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Ultimately associative learning is a function of the temporal features and relationships between experienced stimuli. Nevertheless how time affects the neural circuit underlying this form of learning remains largely unknown. To address this issue, we used single-trial auditory trace fear conditioning and varied the length of the interval between tone and foot-shock. Through temporary inactivation of the amygdala, medial-prefrontal cortex (mPFC) and dorsal-hippocampus in rats, we tested the hypothesis that different temporal intervals between the tone and the shock influence the neuronal structures necessary for learning. Here, we show for the first time that the amygdala is critically involved in the acquisition of auditory fear learning when there is a temporal gap between the tone and the shock. Moreover, imposing a short interval (5 s) between the two stimuli also recruits the medial pre-frontal cortex (mPFC), while learning the association across a longer interval (40 s) becomes additionally dependent on a third structure, the dorsal-hippocampus. Thus, our results show that increasing the interval length between tone and shock leads to the requirement of an increasing number of brain areas for the association between the two stimuli to be acquired. These findings demonstrate that the temporal relationship between events is a key factor in determining the neuronal mechanisms underlying associative fear learning.

Using a rapid serial visual presentation paradigm, we previously showed that the average amplitudes of six event-related potential (ERP) components were affected by different categories of emotional faces. In the current study, we investigated the six discriminating components on a single-trial level to clarify whether the amplitude difference between experimental conditions results from a difference in the real variability of single-trial amplitudes or from latency jitter across trials. It is found that there were consistent amplitude differences in the single-trial P1, N170, VPP, N3, and P3 components, demonstrating that a substantial proportion of the average amplitude differences can be explained by the pure variability in amplitudes on a single-trial basis between experimental conditions. These single-trial results verified the three-stage scheme of facial expression processing beyond multitrial ERP averaging, and showed the three processing stages of 'fear popup', 'emotional/unemotional discrimination', and 'complete separation' based on the single-trial ERP dynamics. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Theta-alpha range oscillations have been associated with MMN in healthy controls. Our previous studies showed that theta-alpha activities are highly heritable in schizophrenia patients’ families. We aimed to test the hypothesis that theta-alpha activities may contribute to MMN in schizophrenia patients and their family members. Methods: We compared MMN and single trial oscillations during MMN in 95 patients, 75 first-degree relatives, 87 controls, and 34 community subjects with schizophrenia spectrum personality (SSP) traits. Results: We found that (1) MMN was reduced in patients (p <0.001) and SSP subjects (p =0.047) but not in relatives (p =0.42); (2) there were augmented 1–20Hz oscillations in patients (p =0.02 to <0.001) during standard and deviant stimuli; (3) theta-alpha (5–12Hz) oscillations had the strongest correlation to MMN in controls and relatives (ΔR 2 =21.4–23.9%, all p <0.001), while delta (<5Hz) showed the strongest correlation to MMN in schizophrenia and SSP trait subjects; and, (4) MMN (h 2 =0.56, p =0.002) and theta-alpha (h 2 =0.55, p =0.004) were heritable traits. Conclusions: Low frequency oscillations have a robust relationship with MMN and the relationship appears altered by schizophrenia; and schizophrenia patients showed augmented low frequency activities during the MMN paradigm. Significance: The results encourage investigation of low frequency oscillations to elucidate the neurophysiological pathology underlying MMN abnormalities in schizophrenia. [Copyright &y& Elsevier]

Abstract: In the early days of fMRI, data were acquired using methods adapted mainly from PET imaging. Sets of similar stimuli were presented in extended blocks, with stimulus conditions changing from block to block. While this method provided optimum statistical power, it also presented a variety of potential confounds, including changes in attention, alertness, expectancy, and practice effects within and between blocks. Event-related paradigms using unpredictable, randomized stimulus sequences had been used in EEG studies for over 50years before the development of fMRI, and provided a means to overcome these issues. However, the temporal dispersion of BOLD fMRI activity resulted in responses to successive stimuli adding together, making it difficult to perform rapid event-related paradigms using fMRI. Here we describe the background and history of methods developed to overcome this limitation, allowing rapid, randomized stimulus sequences to be used with fMRI. The advantages and disadvantages of this technique and how these methods have been applied in a variety of experimental settings are discussed. [Copyright &y& Elsevier]

