Impact of Effortful Word Recognition on Supportive Neural Systems Measured by Alpha and Theta Power.

OBJECTIVES: The goal of this study was to use theta and alpha electroencephalography (EEG) frequency power and self-report measures to examine performance monitoring, cognitive inhibition, and perceived effort required for speech understanding in noise. It was hypothesized that with a linear increase in word recognition task difficulty, there would be a linear increase in listening effort and word recognition performance would decrease in the challenging conditions. In addition, theta and alpha power would have an inverted U-shape across easy to challenging listening conditions. The inverted U-shape would reflect the neural underpinnings of listening effort that cannot be measured by task performance alone. DESIGN: EEG data were collected in 34 normal-hearing adults (18 to 33 years old) during the Words-In-Noise (WIN) test, which was presented in sound field. EEG frequency data were averaged and analyzed at three frontal channels for theta power (4 to 8 Hz), which is thought to reflect performance monitoring, and three parietal channels for alpha power (8 to 12 Hz), which is thought to reflect cognitive inhibition. A ten-point visual analog scale was administered after each WIN signal-to-noise ratio (SNR) condition to capture self-reported required and invested listening effort (RLE and ILE, respectively). The WIN SNR conditions were presented in descending and random order. RESULTS: The SNR presentation (descending or random SNR) had a null effect on word recognition performance; however, presentation did have an effect on theta power, alpha power, and ILE. When controlling for presentation, there were significant effects of SNR and presentation on both theta and alpha frequency power. Theta and alpha power had an inverted U-shape as a function of SNR from easy to challenging, with peak power in the moderate SNR conditions. RLE and ILE both significantly increased as task difficulty increased as expected; however, RLE showed a stronger relation to task performance than ILE. Alpha power was a significant predictor of RLE, ILE, and WIN performance when controlling for SNR. CONCLUSIONS: The elevated theta and alpha power in the easy to moderate SNRs and alpha power predicting self-reported listening effort suggest the activation of supportive neural systems during word recognition that could be considered a marker of listening effort. Moreover, the measures of neural support systems and listening effort were independent from task performance, which is a key element to further understanding the neural bases for listening effort. In the context of the broader literature, these results are consistent with (1) a parietal alpha role in supporting inhibitory control to suppress irrelevant information and (2) a frontal theta role in supporting performance monitoring in difficult listening conditions where speech recognition is feasible.

Toward independent home use of brain-computer interfaces: a decision algorithm for selection of potential end-users.

Noninvasive brain-computer interfaces (BCIs) use scalp-recorded electrical activity from the brain to control an application. Over the past 20 years, research demonstrating that BCIs can provide communication and control to individuals with severe motor impairment has increased almost exponentially. Although considerable effort has been dedicated to offline analysis for improving signal detection and translation, far less effort has been made to conduct online studies with target populations. Thus, there remains a great need for both long-term and translational BCI studies that include individuals with disabilities in their own homes. Completing these studies is the only sure means to answer questions about BCI utility and reliability. Here we suggest an algorithm for candidate selection for electroencephalographic (EEG)-based BCI home studies. This algorithm takes into account BCI end-users and their environment and should assist in study design and substantially improve subject retention rates, thereby improving the overall efficacy of BCI home studies. It is the result of a workshop at the Fifth International BCI Meeting that allowed us to leverage the expertise of multiple research laboratories and people from multiple backgrounds in BCI research.

The cognitive tasks and event-related potentials associated childhood adversity: A systematic review.

In this systematic review, 18 articles met inclusion criteria to be qualitatively analyzed for converging evidence of brain activity, measured using event-related potential (ERP), related to retrospectively reported childhood adversity/trauma. Using the PRISMA guidelines for systematic reviews, 917 articles were assessed for inclusion and were filtered using study parameters. The most common ERP components listed in the literature were P100, N170, N200, P200, P300, ERN, and LPP. We discuss levels of evidence for changed brain activity, each ERP component, and the tasks used to evoke them. The Childhood Trauma Questionnaire was found to be the most commonly cited measure. We note the need to assess the duration and intensity of childhood adversity/trauma measurements in the strengths and limitations of the reported childhood adversity/trauma measurements. No concrete converging evidence was found to support a relationship between ERP-measured brain activity and retrospectively reported childhood adversity/trauma. Thus, a discussion of limitations and future directions for this field of research is presented.

