Bootstrap analysis of the single subject with event related potentials

A Dynamic Multi-Scale Convolution Model for Face Recognition Using Event-Related Potentials

With the development of data mining technology, the analysis of event-related potential (ERP) data has evolved from statistical analysis of time-domain features to data-driven techniques based on supervised and unsupervised learning. However, there are still many challenges in understanding the relationship between ERP components and the representation of familiar and unfamiliar faces. To address this, this paper proposes a model based on Dynamic Multi-Scale Convolution for group recognition of familiar and unfamiliar faces. This approach uses generated weight masks for cross-subject familiar/unfamiliar face recognition using a multi-scale model. The model employs a variable-length filter generator to dynamically determine the optimal filter length for time-series samples, thereby capturing features at different time scales. Comparative experiments are conducted to evaluate the model's performance against SOTA models. The results demonstrate that our model achieves impressive outcomes, with a balanced accuracy rate of 93.20% and an F1 score of 88.54%, outperforming the methods used for comparison. The ERP data extracted from different time regions in the model can also provide data-driven technical support for research based on the representation of different ERP components.

Coherent activity within and between hemispheres: cortico-cortical connectivity revealed by rTMS of the right posterior parietal cortex

Introduction

Low frequency (1 Hz) repetitive transcranial stimulation (rTMS) applied over right posterior parietal cortex (rPPC) has been shown to reduce cortical excitability both of the stimulated area and of the interconnected contralateral homologous areas. In the present study, we investigated the whole pattern of intra- and inter-hemispheric cortico-cortical connectivity changes induced by rTMS over rPPC.

Methods

To do so, 14 healthy participants underwent resting state EEG recording before and after 30 min of rTMS at 1 Hz or sham stimulation over the rPPC (electrode position P6). Real stimulation was applied at 90% of motor threshold. Coherence values were computed on the electrodes nearby the stimulated site (i.e., P4, P8, and CP6) considering all possible inter- and intra-hemispheric combinations for the following frequency bands: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12Hz), low beta (12-20 Hz), high beta (20-30 Hz), and gamma (30-50 Hz).

Results and discussion

Results revealed a significant increase in coherence in delta, theta, alpha and beta frequency bands between rPPC and the contralateral homologous sites. Moreover, an increase in coherence in theta, alpha, beta and gamma frequency bands was found between rPPC and right frontal sites, reflecting the activation of the fronto-parietal network within the right hemisphere. Summarizing, subthreshold rTMS over rPPC revealed cortico-cortical inter- and intra-hemispheric connectivity as measured by the increase in coherence among these areas. Moreover, the present results further confirm previous evidence indicating that the increase of coherence values is related to intra- and inter-hemispheric inhibitory effects of rTMS. These results can have implications for devising evidence-based rehabilitation protocols after stroke.

The Relation Between Belief in a Just World and Early Processing of Deserved and Undeserved Outcomes: An ERP Study

We used event-related potentials (ERPs) to examine how quickly people in general, and certain people in particular, process deservingness-relevant information. Female university students completed individual difference measures, including individual differences in the belief in a just world (BJW), a belief that people get what they deserve. They then read stories in which an outcome was deserved, undeserved, or neither deserved nor undeserved (i.e., "neutral") while their ERPs were recorded with scalp electrodes. We found no overall differentiation between early ERP responses (< 300 ms post stimulus onset) to deserved, undeserved, and neutral outcomes. However, BJW correlated with the difference between early ERP responses to these forms of information (rs from |.44| to |.61|; ps from .018 to < .001). The early nature of our effects (e.g., 96 ms after stimulus onset) suggests individual differences in socially-relevant information processing that begins before conscious evaluation of the stimuli. Potential underlying processes include automatic attention to schema-relevant information and to unexpected (and therefore salient) information and automatic processing of belief-consistent information. Our research underscores the importance of the concept of deservingness in human information processing as well as the utility of ERP technology and robust statistical analyses in investigations of complex social stimuli.