Abstract: Objective: We evaluated the potential of recurrence quantification analysis (RQA) to improve the analysis of trial-by-trial-variability in event-related potentials (ERPs) experiments. Methods: We use an acoustic oddball paradigm to compare the efficiency of RQA with a linear amplitude based analysis of single trial ERPs with regard to the power to distinguish responses to different tone types. We further probed the robustness of both analyses towards structured noise induced by parallel magnetic resonance imaging (MRI). Results: RQA provided robust discrimination of responses to different tone types, even when EEG data were contaminated by structured noise. Yet, its power to discriminate responses to different tone types was not significantly superior to a linear amplitude analysis. RQA measures were only moderately correlated with EEG amplitudes, suggesting that RQA may extract additional information from single trial responses not detected by amplitude evaluation. Conclusions: RQA allows quantifying signal characteristics of single trial ERPs measured with and without noise induced by parallel MRI. RQA power to discriminate responses to different tone types was similar to linear amplitude based analysis. Significance: RQA has the potential to detect differences of signal features in response to a standard oddball paradigm and provide additional trial-by-trial information compared to classical amplitude based analysis. [Copyright &y& Elsevier]

Searching for target images in large volume imagery is a challenging problem and the rapid serial visual presentation (RSVP) triage is potentially a promising solution to the problem. RSVP triage is essentially a cortically-coupled computer vision technique that relies on single-trial detection of event-related potentials (ERP). In RSVP triage, images are shown to a subject in a rapid serial sequence. When a target image is seen by the subject, unique ERP characterized by P300 are elicited. Thus, in RSVP triage, accurate detection of such distinct ERP allows for fast searching of target images in large volume imagery. The accuracy of the distinct ERP detection in RSVP triage depends on the feature extraction method, for which the common spatial pattern analysis (CSP) was used with limited success. This paper presents a novel feature extraction method, termed common spatio-temporal pattern (CSTP), which is critical for robust single-trial detection of ERP. Unlike the conventional CSP, whereby only spatial patterns of ERP are considered, the present proposed method exploits spatial and temporal patterns of ERP separately, providing complementary spatial and temporal features for high accurate single-trial ERP detection. Numerical study using data collected from 20 subjects in RSVP triage experiments demonstrates that the proposed method offers significant performance improvement over the conventional CSP method (corrected p-value < 0.05, Pearson r=0.64) and other competing methods in the literature. This paper further shows that the main idea of CSTP can be easily applied to other methods. [ABSTRACT FROM PUBLISHER]

Abstract: The readiness potential (RP), a slow negative electroencephalographic pre-movement potential, was reported to commence earlier for movements with the non-dominant left hand than with the dominant right hand. Latencies in these reports were always calculated from averaged RPs, whereas onset times of individual trials remained inaccessible. The aim was to use a new statistical approach to examine whether a few left hand trials with very early pre-movement activity disproportionally affect the onset of the average. We recorded RPs in 28 right-handed subjects while they made self-paced repetitive unilateral movements with their dominant and non-dominant hand. Skewness, a measure of distribution asymmetry, was analysed in sets of single-trial RPs to discriminate between a symmetric distribution and an asymmetric distribution containing outlier trials with early onset. Results show that for right hand movements skewness has values around zero across electrodes and pre-movement intervals, whereas for left hand movements skewness has initially negative values which increase to neutral values closer to movement onset. This indicates a symmetric (e.g., Gaussian) distribution of onset times across trials for simple right hand movements, whereas cortical activation preceding movements with the non-dominant hand is characterised by outlier trials with early onset of negativity. These findings may explain differences in the averaged brain activation preceding dominant versus non-dominant hand movements described in previous electrophysiological/neuroimaging studies. The findings also constrain mental chronometry, a technique that makes conclusions upon the time and temporal order of brain processes by measuring and comparing onset times of averaged electroencephalographic potentials evoked by these processes. [Copyright &y& Elsevier]

