Evaluation of a headphones-fitted EEG system for the recording of auditory evoked potentials and mental workload assessment.

Advancements in portable neuroimaging technologies open up new opportunities to gain insight into the neural dynamics and cognitive processes underlying day-to-day behaviors. In this study, we evaluated the relevance of a headphone- mounted electroencephalogram (EEG) system for monitoring mental workload. The participants (N = 12) were instructed to pay attention to auditory alarms presented sporadically while performing the Multi-Attribute Task Battery (MATB) whose difficulty was staged across three conditions to manipulate mental workload. The P300 Event-Related Potentials (ERP) elicited by the presentation of auditory alarms were used as probes of attentional resources available. The amplitude and latency of P300 ERPs were compared across experimental conditions. Our findings indicate that the P300 ERP component can be captured using a headphone-mounted EEG system. Moreover, neural responses to alarm could be used to classify mental workload with high accuracy (over 80%) at a single-trial level. Our analyses indicated that the signal-to-noise ratio acquired by the sponge-based sensors remained stable throughout the recordings. These results highlight the potential of portable neuroimaging technology for the development of neuroassistive applications while underscoring the current limitations and challenges associated with the integration of EEG sensors in everyday-life wearable technologies. Overall, our study contributes to the growing body of research exploring the feasibility and validity of wearable neuroimaging technologies for the study of human cognition and behavior in real-world settings.

Electrophysiological and neuropsychological assessment of cognition in spinocerebellar ataxia type 1 patients: a pilot study.

BACKGROUND: Event-related potentials (ERPs) reflect cognitive processing: negative early components (N100, N200) are involved in the sensory and perceptual processing of a stimulus, whereas late positive component P300 requires conscious attention. Both neuropsychological and affective disorders are present in patients with spinocerebellar ataxia type 1 (SCA1), but the underlying mechanisms need further clarification. MATERIALS AND METHODS: In this pilot study, we assessed cognitive processing by recording auditory ERPs in 16 consecutive SCA1 patients and 16 healthy controls (HC) matched for age and sex. Motor and nonmotor symptoms were evaluated using the Scale for the Assessment and Rating of Ataxia (SARA) and an extensive neuropsychological battery. ERPs were recorded using an oddball paradigm, and peak latency and amplitude of N100, N200, and P300 were measured in the averaged responses to target tones. RESULTS: We found in SCA1 significantly increased latencies of N200 and P300 (p=0.033, p=0.007) and decreased amplitudes of N100 and P300 (p=0.024, p=0.038) compared with HC. Furthermore, P300 latency had the highest AUC in the discrimination of SCA1 in ROC analysis. The expansion of trinucleotide repeats correlated with P300 latency (r=-0.607, p=0.048), whereas both P300 and N100 amplitudes correlated with the severity of motor symptoms (r=-0.692, p=0.003; r=-0.621; p=0.010). Significant correlations between P300 latency and the scores of Emotion Attribution Task (r=-0.633, p=0.027), as well as between N200 latency and the scores of Frontal Assessment Battery and Stroop test (r=-0.520, p=0.047; r=0.538, p=0.039), were observed. CONCLUSIONS: This research provides for the first time an extensive characterization of ERPs as useful electrophysiological markers to identify early cognitive dysfunction in SCA1.

Event-related brain potentials reflect predictive coding of anticipated economic change.

Research has demonstrated the importance of economic forecasts for financial decisions at the aggregate economic level. However, little is known about the psychological and neurophysiological mechanisms that economic forecasts activate at the level of individual decision-making. In the present study, we used event-related brain potentials (ERPs) to test the hypothesis that economic forecasts influence individuals' internal model of the economy and their subsequent decision behavior. Using a simple economic decision-making game, the Balloon Analogue of Risk Task (BART) and predictive messages about possible economic changes in the game before each block, we test the idea that brain potentials time-locked to decision outcomes can vary as a function of exposure to economic forecasts. Behavioural results indicate that economic forecasts influenced the amount of risk that participants were willing to take. Analyses of brain potentials indicated parametric increases of the N1, P2, P3a, and P3b amplitudes as a function of the level of risk in subsequent inflation steps in the BART. Mismatches between economic forecasts and decision outcomes in the BART (i.e., reward prediction errors) were reflected in the amplitude of the P2, P3a, and P3b, suggesting increased attentional processing of unexpected outcomes. These electrophysiological results corroborate the idea that economic messages may indeed influence people's beliefs about the economy and bias their subsequent financial decision-making. Our findings present a first important step in the development of a low-level neurophysiological model that may help to explain the self-fulfilling prophecy effect of economic news in the larger economy.

