P300 Waveform Research Articles

An Intrinsically Explainable Method to Decode P300 Waveforms from EEG Signal Plots Based on Convolutional Neural Networks.

This work proposes an intrinsically explainable, straightforward method to decode P300 waveforms from electroencephalography (EEG) signals, overcoming the black box nature of deep learning techniques. The proposed method allows convolutional neural networks to decode information from images, an area where they have achieved astonishing performance. By plotting the EEG signal as an image, it can be both visually interpreted by physicians and technicians and detected by the network, offering a straightforward way of explaining the decision. The identification of this pattern is used to implement a P300-based speller device, which can serve as an alternative communication channel for persons affected by amyotrophic lateral sclerosis (ALS). This method is validated by identifying this signal by performing a brain-computer interface simulation on a public dataset from ALS patients. Letter identification rates from the speller on the dataset show that this method can identify the P300 signature on the set of 8 patients. The proposed approach achieves similar performance to other state-of-the-art proposals while providing clinically relevant explainability (XAI).

Resolving a "W-Shaped" P100 Waveform: Is It Normal or Abnormal?

Pattern-reversal visual evoked potentials are used to assess the visual pathways. The main waveform of interest is the P100, which is best recorded with electrodes over the mid-occipital region. Most often, the P100 waveform has negative-positive-negative components. Occasionally, it is "W-shaped," with positive-negative-positive components. Although most often a W-shaped P100 waveform indicates an abnormality in the visual pathway, occasionally, it can be normal. A case is presented in which a W-shaped P100 waveform is seen after monocular full-field stimulation of both eyes with 30' checks. To resolve this finding, the pattern-reversal visual evoked potentials is repeated with 60' and 15' checks. With 15' checks a single typical single-peak P100 waveform is seen with normal latency. Evaluation of a W-shaped P100 waveform should involve analysis of various montages, stimulation with different check sizes, and hemifield stimulation to confirm whether the W-shaped waveform is normal or abnormal.

Association between physical health and neurocognition in first-episode schizophrenia

IntroductionImpaired cognition is a core feature of schizophrenia that is evident early in the first episode and is frequently accompanied by compromised physical health. Although physical health confers benefits to cognition, it remains unclear whether physical activity, body mass index (BMI) and cardiorespiratory fitness are associated with neurocognition in first episode schizophrenia patients. The purpose of this study was to examine differences in stimulus categorization and motor response selection processes between first-episode schizophrenia patients compared to age-matched controls and explore associations between physical health and these stages of information processing.MethodsFourteen young adult patients receiving care following a first episode of psychosis and a matched sample of nonpsychiatric controls completed a visual oddball task from which the P3 and LRP (lateralized readiness potential) event-related potential (ERP) components were extracted to assess stimulus categorization and response selection processes, respectively. Physical activity, aerobic fitness, and BMI were correlated with ERP measures.ResultsCompared with controls, patients had lower physical activity levels and longer P3 and LRP latencies. Regardless of stimulus probability, patients had reduced accuracy and slower reaction times relative to controls. In patients, marginal associations were found between physical activity and P3 difference waveform amplitude, and BMI was negatively associated with parent P3 waveform amplitude.DiscussionThe present findings suggest that cognitive impairment in first-episode schizophrenia spans both stimulus- and response-related stages of information processing, and may be targeted through physical activity interventions.

