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Biomedical subjects

G Pfurtscheller

Publications and source records attributed to G Pfurtscheller.

At least 91 records · Page 5Linked to original sources
PubMed1997

Foot and hand area mu rhythms.

Spontaneous EEG can display spatio-temporal patterns of desynchronized or synchronized alpha band activity. Event-related desynchronization (ERD) of rhythms within alpha and lower beta bands is characteristic of activated cortical areas ready to process information or to prepare a movement, while event-related synchronization (ERS) in the same frequency bands can be seen as an electrophysiological correlate of resting or idling cortical areas. EEG was investigated over primary sensorimotor and premotor areas during discrete hand and foot movements. ERD was found over the primary hand area during finger movement and over the primary foot area during toe movement. The former was observed in every subject, the latter was more difficult to find. From these results it can be speculated that each primary sensorimotor area has its own intrinsic rhythm, which becomes desynchronized when the corresponding area is activated. ERS, in the form of an enhanced mu rhythm on electrodes overlying the primary hand area, was observed not only during visual processing but also during foot movement. In both cases, the hand area is not needed to perform a task and, therefore, can be considered to be in an idling state. The supplementary motor area (SMA) also plays an important role in preparation and planning of movement. It is demonstrated that this area also displays rhythmic activity within the alpha band, that is both linearly and non-linearly phase coupled to the intrinsic (mu) rhythm of the primary hand area. With planning and preparation of movement, this SMA rhythm is desynchronized and also the degree of coupling between the two areas decreases.

Electroencephalography↗
PubMed1997

Post-movement EEG synchronization studied with different high resolution methods.

In this paper we present a study of spline surface Laplacian (LP), linear estimation (LE) and analytical deblurring (AD) utilized to improve the spatial resolution of single trial EEG data. AD is a method to reconstruct the potential distribution on the cortical surface. The dependency of AD on the electrode grid size as well as the sensitivity to uncorrelated noise and errors in the volume conductor model are investigated in detail and compared with LP. Finally, all methods (LP,LE and AD) are applied to single trial EEG data recorded in three subjects during voluntary and self-paced extension and flexion movements of the right index finger. In each subject postmovement beta oscillations were found in specific frequency bands. Cortical dipolar source strengths were reconstructed by LE and cortex potentials were estimated with AD. Both results are compared with LP calculated from the scalp EEG. All methods, although having different theoretical basis, yield similar results and reveal a maximal event-related synchronization over the left sensorimotor area approximately 500-875 ms after termination of the movement.

Adult↗
PubMed1997

Effects of handedness on movement-related changes of central beta rhythms.

The effects of handedness on the movement-related changes in beta rhythms (14-30 Hz) in the left and right perirolandic area were analyzed in 12 right-handed and 11 left-handed subjects. The motor task consisted of unilateral brisk or slow self-paced extension of the right or left index finger. The handedness effects were as follows. First, in both handedness groups, the premovement desynchronization of beta rhythms at both hemispheres was greatest before slow movement of the "nondominant" finger, especially at electrodes presumably overlying the MI areas. Second, the lefthanded group showed less desynchronization in both hemispheres during execution of a slow movement than the righthanded group. Third, the postmovement beta synchronization showed a contralateral preponderance which was greater after movements of the nondominant than the "dominant" finger in the righthanded group and was equal for both fingers in the lefthanded group. The results suggest that handedness effects on movement-related changes in central beta rhythms are coupled to movements of the nondominant finger and that their manifestation differs in the pre- and postmovement periods.

Adult↗
PubMed1997

Timing of EEG-based cursor control.

Recent studies show that humans can learn to control the amplitude of electroencephalography (EEG) activity in specific frequency bands over sensorimotor cortex and use it to move a cursor to a target on a computer screen. EEG-based communication could be a valuable new communication and control option for those with severe motor disabilities. Realization of this potential requires detailed knowledge of the characteristic features of EEG control. This study examined the course of EEG control after presentation of a target. At the beginning of each trial, a target appeared at the top or bottom edge of the subject's video screen and 1 sec later a cursor began to move vertically as a function of EEG amplitude in a specific frequency band. In well-trained subjects, this amplitude was high at the time the target appeared and then either remained high (i.e., for a top target) or fell rapidly (i.e., for a bottom target). Target-specific EEG amplitude control began 0.5 sec after the target appeared and appeared to wax and wane with a period of approximately 1 sec until the cursor reached the target (i.e., a hit) or the opposite edge of the screen (i.e., a miss). Accuracy was 90% or greater for each subject. Top-target errors usually occurred later in the trial because of failure to reach and/or maintain sufficiently high amplitude, whereas bottom-target errors usually occurred immediately because of failure to reduce an initially high amplitude quickly enough. The results suggest modifications that could improve performance. These include lengthening the intertrial period, shortening the delay between target appearance and cursor movement, and including time within the trial as a variable in the equation that translates EEG into cursor movement.

Adult↗
PubMed1997

Adaptive autoregressive modeling used for single-trial EEG classification.

An adaptive autoregressive (AAR) model is used for analyzing event-related EEG changes. Such an AAR model is applied to single EEG trials of three subjects, recorded over both sensorimotor areas during imagination of left and right hand movements. It is found that discrimination between both types of motor-imagery is possible using linear discriminant analysis, but the time point for optimal classification is different in each subject. For the estimation of the AAR parameters, the Least-mean-squares and the Recursive-least-squares algorithms are compared. In both methods, the update coefficient plays a key role: it determines the adaptation ratio as well as the estimation accuracy. A new method, based on minimizing the prediction error, is introduced for determining the update coefficient.