Performance Monitoring and Cognitive Inhibition during a Speech-in-Noise Task in Older Listeners.

The goal of this study was to examine the effect of hearing loss on theta and alpha electroencephalography (EEG) frequency power measures of performance monitoring and cognitive inhibition, respectively, during a speech-in-noise task. It was hypothesized that hearing loss would be associated with an increase in the peak power of theta and alpha frequencies toward easier conditions compared to normal hearing adults. The shift would reflect how hearing loss modulates the recruitment of listening effort to easier listening conditions. Nine older adults with normal hearing (ONH) and 10 older adults with hearing loss (OHL) participated in this study. EEG data were collected from all participants while they completed the words-in-noise task. It hypothesized that hearing loss would also have an effect on theta and alpha power. The ONH group showed an inverted U -shape effect of signal-to-noise ratio (SNR), but there were limited effects of SNR on theta or alpha power in the OHL group. The results of the ONH group support the growing body of literature showing effects of listening conditions on alpha and theta power. The null results of listening condition in the OHL group add to a smaller body of literature, suggesting that listening effort research conditions should have near ceiling performance.

A brain-computer interface for long-term independent home use.

Our objective was to develop and validate a new brain-computer interface (BCI) system suitable for long-term independent home use by people with severe motor disabilities. The BCI was used by a 51-year-old male with ALS who could no longer use conventional assistive devices. Caregivers learned to place the electrode cap, add electrode gel, and turn on the BCI. After calibration, the system allowed the user to communicate via EEG. Re-calibration was performed remotely (via the internet), and BCI accuracy assessed in periodic tests. Reports of BCI usefulness by the user and the family were also recorded. Results showed that BCI accuracy remained at 83% (r = -.07, n.s.) for over 2.5 years (1.4% expected by chance). The BCI user and his family state that the BCI had restored his independence in social interactions and at work. He uses the BCI to run his NIH-funded research laboratory and to communicate via e-mail with family, friends, and colleagues. In addition to this first user, several other similarly disabled people are now using the BCI in their daily lives. In conclusion, long-term independent home use of this BCI system is practical for severely disabled people, and can contribute significantly to quality of life and productivity.

A comprehensive review of EEG-based brain-computer interface paradigms.

Advances in brain science and computer technology in the past decade have led to exciting developments in brain-computer interface (BCI), thereby making BCI a top research area in applied science. The renaissance of BCI opens new methods of neurorehabilitation for physically disabled people (e.g. paralyzed patients and amputees) and patients with brain injuries (e.g. stroke patients). Recent technological advances such as wireless recording, machine learning analysis, and real-time temporal resolution have increased interest in electroencephalographic (EEG) based BCI approaches. Many BCI studies have focused on decoding EEG signals associated with whole-body kinematics/kinetics, motor imagery, and various senses. Thus, there is a need to understand the various experimental paradigms used in EEG-based BCI systems. Moreover, given that there are many available options, it is essential to choose the most appropriate BCI application to properly manipulate a neuroprosthetic or neurorehabilitation device. The current review evaluates EEG-based BCI paradigms regarding their advantages and disadvantages from a variety of perspectives. For each paradigm, various EEG decoding algorithms and classification methods are evaluated. The applications of these paradigms with targeted patients are summarized. Finally, potential problems with EEG-based BCI systems are discussed, and possible solutions are proposed.

Evaluating Brain-Computer Interface Performance in an ALS Population: Checkerboard and Color Paradigms.