Your losses are mine: The influence of empathic concern on evaluative processing of others' outcomes.

Neural responses to others' decision-making outcomes can be modulated by many social factors. Using the event-related potential (ERP) technique, we explored the neural mechanisms of empathic concern modulating evaluative processing of others' outcomes. Participants were asked to perform a gambling task for three beneficiaries: themselves and two strangers. One stranger was an economically underprivileged student requiring help (high-empathy condition); the other stranger was a student with no upsetting information to induce empathic concern (low-empathy condition). ERP results showed that the valence effect of the feedback-related negativity (FRN) was larger when participants exhibited high empathic concern than when they did not. The FRN responses to strangers' outcomes in the high-empathy condition were as strong as those to their own outcomes. The P300 showed no differences between the low- and high-empathy conditions. These findings indicate that empathic concern could modulate the early stage of outcome processing, implying empathic emotional/altruistic motivational impacts of others' outcomes.

Socioeconomic status and neural processing of a go/no-go task in preschoolers: An assessment of the P3b.

While it is well established that lower socioeconomic status (SES) is associated with poorer executive functioning (EF), how SES relates to the neural processing of EF in childhood remains largely unexplored. We examined how household income and parent education related to amplitudes of the P3b, an event-related potential component, during one EF task. We assessed the P3b, indexing inhibition and attention allocation processes, given the importance of these skills for academic success. Children aged 4.5-5.5 years completed a go/no-task, which assesses inhibitory control and attention, while recording EEG. The P3b was assessed for both go trials (indexing sustained attention) and no-go trials (indexing inhibition processes). Higher household income was related to larger P3b amplitudes on both go and no-go trials. This was a highly educated sample, thus results indicate that P3b amplitudes are sensitive to household income even within the context of high parental education. Findings build on the behavioral literature and demonstrate that SES also has implications for the neural mechanisms underlying inhibition and attention processing in early childhood.

Use of the Stockwell Transform in the Detection of P300 Evoked Potentials with Low-Cost Brain Sensors.

The evoked potential is a neuronal activity that originates when a stimulus is presented. To achieve its detection, various techniques of brain signal processing can be used. One of the most studied evoked potentials is the P300 brain wave, which usually appears between 300 and 500 ms after the stimulus. Currently, the detection of P300 evoked potentials is of great importance due to its unique properties that allow the development of applications such as spellers, lie detectors, and diagnosis of psychiatric disorders. The present study was developed to demonstrate the usefulness of the Stockwell transform in the process of identifying P300 evoked potentials using a low-cost electroencephalography (EEG) device with only two brain sensors. The acquisition of signals was carried out using the Emotiv EPOC® device—a wireless EEG headset. In the feature extraction, the Stockwell transform was used to obtain time-frequency information. The algorithms of linear discriminant analysis and a support vector machine were used in the classification process. The experiments were carried out with 10 participants; men with an average age of 25.3 years in good health. In general, a good performance (75⁻92%) was obtained in identifying P300 evoked potentials.

Utility of P300 ERP in monitoring post-trauma mental health: A longitudinal study in military personnel returning from combat deployment.

Military service members (SMs) returning from combat are at high risk of developing neuropsychiatric conditions such as posttraumatic stress disorder (PTSD) and major depression. Symptom dynamics following reintegration into civilian life may be magnified over time such that some SMs present with delayed onset and may not reach a diagnostic threshold for months to years. Monitoring the trajectory of mental health in the aftermath of combat trauma can therefore be particularly important in enhancing diagnosis. In this study, we investigated the possible utility of the P300 event-related potential (ERP) as an objective marker for monitoring post-trauma mental health. SMs recently returned from a combat deployment were recruited to undergo a baseline assessment, with subsequent follow-up assessment at 6 or 12 months later. At each assessment, ERPs were recorded using a conventional visual oddball task and a set of psychological scores assessing PTSD, depression, and psychosocial functioning were obtained. We observed that the individuals with overall improved psychological scores at follow-up had increased P300 amplitude and shortened P300 latency, and the individuals with overall worsened psychological scores at follow-up had prolonged P300 latency. The degree of change in aggregate psychological score was significantly correlated with the magnitude of change in P300 amplitude (r = -0.72, p < 0.0001) and latency (r = 0.42, p = 0.0201). These findings suggest that the P300 may be utilized as a quantitative biomarker for tracking the changes of mental health longitudinally. It may offer clinicians an objective tool for the assessment of the dynamics of mental health following trauma, and perhaps also for monitoring recovery during treatment.