Neural Correlates of Affective Stimulus Evaluation: A Case-by-Case Analysis

A recent study provided first evidence that neural correlates of affective stimulus evaluation, that is, the early posterior negativity (EPN) and late positive potential (LPP), can be assessed at the individual case level. Expanding the case-by-case approach, the main aim of the present study was to explore the process of affective stimulus evaluation within the individual participant with respect to multiple emotional stimulus classes. Towards this end, each participant viewed separate blocks of low and high arousing pictures from behavior systems of predator fear, disease avoidance, and sexual reproduction. 13 out of 16 participants showed larger EPN and LPP amplitudes for higher than lower arousing stimuli for all three behavior systems. Furthermore, rather than indicating a general lack of emotional modulation, cases of non-significant EPN (N= 3) and LPP (N= 2) tests in individual participants appeared to be specific to a single emotion category. Overall, assessing the emotional modulation of the EPN and LPP across multiple behavior systems strengthens the case-by-case approach regarding an effect "common-to-all" as well as by differentiating non-significant effects within individuals in terms of a content-specific or general phenomenon. Implications for revealing a general principle of emotion functioning and biomarker development are discussed.

Characterizing the neural signature of face processing in Williams syndrome via multivariate pattern analysis and event related potentials

Face recognition ability is often reported to be a relative strength in Williams syndrome (WS). Yet methodological issues associated with the supporting research, and evidence that atypical face processing mechanisms may drive outcomes 'in the typical range', challenge these simplistic characterisations of this important social ability. Detailed investigations of face processing abilities in WS both at a behavioural and neural level provide critical insights. Here, we behaviourally characterised face recognition ability in 18 individuals with WS comparatively to typically developing children and adult control groups. A subset of 11 participants with WS as well as chronologically age matched typical adults further took part in an EEG task where they were asked to attentively view a series of upright and inverted faces and houses. State-of-the-art multivariate pattern analysis (MVPA) was used alongside standard ERP analysis to obtain a detailed characterisation of the neural profile associated with 1) viewing faces as an overall category (by examining neural activity associated with upright faces and houses), and to 2) the canonical upright configuration of a face, critically associated with expertise in typical development and often linked with holistic processing (upright and inverted faces). Our results show that while face recognition ability is not on average at a chronological age-appropriate level in individuals with WS, it nonetheless appears to be a relative strength within their cognitive profile. Furthermore, all participants with WS revealed a differential pattern of neural activity to faces compared to objects, showing a distinct response to faces as a category, as well as a differential neural pattern for upright vs. inverted faces. Nonetheless, an atypical profile of face orientation classification was found in WS, suggesting that this group differs from typical individuals in their face processing mechanisms. Through this innovative application of MVPA, alongside the high temporal resolution of EEG, we provide important new insights into the neural processing of faces in WS.

Multimodal exploration of non-motor neural functions in ALS patients using simultaneous EEG-fNIRS recording

OBJECTIVE

Despite the high prevalence of non-motor impairments reported in patients with amyotrophic lateral sclerosis (ALS), little is known about the functional neural markers underlying such dysfunctions. In this study, a new dual-task multimodal framework relying on simultaneous electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) recordings was developed to characterize integrative non-motor neural functions in people with ALS.

APPROACH

Simultaneous EEG-fNIRS data were recorded from six subjects with ALS and twelve healthy controls. Through a proposed visuo-mental paradigm, subjects performed a set of visuo-mental arithmetic operations. The data recorded were analyzed with respect to event-related changes both in the time and frequency domains for EEG and de/oxygen-hemoglobin level (HbR/HbO) changes for fNIRS. The correlation of EEG spectral features with fNIRS HbO/HbR features were then evaluated to assess the mechanisms of ALS on the electrical (EEG)-vascular (fNIRS) interrelationships.

MAIN RESULTS

We observed overall smaller increases in EEG delta and theta power, decreases in beta power, reductions in HbO responses, and distortions both in early and later EEG event-related potentials in ALS subjects compared to healthy controls. While significant correlations between EEG features and HbO responses were observed in healthy controls, these patterns were absent in ALS patients. Distortions in both electrical and hemodynamic responses are speculated to be associated with cognitive deficits in ALS that center primarily on attentional and working memory processing.

