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Executive function measures of participants with mild cognitive impairment: Systematic review and meta-analysis of event-related potential studies

Che J, Cheng N, Jiang B, Liu Y, Liu H, Li Y, et al.

Int J Psychophysiol, 2024 Mar;197:112295.
PMID: 38266685 DOI: 10.1016/j.ijpsycho.2023.112295

OBJECTIVE: Objective measurements of executive functions using event-related potential (ERP) may be used as markers for differentiating healthy controls (HC) from patients with mild cognitive impairment (MCI). ERP is non-invasive, cost-effective, and affordable. Older adults with MCI demonstrate deteriorated executive function, serving as a potentially valid neurophysiological marker for identifying MCI. We aimed to review published ERP studies on executive function in older adults with MCI and summarize the performance differences by component between healthy older adults and older adults with MCI.
METHODS: Eight electronic databases (Web of Science, PubMed, ScienceDirect, American Psychological Association PsycNet, Cochrane Library, Scopus, Embase, and Ovid) were searched for the study. Articles published from January 1 to December 31, 2022, were considered for this review. A random-effects meta-analysis and between-study heterogeneity analysis were conducted using Comprehensive Meta-Analysis V3.0 software.
RESULTS: We identified 7829 articles of which 28 met the full inclusion criteria and were included in the systematic review and analyses. Our pooled analysis suggested that participants with MCI can be differentiated from HC by significant P200, P300, and N200 latencies. The P100 and P300 amplitudes were significantly smaller in participants with MCI when compared with those in the HCs, and the patients with MCI showed increased N200 amplitudes. Our findings provide new insights into potential electrophysiological biomarkers for diagnosing MCI.

Matched MeSH terms: Evoked Potentials/physiology
Neuroelectrophysiological approaches in heroin addiction research: A review of literatures

Motlagh F, Ibrahim F, Menke JM, Rashid R, Seghatoleslam T, Habil H

J Neurosci Res, 2016 Apr;94(4):297-309.
PMID: 26748947 DOI: 10.1002/jnr.23703

Neuroelectrophysiological properties have been used in human heroin addiction studies. These studies vary in their approach, experimental conditions, paradigms, and outcomes. However, it is essential to integrate previous findings and experimental methods for a better demonstration of current issues and challenges in designing such studies. This Review examines methodologies and experimental conditions of neuroelectrophysiological research among heroin addicts during withdrawal, abstinence, and methadone maintenance treatment and presents the findings. The results show decrements in attentional processing and dysfunctions in brain response inhibition as well as brain activity abnormalities induced by chronic heroin abuse. Chronic heroin addiction causes increased β and α2 power activity, latency of P300 and P600, and diminished P300 and P600 amplitude. Findings confirm that electroencephalography (EEG) band power and coherence are associated with craving indices and heroin abuse history. First symptoms of withdrawal can be seen in high-frequency EEG bands, and the severity of these symptoms is associated with brain functional connectivity. EEG spectral changes and event-related potential (ERP) properties have been shown to be associated with abstinence length and tend to normalize within 3-6 months of abstinence. From the conflicting criteria and confounding effects in neuroelectrophysiological studies, the authors suggest a comprehensive longitudinal study with a multimethod approach for monitoring EEG and ERP attributes of heroin addicts from early stages of withdrawal until long-term abstinence to control the confounding effects, such as nicotine abuse and other comorbid and premorbid conditions.

Matched MeSH terms: Evoked Potentials/physiology
Study of target and non-target interplay in spatial attention task

Sweeti, Joshi D, Panigrahi BK, Anand S, Santhosh J

J Med Eng Technol, 2018 Feb;42(2):113-120.
PMID: 29448856 DOI: 10.1080/03091902.2018.1433244

Selective visual attention is the ability to selectively pay attention to the targets while inhibiting the distractors. This paper aims to study the targets and non-targets interplay in spatial attention task while subject attends to the target object present in one visual hemifield and ignores the distractor present in another visual hemifield. This paper performs the averaged evoked response potential (ERP) analysis and time-frequency analysis. ERP analysis agrees to the left hemisphere superiority over late potentials for the targets present in right visual hemifield. Time-frequency analysis performed suggests two parameters i.e. event-related spectral perturbation (ERSP) and inter-trial coherence (ITC). These parameters show the same properties for the target present in either of the visual hemifields but show the difference while comparing the activity corresponding to the targets and non-targets. In this way, this study helps to visualise the difference between targets present in the left and right visual hemifields and, also the targets and non-targets present in the left and right visual hemifields. These results could be utilised to monitor subjects' performance in brain-computer interface (BCI) and neurorehabilitation.