Moderate financial incentive does not appear to influence the P300 Concealed Information Test (CIT) effect in the Complex Trial Protocol (CTP) version of the CIT in a forensic scenario, while affecting P300 peak latencies and behavior.

Previous research indicated that the skin conductance response (SCR) of the Autonomic Nervous System (ANS) in the Concealed Information Test (CIT) is typically increased in subjects who are financially and otherwise incentivized to defeat the CIT (the paradoxical "motivational impairment" effect). This is not the case for RT-based CITs, nor for P300 tests based on the 3-stimulus protocol or Complex Trial Protocol for detection of cognitive malingering (although these are not the same as forensic CITs). The present report extends earlier studies of malingerers by running five groups of subjects (15-16 per group yielding 78 total) in a mock crime (forensic) scenario: paid (to beat the test) and unpaid, instructed and uninstructed, and simply guilty. There was no evidence that the "CIT effect" (probe-minus-irrelevant P300 differences) differed among groups, although behavioral differences among groups were seen.

Age differences in neural correlates of feedback processing after economic decisions under risk.

This study examines age-related differences in behavioral responses to risk and in the neurophysiological correlates of feedback processing. Our sample was composed of younger, middle-aged, and older adults, who were asked to decide between 2 risky options, in the gain and loss domains, during an EEG recording. Results evidenced group-related differences in early and later stages of feedback processing, indexed by differences in the feedback-related negativity (FRN) and P3 amplitudes. Specifically, in the loss domain, younger adults showed higher FRN amplitudes after non-losses than after losses, whereas middle-aged and older adults had similar FRN amplitudes after both. In the gain domain, younger and middle-aged adults had higher P3 amplitudes after gains than after non-gains, whereas older adults had similar P3 amplitudes after both. Behaviorally, older adults had higher rates of risky decisions than younger adults in the loss domain, a result that was correlated with poorer performance in memory and executive functions. Our results suggest age-related differences in the outcome-related expectations, as well as in the affective relevance attributed to the outcomes, which may underlie the group differences found in risk-aversion.

Social status level and dimension interactively influence person evaluations indexed by P300s.

Functional neuroimaging research suggests that status-based evaluations may not solely depend on the level of social status but also on the conferred status dimension. However, no reports to date have studied how status level and dimension shape early person evaluations. To explore early status-based person evaluations, event-related brain potential data were collected from 29 participants while they indicated the status level and dimension of faces that had been previously trained to be associated with one of four status types: high moral, low moral, high financial, or low financial. Analysis of the P300 amplitude (previously implicated in social evaluation) revealed an interaction of status level and status dimension such that enhanced P300 amplitudes were observed in response to targets of high financial and low moral status relative to targets of low financial and high moral status. Implications of these findings are discussed in the context of our current understanding of status-based evaluation and, more broadly, of the processes by which person knowledge may shape person perception and evaluation.

Being low prepares for being neglected: Verticality affects expectancy of social participation.

Previous research suggests that the established link of vertical position and self-assignment of social power affects the processing of social exclusion. We hypothesized that verticality-induced self-assignment of social power moderates the evaluation of exclusion via a change in subjective expectancy of social participation. Following this idea, a superior position-associated with higher power-was supposed to increase the sensitivity for a transition to social exclusion. The transition was simulated in a virtual ball tossing game (cyberball): an inclusionary block was followed by partial exclusion of the participant. The participants' vertical position relative to the co-players was varied in three experimental groups (superior vs. even vs. inferior). From inclusion to partial exclusion, we observed an increase of an event-related brain potential related to the violation of subjective expectancy (P3), and participants reported a corresponding increase in threat to social needs and negative mood. For participants at inferior position exclusionary effects on both, P3 and need threat, were less pronounced as compared to participants at even or superior position. These results indicate that verticality impacts basic cognitive processes of subjective expectancy formation. An inferior position already provides a bias for the loss of social power, and the transition to social exclusion is less unexpected.

Using the detectability index to predict P300 speller performance.