Effects of parietal repetitive transcranial magnetic stimulation in prolonged disorders of consciousness: A pilot study

ObjectiveAlthough the parietal cortex is related to consciousness, the dorsolateral prefrontal and primary motor cortices are the usual targets for repetitive transcranial magnetic stimulation (rTMS) for prolonged disorders of consciousness (pDoC). Herein, we applied parietal rTMS to patients with pDoC, to verify its neurobehavioral effects and explore a new potential rTMS target. Materials and methodsTwenty-six patients with pDoC were assigned to a rTMS or sham group. The rTMS group received 10 sessions of parietal rTMS; the sham group received 10 sessions of sham stimulation. The Coma Recovery Scale-Revised (CRS-R) and event-related potential (ERP) were collected before and after the 10 sessions or sham sessions. ResultsAfter the 10 sessions, the rTMS group showed: a significant CRS-R score increase; ERP appearance of a P300 waveform and significantly increased Fz amplitudes; increased potentials on topographic mapping, especially in the left prefrontal cortex; and an increase in delta and theta band powers at Fz, Cz, and Pz. The sham group did not show such changes in CRS-R score or ERP results statistically. ConclusionParietal rTMS shows promise as a novel intervention in the recovery of consciousness in pDoC. It showed neurobehavioral enhancement of residual brain function and may promote frontal activity by enhancing frontal–parietal connections. The parietal cortex may thus be an alternative for rTMS therapy protocols.

Comparative study of event-related potential responses within syllables of intra and inter phoneme classes

The present study was carried out to assess the signature neural dynamics as evinced through event-related potential (ERP) responses of the P300 waveform across different inter and intra phoneme consonant classes and to quantify the differential neural dynamical response in real-time. The ERP responses to non-sense three-syllable consonantvowel transitions CVCVCV non-words were recorded on 26 healthy individuals of either sex with an age group of 18–25 years. The first syllable of the non-sense word was always fixed, and the ERP responses of the middle syllable were recorded at the phoneme level, and the ERP responses elicited by the middle syllable were evaluated. The results of the present study documented that different consonant phoneme classes (plosives, fricatives, affricatives, liquids, and nasals) elicited differential neural dynamical responses as observed through the P300 waveform response, exhibiting a significant difference in P300 waveform amplitude across the fricatives vs. nasals experimental design.

The Value of VR-PVEP in Objective Evaluation of Monocular Refractive Visual Impairment.

To study the virtual reality-pattern visual evoked potential (VR-PVEP) P100 waveform characteristics of monocular visual impairment with different impaired degrees under simultaneous binocular perception and monocular stimulations. A total of 55 young volunteers with normal vision (using decimal recording method, far vision ≥0.8 and near vision ≥0.5) were selected to simulate three groups of monocular refractive visual impairment by interpolation method. The sum of near and far vision ≤0.2 was Group A, the severe visual impairment group; the sum of near and far vision <0.8 was Group B, the moderate visual impairment group; and the sum of near and far vision ≥0.8 was Group C, the mild visual impairment group. The volunteers' binocular normal visions were set as the control group. The VR-PVEP P100 peak times measured by simultaneous binocular perception and monocular stimulation were compared at four spatial frequencies 16×16, 24×24, 32×32 and 64×64. In Group A, the differences between P100 peak times of simulant visual impairment eyes and simultaneous binocular perception at 24×24, 32×32 and 64×64 spatial frequencies were statistically significant (P<0.05); and the P100 peak time of normal vision eyes at 64×64 spatial frequency was significantly different from the simulant visual impairment eyes (P<0.05). In Group B, the differences between P100 peak times of simulant visual impairment eyes and simultaneous binocular perception at 16×16, 24×24 and 64×64 spatial frequencies were statistically significant (P<0.05); and the P100 peak time of normal vision eyes at 64×64 spatial frequency was significantly different from the simulant visual impairment eyes (P<0.05). In Group C, there was no significant difference between P100 peak times of simulant visual impairment eyes and simultaneous binocular perception at all spatial frequencies (P>0.05). There was no significant difference in the P100 peak times measured at all spatial frequencies between simulant visual impairment eyes and simultaneous binocular perception in the control group (P>0.05). VR-PVEP can be used for visual acuity evaluation of patients with severe and moderate monocular visual impairment, which can reflect the visual impairment degree caused by ametropia. VR-PVEP has application value in the objective evaluation of visual function and forensic clinical identification.