The objective of this study was to investigate the performance of 3 brain-computer interface (BCI) paradigms in an amyotrophic lateral sclerosis (ALS) population (n = 11). Using a repeated-measures design, participants completed 3 BCI conditions: row/column (RCW), checkerboard (CBW), and gray-to-color (CBC). Based on previous studies, it is hypothesized that the CBC and CBW conditions will result in higher accuracy, information transfer rate, waveform amplitude, and user preference over the RCW condition. An offline dynamic stopping simulation will also increase information transfer rate. Higher mean accuracy was observed in the CBC condition (89.7%), followed by the CBW (84.3%) condition, and lowest in the RCW condition (78.7%); however, these differences did not reach statistical significance ( P = .062). Eight of the eleven participants preferred the CBC and the remaining three preferred the CBW conditions. The offline dynamic stopping simulation significantly increased information transfer rate ( P = .005) and decreased accuracy ( P < .000). The findings of this study suggest that color stimuli provide a modest improvement in performance and that participants prefer color stimuli over monochromatic stimuli. Given these findings, BCI paradigms that use color stimuli should be considered for individuals who have ALS.

Independent home use of a brain-computer interface by people with amyotrophic lateral sclerosis.

OBJECTIVE: To assess the reliability and usefulness of an EEG-based brain-computer interface (BCI) for patients with advanced amyotrophic lateral sclerosis (ALS) who used it independently at home for up to 18 months. METHODS: Of 42 patients consented, 39 (93%) met the study criteria, and 37 (88%) were assessed for use of the Wadsworth BCI. Nine (21%) could not use the BCI. Of the other 28, 27 (men, age 28-79 years) (64%) had the BCI placed in their homes, and they and their caregivers were trained to use it. Use data were collected by Internet. Periodic visits evaluated BCI benefit and burden and quality of life. RESULTS: Over subsequent months, 12 (29% of the original 42) left the study because of death or rapid disease progression and 6 (14%) left because of decreased interest. Fourteen (33%) completed training and used the BCI independently, mainly for communication. Technical problems were rare. Patient and caregiver ratings indicated that BCI benefit exceeded burden. Quality of life remained stable. Of those not lost to the disease, half completed the study; all but 1 patient kept the BCI for further use. CONCLUSION: The Wadsworth BCI home system can function reliably and usefully when operated by patients in their homes. BCIs that support communication are at present most suitable for people who are severely disabled but are otherwise in stable health. Improvements in BCI convenience and performance, including some now underway, should increase the number of people who find them useful and the extent to which they are used.

A P300-based brain-computer interface: initial tests by ALS patients.

OBJECTIVE: The current study evaluates the effectiveness of a brain-computer interface (BCI) system that operates by detecting a P300 elicited by one of four randomly presented stimuli (i.e. YES, NO, PASS, END). METHODS: Two groups of participants were tested. The first group included three amyotrophic lateral sclerosis (ALS) patients that varied in degree of disability, but all retained the ability to communicate; the second group included three non-ALS controls. Each participant participated in ten experimental sessions during a period of approximately 6 weeks. During each run the participant's task was to attend to one stimulus and disregard the other three. Stimuli were presented auditorily, visually, or in both modes. RESULTS: Two of the 3 ALS patient's classification rates were equal to those achieved by the non-ALS participants. Waveform morphology varied as a function of the presentation mode, but not in a similar pattern for each participant. CONCLUSIONS: The event-related potentials elicited by the target stimuli could be discriminated from the non-target stimuli for the non-ALS and the ALS groups. Future studies will begin to examine online classification. SIGNIFICANCE: The results of offline classification suggest that a P300-based BCI can serve as a non-muscular communication device in both ALS, and non-ALS control groups.

A comparison of classification techniques for the P300 Speller.

This study assesses the relative performance characteristics of five established classification techniques on data collected using the P300 Speller paradigm, originally described by Farwell and Donchin (1988 Electroenceph. Clin. Neurophysiol. 70 510). Four linear methods: Pearson's correlation method (PCM), Fisher's linear discriminant (FLD), stepwise linear discriminant analysis (SWLDA) and a linear support vector machine (LSVM); and one nonlinear method: Gaussian kernel support vector machine (GSVM), are compared for classifying offline data from eight users. The relative performance of the classifiers is evaluated, along with the practical concerns regarding the implementation of the respective methods. The results indicate that while all methods attained acceptable performance levels, SWLDA and FLD provide the best overall performance and implementation characteristics for practical classification of P300 Speller data.

