Self-initiation of EEG-based communication in paralyzed patients

How standardized are “standard protocols”? Variations in protocol and performance evaluation for slow cortical potential neurofeedback: A systematic review

Neurofeedback (NF) aims to alter neural activity by enhancing self-regulation skills. Over the past decade NF has received considerable attention as a potential intervention option for many somatic and mental conditions and ADHD in particular. However, placebo-controlled trials have demonstrated insufficient superiority of NF compared to treatment as usual and sham conditions. It has been argued that the reason for limited NF effects may be attributable to participants' challenges to self-regulate the targeted neural activity. Still, there is support of NF efficacy when only considering so-called “standard protocols,” such as Slow Cortical Potential NF training (SCP-NF). This PROSPERO registered systematic review following PRISMA criteria searched literature databases for studies applying SCP-NF protocols. Our review focus concerned the operationalization of self-regulatory success, and protocol-details that could influence the evaluation of self-regulation. Such details included; electrode placement, number of trials, length per trial, proportions of training modalities, handling of artifacts and skill-transfer into daily-life. We identified a total of 63 eligible reports published in the year 2000 or later. SCP-NF protocol-details varied considerably on most variables, except for electrode placement. However, due to the increased availability of commercial systems, there was a trend to more uniform protocol-details. Although, token-systems are popular in SCP-NF for ADHD, only half reported a performance-based component. Also, transfer exercises have become a staple part of SCP-NF. Furthermore, multiple operationalizations of regulatory success were identified, limiting comparability between studies, and perhaps usefulness of so-called transfer-exercises, which purpose is to facilitate the transfer of the self-regulatory skills into every-day life. While studies utilizing SCP as Brain-Computer-Interface mainly focused on the acquisition of successful self-regulation, clinically oriented studies often neglected this. Congruently, rates of successful regulators in clinical studies were mostly low (<50%). The relation between SCP self-regulation and behavior, and how symptoms in different disorders are affected, is complex and not fully understood. Future studies need to report self-regulation based on standardized measures, in order to facilitate both comparability and understanding of the effects on symptoms. When applied as treatment, future SCP-NF studies also need to put greater emphasis on the acquisition of self-regulation (before evaluating symptom outcomes).

BCI in practice

Brain-computer interfaces are systems that use signals recorded from the brain to enable communication and control applications for individuals who have impaired function. This technology has developed to the point that it is now being used by individuals who can actually benefit from it. However, there are several outstanding issues that prevent widespread use. These include the ease of obtaining high-quality recordings by home users, the speed, and accuracy of current devices and adapting applications to the needs of the user. In this chapter, we discuss some of these unsolved issues.

Electrophysiological CNS-processes related to associative learning in humans

The neurophysiology of human associative memory has been studied with electroencephalographic techniques since the 1930s. This research has revealed that different types of electrophysiological processes in the human brain can be modified by conditioning: sensory evoked potentials, sensory induced gamma-band activity, periods of frequency-specific waves (alpha and beta waves, the sensorimotor rhythm and the mu-rhythm) and slow cortical potentials. Conditioning of these processes has been studied in experiments that either use operant conditioning or repeated contingent pairings of conditioned and unconditioned stimuli (classical conditioning). In operant conditioning, the appearance of a specific brain process is paired with an external stimulus (neurofeedback) and the feedback enables subjects to obtain varying degrees of control of the CNS-process. Such acquired self-regulation of brain activity has found practical uses for instance in the amelioration of epileptic seizures, Autism Spectrum Disorders (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). It has also provided communicative means of assistance for tetraplegic patients through the use of brain computer interfaces. Both extra and intracortically recorded signals have been coupled with contingent external feedback. It is the aim for this review to summarize essential results on all types of electromagnetic brain processes that have been modified by classical or operant conditioning. The results are organized according to type of conditioned EEG-process, type of conditioning, and sensory modalities of the conditioning stimuli.

Modulation of Craving Related Brain Responses Using Real-Time fMRI in Patients with Alcohol Use Disorder

LITERATURE

One prominent symptom in addiction disorders is the strong desire to consume a particular substance or to display a certain behaviour (craving). Especially the strong association between craving and the probability of relapse emphasises the importance of craving in the therapeutic process. Neuroimaging studies have shown that craving is associated with increased responses, predominantly in fronto-striatal areas.

