which was based on the continuous wavelet transform (CWT) and Student's t-test for extracting ERN features. In the experiment, EEG was recorded from 5 electrode sites (Fz, FC1, Cz, FCz and FC2) during a sustianed attention experiment in 10 subjects. We used a support vector machine for classification. In addition, the algorithm provides fully automated detection and quantification methods for extracting the most discrimantive? ERP components between two cognitive states and are particular suitable for classifying single-trial ERPs. The features extracted by the algorithm can be interpreted in terms of signal characteristics that are contributing to the efficiency of classification, giving a new method for brain activity investigation.