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Biomedical subjects

Thilo Hinterberger

Publications and source records attributed to Thilo Hinterberger.

At least 19 recordsLinked to original sources

Self-regulation of slow cortical potentials: a new treatment for children with attention-deficit/hyperactivity disorder.

OBJECTIVE: We investigated the effects of self-regulation of slow cortical potentials for children with attention-deficit/hyperactivity disorder. Slow cortical potentials are slow event-related direct-current shifts of the electroencephalogram. Slow cortical potential shifts in the electrical negative direction reflect the depolarization of large cortical cell assemblies, reducing their excitation threshold. This training aims at regulation of cortical excitation thresholds considered to be impaired in children with attention-deficit/hyperactivity disorder. Electroencephalographic data from the training and the 6-month follow-up are reported, as are changes in behavior and cognition. METHOD: Twenty-three children with attention-deficit/hyperactivity disorder aged between 8 and 13 years received 30 sessions of self-regulation training of slow cortical potentials in 3 phases of 10 sessions each. Increasing and decreasing slow cortical potentials at central brain regions was fed back visually and auditorily. Transfer trials without feedback were intermixed with feedback trials to allow generalization to everyday-life situations. In addition to the neurofeedback sessions, children exercised during the third training phase to apply the self-regulation strategy while doing their homework. RESULTS: For the first time, electroencephalographic data during the course of slow cortical potential neurofeedback are reported. Measurement before and after the trials showed that children with attention-deficit/hyperactivity disorder learn to regulate negative slow cortical potentials. After training, significant improvement in behavior, attention, and IQ score was observed. The behavior ratings included Diagnostic and Statistical Manual of Mental Disorders criteria, number of problems, and social behavior at school and were conducted by parents and teachers. The cognitive variables were assessed with the Wechsler Intelligence Scale for Children and with a computerized test battery that measures several components of attention. All changes proved to be stable at 6 months' follow-up after the end of training. Clinical outcome was predicted by the ability to produce negative potential shifts in transfer sessions without feedback. CONCLUSIONS: According to the guidelines of the efficacy of treatments, the evidence of the efficacy of slow cortical potential feedback found in this study reaches level 2: "possibly efficacious." In the absence of a control group, no causal relationship between observed improvements and the ability to regulate brain activity can be made. However, it could be shown for the first time that good performance in self-regulation predicts clinical outcome. "Good performance" was defined as the ability to produce negative potential shifts in trials without feedback, because it is known that the ability to self-regulate without feedback is impaired in children and adults with attention problems. Additional research should focus on the control of unspecific effects, medication, and subtypes to confirm the assumption that slow cortical potential feedback is a viable treatment option for attention-deficit/hyperactivity disorder. Regulation of slow cortical potentials may involve similar neurobiological pathways as medical treatment. It is suggested that regulation of frontocentral negative slow cortical potentials affects the cholinergic-dopaminergic balance and allows children to adapt to task requirements more flexibly.

Adolescent↗

Deactivation of brain areas during self-regulation of slow cortical potentials in seizure patients.

This study investigates the neurophysiological basis of EEG feedback for patients with epilepsy. Brain areas are identified that become hemodynamically deactivated when epilepsy patients, trained in EEG self-regulation, generate positive slow cortical potentials (SCPs). Five patients were trained in producing positive SCPs, using a training protocol previously established to reduce seizure frequency in patients with drug refractory epilepsy. Patients attempted to produce positive SCP shifts in a functional magnetic resonance imaging (fMRI) scanner. Two patients were able to reliably produce positive SCP shifts. When these successful regulators were prompted to produce positive SCPs, blood oxygen level-dependent (BOLD) response indicated deactivation, in comparison to a control state, around the recording electrode, frontal lobe, and thalamus. Unsuccessful regulators' BOLD response indicated no deactivation in cortical areas proximal to the active electrode. No thalamic deactivation was found in poor regulators. Decreased seizure frequency from SCP training may be the result of positively reinforced inhibition in cortical areas proximal to active electrode placement, the frontal cortex, and the thalamus.