Matched MeSH terms: Evoked Potentials/physiology*
Single-trial extraction of event-related potentials (ERPs) and classification of visual stimuli by ensemble use of discrete wavelet transform with Huffman coding and machine learning techniques

Amin HU, Ullah R, Reza MF, Malik AS

J Neuroeng Rehabil, 2023 Jun 02;20(1):70.
PMID: 37269019 DOI: 10.1186/s12984-023-01179-8

BACKGROUND: Presentation of visual stimuli can induce changes in EEG signals that are typically detectable by averaging together data from multiple trials for individual participant analysis as well as for groups or conditions analysis of multiple participants. This study proposes a new method based on the discrete wavelet transform with Huffman coding and machine learning for single-trial analysis of evenal (ERPs) and classification of different visual events in the visual object detection task.
METHODS: EEG single trials are decomposed with discrete wavelet transform (DWT) up to the [Formula: see text] level of decomposition using a biorthogonal B-spline wavelet. The coefficients of DWT in each trial are thresholded to discard sparse wavelet coefficients, while the quality of the signal is well maintained. The remaining optimum coefficients in each trial are encoded into bitstreams using Huffman coding, and the codewords are represented as a feature of the ERP signal. The performance of this method is tested with real visual ERPs of sixty-eight subjects.
RESULTS: The proposed method significantly discards the spontaneous EEG activity, extracts the single-trial visual ERPs, represents the ERP waveform into a compact bitstream as a feature, and achieves promising results in classifying the visual objects with classification performance metrics: accuracies 93.60[Formula: see text], sensitivities 93.55[Formula: see text], specificities 94.85[Formula: see text], precisions 92.50[Formula: see text], and area under the curve (AUC) 0.93[Formula: see text] using SVM and k-NN machine learning classifiers.
CONCLUSION: The proposed method suggests that the joint use of discrete wavelet transform (DWT) with Huffman coding has the potential to efficiently extract ERPs from background EEG for studying evoked responses in single-trial ERPs and classifying visual stimuli. The proposed approach has O(N) time complexity and could be implemented in real-time systems, such as the brain-computer interface (BCI), where fast detection of mental events is desired to smoothly operate a machine with minds.

Matched MeSH terms: Evoked Potentials/physiology
Fulltext Local context influences memory for emotional stimuli but not electrophysiological markers of emotion-dependent attention

Barnacle GE, Tsivilis D, Schaefer A, Talmi D

Psychophysiology, 2018 04;55(4).
PMID: 29023754 DOI: 10.1111/psyp.13014

Emotional enhancement of free recall can be context dependent. It is readily observed when emotional and neutral scenes are encoded and recalled together in a "mixed" list, but diminishes when these scenes are encoded separately in "pure" lists. We examined the hypothesis that this effect is due to differences in allocation of attention to neutral stimuli according to whether they are presented in mixed or pure lists, especially when encoding is intentional. Using picture stimuli that were controlled for semantic relatedness, our results contradicted this hypothesis. The amplitude of well-known electrophysiological markers of emotion-related attention-the early posterior negativity (EPN), the late positive potential (LPP), and the slow wave (SW)-was higher for emotional stimuli. Crucially, the emotional modulation of these ERPs was insensitive to list context, observed equally in pure and mixed lists. Although list context did not modulate neural markers of emotion-related attention, list context did modulate the effect of emotion on free recall. The apparent decoupling of the emotional effects on attention and memory, challenges existing hypotheses accounting for the emotional enhancement of memory. We close by discussing whether findings are more compatible with an alternative hypothesis, where the magnitude of emotional memory enhancement is, at least in part, a consequence of retrieval dynamics.

Matched MeSH terms: Evoked Potentials/physiology*
A rapid event-related potential (ERP) method for point-of-care evaluation of brain function: development of the Halifax Consciousness Scanner

Sculthorpe-Petley L, Liu C, Hajra SG, Parvar H, Satel J, Trappenberg TP, et al.

J Neurosci Methods, 2015 Apr 30;245:64-72.
PMID: 25701685 DOI: 10.1016/j.jneumeth.2015.02.008

Event-related potentials (ERPs) may provide a non-invasive index of brain function for a range of clinical applications. However, as a lab-based technique, ERPs are limited by technical challenges that prevent full integration into clinical settings.