Abstract: Behavioral and electrophysiological data related to performance in an auditory Go/NoGo task were analyzed in young and older adults in the present study. Especially, differences in within-person variability in behavior and neural activity between young and older adults and changes in topography of slow event-related oscillations (EROs) were of interest. Within-person variability in behavior was assessed by reaction time (RT) variability. Event-related delta and theta oscillations were analyzed using time–frequency transformation, which can give information on the time-course of single trial event-related EEG spectral power enhancement and intertrial phase-locking (ITC). In contrast to our previous visual Go/NoGo study, no under-recruitment of task-relevant brain regions was found for the auditory theta and delta EROs. Young did not differ from older adults in RT variability or in single trial delta/theta ITC. Altered recruitment of brain activity at advanced age was indicated, first, by stronger early theta phase-locking in older compared to young adults and, second, by a Go-specific lateralization of delta/theta activity. We conclude that within-person variability may increase with age, but the degree depends on performance level and the modality investigated. [Copyright &y& Elsevier]

One of the major aims of BCI research is devoted to achieving faster and more efficient control of external devices. The identification of individual tap events in a motor imagery BCI is therefore a desirable goal. EEG is recorded from subjects performing and imagining finger taps with their left and right hands. A Differential Evolution based feature selection wrapper is used in order to identify optimal features in the spatial and frequency domains for tap identification. Channel-frequency band combinations are found which allow differentiation of tap vs. no-tap control conditions for executed and imagined taps. Left vs. right hand taps may also be differentiated with features found in this manner. A sliding time window is then used to accurately identify individual taps in the executed tap and imagined tap conditions. Highly statistically significant classification accuracies are achieved with time windows of 0.5 s and more allowing taps to be identified on a single trial basis. [ABSTRACT FROM AUTHOR]

Abstract: The classical approach for extracting event-related potentials (ERPs) from the brain is ensemble averaging. For long latency ERPs this is not optimal, partly due to the time-delay in obtaining a response and partly because the latency and amplitude for the ERP components, like the P300, are variable and depend on cognitive function. This study compares the performance of a simplified Kalman filter with Sliding Window Averaging in tracking dynamical changes in single trial P300. The comparison is performed on simulated P300 data with added background noise consisting of both simulated and real background EEG in various input signal to noise ratios. While both methods can be applied to track dynamical changes, the simplified Kalman filter has an advantage over the Sliding Window Averaging, most notable in a better noise suppression when both are optimized for faster changing latency and amplitude in the P300 component and in a considerably higher robustness towards suboptimal settings. The latter is of great importance in a clinical setting where the optimal setting cannot be determined. [ABSTRACT FROM AUTHOR]

Bistable perception arises when an ambiguous stimulus under continuous view is perceived as an alternation of two mutually exclusive states. Such a stimulus provides a unique opportunity for understanding the neural basis of visual perception because it dissociates the perception from the visual input. In this paper, we focus on extracting the percept-related features from the local field potential (LFP) in monkey visual cortex for decoding its bistable structure-from-motion (SFM) perception. Our proposed feature extraction approach consists of two stages. First, we estimate and remove from each LFP trial the nonpercept-related stimulus-evoked activity via a local regression method called the locally weighted scatterplot smoothing because of the dissociation between the perception and the stimulus in our experimental paradigm. Second, we use the common spatial patterns approach to design spatial filters based on the residue signals of multiple channels to extract the percept-related features. We exploit a support vector machine (SVM) classifier on the extracted features to decode the reported perception on a single-trial basis. We apply the proposed approach to the multichannel intracortical LFP data collected from the middle temporal (MT) visual cortex in a macaque monkey performing an SFM task. We demonstrate that our approach is effective in extracting the discriminative features of the percept-related activity from LFP and achieves excellent decoding performance. We also find that the enhanced gamma band synchronization and reduced alpha and beta band desynchronization may be the underpinnings of the percept-related activity. [ABSTRACT FROM AUTHOR]