Adult↗

Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects.

We summarize results from a series of related studies that aim to develop a motor-imagery-based brain-computer interface using a single recording session of electroencephalogram (EEG) or electrocorticogram (ECoG) signals for each subject. We apply the same experimental and analytical methods to 11 nonparalysed subjects (eight EEG, three ECoG), and to five paralyzed subjects (four EEG, one ECoG) who had been unable to communicate for some time. While it was relatively easy to obtain classifiable signals quickly from most of the nonparalyzed subjects, it proved impossible to classify the signals obtained from the paralyzed patients by the same methods. This highlights the fact that though certain BCI paradigms may work well with healthy subjects, this does not necessarily indicate success with the target user group. We outline possible reasons for this failure to transfer.

Algorithms↗

Neural internet: Web surfing with brain potentials for the completely paralyzed.

Neural Internet is a new technological advancement in brain-computer interface research, which enables locked-in patients to operate a Web browser directly with their brain potentials. Neural Internet was successfully tested with a locked-in patient diagnosed with amyotrophic lateral sclerosis rendering him the first paralyzed person to surf the Internet solely by regulating his electrical brain activity. The functioning of Neural Internet and its clinical implications for motor-impaired patients are highlighted.

Amyotrophic Lateral Sclerosis↗

[Neurofeedback for children with ADHD: a comparison of SCP- and theta/beta-protocols].

Research groups have consistently reported on behavioral and cognitive improvements of children with ADHD after neurofeedback. However, neurofeedback has not been commonly accepted as a treatment for ADHD. This is due, in part, to several methodological limitations. The neurofeedback literature is further complicated by having several different training protocols. Differences between the clinical efficacy of such protocols have not been examined. This study addresses previous methodological shortcomings while comparing the training of theta-beta-frequencies (theta-beta-group) with the training of slow cortical potentials (SCP-group). Each group comprised of 19 children with ADHD that were blind to group assignment. The training procedure consisted of 30 sessions and a six months follow-up training. Pre-/post measures at pretest, the end of the training and the follow-up included tests of attention, intelligence and behavioral variables. After having already reported intermediate data (Strehl et al. 2004), this paper gives account on final results: Both groups are able to voluntarily regulate cortical activity, with the extent of learned self-regulation depending on task and condition. Both groups improve in attention and IQ. Parents and teachers report significant behavioral and cognitive improvements. Clinical effects for both groups remain stable six months after training. Groups do not differ in behavioral or cognitive outcome variables.

Adolescent↗

A device for the detection of cognitive brain functions in completely paralyzed or unresponsive patients.

Unresponsive patients with remaining cognitive abilities may be able to communicate with a brain-computer interface (BCI) such as the Thought Translation Device (TTD). Before initiating TTD learning, which may imply considerable effort, it is important to classify the patients' state of awareness and their remaining cognitive abilities. A tool for detection of cognitive activity (DCA) in the completely paralyzed was developed and integrated into the TTD which is a psychophysiological system for direct brain communication. In the present version, DCA entails five event-related brain-potential (ERP) experiments and investigates the capability of a patient to discriminate, e.g., between semantically related and unrelated concepts and categories. ERPs serve as an indicator of the patients' cortical information processing. Data from five severely brain-injured patients in persistent vegetative state diagnosed as unresponsive and five healthy controls are presented to illustrate the methodology. Two patients showing the highest responsiveness were selected for TTD training. The DCA integrated in the TTD allows screening of cognitive abilities and direct brain communication in the patients' home.

Adult↗

Neuronal mechanisms underlying control of a brain-computer interface.

