Event-Related changes of band power and coherence: methodology and interpretation.

Event-related calculation of band power changes can be used to quantify event-related desynchronization, event-related synchronization, and event-related coherence (ERCoh). It is shown that in the case of a motor task especially, the ERCoh time course depends on the type of EEG derivation used, whereby referenced EEG data can result in a bilateral coherence increase, although both hemispheres generate independent sensorimotor rhythms. It is further shown that not only Rolandic mu rhythms but also central beta rhythms display a lack of interhemispheric linear phase coupling.

Enhancement of left-right sensorimotor EEG differences during feedback-regulated motor imagery.

EEG feedback studies demonstrate that human subjects can learn to regulate electrocortical activity over the sensorimotor cortex. Such self-induced EEG changes could serve as control signals for a Brain Computer Interface. The experimental task of the current study was to imagine either right-hand or left-hand movement depending on a visual cue stimulus on a computer monitor.

Visually guided motor imagery activates sensorimotor areas in humans.

Stimulus-related changes in ongoing electroencephalography (EEG) over sensorimotor areas were investigated during a visually cued motor imagery task. Four subjects were instructed to imagine one-sided hand movements in response to visual cue stimuli. The EEG was recorded from central areas using 27 electrodes set at distances of 2.

Hidden Markov models used for the offline classification of EEG data.

Hidden Markov models (HMM) are introduced for the offline classification of single-trail EEG data in a brain-computer-interface (BCI). The HMMs are used to classify Hjorth parameters calculated from bipolar EEG data, recorded during the imagination of a left or right hand movement. The effects of different types of HMMs on the recognition rate are discussed.

Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters.

Electroencephalogram (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by, e.

Feature extraction for on-line EEG classification using principal components and linear discriminants.

The study focuses on the problems of dimensionality reduction by means of principal component analysis (PCA) in the context of single-trial EEG data classification (i.e. discriminating between imagined left- and right-hand movement).

Post-movement beta oscillations studied with linear estimation.

The application of surface laplacian and linear estimation methods to single trial EEG data was studied. EEG was recorded in 3 subjects during voluntary, self-paced extensions and flexions of the index finger. In each subject a post-movement beta synchronisation was found in specific frequency bands.

Do changes in coherence always reflect changes in functional coupling?

It is well known that the rhythmic activity within the alpha band in the central area may be composed of two different types of rhythms: (i) the Rolandic mu rhythm, representing the intrinsic activity of the sensorimotor area, and (ii) rhythmic activity believed to be generated within parieto-occipital areas and to extend into central regions through volume conduction (the 'classical alpha rhythm'). In this paper we clearly demonstrate that this second type of rhythmic activity is not due to volume conduction from parieto-occipital areas. We also demonstrate the significant impact of the coexistence of these two types of rhythms on the interpretation of interhemispheric coherence measurements.

On the realization of an analytic high-resolution EEG.

The analytic solution of the harmonic downward continuation of the scalp potential field in an N-shell heterogeneous, but isotropic, spherical volume conductor model has been derived. The objective of this paper was to investigate the realization of a so-called "high-resolution electroencephalogram (EEG)": by enhancing the poor spatial resolution of EEG recordings. To this end, the forward problem for a dipolar source arbitrarily located at the source point Q = Q(rs, phi s, theta s) has been determined in a compact matrix notation.

EEG-based discrimination between imagination of right and left hand movement.

Three subjects were asked to imagine either right or left hand movement depending on a visual cue stimulus. The interval between two consecutive imagination tasks was > 10 s. Each subject imagined a total of 160 hand movements in each of 3-4 sessions (training) without feedback and 7-8 sessions with feedback.

Cardiac response induced by voluntary self-paced finger movement.

Cardiac responses induced by slow and brisk voluntary self-paced index finger movements of the dominant and non-dominant hand were investigated in a group of 12 right-handed subjects. Since subjects synchronised movement and respiration, initiating movement preferably during inspiration, a novel method of evaluating the movement-induced cardiac response was used. This method allows one to distinguish the differential effects on the cardiac response due to movement and respiration.

On the existence of different types of central beta rhythms below 30 Hz.

EEGs were recorded from sensorimotor areas of 12 subjects performing unilateral self-paced brisk and slow finger movements. Two different beta components were found below 30 Hz: (i) One component, at about twice the frequency of the mu rhythm, showed desynchronization in parallel with the mu rhythm starting at about 2 s prior to movement. Measurements of bicoherence have shown that this beta component can be non-linearly related to the arch-shaped mu rhythm.

On the existence of different alpha band rhythms in the hand area of man.

Earlier investigations have reported that the Rolandic mu rhythm and the parieto-occipital alpha rhythm, the latter thought to be volume-conducted into central areas, both contribute to scalp-recorded electroencephalogram (EEG) in the central region of humans. The present study applies dynamic cross-spectral analysis to event-related EEG data recorded during finger movement. In 10 of 12 subjects, a superposition of Rolandic mu rhythms and bilaterally coherent alpha band rhythms is found in the central area; however, the use of closely-spaced Laplacian derivations rules out volume-conduction effects, providing evidence that both rhythms are generated in the underlying neocortical circuitry.

On-line EEG classification during externally-paced hand movements using a neural network-based classifier.