SIGNIFICANCE

Our results highlight the important role of ALS non-motor dysfunctions in electrical and hemodynamic neural dynamics as well as their interrelationships. The insights obtained through this study can enhance our understanding of the underlying non-motor neural processes in ALS and enrich future diagnostic and prognostic techniques.

Impairments in action and perception after right intraparietal damage

We examined visually-guided reaching and perception in an individual who underwent resection of a small tumor in right intraparietal sulcus (pIPS). In the first experiment, she reached to targets presented on a touch screen. Vision was occluded from reach onset on half of the trials, whereas on the other half she had vision during the entire reach. For visually-guided reaching, she demonstrated significantly more reach errors for targets left of fixation versus right of fixation. However, there were no hemispatial differences when reaching without vision. Furthermore, her performance was consistent for reaches with either hand, providing evidence that pIPS encodes location based on an eye-centered reference frame. Second, previous studies reported that optic ataxics are more accurate when reaching to remembered versus visible target locations. We repeated the first experiment, adding a five second delay between stimulus presentation and reach initiation. In contrast to prior reports, she was less accurate in delayed versus immediate reaching. Finally, we examined whether a small pIPS resection would disrupt visuospatial processing in a simple perceptual task. We presented two small circles in succession in either the same location or offset at varying distances, and asked whether the two circles were presented in the same or different position. She was significantly more impaired left of fixation compared to right of fixation, providing evidence for a perceptual deficit after a dorsal stream lesion.

STATSLAB: An open-source EEG toolbox for computing single-subject effects using robust statistics

Research on robust statistics during the past half century provides concrete evidence that classical hypothesis tests that rely on the sample mean and variance are problematic. Even seemingly minor departures from normality are now known to create major problems in terms of increased error rates and decreased power. Fortunately, numerous robust estimation techniques have been developed that circumvent the need for strict assumptions of normality and equal variances, leading to increased power and accuracy when testing hypotheses. Two robust methods that have been shown to have practical value across a wide range of applied situations are the trimmed mean and percentile bootstrap test. To facilitate the uptake of robust methods into the behavioural sciences, especially when dealing with trial-based data such as EEG, we introduce STATSLAB: An open-source EEG toolbox for computing single-subject effects using robust statistics. With the STATSLAB toolbox users can apply the percentile bootstrap test, with trimmed means, to a variety of neural signals including voltages, global field amplitude, and spectral features for both scalp channels and independent components. The toolbox offers a range of analytical strategies and is packaged with a fully functional graphical user interface that includes documentation.

Markers of TMS-evoked visual conscious experience in a patient with altitudinal hemianopia

Transcranial magnetic stimulation (TMS) of the occipital and parietal cortices can induce phosphenes, i.e. visual sensations of light without light entering the eyes. In this paper, we adopted a TMS-EEG interactive co-registration approach with a patient (AM) showing altitudinal hemianopia. Occipital and parietal cortices in both hemispheres were stimulated while concurrently recording EEG signal. Results showed that, for all sites, neural activity differentially encoding for the presence vs. absence of a conscious experience could be found in a cluster of electrodes close to the stimulation site at an early (70ms) time-period after TMS. The present data indicate that both occipital and parietal sites are independent early gatekeepers of perceptual awareness, thus, in line with evidence in favor of early correlates of perceptual awareness. Moreover, these data support the valuable contribution of the TMS-EEG approach in patients with visual field defects to investigate the neural processes responsible for perceptual awareness.

The elicitation of steady-state visual evoked potentials during sleep

This study confirmed the hypothesis that it is possible to elicit SSVEPs through closed eyelids during NREM sleep. To test this hypothesis, SSVEP amplitudes were measured in eight subjects across two conditions of stimulation (stimulation on and stimulation off) and three brain states (waking, light sleep, and deep sleep). Results showed a significant interaction between stimulation and brain state. In particular, EEG activity at the frequency of stimulation was higher during both light sleep and deep sleep in the stimulation on condition than in the stimulation off condition. The fact that it is possible to elicit SSVEPs during sleep may provide a new way to study how SSVEPs are generated in the brain-one that might help resolve open questions such as identifying the SSVEP activation sequence or deciding if SSVEPs derive from evoked or oscillatory neural processes.