AIM AND METHODS

The aim of the present study is the modification of craving-related neuronal responses in patients with alcohol addiction using fMRI real-time neurofeedback. For that purpose, patients with alcohol use disorder and healthy controls participated once in neurofeedback training; during the sessions neuronal activity within an individualized cortical region of interest (ROI) (anterior cingulate cortex, insula, dorsolateral prefrontal cortex) was evaluated. In addition, variations regarding the connectivity between brain regions were assessed in the resting state.

RESULTS AND DISCUSSION

The results showed a significant reduction of neuronal activity in patients at the end of the training compared to the beginning, especially in the anterior cingulate cortex, the insula, the inferior temporal gyrus and the medial frontal gyrus. Furthermore, the results show that patients were able to regulate their neuronal activities in the ROI, whereas healthy subjects achieved no significant reduction. However, there was a wide variability regarding the effects of the training within the group of patients. After the neurofeedback-sessions, individual craving was slightly reduced compared to baseline. The results demonstrate that it seems feasible for patients with alcohol dependency to reduce their neuronal activity using rtfMRI neurofeedback. In addition, there is some evidence that craving can be influenced with the help of this technique.

FUTURE PROSPECTS

In future, real-time fMRI might be a complementary neurophysiological-based strategy for the psychotherapy of patients with psychiatric or psychosomatic diseases. For that purpose, the stability of this effect and the generalizability needs to be assessed.

Brain computer interfaces, a review

A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Finally, the review provides an overview of various BCI applications that control a range of devices.

Dysarthria in amyotrophic lateral sclerosis: A review

Dysarthria is a motor disorder of speech characterized by abnormalities of the articulation and intelligibility of speech. Phonation and the rate of facial movements may also be affected. Understanding the nature and course of dysarthria in amyotrophic lateral sclerosis (ALS) is important because loss of communication prevents patients from participating in many activities, may lead to social isolation, and reduces the quality of life. The goal of management of dysarthria in ALS patients is to optimize communication effectiveness for as long as possible. The information about dysarthria in ALS is dispersed in physiological, pathological, speech therapy, otorhinolaringological and neurological publications. This review summarizes the current state of knowledge on the clinical features, differential diagnosis, pathophysiology, investigations and management of dysarthria in ALS patients. There is a need to compare the different methods used to assess dysarthria and for controlled clinical trials to assess therapeutic strategies.

Conditional associative learning examined in a paralyzed patient with amyotrophic lateral sclerosis using brain-computer interface technology

Background

Brain-computer interface methodology based on self-regulation of slow-cortical potentials (SCPs) of the EEG (electroencephalogram) was used to assess conditional associative learning in one severely paralyzed, late-stage ALS patient. After having been taught arbitrary stimulus relations, he was evaluated for formation of equivalence classes among the trained stimuli.

Methods

A monitor presented visual information in two targets. The method of teaching was matching to sample. Three types of stimuli were presented: signs (A), colored disks (B), and geometrical shapes (C). The sample was one type, and the choice was between two stimuli from another type. The patient used his SCP to steer a cursor to one of the targets. A smiley was presented as a reward when he hit the correct target. The patient was taught A-B and B-C (sample – comparison) matching with three stimuli of each type. Tests for stimulus equivalence involved the untaught B-A, C-B, A-C, and C-A relations. An additional test was discrimination between all three stimuli of one equivalence class presented together versus three unrelated stimuli. The patient also had sessions with identity matching using the same stimuli.

Results

The patient showed high accuracy, close to 100%, on identity matching and could therefore discriminate the stimuli and control the cursor correctly. Acquisition of A-B matching took 11 sessions (of 70 trials each) and had to be broken into simpler units before he could learn it. Acquisition of B-C matching took two sessions. The patient passed all equivalence class tests at 90% or higher.

Conclusion

The patient may have had a deficit in acquisition of the first conditional association of signs and colored disks. In contrast, the patient showed clear evidence that A-B and B-C training had resulted in formation of equivalence classes. The brain-computer interface technology combined with the matching to sample method is a useful way to assess various cognitive abilities of severely paralyzed patients, who are without reliable motor control.