EEGs of 6 normal subjects were recorded during sequences of periodic left or right hand movement. Left or right was indicated by a visual cue. The question posed was: 'Is it possible to move a cursor on a monitor to the right or left side using the EEG signals for cursor control?' For this purpose the EEG during performance of hand movement was analyzed and classified on-line.

Event-related desynchronisation of central beta-rhythms during brisk and slow self-paced finger movements of dominant and nondominant hand.

Changes in central beta-rhythms (14-29 Hz) during movement were investigated in 12 right-handed subjects by quantifying event-related desynchronisation (ERD). EEG was recorded from 24 closely spaced electrodes overlaying the left and right sensorimotor hand area. The subjects performed approximately 80 brisk (movement time < 0.

Post-movement synchronization of beta rhythms in the EEG over the cortical foot area in man.

Post-movement synchronization of the electroencephalogram (EEG) was studied in nine right-handed subjects who performed voluntary self-paced dorsal flexions with the right and left foot. The findings revealed that foot movement results in enhanced beta oscillations after movement. These beta bursts showed subject-specific resonance frequencies in the range between 12 and 32 Hz and were localized to electrode Cz and to one electrode 2.

Sleep classification in infants by decision tree-based neural networks.

This paper presents an AI-based approach to automatic sleep stage scoring. The system TBNN (Tree-Based Neural Network) uses a decision-tree generator to provide knowledge that defines the architecture of a backpropagation neural network, including feature selection and initialisation of the weights. The case study reports a successful application to the data from polygraphic all-night sleep of 8 babies aged 6 months.

The effects of handedness and type of movement on the contralateral preponderance of mu-rhythm desynchronisation.

Event-related desynchronisation (ERD) of mu-rhythm was studied in 12 right-handed and 11 left-handed subjects during brisk and slow self-paced index finger movements of dominant and nondominant hand. Electroencephalogram (EEG) was recorded from the sensorimotor hand area of both hemispheres. The contralateral preponderance of mu-rhythm ERD in the pre-movement period showed the following changes: (i) the contrasts between left- and right-finger movements were larger and earlier in the dominant than nondominant hemisphere in both handedness groups; (ii) right-handed subjects showed larger lateralisation of mu-rhythm ERD prior to right-finger as compared to left-finger movements, whereas about equal contralateral preponderance for both sides was found in the left-handed; (iii) the lateralisation of mu-rhythm ERD was lower prior to brisk as compared to slow movements, especially in the left-handed subjects.

Mu-rhythm changes in brisk and slow self-paced finger movements.

We analysed whether type of movement (brisk vs slow) and active muscle force are encoded in the time course of mu-rhythm desynchronization during self-paced finger movements. Ten subjects performed 100 brisk and slow extensions of the right index finger. The time course of mu-rhythm desynchronization in the contralateral sensorimotor area before movement was identical for both types of movements.

Post-movement beta synchronization. A correlate of an idling motor area?

Post-movement beta (around 20 Hz) synchronization was investigated in 2 experiments with self-paced finger extension and flexion and externally paced wrist movement. The electrodes were fixed over the sensorimotor area in distances of 2.5 cm.

Event-related coherence as a tool for studying dynamic interaction of brain regions.

This paper demonstrates a simple approach to calculating time courses of coherence for data recorded during an event-related paradigm. Event-related coherence (ERCoh) was investigated between left and right sensorimotor areas, and between contralateral sensorimotor and SMA during discrete right index finger movements. It is demonstrated that ERCoh can provide information regarding the dynamic interaction of spatially separated brain regions.

Event-related coherence during finger movement: a pilot study.

Dynamic functional coupling between contralateral sensorimotor and supplementary motor areas during unilateral finger movements is studied using event-related coherence analysis. It is demonstrated in 3 subjects that the intrinsic rhythm of the sensorimotor area (mu rhythm) is phase coupled to intrinsic rhythmic activity of the supplementary motor area during rest. With preparation and execution of discrete, unilateral finger movements, these intrinsic rhythms are desynchronized due to activation of each of the local cortical networks, and the degree of synchrony or phase consistency between these rhythms decreases.

Dynamic spectral analysis of event-related EEG data.

A method for analysing the time course of power spectra of event-related EEG data is presented. A sequence of autoregressive models is fitted to segments of the EEG within which the data exhibit local stationarity. For parameter estimation a method involving ensemble averages is introduced.

Selection of electrode positions for an EEG-based brain computer interface (BCI).

One major question in designing an EEG-based Brain Computer Interface to bypass the normal motor pathways is the selection of proper electrode positions. This study investigates electrode selection with a Distinction Sensitive Learning Vector Quantizer (DSLVQ). DSLVQ is an extended Learning Vector Quantizer (LVQ) which employs a weighted distance function for dynamical scaling and feature selection.

Event-related synchronization of mu rhythm in the EEG over the cortical hand area in man.

Spontaneous EEG activity was recorded at 56 electrodes in 3 healthy subjects. All subjects displayed event-related desynchronization (ERD) of mu rhythms over the cortical hand area during discrete finger movement. In contrast to this, foot movement resulted in an enhancement or event-related synchronization (ERS) of mu rhythms over the hand area.