Matched MeSH terms: Evoked Potentials/physiology*
Influence of education level on design-induced N170 and P300 components of event related potentials in the human brain

Begum T, Reza F, Ahmed I, Abdullah JM

J Integr Neurosci, 2014 Mar;13(1):71-88.
PMID: 24738540 DOI: 10.1142/S0219635214500058

Simple geometric and organic shapes and their arrangement are being used in different neuropsychology tests for the assessment of cognitive function, special memory and also for the therapy purpose in different patient groups. Until now there is no electrophysiological evidence of cognitive function determination for simple geometric, organic shapes and their arrangement. Then the main objective of this study is to know the cortical processing and amplitude, latency of visual induced N170 and P300 event related potential components on different geometric, organic shapes and their arrangement and different educational influence on it, which is worthwhile to know for the early and better treatment for those patient groups. While education influenced on cognitive function by using auditory oddball task, little is known about the influence of education on cognitive function induced by visual attention task in case of the choice of geometric, organic shapes and their arrangements. Using a 128-electrode sensor net, we studied the responses of the choice of the different geometric and organic shapes randomly in experiment 1 and their arrangements in experiment 2 in the high, medium and low education groups. In both experiments, subjects push the button "1" or "2" if like or dislike, respectively. Total 45 healthy subjects (15 in each group) were recruited. ERPs were measured from 11 electrode sites and analyzed to see the evoked N170/N240 and P300 ERP components. There were no differences between like and dislike in amplitudes even in latencies in every stimulus in both experiments. We fixed geometric shapes and organic shapes stimuli only, not like and dislike. Upon the stimulus types, N170 ERP component was found instead of N240, in occipito-temporal (T5, T6, O1 and O2) locations where the amplitude is the highest at O2 location and P300 was distributed in the central (Cz and Pz) locations in both experiments in all groups. In experiment 1, significant low amplitude and non-significant larger latency of the N170 component are found out at O1 location for both stimuli in low education group comparing medium education groups, but in experiment 2, there is no significant difference between stimuli among groups in amplitude and latency. In both experiments, P300 component was found in Cz and Pz locations though the amplitudes are higher at Cz than Pz areas. In experiment 1, medium education group evoked significantly (geometric shape stimuli, P = 0.05; organic shape stimuli, P = 0.02) higher amplitude of P300 component comparing low education group at Cz location. Whereas, there is no significant difference of amplitudes among groups across stimuli in Cz and Pz locations in experiment 2. Latencies have no significant differences in both experiments among groups also, but longer latency are found in low education group at Cz location comparing medium education group, though not significant. We conclude that simple geometric shapes, organic shapes and their arrangements evoked visual N170 component at temporo-occipital areas with right lateralization and P300 ERP component at centro-parietal areas. Significant low amplitude of N170 and P300 ERP components and longer latencies during different shape stimuli in low education group prove that, low education significantly influence on visual cognitive functions in low education group.

Matched MeSH terms: Evoked Potentials/physiology*
An expectation-maximization algorithm based Kalman smoother approach for single-trial estimation of event-related potentials

Ting CM, Samdin SB, Salleh ShH, Omar MH, Kamarulafizam I

Annu Int Conf IEEE Eng Med Biol Soc, 2012;2012:6534-8.
PMID: 23367426 DOI: 10.1109/EMBC.2012.6347491

This paper applies an expectation-maximization (EM) based Kalman smoother (KS) approach for single-trial event-related potential (ERP) estimation. Existing studies assume a Markov diffusion process for the dynamics of ERP parameters which is recursively estimated by optimal filtering approaches such as Kalman filter (KF). However, these studies only consider estimation of ERP state parameters while the model parameters are pre-specified using manual tuning, which is time-consuming for practical usage besides giving suboptimal estimates. We extend the KF approach by adding EM based maximum likelihood estimation of the model parameters to obtain more accurate ERP estimates automatically. We also introduce different model variants by allowing flexibility in the covariance structure of model noises. Optimal model selection is performed based on Akaike Information Criterion (AIC). The method is applied to estimation of chirp-evoked auditory brainstem responses (ABRs) for detection of wave V critical for assessment of hearing loss. Results shows that use of more complex covariances are better estimating inter-trial variability.