Predictive Power of Cognitive Biomarkers in Neurodegenerative Disease Drug Development: Utility of the P300 Event-Related Potential.

Neurodegenerative diseases, such as Alzheimer's disease (AD), and their associated deterioration of cognitive function are common causes of disability. The slowly developing pathology of neurodegenerative diseases necessitates early diagnosis and monitored long-term treatment. Lack of effective therapies coupled with an improved rate of early diagnosis in our aging population have created an urgent need for the development of novel drugs, as well as the need for reliable biomarkers for treatment response. These issues are especially relevant for AD, in which the rate of clinical trial drug failures has been very high. Frequently used biomarker evaluation procedures, such as positron emission tomography or cerebrospinal fluid measurements of phospho-tau and amyloid beta, are invasive and costly, and not universally available or accessible. This review considers the functionality of the event-related potential (ERP) P300 methodology as a surrogate biomarker for predicting the procognitive potential of drugs in clinical development for neurocognitive disorders. Through the application of standardized electroencephalography (EEG) described here, ERP P300 can be reliably measured. The P300 waveform objectively measures large-scale neuronal network functioning and working memory processes. Increased ERP P300 latency has been reported throughout the literature in disorders of cognition, supporting the potential utility of ERP P300 as a biomarker in many neurological and neuropsychiatric disorders, including AD. Specifically, evidence presented here supports ERP P300 latency as a quantitative, unbiased measure for detecting changes in cognition in patients with AD dementia through the progression from mild to moderate cognitive impairment and after drug treatment.

Event-Related Potentials of Individuals with Attention-Deficit/Hyperactivity Disorder Performing the Attention Network Task

The current study sought to investigate the neural basis of attention-deficit/hyperactivity disorder (ADHD) by examining the performance of individuals with ADHD on the Attentional Networks Test (ANT) by Fan, McCandliss, Sommer, Raz, and Posner (2002), while recording electroencephalography (EEG) utilizing event-related potentials (ERP) methodology. Fifty-seven university students were divided into three groups: control, ADHD-inattentive subtype (ADHD-IA), and ADHD-combined/hyperactive impulsive subtype (ADHD-C/HI). The average peak amplitudes of the P300 waveform for each group were compared and analyzed for performance on each attention network measured by the ANT: the alerting network, the orienting network, and the executive control network. The average P3 peaks were significantly different for controls in comparison to the ADHD-IA group for the alerting and executive networks, and for controls in comparison to ADHD-C/HI for the orienting network. Controls and ADHD-IA had faster behavioral reaction times (RTs) than ADHD-C/HI, but all groups performed at a high level of accuracy. Results suggest that ADHD-IA and ADHD-C/HI comprise heterogeneous disorders. Not only do their symptoms differ but also their electrical potentials compared to controls.

EEG Features of Evoked Tactile Sensation: Two Cases Study.

Purpose: Sensory feedback for prosthetics is an important issue. The area of forearm stump skin that has evoked tactile sensation (ETS) of fingers is defined as the projected finger map (PFM), and the area close to the PFM region that does not have ETS is defined as the non-projected finger map (NPFM). Previous studies have confirmed that ETS can restore the tactile pathway of the lost finger, which was induced by stimulation of transcutaneous electrical nerve stimulation (TENS) on the end of stump skin. This study aims to reveal EEG features between the PFM and the NPFM regions of the stumps under the same TENS stimulation condition.Methods: The PFM and NPFM regions of the two subjects were stimulated with the same intensity of TENS, respectively. TENS as target stimuli are modulated according to the Oddball paradigm to evoke the P300 components.Result: The PFM regions of both subjects were able to elicit P300 components, while their NPFM regions were not able to elicit P300 components. However, this P300 appears early (249 ms for subject 1,230 ms for subject 2) and has continuous positive peaks (peak 1,139 ± 3 ms, peak 2,194 ± 0.5 ms) in front of it.Discussion: N30 and P300 can prove that the two subjects with PFM can perceive and recognize ETS. The heteromorphisms of the P300 waveform may be related to the difficulty in subjects’ cognition of ETS or caused by the fusion of P150, P200, and P300.