Bootstrap Signal-to-Noise Confidence Intervals: An Objective Method for Subject Exclusion and Quality Control in ERP Studies

Analysis of event-related potential (ERP) data includes several steps to ensure that ERPs meet an appropriate level of signal quality. One such step, subject exclusion, rejects subject data if ERP waveforms fail to meet an appropriate level of signal quality. Subject exclusion is an important quality control step in the ERP analysis pipeline as it ensures that statistical inference is based only upon those subjects exhibiting clear evoked brain responses. This critical quality control step is most often performed simply through visual inspection of subject-level ERPs by investigators. Such an approach is qualitative, subjective, and susceptible to investigator bias, as there are no standards as to what constitutes an ERP of sufficient signal quality. Here, we describe a standardized and objective method for quantifying waveform quality in individual subjects and establishing criteria for subject exclusion. The approach uses bootstrap resampling of ERP waveforms (from a pool of all available trials) to compute a signal-to-noise ratio confidence interval (SNR-CI) for individual subject waveforms. The lower bound of this SNR-CI (SNR_LB) yields an effective and objective measure of signal quality as it ensures that ERP waveforms statistically exceed a desired signal-to-noise criterion. SNR_LB provides a quantifiable metric of individual subject ERP quality and eliminates the need for subjective evaluation of waveform quality by the investigator. We detail the SNR-CI methodology, establish the efficacy of employing this approach with Monte Carlo simulations, and demonstrate its utility in practice when applied to ERP datasets.

Perceptual face processing in developmental prosopagnosia is not sensitive to the canonical location of face parts

Individuals with developmental prosopagnosia (DP) are strongly impaired in recognizing faces, but it is controversial whether this deficit is linked to atypical visual-perceptual face processing mechanisms. Previous behavioural studies have suggested that face perception in DP might be less sensitive to the canonical spatial configuration of face parts in upright faces. To test this prediction, we recorded event-related brain potentials (ERPs) to intact upright faces and to faces with spatially scrambled parts (eyes, nose, and mouth) in a group of ten participants with DP and a group of ten age-matched control participants with normal face recognition abilities. The face-sensitive N170 component and the vertex positive potential (VPP) were both enhanced and delayed for scrambled as compared to intact faces in the control group. In contrast, N170 and VPP amplitude enhancements to scrambled faces were absent in the DP group. For control participants, the N170 to scrambled faces was also sensitive to feature locations, with larger and delayed N170 components contralateral to the side where all features appeared in a non-canonical position. No such differences were present in the DP group. These findings suggest that spatial templates of the prototypical feature locations within an upright face are selectively impaired in DP.

Extraction of mismatch negativity using a resampling-based spatial filtering method

OBJECTIVE

It is currently a challenge to extract the mismatch negativity (MMN) waveform on the basis of a small number of EEG trials, which are typically unbalanced between conditions.

APPROACH

In order to address this issue, a method combining the techniques of resampling and spatial filtering is proposed in this paper. Specifically, the first step of the method, termed 'resampling difference', randomly samples the standard and deviant sweeps, and then subtracts standard sweeps from deviant sweeps. The second step of the method employs the spatial filters designed by a signal-to-noise ratio maximizer (SIM) to extract the MMN component. The SIM algorithm can maximize the signal-to-noise ratio for event-related potentials (ERPs) to improve extraction. Simulation data were used to evaluate the influence of three parameters (i.e. trial number, repeated-SIM times and sampling times) on the performance of the proposed method.

MAIN RESULTS

Results demonstrated that it was feasible and reliable to extract the MMN waveform using the method. Finally, an oddball paradigm with auditory stimuli of different frequencies was employed to record a few trials (50 trials of deviant sweeps and 250 trials of standard sweeps) of EEG data from 11 adult subjects. Results showed that the method could effectively extract the MMN using the EEG data of each individual subject.

SIGNIFICANCE

The extracted MMN waveform has a significantly larger peak amplitude and shorter latencies in response to the more deviant stimuli than in response to the less deviant stimuli, which agreed with the MMN properties reported in previous literature using grand-averaged EEG data of multi-subjects.