Matched MeSH terms: Evoked Potentials/physiology*
Brain activity elicited by reward and reward omission in individuals with psychopathic traits: An ERP study

Salim MA, van der Veen FM, van Dongen JD, Franken IH

Biol Psychol, 2015 Sep;110:50-8.
PMID: 26188154 DOI: 10.1016/j.biopsycho.2015.07.001

Psychopathy has been associated with behavioral adaptation deficits, which might be associated with problems in feedback and reward processing. In the present study, we examined the relation between psychopathic traits and reward processing in a passive gambling task. A total of 39 male participants who scored high (HP) and 39 male participants who scored low (LP) on the Triarchic Psychopathy Measure (TriPM), total score were tested. Feedback-related Event-Related Potentials (ERPs; i.e., P2, FRN, and P3) on predicted and unpredicted rewards and reward omissions were compared between both groups. It was found that in HP individuals, the P2 was enhanced for predicted rewards and reward omissions, but not for unpredicted stimuli. Moreover, HP individuals as compared to the LP individuals demonstrated a generally reduced P3 amplitude. The FRN amplitude, however, did not differ between the two groups. In addition, HP individuals showed enhanced reward sensitivity on the self-report level. Taken together, these findings suggest that HP individuals show enhanced sensitivity to early and reduced sensitivity to later markers of processing reinforcement learning signals, which points in the direction of compromised behavioral adaptation.

Matched MeSH terms: Evoked Potentials/physiology*
Investigation of brain electrophysiological properties among heroin addicts: Quantitative EEG and event-related potentials

Motlagh F, Ibrahim F, Rashid R, Seghatoleslam T, Habil H

J Neurosci Res, 2017 08;95(8):1633-1646.
PMID: 27862172 DOI: 10.1002/jnr.23988

This study aims to introduce a new approach of a comprehensive paradigm to evaluate brain electrophysiological properties among addicts. Electroencephalographic spectral power as well as amplitudes and latencies of mismatch negativity (MMN), P300, and P600 components were evaluated among 19 male heroin addicts and 19 healthy nonsmoker subjects using a paradigm consisting of three subparadigms, namely (1) digit span Wechsler test, (2) auditory oddball, and (3) visual cue-reactivity oddball paradigms. Task 1 provided auditory P300 and P600 in association with working memory. Task 2 provided auditory P300 as well as small and large deviant MMN event-related potential (ERPs). Finally, task 3 provided visual cue-reactivity P300. Results show that beta power was higher among heroin addicts while delta, theta, and alpha powers were decreased compared with healthy subjects. ERP analysis confirmed the decline of brain-evoked potential amplitudes when compared with healthy subjects, thus indicating a broad neurobiological vulnerability of preattentive and attentional processing including attentional deficits and compromise of discrimination abilities. The prolonged latency of ERPs reflects poor cognitive capacity in the engagement of attention and memory resources. On the other hand, an increase of attention towards the heroin-related stimuli could be concluded from the increase of P300 in the cue-reactivity condition among heroin addicts. Findings suggest that applying this paradigm in addiction studies benefits comprehensive evaluation of neuroelectrophysiological activity among addicts, which can promote a better understanding of drugs' effects on the brain as well as define new neuroelectrophysiological characteristics of addiction properties. © 2016 Wiley Periodicals, Inc.

Matched MeSH terms: Evoked Potentials/physiology*
The Time Course of Activity within the Dorsal and Rostral-Ventral Anterior Cingulate Cortex in the Emotional Stroop Task

Feroz FS, Leicht G, Steinmann S, Andreou C, Mulert C

Brain Topogr, 2017 Jan;30(1):30-45.
PMID: 27659288 DOI: 10.1007/s10548-016-0521-3

Growing evidence from neuroimaging studies suggest that emotional and cognitive processes are interrelated. Anatomical key structures in this context are the dorsal and rostral-ventral anterior cingulate cortex (dACC and rvACC). However, up to now, the time course of activations within these regions during emotion-cognition interactions has not been disentangled. In the present study, we used event-related potentials (ERP) and standardized low-resolution electromagnetic tomography (sLORETA) region of interest (ROI) source localization analyses to explore the time course of neural activations within the dACC and rvACC using a modified emotional Stroop paradigm. ERP components related to Stroop conflict (N200, N450 and late negativity) were analyzed. The time course of brain activations in the dACC and rvACC was strikingly different with more pronounced initial responses in the rvACC followed by increased dACC activity mainly at the late negativity window. Moreover, emotional valence modulated the earlier N450 stage within the rvACC region with higher neural activations in the positive compared to the negative and neutral conditions. Emotional arousal modulated the late negativity stage; firstly in the significant arousal × congruence ERP effect and then the significant higher current density in the low arousal condition within the dACC. Using sLORETA source localization, substantial differences in the activation time courses in the dACC and rvACC could be found during the emotional Stroop task. We suggest that during late negativity, within the dACC, emotional arousal modulated the processing of response conflict, reflected in the correlation between the ex-Gaussian µ and the current density in the dACC.