A Systematic Deep Learning Model Selection for P300-Based Brain–Computer Interfaces

Predicting attention-modulated brain responses is a major area of investigation in brain&#x2013;computer interface (BCI) research that aims to translate neural activities into useful control and communication commands. Such studies involve collecting electroencephalographic (EEG) data from subjects to train classifiers for decoding users&#x2019; mental states. However, various sources of inter or intrasubject variabilities in brain signals render training classifiers in BCI systems challenging. From a machine learning perspective, this model training generally follows a common methodology: 1) apply some type of feature extraction, which can be time-consuming and may require domain knowledge and 2) train a classifier using extracted features. The advent of deep learning technologies has offered unprecedented opportunities to not only construct remarkably accurate classifiers but also to integrate the feature extraction stage into the classifier construction. Although integrating feature extraction, which is generally domain-dependent, into the classifier construction is a considerable advantage of deep learning models, the process of architecture selection for BCIs generally depends on domain knowledge. In this study, we examine the feasibility of conducting a systematic model selection combined with mainstream deep learning architectures to construct accurate classifiers for decoding P300 event-related potentials. In particular, we present the results of 232 convolutional neural networks (CNNs) (4 datasets <inline-formula> <tex-math notation="LaTeX">$\times58$ </tex-math></inline-formula> structures), 36 long short-term memory cells (LSTMs) (4 datasets <inline-formula> <tex-math notation="LaTeX">$\times9$ </tex-math></inline-formula> structures), and 320 hybrid CNN-LSTM models (4 datasets <inline-formula> <tex-math notation="LaTeX">$\times80$ </tex-math></inline-formula> structures) of varying complexity. Our empirical results show that in the classification of P300 waveforms, the constructed predictive models can outperform the current state-of-the-art deep learning architectures, which are partially or entirely inspired by domain knowledge. The source codes and constructed models are available at <uri>https://github.com/berdakh/P3Net</uri>.

Exploring the Effect of Silence on Auditory Network Regions in Young Female Adults who Experience Temporary Tinnitus on Exposure to Silence.

To examine the differences in auditory evoked cortical responses that may underlie the tendency of some people to perceive tinnitus. The study hypothesis is that the mean ALR and P300 amplitudes in normal hearing adults who perceive temporary tinnitus after exposure to sustained silence will be larger than the mean ALR and P300 amplitudes in normal hearing adults who do not perceive temporary tinnitus after exposure to sustained silence. This was a prospective cross-sectional study. The approval for the study was obtained from the IRB and COVID ramp up committee of University of North Carolina Greensboro (UNCG). Participants completed comprehensive hearing screening and preand postsilence ALR and P300 recordings were obtained. After the first ALR/P300 recording participants were exposed to ten minutes of silence. Participants completed a Qualtrics questionnaire to report any tinnitus perception that emerged during silence exposure. Absolute N1, P2 and P300 waveform amplitudes and latencies were identified and were entered into an SPSS spreadsheet for data analysis. Thirty adult females with normal pure tone hearing thresholds and no history of persistent tinnitus were included in the study. The mean age of the participants was 22.5 ± 3.9 years. When exposed to silence, eight (26.7%) participants perceived temporary tinnitus. N1 and P300 waveforms were smaller in amplitude and faster in latency in the tinnitus perception group; however, the ALR and P300 waveform latencies and amplitudes did not statistically differ significantly between the participants who perceived temporary tinnitus in silence and those who did not (p>0.05). The difference in waveform morphology between the tinnitus perception group and the non-tinnitus perception group revealed a greater difference in P300 amplitude after exposure to silence. Differences in ALR and P300 latencies and amplitudes were observed between the tinnitus perception group and non-tinnitus perception group, with smaller P300 amplitudes appearing in the group perceiving tinnitus. While the results did not statistically significant, this pattern may reflect a mismatch between the neuronal response in the auditory cortex (N1 and P2 amplitudes and latencies) and the neuronal activity in the modulatory network regions (P300).