OBJECTIVE: The P300 speller is a popular brain-computer interface (BCI) system that has been investigated as a potential communication alternative for individuals with severe neuromuscular limitations. To achieve acceptable accuracy levels for communication, the system requires repeated data measurements in a given signal condition to enhance the signal-to-noise ratio of elicited brain responses. These elicited brain responses, which are used as control signals, are embedded in noisy electroencephalography (EEG) data. The discriminability between target and non-target EEG responses defines a user's performance with the system. A previous P300 speller model has been proposed to estimate system accuracy given a certain amount of data collection. However, the approach was limited to a static stopping algorithm, i.e. averaging over a fixed number of measurements, and the row-column paradigm. A generalized method that is also applicable to dynamic stopping (DS) algorithms and other stimulus paradigms is desirable. APPROACH: We developed a new probabilistic model-based approach to predicting BCI performance, where performance functions can be derived analytically or via Monte Carlo methods. Within this framework, we introduce a new model for the P300 speller with the Bayesian DS algorithm, by simplifying a multi-hypothesis to a binary hypothesis problem using the likelihood ratio test. Under a normality assumption, the performance functions for the Bayesian algorithm can be parameterized with the detectability index, a measure which quantifies the discriminability between target and non-target EEG responses. MAIN RESULTS: Simulations with synthetic and empirical data provided initial verification of the proposed method of estimating performance with Bayesian DS using the detectability index. Analysis of results from previous online studies validated the proposed method. SIGNIFICANCE: The proposed method could serve as a useful tool to initially assess BCI performance without extensive online testing, in order to estimate the amount of data required to achieve a desired accuracy level.

Cognitive assessment in Amyotrophic Lateral Sclerosis by means of P300-Brain Computer Interface: a preliminary study.

OBJECTIVE: To investigate the use of P300-based Brain Computer Interface (BCI) technology for the administration of motor-verbal free cognitive tests in Amyotrophic Lateral Sclerosis (ALS). METHODS: We recruited 15 ALS patients and 15 age- and education-matched healthy subjects. All participants underwent a BCI-based neuropsychological assessment, together with two standard cognitive screening tools (FAB, MoCA), two psychological questionnaires (BDI, STAI-Y) and a usability questionnaire. For patients, clinical and respiratory examinations were also performed, together with a behavioural assessment (FBI). RESULTS: Correlations were observed between standard cognitive and BCI-based neuropsychological assessment, mainly concerning execution times in the ALS group. Moreover, patients provided positive rates concerning the BCI perceived usability and subjective experience. Finally, execution times at the BCI-based neuropsychological assessment were useful to discriminate patients from controls, with patients achieving lower processing speed than controls regarding executive functions. CONCLUSIONS: The developed motor-verbal free neuropsychological battery represents an innovative approach, that could provide relevant information for clinical practice and ethical issues. Its use for cognitive evaluation throughout the course of ALS, currently not available by means of standard assessment, must be addressed in further longitudinal validation studies. Further work will be aimed at refining the developed system and enlarging the cognitive spectrum investigated.

Relevance of a neurophysiological marker of attention allocation for children's learning-related behaviors and academic performance.

Learning-related behaviors are important for school success. Socioeconomic disadvantage confers risk for less adaptive learning-related behaviors at school entry, yet substantial variability in school readiness exists within socioeconomically disadvantaged populations. Investigation of neurophysiological systems associated with learning-related behaviors in high-risk populations could illuminate resilience processes. This study examined the relevance of a neurophysiological measure of controlled attention allocation, amplitude of the P3b event-related potential, for learning-related behaviors and academic performance in a sample of socioeconomically disadvantaged kindergarteners. The sample consisted of 239 children from an urban, low-income community, approximately half of whom exhibited behavior problems at school entry (45% aggressive/oppositional; 64% male; 69% African American, 21% Hispanic). Results revealed that higher P3b amplitudes to target stimuli in a go/no-go task were associated with more adaptive learning-related behaviors in kindergarten. Furthermore, children's learning-related behaviors in kindergarten mediated a positive indirect effect of P3b amplitude on growth in academic performance from kindergarten to 1st grade. Given that P3b amplitude reflects attention allocation processes, these findings build on the scientific justification for interventions targeting young children's attention skills in order to promote effective learning-related behaviors and academic achievement within socioeconomically disadvantaged populations.

A method for optimizing EEG electrode number and configuration for signal acquisition in P300 speller systems.

OBJECTIVE: The P300 speller is intended to restore communication to patients with advanced neuromuscular disorders, but clinical implementation may be hindered by several factors, including system setup, burden, and cost. Our goal was to develop a method that can overcome these barriers by optimizing EEG electrode number and placement for P300 studies within a population of subjects. METHODS: A Gibbs sampling method was developed to find the optimal electrode configuration given a set of P300 speller data. The method was tested on a set of data from 15 healthy subjects using an established 32-electrode pattern. Resulting electrode configurations were then validated using online prospective testing with a naïve Bayes classifier in 15 additional healthy subjects. RESULTS: The method yielded a set of four posterior electrodes (PO8, PO7, POZ, CPZ), which produced results that are likely sufficient to be clinically effective. In online prospective validation testing, no significant difference was found between subjects' performances using the reduced and the full electrode configurations. CONCLUSIONS: The proposed method can find reduced sets of electrodes within a subject population without reducing performance. SIGNIFICANCE: Reducing the number of channels may reduce costs, set-up time, signal bandwidth, and computation requirements for practical online P300 speller implementation.