Brain-computer interface systems: progress and prospects

Brain-computer interface (BCI) systems support communication through direct measures of neural activity without muscle activity. BCIs may provide the best and sometimes the only communication option for users disabled by the most severe neuromuscular disorders and may eventually become useful to less severely disabled and/or healthy individuals across a wide range of applications. This review discusses the structure and functions of BCI systems, clarifies terminology and addresses practical applications. Progress and opportunities in the field are also identified and explicated.

Self-initiation of EEG-based brain-computer communication using the heart rate response

Self-initiation, that is the ability of a brain-computer interface (BCI) user to autonomously switch on and off the system, is a very important issue. In this work we analyze whether the respiratory heart rate response, induced by brisk inspiration, can be used as an additional communication channel. After only 20 min of feedback training, ten healthy subjects were able to self-initiate and operate a 4-class steady-state visual evoked potential-based (SSVEP) BCI by using one bipolar ECG and one bipolar EEG channel only. Threshold detection was used to measure a beat-to-beat heart rate increase. Despite this simple method, during a 30 min evaluation period on average only 2.9 non-intentional switches (heart rate changes) were detected.

A Comprehensive Survey of Brain Interface Technology Designs

In this work we present the first comprehensive survey of Brain Interface (BI) technology designs published prior to January 2006. Detailed results from this survey, which was based on the Brain Interface Design Framework proposed by Mason and Birch, are presented and discussed to address the following research questions: (1) which BI technologies are directly comparable, (2) what technology designs exist, (3) which application areas (users, activities and environments) have been targeted in these designs, (4) which design approaches have received little or no research and are possible opportunities for new technology, and (5) how well are designs reported. The results of this work demonstrate that meta-analysis of high-level BI design attributes is possible and informative. The survey also produced a valuable, historical cross-reference where BI technology designers can identify what types of technology have been proposed and by whom.

An asynchronously controlled EEG-based virtual keyboard: improvement of the spelling rate

An improvement of the information transfer rate of brain-computer communication is necessary for the creation of more powerful and convenient applications. This paper presents an asynchronously controlled three-class brain-computer interface-based spelling device [virtual keyboard (VK)], operated by spontaneous electroencephalogram and modulated by motor imagery. Of the first results of three able-bodied subjects operating the VK, two were successful, showing an improvement of the spelling rate sigma, the number of correctly spelled letters/min, up to sigma = 3.38 (average sigma = 1.99).

Automatic processing of self-regulation of slow cortical potentials: evidence from brain-computer communication in paralysed patients

OBJECTIVE

Direct brain-computer communication utilizes self-regulation of brain potentials to select letters, words or symbols from a computer menu. Selection of letters or words with brain potentials requires simultaneous processing of several tasks such as production of certain brain potentials at predefined time points simultaneously with processing of presented letter strings. This study addresses the question of whether the self-regulation of slow cortical potentials (SCP) automatizes with practice and can thus be considered as a skill comparable to motor or cognitive skills.

METHODS

Two nearly completely paralysed patients learned over several months to produce electrocortically negative and positive SCP by means of visual feedback. Improved performance and a reduction in performance variability were regarded as behavioural indicators for automaticity, while the topographic focalization of cortical activation was considered as a neurophysiological indicator for automaticity. Different indicators of automaticity were expected to covary along with practice.

RESULTS

In patient 1, performance measured as the percentage of correct SCP shifts increased simultaneously with the topographic focalization of cortical activation. His performance became more stable with practice. For this patient the criteria for automaticity were all met. In patient 2, performance also improved, but his cortical activity became topographically less focal. His performance was less stable than that of patient 1.

CONCLUSIONS

The present findings, albeit on only two subjects, provide preliminary evidence that SCP self-regulation may automatize with long-term practice and can therefore be considered a skill.

A multimodal brain-based feedback and communication system

The Thought Translation Device (TTD) is a brain-computer interface based on the self-regulation of slow cortical potentials (SCPs) and enables completely paralyzed patients to communicate using their brain potentials. Here, an extended version of the TTD is presented that has an auditory and a combined visual and auditory feedback modality added to the standard visual feedback. This feature is necessary for locked-in patients who are no longer able to focus their gaze. In order to test performance of physiological regulation with auditory feedback 54 healthy participants were randomly assigned to visual, auditory or combined visual-auditory feedback of slow cortical potentials. The training consisted of three sessions with 500 trials per session with random assignment of required cortical positivity or negativity in half of the trials. The data show that physiological regulation of SCPs can be learned with auditory and combined auditory and visual feedback although the performance of auditory feedback alone was significantly worse than with visual feedback alone.