Measuring Mental Workload Using ERPs Based on FIR, ICA, and MARA

Mental workload is considered to be strongly linked to human performance, and the ability to measure it accurately is key for balancing human health and work. In this study, brain signals were elicited by mental arithmetic tasks of varying difficulty to stimulate different levels of mental workload. In addition, a finite impulse response (FIR) filter, independent component analysis (ICA), and multiple artifact rejection algorithms (MARAs) were used to filter event-related potentials (ERPs). Then, the data consisting of ERPs, subjective ratings of mental workload, and task performance, were analyzed through the use of variance and Spearman’s correlation during a simulated computer task. We found that participants responded faster and performed better in the easy task condition, followed by the medium and high-difficulty conditions, which verifies the validity of the ERP filtering. Moreover, larger P2 and P3 waveforms were evoked as the task difficulty increased, and a higher task difficulty elicited a more enhanced N300. Correlation analysis revealed a negative relationship between the amplitude of P3 and the subjective ratings, and a positive relationship between the P3 amplitude and accuracy. The results presented in this paper demonstrate that a combination of FIR, ICA, and MARA methods can filter ERPs in the non-invasive real-time measurement of workload. Additionally, frontocentral P2, N3, and parietal P3 components showed differences between genders. The proposed measurement of mental workload can be useful for real-time identification of mental states and can be applied to human–computer interaction in the future.

Hierarchical Classification of Event-Related Potentials for the Recognition of Gender Differences in the Attention Task.

Research on the functioning of human cognition has been a crucial problem studied for years. Electroencephalography (EEG) classification methods may serve as a precious tool for understanding the temporal dynamics of human brain activity, and the purpose of such an approach is to increase the statistical power of the differences between conditions that are too weak to be detected using standard EEG methods. Following that line of research, in this paper, we focus on recognizing gender differences in the functioning of the human brain in the attention task. For that purpose, we gathered, analyzed, and finally classified event-related potentials (ERPs). We propose a hierarchical approach, in which the electrophysiological signal preprocessing is combined with the classification method, enriched with a segmentation step, which creates a full line of electrophysiological signal classification during an attention task. This approach allowed us to detect differences between men and women in the P3 waveform, an ERP component related to attention, which were not observed using standard ERP analysis. The results provide evidence for the high effectiveness of the proposed method, which outperformed a traditional statistical analysis approach. This is a step towards understanding neuronal differences between men’s and women’s brains during cognition, aiming to reduce the misdiagnosis and adverse side effects in underrepresented women groups in health and biomedical research.

Visual Abnormalities Associate With Hippocampus in Mild Cognitive Impairment and Early Alzheimer's Disease.