Brain-computer interface research at the University of South Florida Cognitive Psychophysiology Laboratory: the P300 Speller.

We describe current efforts to implement and improve P300-BCI communication tools. The P300 Speller first described by Farwell and Donchin (in 1988) adapted the so-called oddball paradigm (OP) as the operating principle of the brain-computer interface (BCI) and was the first P300-BCI. The system operated by briefly intensifying each row and column of a matrix and the attended row and column elicited a P300 response. This paradigm has been the benchmark in P300-BCI systems, and in the past few years the P300 Speller paradigm has been solidified as a promising communication tool. While promising, we have found that some people who have amyotrophic lateral sclerosis (ALS) would be better suited with a system that has a limited number of choices, particularly if the 6 x 6 matrix is difficult to use. Therefore, we used the OP to implement a four-choice system using the commands: Yes, No, Pass, and End; we also used three presentation modes: auditory, visual, and auditory and visual. We summarize results from both paradigms and also discuss obstacles we have identified while working with the ALS population outside of the laboratory environment.

The Wadsworth BCI Research and Development Program: at home with BCI.

The ultimate goal of brain-computer interface (BCI) technology is to provide communication and control capacities to people with severe motor disabilities. BCI research at the Wadsworth Center focuses primarily on noninvasive, electroencephalography (EEG)-based BCI methods. We have shown that people, including those with severe motor disabilities, can learn to use sensorimotor rhythms (SMRs) to move a cursor rapidly and accurately in one or two dimensions. We have also improved P300-based BCI operation. We are now translating this laboratory-proven BCI technology into a system that can be used by severely disabled people in their homes with minimal ongoing technical oversight. To accomplish this, we have: improved our general-purpose BCI software (BCI2000); improved online adaptation and feature translation for SMR-based BCI operation; improved the accuracy and bandwidth of P300-based BCI operation; reduced the complexity of system hardware and software and begun to evaluate home system use in appropriate users. These developments have resulted in prototype systems for every day use in people's homes.

A P300 event-related potential brain-computer interface (BCI): the effects of matrix size and inter stimulus interval on performance.

We describe a study designed to assess properties of a P300 brain-computer interface (BCI). The BCI presents the user with a matrix containing letters and numbers. The user attends to a character to be communicated and the rows and columns of the matrix briefly intensify. Each time the attended character is intensified it serves as a rare event in an oddball sequence and it elicits a P300 response. The BCI works by detecting which character elicited a P300 response. We manipulated the size of the character matrix (either 3 x 3 or 6 x 6) and the duration of the inter stimulus interval (ISI) between intensifications (either 175 or 350 ms). Online accuracy was highest for the 3 x 3 matrix 175-ms ISI condition, while bit rate was highest for the 6 x 6 matrix 175-ms ISI condition. Average accuracy in the best condition for each subject was 88%. P300 amplitude was significantly greater for the attended stimulus and for the 6 x 6 matrix. This work demonstrates that matrix size and ISI are important variables to consider when optimizing a BCI system for individual users and that a P300-BCI can be used for effective communication.

The effects of working memory on brain-computer interface performance.

OBJECTIVE: The purpose of the present study is to evaluate the relationship between working memory and BCI performance. METHODS: Participants took part in two separate sessions. The first session consisted of three computerized tasks. The List Sorting Working Memory Task was used to measure working memory, the Picture Vocabulary Test was used to measure general intelligence, and the Dimensional Change Card Sort Test was used to measure executive function, specifically cognitive flexibility. The second session consisted of a P300-based BCI copy-spelling task. RESULTS: The results indicate that both working memory and general intelligence are significant predictors of BCI performance. CONCLUSIONS: This suggests that working memory training could be used to improve performance on a BCI task. SIGNIFICANCE: Working memory training may help to reduce a portion of the individual differences that exist in BCI performance allowing for a wider range of users to successfully operate the BCI system as well as increase the BCI performance of current users.