A brain-computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device

OBJECTIVE

The Thought Translation Device (TTD) for brain-computer interaction was developed to enable totally paralyzed patients to communicate. Patients learn to regulate slow cortical potentials (SCPs) voluntarily with feedback training to select letters. This study reports the comparison of different methods of electroencephalographic (EEG) analysis to improve spelling accuracy with the TTD on a data set of 6,650 trials of a severely paralyzed patient.

METHODS

Selections of letters occurred by exceeding a certain SCP amplitude threshold. To enhance the patient's control of an additional event-related cortical potential, a filter with two filter characteristics ('mixed filter') was developed and applied on-line. To improve performance off-line the criterion for threshold-related decisions was varied. Different types of discriminant analysis were applied to the EEG data set as well as on wavelet transformed EEG data.

RESULTS

The mixed filter condition increased the patients' performance on-line compared to the SCP filter alone. A threshold, based on the ratio between required selections and rejections, resulted in a further improvement off-line. Discriminant analysis of both time-series SCP data and wavelet transformed data increased the patient's correct response rate off-line.

CONCLUSIONS

It is possible to communicate with event-related potentials using the mixed filter feedback method. As wavelet transformed data cannot be fed back on-line before the end of a trial, they are applicable only if immediate feedback is not necessary for a brain-computer interface (BCI). For future BCIs, wavelet transformed data should serve for BCIs without immediate feedback. A stepwise wavelet transformation would even allow immediate feedback.

Brain-computer interfaces for communication and control

For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain function might provide a new non-muscular channel for sending messages and commands to the external world - a brain-computer interface (BCI). Over the past 15 years, productive BCI research programs have arisen. Encouraged by new understanding of brain function, by the advent of powerful low-cost computer equipment, and by growing recognition of the needs and potentials of people with disabilities, these programs concentrate on developing new augmentative communication and control technology for those with severe neuromuscular disorders, such as amyotrophic lateral sclerosis, brainstem stroke, and spinal cord injury. The immediate goal is to provide these users, who may be completely paralyzed, or 'locked in', with basic communication capabilities so that they can express their wishes to caregivers or even operate word processing programs or neuroprostheses. Present-day BCIs determine the intent of the user from a variety of different electrophysiological signals. These signals include slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronal activity recorded by implanted electrodes. They are translated in real-time into commands that operate a computer display or other device. Successful operation requires that the user encode commands in these signals and that the BCI derive the commands from the signals. Thus, the user and the BCI system need to adapt to each other both initially and continually so as to ensure stable performance. Current BCIs have maximum information transfer rates up to 10-25bits/min. This limited capacity can be valuable for people whose severe disabilities prevent them from using conventional augmentative communication methods. At the same time, many possible applications of BCI technology, such as neuroprosthesis control, may require higher information transfer rates. Future progress will depend on: recognition that BCI research and development is an interdisciplinary problem, involving neurobiology, psychology, engineering, mathematics, and computer science; identification of those signals, whether evoked potentials, spontaneous rhythms, or neuronal firing rates, that users are best able to control independent of activity in conventional motor output pathways; development of training methods for helping users to gain and maintain that control; delineation of the best algorithms for translating these signals into device commands; attention to the identification and elimination of artifacts such as electromyographic and electro-oculographic activity; adoption of precise and objective procedures for evaluating BCI performance; recognition of the need for long-term as well as short-term assessment of BCI performance; identification of appropriate BCI applications and appropriate matching of applications and users; and attention to factors that affect user acceptance of augmentative technology, including ease of use, cosmesis, and provision of those communication and control capacities that are most important to the user. Development of BCI technology will also benefit from greater emphasis on peer-reviewed research publications and avoidance of the hyperbolic and often misleading media attention that tends to generate unrealistic expectations in the public and skepticism in other researchers. With adequate recognition and effective engagement of all these issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.