Background and Objective: Alzheimer's disease (AD) has been shown to affect vision in human patients and animal models. This study was conducted to explore ocular abnormalities in the primary visual pathway and their relationship with hippocampal atrophy in patients with AD and mild cognitive impairment (MCI). The aim of this study was to investigate the potential value of ocular examinations as a biomarker during the AD progression.Methods: Patients with MCI (n = 23) or AD (n = 17) and age-matched cognitively normal controls (NC; n = 19) were enrolled. Pattern visual-evoked potentials (PVEP), flash electroretinogram (FERG) recordings and optical coherence tomography (OCT) were performed for all participants. Hippocampal volumes were measured by 3T magnetic resonance imaging. Cognitive function was assessed by Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog). Pearson correlation was employed to analyze the potential associations between ocular abnormalities and hippocampal volumes. Hierarchical regression models were conducted to determine associations between cognitive performances and ocular abnormalities as well as hippocampal volumes after adjusting for confounding factors including age, sex, cognitive reserve, and APOE4 status.Results: PVEP amplitude of P100 waveform was significantly decreased in AD patients compared to MCI and normal individuals. In FERG test, delayed latencies of rod response, rod cone response and 3.0 flicker time were found in cognitively impaired groups, indicating dysfunctions of both the rod and cone systems in the disease progression. OCT test revealed reduced macular retinal nerve fiber layer (m-RNFL) thickness in MCI and AD patients, which significantly correlated with brain structure of hippocampus particularly vulnerable during the progression of AD. Interestingly, P100 amplitude showed a significant association with hippocampal volumes even after adjusting confounding factors including age, sex, and cognitive reserve. Hierarchical regression analysis further demonstrated that m-RNFL thickness, as well as hippocampal volumes, significantly associated with ADAS-cog scores.Conclusion: P100 amplitude and m-RNFL thickness showed significant correlations with brain structure involved in AD-related neurodegeneration, and therefore proved to be potential indicators of brain imaging pathologies.

Riemann-Based Algorithms Assessment for Single- and Multiple-Trial P300 Classification in Non-Optimal Environments.

The P300 wave is commonly used in Brain-Computer Interface technology due to its higher bit rates when compared to other BCI paradigms. P300 classification pipelines based on Riemannian Geometry provide accuracies on par with state-of-the-art pipelines, without having the need for spatial filters, and also possess the ability to be calibrated with little data. In this study, five different P300 detection pipelines are compared, with three of them using Riemannian Geometry as either feature extraction or classification algorithms. The goal of this study is to assess the viability of Riemannian Geometry-based methods in non-optimal environments with sudden background noise changes, rather than maximizing classification accuracy values. For fifteen subjects, the average single-trial accuracy obtained for each pipeline was: 56.06% for Linear Discriminant Analysis (LDA), 72.13% for Bayesian Linear Discriminant Analysis (BLDA), 63.56% for Riemannian Minimum Distance to Mean (MDM), 69.22% for Riemannian Tangent Space with Logistic Regression (TS-LogR), and 63.30% for Riemannian Tangent Space with Support Vector Machine (TS-SVM). The results are higher for the pipelines based on BLDA and TS-LogR, suggesting that they could be viable methods for the detection of the P300 component when maximizing the bit rate is needed. For multiple-trial classification, the BLDA pipeline converged faster towards higher average values, closely followed by the TS-LogR pipeline. The two remaining Riemannian methods' accuracy also increases with the number of trials, but towards a lower value compared to the aforementioned ones. Single-stimulus detection metrics revealed that the TS-LogR pipeline can be a viable classification method, as its results are only slightly lower than those obtained with BLDA. P300 waveforms were also analyzed to check for evidence of the component being elicited. Finally, a questionnaire was used to retrieve the most intuitive focusing methods employed by the subjects.

Corticotrophin-Releasing Factor Modulates the Facial Stimulation-Evoked Molecular Layer Interneuron-Purkinje Cell Synaptic Transmission in vivo in Mice.