Moving Away From Error-Related Potentials to Achieve Spelling Correction in P300 Spellers.

P300 spellers can provide a means of communication for individuals with severe neuromuscular limitations. However, its use as an effective communication tool is reliant on high P300 classification accuracies ( > 70%) to account for error revisions. Error-related potentials (ErrP), which are changes in EEG potentials when a person is aware of or perceives erroneous behavior or feedback, have been proposed as inputs to drive corrective mechanisms that veto erroneous actions by BCI systems. The goal of this study is to demonstrate that training an additional ErrP classifier for a P300 speller is not necessary, as we hypothesize that error information is encoded in the P300 classifier responses used for character selection. We perform offline simulations of P300 spelling to compare ErrP and non-ErrP based corrective algorithms. A simple dictionary correction based on string matching and word frequency significantly improved accuracy (35-185%), in contrast to an ErrP-based method that flagged, deleted and replaced erroneous characters (-47-0%) . Providing additional information about the likelihood of characters to a dictionary-based correction further improves accuracy. Our Bayesian dictionary-based correction algorithm that utilizes P300 classifier confidences performed comparably (44-416%) to an oracle ErrP dictionary-based method that assumed perfect ErrP classification (43-433%).

A P300 brain-computer interface based on a modification of the mismatch negativity paradigm.

The P300-based brain-computer interface (BCI) is an extension of the oddball paradigm, and can facilitate communication for people with severe neuromuscular disorders. It has been shown that, in addition to the P300, other event-related potential (ERP) components have been shown to contribute to successful operation of the P300 BCI. Incorporating these components into the classification algorithm can improve the classification accuracy and information transfer rate (ITR). In this paper, a single character presentation paradigm was compared to a presentation paradigm that is based on the visual mismatch negativity. The mismatch negativity paradigm showed significantly higher classification accuracy and ITRs than a single character presentation paradigm. In addition, the mismatch paradigm elicited larger N200 and N400 components than the single character paradigm. The components elicited by the presentation method were consistent with what would be expected from a mismatch paradigm and a typical P300 was also observed. The results show that increasing the signal-to-noise ratio by increasing the amplitude of ERP components can significantly improve BCI speed and accuracy. The mismatch presentation paradigm may be considered a viable option to the traditional P300 BCI paradigm.

P300-based brain-computer interface (BCI) event-related potentials (ERPs): People with amyotrophic lateral sclerosis (ALS) vs. age-matched controls.

OBJECTIVE: Brain-computer interfaces (BCIs) aimed at restoring communication to people with severe neuromuscular disabilities often use event-related potentials (ERPs) in scalp-recorded EEG activity. Up to the present, most research and development in this area has been done in the laboratory with young healthy control subjects. In order to facilitate the development of BCI most useful to people with disabilities, the present study set out to: (1) determine whether people with amyotrophic lateral sclerosis (ALS) and healthy, age-matched volunteers (HVs) differ in the speed and accuracy of their ERP-based BCI use; (2) compare the ERP characteristics of these two groups; and (3) identify ERP-related factors that might enable improvement in BCI performance for people with disabilities. METHODS: Sixteen EEG channels were recorded while people with ALS or healthy age-matched volunteers (HVs) used a P300-based BCI. The subjects with ALS had little or no remaining useful motor control (mean ALS Functional Rating Scale-Revised 9.4 (±9.5SD) (range 0-25)). Each subject attended to a target item as the items in a 6×6 visual matrix flashed. The BCI used a stepwise linear discriminant function (SWLDA) to determine the item the user wished to select (i.e., the target item). Offline analyses assessed the latencies, amplitudes, and locations of ERPs to the target and non-target items for people with ALS and age-matched control subjects. RESULTS: BCI accuracy and communication rate did not differ significantly between ALS users and HVs. Although ERP morphology was similar for the two groups, their target ERPs differed significantly in the location and amplitude of the late positivity (P300), the amplitude of the early negativity (N200), and the latency of the late negativity (LN). CONCLUSIONS: The differences in target ERP components between people with ALS and age-matched HVs are consistent with the growing recognition that ALS may affect cortical function. The development of BCIs for use by this population may begin with studies in HVs but also needs to include studies in people with ALS. Their differences in ERP components may affect the selection of electrode montages, and might also affect the selection of presentation parameters (e.g., matrix design, stimulation rate). SIGNIFICANCE: P300-based BCI performance in people severely disabled by ALS is similar to that of age-matched control subjects. At the same time, their ERP components differ to some degree from those of controls. Attention to these differences could contribute to the development of BCIs useful to those with ALS and possibly to others with severe neuromuscular disabilities.