Event-related potentials (ERPs) were recorded by measuring a dense sensor EEG from eight healthy volunteers in a visual oddball experiment. Single trials were analyzed with an extremely simple high-dimensional version of discriminant analysis. The question was how many of the target trials contribute to the average P3, and to test whether other components in the ERP are sensitive to discriminate between target and non-target trials. One common classification rule for all participants expressing the P3 component correctly classified 88% of the ERPs of all subjects in response to a target or non-target trial. For four of the eight participants, there were strong differences in an early ERP component over the occipital recording sites. Their individual classification rules, obtained from the training data in the time interval up to 200 ms, correctly classified 85% of the trials of the test data. [ABSTRACT FROM AUTHOR]

Abstract: The readiness potential (RP), a slow electroencephalographic (EEG) pre-movement potential, was used in earlier studies to determine the onset and order of neural processes preceding voluntary movement. Latencies in these studies were always calculated from the averaged RP, whereas onset times of individual trials remained inaccessible. The aim of this study was to use a different, statistical approach to examine how variable the onset of single-trial RPs within subjects is. We recorded RPs in 15 right-handed healthy subjects while they made self-paced repetitive unilateral button presses with their dominant right hand. Skewness, a measure of distribution asymmetry, was analysed in sets of single-trial RPs to discriminate between fixed onset and variable onset models. Results show that skewness has values around zero across all electrodes and pre-movement intervals without any significant deviation. This result obtained for the original data was replicated using modelled data with fixed onset times, whereas alternative models with variable onset times (i.e., including trials with exceptionally early onset) showed significant deviations of skewness from zero. In conclusion, for simple repetitive movements with the dominant hand these results confirm a fixed onset model of the RP with similar onset times of pre-movement cortical activation across trials. The methodology might be also applicable for other paradigms to test basic assumptions of mental chronometry. [Copyright &y& Elsevier]

Abstract: Selective attention increases the amplitude of the averaged N100 event-related potential (ERP). This increase may result from more neurons responding to the stimulus or from the same number of neurons better synchronised with the stimulus, or both. We investigated the synchronization mechanism using a new response latency jitter measurement algorithm that performed well for all the signal-to-noise ratios obtained in the experiment. We found that the significantly increased N100 amplitude is accounted for by a significantly decreased latency jitter variance for the attended stimuli. [Copyright &y& Elsevier]

Abstract: Being able to estimate the fMRI-BOLD response following a single task or stimulus is certainly of value, since it allows to characterize its relationship to different aspects either of the stimulus, or of the subject''s performance. In order to detect and characterize BOLD responses in single trials, we developed and validated a procedure based on an AutoRegressive model with eXogenous Input (ARX). The use of an individual exogenous input for each voxel makes the modeling sensitive enough to reveal differences across regions, avoiding any a priori assumption about the reference signal. The detection of variability across trials is ensured by a suitable choice, for each voxel, of the order of the moving average, which in our implementation determines the relative delay between the recorded and the reference signal. This is a quality useful in finding different time profiles of activation from high temporal resolution fMRI data. The results obtained from simulated fMRI data resulting from synthetic activations in actual noise indicate that such approach allows to evaluate important features of the response, such as the time to onset, and time to peak. Moreover, the results obtained from real high temporal resolution fMRI data acquired at l.5 T during a motor task are consistent with previous knowledge about the responses of different cortical areas in motor programming and execution. The proposed procedure should also prove useful as a pre-processing step in different approaches to the analysis of fMRI data. [Copyright &y& Elsevier]