Integrating language information with a hidden Markov model to improve communication rate in the P300 speller.

The P300 speller is a common brain-computer interface (BCI) application designed to communicate language by detecting event related potentials in a subject's electroencephalogram (EEG) signal. Information about the structure of natural language can be valuable for BCI communication systems, but few attempts have been made to incorporate this domain knowledge into the classifier. In this study, we treat BCI communication as a hidden Markov model (HMM) where hidden states are target characters and the EEG signal is the visible output. Using the Viterbi algorithm, language information can be incorporated in classification and errors can be corrected automatically. This method was first evaluated offline on a dataset of 15 healthy subjects who had a significant increase in bit rate from a previously published naïve Bayes approach and an average 32% increase from standard classification with dynamic stopping. An online pilot study of five healthy subjects verified these results as the average bit rate achieved using the HMM method was significantly higher than that using the naïve Bayes and standard methods. These findings strongly support the integration of domain-specific knowledge into BCI classification to improve system performance and accuracy.

The impacts of racial group membership on people's distributive justice: an event-related potential study.

How individuals and societies distribute benefits has long been studied by psychologists and sociologists. Previous work has highlighted the importance of social identity on people's justice concerns. However, it is not entirely clear how racial in-group/out-group relationship affects the brain activity in distributive justice. In this study, event-related potentials were recorded while participants made their decisions about donation allocation. Behavioral results showed that racial in-group factor affected participants' decisions on justice consideration. Participants were more likely to make relatively equity decisions when racial in-group factor was congruent with equity compared with the corresponding incongruent condition. Moreover, this incongruent condition took longer response times than congruent condition. Meanwhile, less equity decisions were made when efficiency was larger in the opposite side to equity than it was equal between the two options. Scalp event-related potential analyses revealed that greater P300 and late positive potential amplitudes were elicited by the incongruent condition compared with the congruent condition. These findings suggest that the decision-making of distributive justice could be modulated by racial group membership, and greater attentional resources or cognitive efforts are required when racial in-group factor and equity conflict with each other.

Restrictive feeding practices and adiposity are differentially related to P3b cortical responses to food stimuli in children.

Across two studies, we examined the association between adiposity, restrictive feeding practices and cortical processing bias to food stimuli in children. We assessed P3b event-related potential (ERP) during visual oddball tasks in which the frequently presented stimulus was non-food and the infrequently presented stimulus was either a food (Study 1) or non-food (Study 2) item. Children responded to the infrequently presented stimulus and accuracy and speed responses were collected. Restrictive feeding practices, children's height and weight were also measured. In Study 1, the difference in P3b amplitude for infrequently presented food stimuli, relative to frequently presented non-food stimuli, was negatively associated with adiposity and positively associated with restrictive feeding practices after controlling for adiposity. There was no association between P3b amplitude difference and adiposity or restriction in Study 2, suggesting that the effects seen in Study 1 were not due to general attentional processes. Taken together, our results suggest that attentional salience, as indexed by the P3b amplitude, may be important for understanding the neural correlates of adiposity and restrictive feeding practices in children.

How about taking a low-cost, small, and wireless EEG for a walk?

To build a low-cost, small, and wireless electroencephalogram (EEG) system suitable for field recordings, we merged consumer EEG hardware with an EEG electrode cap. Auditory oddball data were obtained while participants walked outdoors on university campus. Single-trial P300 classification with linear discriminant analysis revealed high classification accuracies for both indoor (77%) and outdoor (69%) recording conditions. We conclude that good quality, single-trial EEG data suitable for mobile brain-computer interfaces can be obtained with affordable hardware.

A POMDP approach to optimizing P300 speller BCI paradigm.

To achieve high performance in brain-computer interfaces (BCIs) using P300, most of the work has been focused on feature extraction and classification algorithms. Although significant progress has been made in such signal processing methods in the lower layer, the issues in the higher layer, specifically determining the stimulus schedule in order to identify the target reliably and efficiently, remain relatively unexplored. In this paper, we propose a systematic approach to compute an optimal stimulus schedule in P300 BCIs. Our approach adopts the partially observable Markov decision process, which is a model for planning in partially observable stochastic environments. We show that the thus obtained stimulus schedule achieves a significant performance improvement in terms of the success rate, bit rate, and practical bit rate through human subject experiments.