Phase relationships between different subdural electrode recordings in man.

Almost all brain-computer interfaces (BCIs) ignore information related to the phase coupling between electroencephalogram (EEG) or electrocorticogram (ECoG) recordings from different electrodes. This paper investigates whether additional information can be found when calculating the amount of synchronization between two electrode channels by using a phase locking measurement called the phase locking value (PLV). Special emphasis is put on the beta band (around 20 Hz) as well as the gamma band (high frequencies up to 95 Hz), which can only be used when subdural electrode recordings are available.

"Virtual keyboard" controlled by spontaneous EEG activity.

A "virtual keyboard" (VK) is a letter spelling device operated for example by spontaneous electroencephalogram (EEG), whereby the EEG is modulated by mental hand and leg motor imagery. We report on three able-bodied subjects, operating the VK. The ability in the use of the VK varies between 0.

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.

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.

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.

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.

Differentiation between finger, toe and tongue movement in man based on 40 Hz EEG.

Movements of right and left index fingers, right toe and tongue were studied by EEG measurement in the alpha and gamma (30-40 Hz) bands. The EEG was recorded with a 56-electrode array over pre- and postcentral areas. For each movement the average power decrease, as a measurement of the event-related desynchronization or power increase in narrow frequency bands, was calculated.

Event-related desynchronization (ERD) during visual processing.

Event-related desynchronization (ERD) is the short-lasting attenuation or blocking of rhythms within the alpha (beta) band. ERD is found during but also before visual stimulation. Two different types of ERD can be differentiated: one short-lasting, localized to occipital areas and involving upper alpha components; the other longer lasting, more widespread, most prominent over parietal areas and maximal for lower alpha components.

AI-based approach to automatic sleep classification.

The primary goal of this paper is to introduce the potential of artificial intelligence (AI) methods to researchers in sleep classification. AI provides learning procedures for the construction of a sleep classifier, prescribing how to combine the observed parameters and how to derive the corresponding decision thresholds. A case study reporting a successful application of an automatic induction of decision trees and of a learning vector quantizer to this domain is presented.

Towards automated sleep classification in infants using symbolic and subsymbolic approaches.

The paper addresses the problem of automatic sleep classification. A special effort is made to find a method of extracting reasonable descriptions of the individual sleep stages from sample measurements of EGG, EMG, EOG, etc., and from a classification of these measurements provided by an expert.

Simultaneous EEG 10 Hz desynchronization and 40 Hz synchronization during finger movements.

Nineteen-channel EEG was recorded with closely spaced electrodes overlaying the left sensorimotor cortex during self-paced, voluntary right finger movements. Three right-handed people served as subjects. The EEG was analysed in the 10 Hz band (10-12 Hz) and in four 40 Hz bands (34-36, 36-38, 38-40, 40-42) by calculation of ERD time courses and ERD maps, whereby a ERD is characterized by a movement-related band power decrease.

Sleep classification in infants based on artificial neural networks.

The study reports on the possibility of classifying sleep stages in infants using an artificial neural network. The polygraphic data from 4 babies aged 6 weeks, 6 months and 1 year recorded over 8 hours were available for classification. From each baby 22 signals were recorded, digitized and stored on an optical disc.