Band Power Features Research Articles

Using phase information to reveal the nature of event-related desynchronization

It is common knowledge among brain researchers that certain events, such as motor imagery, can elicit event-related synchronization/desynchronization (ERD/ERS) of neurons in the brain, and that these phenomena manifest themselves in terms of band power changes in brain signals. There are, however, also important phase related changes in the brain signals associated with ERD/ERS which we investigate here. We quantify for the first time the “delta-phase” component of the Complex Band Power (CBP) features introduced in [G. Townsend, B. Graimann, G. Pfurtscheller, A comparison of common spatial patterns with complex band power features in a four-class BCI Experiment, IEEE Trans. Biomed. Eng. 53 (2006) 642–651] and [G. Townsend, Brain Computer Interfaces: Phase Features and Post Processing Issues, Ph.D. Thesis, 2006, p. 97]. Although this component, which makes explicit use of phase, is known from these earlier studies to provide improved classification results in a brain–computer interface (BCI), this phenomenon has never been investigated purely in the context of a physiological phenomenon. The importance of this study is to fill this gap in our knowledge by providing an analysis and quantification of this new feature so that an improved understanding of its nature will allow further exploitation of this feature to further improve BCI systems. Given that the primary use of BCIs is as an assistive technology for the disabled, the importance of this work to society cannot be overstated. Changes in band power in the context of ERD/ERS have been investigated in the past using a visualization tool called an ERD/ERS map [B. Graimann, Movement-Related Patterns in ECoG and EEG: Visualization and Detection, Ph.D. Thesis, 2003, p. 107]. We present and discuss here for the first time, an equivalent tool called the delta-phase map used to visualize the occurrence of delta-phase in different frequency bands and over the time courses of motor imagery trials. In this study, the delta-phase feature is shown to be proportional to frequency and is quantified and presented in that context for clarity. It was found that the most prominent ERD activity occurring in the frequency bands studied here are correlated to the activity captured in the delta-phase maps. The underlying nature of ERD/ERS is explored based on evidence provided by the delta-phase feature.

A Comparison of Common Spatial Patterns With Complex Band Power Features in a Four-Class BCI Experiment

We report on the offline analysis of four-class brain-computer interface (BCI) data recordings. Although the analysis is done within defined time windows (cue-based BCI), our goal is to work toward an approach which classifies on-going electroencephalogram (EEG) signals without the use of such windows (un-cued BCI). To that end, we provide some elements of that analysis related to timing issues that will become important as we pursue this goal in the future. A new set of features called complex band power (CBP) features which make explicit use of phase are introduced and are shown to produce good results. As reference methods we used traditional band power features and the method of common spatial patterns. We consider also for the first time in the context of a four-class problem the issue of variability of the features over time and how much data is required to give good classification results. We do this in a practical way where training data precedes testing data in time.

SVM-based recursive feature elimination to compare phase synchronization computed from broadband and narrowband EEG signals in Brain–Computer Interfaces

To allow motor-disabled people for communication, Brain–Computer Interfaces (BCIs) are being developed. Such a communication does not depend on the brain's normal output pathways of peripheral nerves and muscles, but is based on analysis of recorded brain activity. In this paper, we compare the performance of power features and phase locking values (PLVs) computed from broadband and narrowband filtered EEG signals for discriminating 3 mental tasks in the framework of a BCI. EEG signals were recorded from 5 subjects while performing the 3 mental tasks left- and right-hand movement imagination and word generation. To reduce the total amount of features, the most discriminative features were selected in a 2-step feature selection procedure by SVM-based recursive feature elimination. Significance tests demonstrated that band power features were more discriminative when they were computed in the narrower frequency band 8–12 Hz. In case of PLV features, the discrimination of mental tasks was significantly better when they were computed from the broader 8–30 Hz frequency band, as compared to the narrower bands 8–12, 13–18 and 19–30 Hz.

Dynamics of human slow brain potentials and changes of cortisol and hGH under mental load

Meditation is one of the accepted practices to flourish in life. Emotional harmony is essential for personal well-being. In this paper, the effect of meditation on emotional response using EEG is investigated. The simple meditative technique such as focused attention on breathing is taught to the subjects. EEG is recorded at the beginning of meditation experiment and after eight weeks of regular meditation (every day 20 min). EEG signals are recorded using 14 electrodes EMOTIV EPOC+ device. The asymmetry of band power (theta, alpha and beta band) and Hjorth features are used as emotion-specific EEG features. The average effect of these features is more on frontal asymmetry. EEG functional connectivity of selected brain regions during four emotions (Happy, Angry, Sad, and Relax) in pre and post-meditation state is examined. The results revealed that more coherence in the post-meditation is found for all emotions. The K-Nearest Neighbors (K-NN) classifier is used and emotion classification accuracy after 8 weeks of meditation is decreased. This indicates the divergence of four emotions (happy, angry, sad, and relax) are less as a result of increased awareness and reduced aversion in the 11 subjects after 8 weeks of meditation.