Matched MeSH terms: Evoked Potentials/physiology*
Fulltext The Time Course of Dorsal and Rostral-Ventral Anterior Cingulate Cortex Activity in the Emotional Stroop Experiment Reveals Valence and Arousal Aberrant Modulation in Patients with Schizophrenia

Feroz FS, Leicht G, Rauh J, Mulert C

Brain Topogr, 2019 01;32(1):161-177.
PMID: 30288663 DOI: 10.1007/s10548-018-0677-0

This paper aims to investigate the temporal dynamics within the dorsal anterior cingulate cortex (dACC) and the rostral-ventral (rv) ACC during the interaction of emotional valence and arousal with cognitive control in patients with Schizophrenia (SZ). Although cognitive deficits in SZ are highly relevant and emotional disturbances are common, the temporal relationship of brain regions involved in the interaction of emotional and cognitive processing in SZ is yet to be determined. To address this issue, the reaction time (RT), event-related potential (ERP) and temporal dynamics of the dACC and rvACC activity were compared between SZ subjects and healthy controls (HC), using a modified emotional Stroop experiment (with factors namely congruence, arousal and valence). EEG was recorded with 64 channels and source localisation was performed using the sLORETA software package. We observed slower initial increase and lower peaks of time course activity within the dACC and rvACC in the SZ group. In this particular group, the dACC activity during late negativity was negatively correlated with a significantly higher RT in the high arousal conflict condition. In contrast to HC subjects, at the N450 window, there was no significant valence (ERP and rvACC ROI) modulation effect in the SZ subjects. Using high density EEG and source localisation, it was possible to distinguish various disturbances within the dACC and rvACC in patients with SZ, during emotion-cognition processing.

Matched MeSH terms: Evoked Potentials/physiology*
Fulltext In search of a reliable electrophysiological marker of oculomotor inhibition of return

Satel J, Hilchey MD, Wang Z, Reiss CS, Klein RM

Psychophysiology, 2014 Oct;51(10):1037-45.
PMID: 24976355 DOI: 10.1111/psyp.12245

Inhibition of return (IOR) operationalizes a behavioral phenomenon characterized by slower responding to cued, relative to uncued, targets. Two independent forms of IOR have been theorized: input-based IOR occurs when the oculomotor system is quiescent, while output-based IOR occurs when the oculomotor system is engaged. EEG studies forbidding eye movements have demonstrated that reductions of target-elicited P1 components are correlated with IOR magnitude, but when eye movements occur, P1 effects bear no relationship to behavior. We expand on this work by adapting the cueing paradigm and recording event-related potentials: IOR is caused by oculomotor responses to central arrows or peripheral onsets and measured by key presses to peripheral targets. Behavioral IOR is observed in both conditions, but P1 reductions are absent in the central arrow condition. By contrast, arrow and peripheral cues enhance Nd, especially over contralateral electrode sites.

Matched MeSH terms: Evoked Potentials/physiology*
Emotion classification in Parkinson's disease by higher-order spectra and power spectrum features using EEG signals: a comparative study

Yuvaraj R, Murugappan M, Ibrahim NM, Omar MI, Sundaraj K, Mohamad K, et al.

