Factors of Influence on the Performance of a Short-Latency Non-Invasive Brain Switch: Evidence in Healthy Individuals and Implication for Motor Function Rehabilitation.

Brain-computer interfacing (BCI) has recently been applied as a rehabilitation approach for patients with motor disorders, such as stroke. In these closed-loop applications, a brain switch detects the motor intention from brain signals, e.g., scalp EEG, and triggers a neuroprosthetic device, either to deliver sensory feedback or to mimic real movements, thus re-establishing the compromised sensory-motor control loop and promoting neural plasticity. In this context, single trial detection of motor intention with short latency is a prerequisite. The performance of the event detection from EEG recordings is mainly determined by three factors: the type of motor imagery (e.g., repetitive, ballistic), the frequency band (or signal modality) used for discrimination (e.g., alpha, beta, gamma, and MRCP, i.e., movement-related cortical potential), and the processing technique (e.g., time-series analysis, sub-band power estimation). In this study, we investigated single trial EEG traces during movement imagination on healthy individuals, and provided a comprehensive analysis of the performance of a short-latency brain switch when varying these three factors. The morphological investigation showed a cross-subject consistency of a prolonged negative phase in MRCP, and a delayed beta rebound in sensory-motor rhythms during repetitive tasks. The detection performance had the greatest accuracy when using ballistic MRCP with time-series analysis. In this case, the true positive rate (TPR) was ~70% for a detection latency of ~200 ms. The results presented here are of practical relevance for designing BCI systems for motor function rehabilitation

Detecting and classifying three different hand movement types through electroencephalography recordings for neurorehabilitation

Brain–computer interfaces can be used for motor substitution and recovery; therefore, detection and classification of movement intention are crucial for optimal control. In this study, palmar, lateral and pinch grasps were differentiated from the idle state and classified from single-trial EEG using only information prior to the movement onset. Fourteen healthy subjects performed the three grasps 100 times, while EEG was recorded from 25 electrodes. Temporal and spectral features were extracted from each electrode, and feature reduction was performed using sequential forward selection (SFS) and principal component analysis (PCA). The detection problem was investigated as the ability to discriminate between movement preparation and the idle state. Furthermore, all task pairs and the three movements together were classified. The best detection performance across movements (79 ± 8 %) was obtained by combining temporal and spectral features. The best movement–movement discrimination was obtained using spectral features: 76 ± 9 % (2-class) and 63 ± 10 % (3-class). For movement detection and discrimination, the performance was similar across grasp types and task pairs; SFS outperformed PCA. The results show it is feasible to detect different grasps and classify the distinct movements using only information prior to the movement onset, which may enable brain–computer interface-based neurorehabilitation of upper limb function through Hebbian learning mechanisms

Influence of attention alternation on movement-related cortical potentials in healthy individuals and stroke patients.

OBJECTIVE: In this study, we analyzed the influence of artificially imposed attention variations using the auditory oddball paradigm on the cortical activity associated to motor preparation/execution. METHODS: EEG signals from Cz and its surrounding channels were recorded during three sets of ankle dorsiflexion movements. Each set was interspersed with either a complex or a simple auditory oddball task for healthy participants and a complex auditory oddball task for stroke patients. RESULTS: The amplitude of the movement-related cortical potentials (MRCPs) decreased with the complex oddball paradigm, while MRCP variability increased. Both oddball paradigms increased the detection latency significantly (p<0.05) and the complex paradigm decreased the true positive rate (TPR) (p=0.04). In patients, the negativity of the MRCP decreased while pre-phase variability increased, and the detection latency and accuracy deteriorated with attention diversion. CONCLUSION: Attention diversion has a significant influence on MRCP features and detection parameters, although these changes were counteracted by the application of the laplacian method. SIGNIFICANCE: Brain-computer interfaces for neuromodulation that use the MRCP as the control signal are robust to changes in attention. However, attention must be monitored since it plays a key role in plasticity induction. Here we demonstrate that this can be achieved using the single channel Cz

Multimedia education in headache: the European Neurological Network.

The European Neurological Network is a European Economic Community supported project. The purpose of the project was to develop a multimedia educational tool for general practitioners in order to improve their management of sleep disorders, epilepsy and headache. The project involves approximately one hundred engineers and physicians from Belgium, Denmark, England, Finland, France, Germany, Italy, Portugal and Spain. This paper concerns the multimedia educational tool on headache. The system consists of five different modules, i.e. classification, clinical data, headache tutorial, diagnostic headache diary and nomenclature. It is possible to move between the modules both vertically and horizontally. The headache classification of the International Headache Society is provided in full text as a work of reference. This classification is used world wide and has been adopted by International Classification of Diseases 10 Neurological Adaptation (ICD-10 NA) and the World Health Organisation. The clinical data concentrate on migraine and tension-type headache, the two most common headache disorders, but data on familial hemiplegic migraine, cluster headache, drug-induced headache and secondary headaches are also available. The headache tutorial consists of case records that the user can test their diagnostic abilities on. The diagnostic headache diary is an expert system on headache diagnostics. It can be filled in during a consultation in order to provide the headache diagnosis or it can be printed and used by the headache patient to record headache attacks and medicine consumption. The nomenclature module provides an explanation of words and expressions used in the system