Brain-computer interfaces (BCIs) enable humans or animals to communicate or control external devices without muscle activity using electric brain signals. The BCI used here is based on self-regulation of slow cortical potentials (SCPs), a skill that most people and paralyzed patients can acquire with training periods of several hours up to months. The neurophysiological mechanisms and anatomical sources of SCPs and other event-related brain potentials have been described but the neural mechanisms underlying the self-regulation skill for the use of a BCI are unknown. To uncover the relevant areas of brain activation during regulation of SCPs, the BCI was combined with functional magnetic resonance imaging. The electroencephalogram was recorded inside the magnetic resonance imaging scanner in 12 healthy participants who learned to regulate their SCP with feedback and reinforcement. The results demonstrate activation of specific brain areas during execution of the brain regulation skill allowing a person to activate an external device; a successful positive SCP shift compared with a negative shift was closely related to an increase of the blood oxygen level-dependent response in the basal ganglia. Successful negativity was related to an increased blood oxygen level-dependent response in the thalamus compared with successful positivity. These results may indicate learned regulation of a cortico-striatal-thalamic loop modulating local excitation thresholds of cortical assemblies. The data support the assumption that human subjects learn the regulation of cortical excitation thresholds of large neuronal assemblies as a prerequisite for direct brain communication using an SCP-driven BCI. This skill depends critically on an intact and flexible interaction between the cortico-basal ganglia-thalamic circuits.

Adult↗

An auditory brain-computer interface based on the self-regulation of slow cortical potentials.

OBJECTIVES: Communication support for severely paralyzed patients with visual impairment is needed. Therefore, the feasibility of a brain-computer interface (BCI) using auditory stimuli alone, based on the self-regulation of slow cortical potentials (SCPs), was investigated. METHODS: Auditory stimuli were used for task and feedback presentation in an SCP self-regulation paradigm. Voluntarily produced SCP responses and measures of communication performance were compared between 3 groups (total of N = 59) of visual, auditory, and cross-modal visual-auditory modality. Electroencephalogram recordings and training from Cz-mastoids were carried out on 3 consecutive sessions. Data of 1500 trials per subject were collected. RESULTS: Best performance was achieved for the visual, followed by the auditory condition. The performance deficit of the auditory condition was partly due to decreased self-produced positivity. Larger SCP response variability also accounted for lower performance of the auditory condition. Cross-modally presented stimuli did not lead to significant learning and control of SCP. CONCLUSIONS: Brain-computer communication using auditory stimuli only is possible. Smaller cortical positivity achieved in the auditory condition, as compared to the visual condition, may be a consequence of increased selective attention to simultaneously presented auditory stimuli. To optimize performance, auditory stimuli characteristics may have to be adapted. Other suggestions for enhancement of communication performance with auditory stimuli are discussed.

Adult↗

The BCI Competition 2003: progress and perspectives in detection and discrimination of EEG single trials.

Interest in developing a new method of man-to-machine communication--a brain-computer interface (BCI)--has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, the surface of the cortex, or from inside the brain to enable users to control a variety of applications including simple word-processing software and orthotics. BCI technology could therefore provide a new communication and control option for individuals who cannot otherwise express their wishes to the outside world. Signal processing and classification methods are essential tools in the development of improved BCI technology. We organized the BCI Competition 2003 to evaluate the current state of the art of these tools. Four laboratories well versed in EEG-based BCI research provided six data sets in a documented format. We made these data sets (i.e., labeled training sets and unlabeled test sets) and their descriptions available on the Internet. The goal in the competition was to maximize the performance measure for the test labels. Researchers worldwide tested their algorithms and competed for the best classification results. This paper describes the six data sets and the results and function of the most successful algorithms.

Adult↗

Brain-computer communication and slow cortical potentials.

A thought translation device (TTD) has been designed to enable direct brain-computer communication using self-regulation of slow cortical potentials (SCPs). However, accuracy of SCP control reveals high intersubject variability. To guarantee the highest possible communication speed, some important aspects of training SCPs are discussed. A baseline correction of SCPs can increase performance. Multichannel recordings show that SCPs are of highest amplitude around the vertex electrode used for feedback, but in some subjects more global distributions were observed. A new method for control of eye movement is presented. Sequential effects of trial-to-trial interaction may also cause difficulties for the user. Finally, psychophysiological factors determining SCP communication are discussed.