A method for on-line single sweep detection of somatosensory evoked potentials (SEPs) during intraoperative neuromonitoring is proposed. It is based on a radial-basis function neural network with Gaussian activations. In order to improve its tracking capabilities, the radial-basis functions location is partially learnt sweep-by-sweep; the training algorithm is effective, though consistent with real-time applications. This new detection method has been tested on simulated data so as to set the network parameters. Moreover, it has been applied to real recordings obtained from a new neuromonitoring technique which is based on the simultaneous observation of the SEP and of the evoked H-reflex elicited by the same electric stimulus. The SEPs have been extracted using the neural network and the results have then been compared to those obtained by ARX filtering and correlated with the spinal cord integrity information obtained by the H-reflex. The proposed algorithm has been proved to be particularly effective and suitable for single-sweep detection. It is able to track both sudden and smooth signal changes of both amplitude and latency and the needed computational time is moderate. [ABSTRACT FROM AUTHOR]

While magnetoencephalography (MEG) is widely used to identify spatial locations of brain activations associated with various tasks, classification of single trials in stimulus-locked experiments remains an open subject. Very significant single-trial classification results have been published using electroencephalogram (EEG) data, but in the MEG case, the weakness of the magnetic fields originating from the relevant sources relative to external noise, and the high dimensionality of the data are difficult obstacles to overcome. We present here very significant MEG single-trial mean classification rates of words. The number of words classified varied from seven to nine and both visual and auditory modalities were studied. These results were obtained by using a variety of blind sources separation methods: spatial principal components analysis (PCA), Infomax independent components analysis (Infomax ICA) and second-order blind identification (SOBI). The sources obtained were classified using two methods, linear discriminant classification (LDC) and ν-support vector machine (ν-SVM). The data used here, auditory and visual presentations of words, presented nontrivial classification problems, but with Infomax ICA associated with LDC we obtained high classification rates. Our best single-trial mean classification rate was 60.1% for classification of 900 single trials of nine auditory words. On two-class problems rates were as high as 97.5%. [ABSTRACT FROM AUTHOR]

Abstract: Objective: This study was aimed at developing a method for extraction and assessment of event-related brain potentials (ERP) from single-trials. This method should be applicable in the assessment of single persons’ ERPs and should be able to handle both single ERP components and whole waveforms. Methods: We adopted a recently developed ERP feature extraction method, the t-CWT, for the purposes of hypothesis testing in the statistical assessment of ERPs. The t-CWT is based on the continuous wavelet transform (CWT) and Student’s t-statistics. The method was tested in two ERP paradigms, oddball and semantic priming, by assessing individual-participant data on a single-trial basis, and testing the significance of selected ERP components, P300 and N400, as well as of whole ERP waveforms. The t-CWT was also compared to other univariate and multivariate ERP assessment methods: peak picking, area computation, discrete wavelet transform (DWT) and principal component analysis (PCA). Results: The t-CWT produced better results than all of the other assessment methods it was compared with. Conclusions: The t-CWT can be used as a reliable and powerful method for ERP-component detection and testing of statistical hypotheses concerning both single ERP components and whole waveforms extracted from either single persons’ or group data. Significance: The t-CWT is the first such method based explicitly on the criteria of maximal statistical difference between two average ERPs in the time–frequency domain and is particularly suitable for ERP assessment of individual data (e.g. in clinical settings), but also for the investigation of small and/or novel ERP effects from group data. [Copyright &y& Elsevier]