Corticotropin-releasing factor (CRF) is an important neuromodulator in central nervous system that modulates neuronal activity via its receptors during stress responses. In cerebellar cortex, CRF modulates the simple spike (SS) firing activity of Purkinje cells (PCs) has been previously demonstrated, whereas the effect of CRF on the molecular layer interneuron (MLI)–PC synaptic transmission is still unknown. In this study, we examined the effect of CRF on the facial stimulation–evoked cerebellar cortical MLI-PC synaptic transmission in urethane-anesthetized mice by in vivo cell-attached recording, neurobiotin juxtacellular labeling, immunohistochemistry techniques, and pharmacological method. Cell-attached recordings from cerebellar PCs showed that air-puff stimulation of ipsilateral whisker pad evoked a sequence of tiny parallel fiber volley (N1) followed by MLI-PC synaptic transmission (P1). Microapplication of CRF in cerebellar cortical molecular layer induced increases in amplitude of P1 and pause of SS firing. The CRF decreases in amplitude of P1 waveform were in a dose-dependent manner with the EC50 of 241 nM. The effects of CRF on amplitude of P1 and pause of SS firing were abolished by either a non-selective CRF receptor antagonist, α-helical CRF-(9-14), or a selective CRF-R1 antagonist, BMS-763534 (BMS, 200 nM), but were not prevented by a selective CRF-R2 antagonist, antisauvagine-30 (200 nM). Notably, application CRF not only induced a significant increase in spontaneous spike firing rate, but also produced a significant increase in the number of the facial stimulation–evoked action potential in MLIs. The effect of CRF on the activity of MLIs was blocked by the selective CRF-R1 antagonist, and the MLIs expressed the CRF-R1 imunoreactivity. These results indicate that CRF increases excitability of MLIs via CRF-R1, resulting in an enhancement of the facial stimulation–evoked MLI-PC synaptic transmission in vivo in mice.

The effects of letter matrix and inter stimulus interval on P300 Event Related Potential

According to the General Statistics Office (Ministry of Planning and investment) collaborated with the United Nations Children’s Fund in Viet Nam, from 2016 to 2017, there were nearly 5 million households which had disabilities in the country. The proportion of people with disabilities who were over 2 years old accounted for 7% of the population. Another statistic is based on the Christopher &amp; Dana Reeve Foundation report in 2013, about 5.4 million Americans suffer from disability [2]. Many research works, therefore, have been built with the aim of improving the ability of movement and communication, based on biomedical signals, especially the Brain-Computer Interface (BCI) system. BCI is a technology that enables the use of the brain’s neural activity to communicate with others or to control machines, artificial limbs, or robots without direct physical movements. BCI based on electroencephalogram (EEG) can be applied to the disabled individual system. In recent years, there are many people suffering from the loss of all voluntary muscle control in Viet Nam. Therefore, they really need alternative interaction methods to control their behaviors with external environment. Thanks to the development of Brain-Computer interfaces and the EEG headset have been helping people who are incapable of any motion for function can communicate with the external world, due to the P300 signal. As the important consideration to discover which factors affect the accuracy of BCI system to improve communication quality for the ability of disabled people, we decide to discover the impact of character matrix size and inter stimulus interval on event related potential. The duration of the inter stimulus interval (ISI) between targets is set at 187,5 ms and 125 ms for two different matrix sizes 3x3 and 6x6. The results provide that the largest amplitudes of P300 waveforms occur remarkably at the occipital and frontal channels and are higher than in 6x6 letter matrix compared with 3x3 matrix. The different matrix size and ISI does not affect on the appearance time of the P300 signal, and it is in the range 235-244 ms after stimulation. These good results promise to help other researches to build a perfect experimental procedure in real assistance application for using BCI – P300 systems.

Macular Carotenoids Are Associated with Neural Efficiency in Children

Abstract Objectives Macular pigmentation has been previously related to benefits for behavioral and neuroelectric aspects of selective attention across the lifespan. The relationship between accumulation of carotenoids beyond the central nervous system and selective attention is less understood, particularly amongst children. Therefore, this study aimed to assess the differential impacts of retinal and skin carotenoid accumulation and behavioral and neuroelectric indices of selective attention. Methods Children between 7–12 years (N = 60) participated in the study. Macular pigment optical density (MPOD) was assessed using heterochromatic flicker photometry and skin carotenoids were assessed using reflection spectroscopy at the fingertip using the Veggie meter. Body Mass Index adjusted for age and sex (BMI%) and general intelligence as assessed using the Woodcock Johnson IV test were used as covariates. Behavioral performance (accuracy and reaction time) and neuroelectric indices (event-related brain potentials [ERPs]) of attentional inhibition were assessed during a modified Eriksen Flanker task. Specifically, amplitude of the P3 waveform was used to index attentional resource allocation. Results After controlling for covariates, MPOD was selectively associated with lower peak amplitude of the P3 waveform during congruent (β = −0.36, P = 0.01) and incongruent task trials (β = −0.39, P &amp;lt; 0.01). No significant relationships were observed between the P3 and skin carotenoids. Skin carotenoids were associated with higher accuracy on the incongruent trials of the Flanker task (β = 0.36, P = 0.02), while no relationships were observed between MPOD and behavioral performance. Conclusions In this study, we were able to replicate previous findings demonstrating that higher accumulation of retinal carotenoids is associated with neural efficiency during a selective attention task. Skin carotenoids were associated with behavioral performance but were not related to neuroelectric indices of selective attention, suggesting site-specific benefits of carotenoid accumulation on cognitive health in childhood. Funding Sources This work is funded by the Egg Nutrition Center.