Adult↗

An EEG-driven brain-computer interface combined with functional magnetic resonance imaging (fMRI).

Self-regulation of slow cortical potentials (SCPs) has been successfully used to prevent epileptic seizures as well as to communicate with completely paralyzed patients. The thought translation device (TTD) is a brain-computer interface (BCI) that was developed for training and application of SCP self-regulation. To investigate the neurophysiological mechanisms of SCP regulation the TTD was combined with functional magnetic resonance imaging (fMRI). The technical aspects and pitfalls of combined fMRI data acquisition and EEG neurofeedback are discussed. First data of SCP feedback during fMRI are presented.

Biofeedback, Psychology↗

BCI2000: a general-purpose brain-computer interface (BCI) system.

Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BC12000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups.

Algorithms↗

Support vector channel selection in BCI.

Designing a brain computer interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying electroencephalogram (EEG) signals we propose the usage of the state of the art feature selection algorithms Recursive Feature Elimination and Zero-Norm Optimization which are based on the training of support vector machines (SVM). These algorithms can provide more accurate solutions than standard filter methods for feature selection. We adapt the methods for the purpose of selecting EEG channels. For a motor imagery paradigm we show that the number of used channels can be reduced significantly without increasing the classification error. The resulting best channels agree well with the expected underlying cortical activity patterns during the mental tasks. Furthermore we show how time dependent task specific information can be visualized.

Algorithms↗

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.

Acoustic Stimulation↗

Brain areas activated in fMRI during self-regulation of slow cortical potentials (SCPs).

In humans, surface-negative slow cortical potentials (SCPs) originating in the apical dendritic layers of the neocortex reflect synchronized depolarization of large groups of neuronal assemblies. They are recorded during states of behavioural or cognitive preparation and during motivational states of apprehension and fear. Surface positive SCPs are thought to indicate reduction of cortical excitation of the underlying neural networks and appear during behavioural inhibition and motivational inertia (e.g. satiety). SCPs at the cortical surface constitute summated population activity of local field potentials (LFPs). SCPs and LFPs may share identical neural substrates. In this study the relationship between negative and positive SCPs and changes in the BOLD signal of the fMRI were examined in ten subjects who were trained to successfully self-regulate their SCPs. FMRI revealed that the generation of negativity (increased cortical excitation) was accompanied by widespread activation in central, pre-frontal, and parietal brain regions as well as the basal ganglia. Positivity (decreased cortical excitation) was associated with widespread deactivations in several cortical sites as well as some activation, primarily in frontal and parietal structures as well as insula and putamen. Regression analyses revealed that cortical positivity was predicted with high accuracy by pallidum and putamen activation and supplementary motor area (SMA) and motor cortex deactivation, while differentiation between cortical negativity and positivity was revealed primarily in parahippocampal regions. These data suggest that negative and positive electrocortical potential shifts in the EEG are related to distinct differences in cerebral activation detected by fMRI and support animal studies showing parallel activations in fMRI and neuroelectric recordings.

Adult↗

Conscious perception of brain states: mental strategies for brain-computer communication.

Direct brain-computer communication utilises self-regulation of brain potentials to select letters, words or symbols from a computer menu. In this study a completely paralysed (locked-in) patient learnt to produce slow cortical potential (SCP) shifts to operate a binary spelling device. After hundreds of training sessions he gave a detailed description of his mental strategies for self-regulation. His cognitive strategies matched with the electrocortical changes perfectly. Thus he produced a contingent negative variation (CNV) with images of preparation such as an arrow being drawn on a bow. To produce a positive potential shift he imagined the arrow shooting up from the bow. To suppress potential shifts he tried to stop thinking. The study demonstrates that patients become sensitive for their brain states with increasing self-regulation practice. The use of conscious cognitive strategies may, however, be incompatible with the complete automatization of the self-regulation skill.

Amyotrophic Lateral Sclerosis↗

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.

Communication Devices for People with Disabilities↗