Abstract: To investigate underlying learning mechanisms in relation to the development of dyslexia, event-related potentials to visual standards were recorded in five-year-old pre-reading children at-risk for familial dyslexia (n =24) and their controls (n =14). At the end of second grade the children aged 8 years were regrouped into three groups according to literacy level and risk factor. Single-trial analyses revealed N1 habituation in the normal-reading controls, but not in the normal-reading at-risks, and a N1 amplitude increase in the group of poor-reading at-risks and poor-reading controls. No P3 habituation was found in either group. The normal-reading at-risk group exhibited the longest N1 and P3 latencies, possibly compensating for their reduced neuronal activity during initial information extraction. In contrast, the poor-reading group only showed prolonged P3, and their increase in (initial small) N1 amplitude together with normal N1 latencies, suggests inefficient processing in an early time window, which might explain automatisation difficulties in dyslexic readers. [Copyright &y& Elsevier]

Abstract: Variation of single-trial P300 responses was studied both in relation to reaction times and to the preceding stimulus sequence in an auditory oddball paradigm. Single-trial responses were estimated with the Subspace regularization method that is based on Bayesian estimation and linear modeling. The results of the single-trial method were compared to those of averaging. Both methods showed that the latency of the P300 was shorter and its amplitude larger for faster than slower reaction times. The P300 latency was shorter for target tones that were preceded by a large number of standard tones compared to those preceded by a small number of standard tones. The P300 amplitude was statistically significantly affected by the stimulus sequence only when analyzed with conventional averaging. In-depth analysis of standard deviations showed that the variability of the P300 single-trial latencies could explain the differences between the two methods. Specifically, the regression analysis showed that the latency correlated negatively with the number of preceding standard tones and positively with the reaction time, whereas the P300 amplitude correlated positively with the number of the preceding standard stimuli and negatively with the reaction time. The analysis of the single-trial responses gives information about the behavior of the P300 component that is lost with conventional averaging. The method used in this study is independent of subjective decision making and can be used to model changes in the dynamical behavior of the P300 component objectively. [Copyright &y& Elsevier]

Abstract: Computer simulations and event-related functional MRI (ER-fMRI) experiments were performed to investigate the effects of single-trial averaging and the corresponding contrast-to-noise ratio (CNR) on the minimal resolvable hemodynamic timing difference between brain areas. Three ER-fMRI sessions with temporally delayed (250, 500 and 1000 ms) visual stimulations between two hemifields, each with 70 repeated single trials, were examined on two subjects. From the computer simulation, the temporal resolution improved as the CNR increased, which reached 500 and 100 ms for CNRs of 1.55 and 6.44, respectively. In the ER-fMRI experiments, the measured CNR increased as more single trials were averaged. The detectability of temporal differences was positively correlated (P<.05) with the CNR in all sessions for one subject but only in the 1000-ms session for the other subject. Temporal resolution of 1000 ms was achieved when more than 10 trials were averaged. The 500- and 250-ms delays might be differentiable when more than 20 trials were averaged, but the results were subject-dependent. This study demonstrated that the CNR could be significantly improved by single-trial averaging, which led to an improved temporal resolution of ER-fMRI. Temporal resolution in the range of hundreds of milliseconds was subject-dependent, which might be attributed to the intrinsic spatial variations in the timing of the blood oxygenation level-dependent (BOLD) response. [Copyright &y& Elsevier]

The present study compared the effects of repeated stimulus presentations on the event-related potential (ERP) of humans and rats. Both species were presented with a total of 100 auditory stimuli, divided into four blocks of 25 stimuli. By means of wavelet denoising, single-trial ERPs were established in both humans and rats. The auditory ERPs were characterized by the presence of two positive and two negative waves in both humans and rats, albeit with different latencies in the two species (P1, N1, P2, and N2). The results showed decreased amplitudes within blocks for the N1, P2, and N2 components in humans and for the N1 and P2 components in rats. Decreased amplitudes across blocks were found for the N2 component in humans and for the P2 and N2 components in rats. In both humans and rats, response decrements within a block were thus most prominent for the early ERP components, whereas the changes across blocks were most prominent for the later components. These results suggest a correspondence of the ERP correlates of elemental stimulus processing between humans and rats. It is further suggested that the observed amplitude reductions may reflect habituation and/or recovery cycle processes. [Copyright &y& Elsevier]