Neurocognitive Inhibitory Control Ability Performance and Correlations with Biochemical Markers in Obese Women.

Inhibitory control, the ability to suppress prepotent responses and resist irrelevant stimuli, is thought to play a critical role in the maintenance of obesity. However, electrophysiological performance related to different inhibitory control processes and their relationship with motor response inhibition and cognitive interference and potential biochemical mechanisms in middle-aged, obese women are as yet unclear. This work thus compared different neurocognitive Go/Nogo and Stroop task performance in healthy sedentary normal-weight and obese women, as well as their correlation with biochemical markers. Twenty-six healthy, sedentary obese women (obese group) and 26 age-matched (21–45 years old) normal-weight women (control group) were the participants, categorized by body mass index and percentage fat, as measured with dual-energy X-ray absorptiometry. They provided a fasting blood sample and performed two cognitive tasks (i.e., Go/Nogo and Stroop tasks) with concomitant electrophysiological recording. The N2 and P3 waveforms of event-related potential (ERP) were recorded. Although the between-group behavioral performance was comparable, the obese group relative to the control group showed significantly longer N2 latency and smaller P3 amplitude in the Stroop task and smaller N2 and P3 amplitudes in the Go/Nogo task. Significant inflammation response indices (e.g., CRP, leptin, adiponectin/leptin ratio) were observed in the obese group. The Nogo P3 amplitude was significantly correlated with the adiponectin/leptin ratio. These findings indicate that healthy obese women still exhibit deviant neurophysiological performance when performing Go/Nogo and Stroop tasks, where the adiponectin/leptin ratio could be one of the influencing factors for the deficit in neural processes of motor response inhibition.

Acute effect of energy boost dietary supplement on P3 waveform: double blind, placebo controlled study

Human cognition may be enhanced by energy drinks containing caffeine and/or other stimulants, which are thought to improve attentional as well as motor performance, and reduce reaction times. Due to the fact that literature shows that even low doses of caffeine may improve cognitive performance, we investigated an acute effect of a single dose of a caffeinated energy dietary supplement, on attention and motor responses by means of event related potentials. Healthy volunteers were examined in double blind, placebo controlled study. EEG recordings from 32 channels were performed in three sessions: before the supplementation (session 1), 30 min after the supplementation (session 2) and 90 min after the supplementation (session 3) in three tasks: visual P3, auditory P3, and motor task. Repeated measures ANOVA analysis showed reduced P3 amplitude increase after energy dietary supplementation (compared to placebo group) throughout all sessions (up to 90 min after consumption) in the visual task, and speeding the classification process observed as a decrease of P3 midpoint latency, but only 30 min after supplementation. The latter effect was present in both, but more pronounced in the visual task. Nonparametric cluster based permutation analysis showed one significant cluster in the placebo group from visual P3 task (approximately between 400 and 520 ms) over the centro‑parietal area, which was absent in the study group. Our results suggest that caffeinated energy dietary supplement containing only 55 mg of caffeine may enhance some attentional processes observed by changes in P3 features, but not in motor performance.