The effects of a stress-management program on self-concept, locus of control, and the acquisition of coping skills in school-age children diagnosed with attention deficit hyperactivity disorder.

PROBLEM: What is the effectiveness of a stress-management program on self-concept, locus of control, and acquisition of appropriate coping strategies in children with attention deficit hyperactivity disorder (ADHD)? METHODS: Forty-two children with ADHD (age range 9-12) were randomly assigned to a control group, a therapist-led group, or a group in which the stress-management techniques were taught by the parents. The subjects were pre- and posttested on self-concept, locus of control, and acquisition of coping skills. FINDINGS: Although there were no significant changes in any of the three groups for acquisition of coping skills, the children in the therapist-led group reported more appropriate coping strategies. CONCLUSIONS: Involving parents in a cognitive-behavioral approach could improve parent-child relationships and further increase the opportunities for successful academic and social functioning.

Noninvasive brain-computer interface enables communication after brainstem stroke.

Brain-computer interfaces (BCIs) provide communication that is independent of muscle control, and can be especially important for individuals with severe neuromuscular disease who cannot use standard communication pathways or other assistive technology. It has previously been shown that people with amyotrophic lateral sclerosis (ALS) can successfully use BCI after all other means of independent communication have failed. The BCI literature has asserted that brainstem stroke survivors can also benefit from BCI use. This study used a P300-based event-related potential spelling system. This case study demonstrates that an individual locked-in owing to brainstem stroke was able to use a noninvasive BCI to communicate volitional messages. Over a period of 13 months, the participant was able to successfully operate the system during 40 of 62 recording sessions. He was able to accurately spell words provided by the experimenter and to initiate dialogues with his family. The results broadly suggest that, regardless of the precipitating event, BCI use may be of benefit to those with locked-in syndrome.

Brain-computer interface (BCI) evaluation in people with amyotrophic lateral sclerosis.

Brain-computer interfaces (BCIs) might restore communication to people severely disabled by amyotrophic lateral sclerosis (ALS) or other disorders. We sought to: 1) define a protocol for determining whether a person with ALS can use a visual P300-based BCI; 2) determine what proportion of this population can use the BCI; and 3) identify factors affecting BCI performance. Twenty-five individuals with ALS completed an evaluation protocol using a standard 6 × 6 matrix and parameters selected by stepwise linear discrimination. With an 8-channel EEG montage, the subjects fell into two groups in BCI accuracy (chance accuracy 3%). Seventeen averaged 92 (± 3)% (range 71-100%), which is adequate for communication (G70 group). Eight averaged 12 (± 6)% (range 0-36%), inadequate for communication (L40 subject group). Performance did not correlate with disability: 11/17 (65%) of G70 subjects were severely disabled (i.e. ALSFRS-R < 5). All L40 subjects had visual impairments (e.g. nystagmus, diplopia, ptosis). P300 was larger and more anterior in G70 subjects. A 16-channel montage did not significantly improve accuracy. In conclusion, most people severely disabled by ALS could use a visual P300-based BCI for communication. In those who could not, visual impairment was the principal obstacle. For these individuals, auditory P300-based BCIs might be effective.