J Integr Neurosci, 2014 Mar;13(1):89-120.
PMID: 24738541 DOI: 10.1142/S021963521450006X

Deficits in the ability to process emotions characterize several neuropsychiatric disorders and are traits of Parkinson's disease (PD), and there is need for a method of quantifying emotion, which is currently performed by clinical diagnosis. Electroencephalogram (EEG) signals, being an activity of central nervous system (CNS), can reflect the underlying true emotional state of a person. This study applied machine-learning algorithms to categorize EEG emotional states in PD patients that would classify six basic emotions (happiness and sadness, fear, anger, surprise and disgust) in comparison with healthy controls (HC). Emotional EEG data were recorded from 20 PD patients and 20 healthy age-, education level- and sex-matched controls using multimodal (audio-visual) stimuli. The use of nonlinear features motivated by the higher-order spectra (HOS) has been reported to be a promising approach to classify the emotional states. In this work, we made the comparative study of the performance of k-nearest neighbor (kNN) and support vector machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Analysis of variance (ANOVA) showed that power spectrum and HOS based features were statistically significant among the six emotional states (p < 0.0001). Classification results shows that using the selected HOS based features instead of power spectrum based features provided comparatively better accuracy for all the six classes with an overall accuracy of 70.10% ± 2.83% and 77.29% ± 1.73% for PD patients and HC in beta (13-30 Hz) band using SVM classifier. Besides, PD patients achieved less accuracy in the processing of negative emotions (sadness, fear, anger and disgust) than in processing of positive emotions (happiness, surprise) compared with HC. These results demonstrate the effectiveness of applying machine learning techniques to the classification of emotional states in PD patients in a user independent manner using EEG signals. The accuracy of the system can be improved by investigating the other HOS based features. This study might lead to a practical system for noninvasive assessment of the emotional impairments associated with neurological disorders.

Matched MeSH terms: Evoked Potentials/physiology*
Neural network classification of autoregressive features from electroencephalogram signals for brain-computer interface design

Huan NJ, Palaniappan R

J Neural Eng, 2004 Sep;1(3):142-50.
PMID: 15876633

In this paper, we have designed a two-state brain-computer interface (BCI) using neural network (NN) classification of autoregressive (AR) features from electroencephalogram (EEG) signals extracted during mental tasks. The main purpose of the study is to use Keirn and Aunon's data to investigate the performance of different mental task combinations and different AR features for BCI design for individual subjects. In the experimental study, EEG signals from five mental tasks were recorded from four subjects. Different combinations of two mental tasks were studied for each subject. Six different feature extraction methods were used to extract the features from the EEG signals: AR coefficients computed with Burg's algorithm, AR coefficients computed with a least-squares (LS) algorithm and adaptive autoregressive (AAR) coefficients computed with a least-mean-square (LMS) algorithm. All the methods used order six applied to 125 data points and these three methods were repeated with the same data but with segmentation into five segments in increments of 25 data points. The multilayer perceptron NN trained by the back-propagation algorithm (MLP-BP) and linear discriminant analysis (LDA) were used to classify the computed features into different categories that represent the mental tasks. We compared the classification performances among the six different feature extraction methods. The results showed that sixth-order AR coefficients with the LS algorithm without segmentation gave the best performance (93.10%) using MLP-BP and (97.00%) using LDA. The results also showed that the segmentation and AAR methods are not suitable for this set of EEG signals. We conclude that, for different subjects, the best mental task combinations are different and proper selection of mental tasks and feature extraction methods are essential for the BCI design.

Matched MeSH terms: Evoked Potentials/physiology
Multisensory stimulation modulates perceptual and post perceptual face representations: Evidence from event-related potentials

Estudillo AJ, Kaufmann JM, Bindemann M, Schweinberger SR

Eur J Neurosci, 2018 09;48(5):2259-2271.
PMID: 30107052 DOI: 10.1111/ejn.14112

Seeing a face being touched in spatial and temporal synchrony with the own face produces a bias in self-recognition, whereby the other face becomes more likely to be perceived as the self. The present study employed event-related potentials to explore whether this enfacement effect reflects initial face encoding, enhanced distinctiveness of the enfaced face, modified self-identity representations, or even later processing stages that are associated with the emotional processing of faces. Participants were stroked in synchrony or asynchrony with an unfamiliar face they observed on a monitor in front of them, in a situation approximating a mirror image. Subsequently, event-related potentials were recorded during the presentation of (a) a previously synchronously stimulated face, (b) an asynchronously stimulated face, (c) observers' own face, (d) filler faces, and (e) a to-be-detected target face, which required a response. Observers reported a consistent enfacement illusion after synchronous stimulation. Importantly, the synchronously stimulated face elicited more prominent N170 and P200 responses than the asynchronously stimulated face. By contrast, similar N250 and P300 responses were observed in these conditions. These results suggest that enfacement modulates early neural correlates of face encoding and facial prototypicality, rather than identity self-representations and associated emotional processes.

Matched MeSH terms: Evoked Potentials/physiology*

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