Adult↗
PubMed1997

EEG-based communication: evaluation of alternative signal prediction methods.

Individuals can learn to control the amplitude of EEG activity in specific frequency bands over sensorimotor cortex and use it to move a cursor to a target on a computer screen. For one-dimensional (i.e., vertical) cursor movement, a linear equation translates the EEG activity into cursor movement. To translate an individual's EEG control into cursor control as effectively as possible, the intercept in this equation, which determines whether upward or downward movement occurs, should be set so that top and bottom targets are equally accessible. The present study compares alternative methods for using an individual's previous performance to select the intercept for subsequent trials. In offline analyses, five different intercept selection methods were applied to EEG data collected while trained subjects were moving the cursor to targets at the top or bottom edge of the screen. In the first two methods-moving average, and weighted sum-a single intercept was selected for the entire 1-2 sec period of each trial. In the other three methods-blocked moving average, blocked weighted sum, and blocked recursive sum (a variation of the weighted sum)-an intercept was selected for each 200-ms segment of the trial. The results from these methods were compared in regard to their balance between upward and downward movements and their consistency of performance across trials. For all subjects combined, the five methods performed similarly. However, performance across subjects was more consistent for the moving average, blocked moving average, and blocked recursive sum methods than for the weighted sum and blocked weighted sum methods. Due to its consistent performance and its computational simplicity, the moving average method, using the five most recent pairs of top and bottom trials, appears to be the method of choice.

Adult↗
PubMed1996

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 2.5 cm more anterior. Comparison of left and right foot movement revealed a larger post-movement beta synchronization (PMBS) with left foot movement, but no differences concerning the topographical distribution of the PMBS.

Adult↗
PubMed1996

Human cortical 40 Hz rhythm is closely related to EMG rhythmicity.

We recorded cortical neuromagnetic rhythms during self-paced index-finger movements from a subject previously reported to show prominent 40 Hz electroencephalographic activity during motor behavior. The 10 and 20 Hz components of the rolandic mu rhythm were bilaterally suppressed, whereas the contralateral 40 Hz (35-41 Hz) activity was slightly enhanced before both fast and slow movements and strongly enhanced during slow movements. The 40 Hz rhythm originated mainly in the hand motor cortex and was clearly correlated with the rhythmicity of the electromyogram from the extensor muscles, with a systematic time lag. In this subject motor preparation, and especially control of finger movements, may thus be associated with enhanced cortical rhythms near 40 Hz. The coherence of these rhythms with muscular firing patterns likely reflects communication between the sensorimotor cortex and the motor units.

Adult↗
PubMed1996

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. Brisk movements accompanied by a stronger extensor muscle contraction were preceded by larger desynchronization. The onset of mu-rhythm recovery was related to the duration of the extensor EMG burst in both types of movement. The results suggest that both amplitude and duration of the extensor muscle contraction are encoded in the time course of murhythm desynchronization.

Analysis of Variance↗
PubMed1996

Graz brain-computer interface II: towards communication between humans and computers based on online classification of three different EEG patterns.

The paper describes work on the brain--computer interface (BCI). The BCI is designed to help patients with severe motor impairment (e.g. amyotropic lateral sclerosis) to communicate with their environment through wilful modification of their EEG. To establish such a communication channel, two major prerequisites have to be fulfilled: features that reliably describe several distinctive brain states have to be available, and these features must be classified on-line, i.e. on a single-trial basis. The prototype Graz BCI II, which is based on the distinction of three different types of EEG pattern, is described, and results of online and offline classification performance of four subjects are reported. The online results suggest that, in the best case, a classification accuracy of about 60% is reached after only three training sessions. The online results show how selection of specific frequency bands influences the classification performance in single-trial data.

Communication↗
PubMed1996

Dependence of coherence measurements on EEG derivation type.

The impact is reported of different EEG derivation types on short-term changes in the inter-hemispheric coherence between the left and right sensorimotor areas, during the planning and execution of right index finger movements. Data are recorded during an event-related paradigm in which cued index finger movements are made: Event-related coherence analysis is then applied to the monopolar (nose reference) data, as well as different reference-independent derivations such as bipolar, local average reference and source derivation. The results show that inter-hemispheric coherence between sensorimotor areas is dependent on the EEG derivation type. An increase in coherence during movement is found with nose reference and bipolar data, whereas for local average reference and source derivations, low inter-hemispheric coherence is observed, with no change in the coherence during movement. It is concluded that the coherence increase seen with nose reference data is due to an indirect effect of mu rhythm desynchronisation, rather than any increase in synchrony of the mu rhythms themselves. Local average reference and source derivations better reflect the activity of the underlying cortical structures (the mu generating networks), and coherence analysis using these derivations shows that the mu rhythms of left and right hemispheres are not coherent.

Electroencephalography↗
PubMed1996

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. In the upper alpha band, the mu rhythm of the contralateral sensorimotor area is shown to be linearly phase-coupled to rhythmic activity recorded over the SMA. This synchrony between the rhythms decreases during planning and execution of movement when the respective areas become active. In the gamma band, a short-lasting increase in coherence is found between the contralateral sensorimotor area and the SMA prior to movement, indicating possible functional interaction of these areas during the final stages of movement preparation.

Electrodes↗
PubMed1996

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. It was found that after a brisk finger movement the desynchronized beta rhythm displayed a fast recovery and a short-lasting synchronization within 1 sec. This post-movement beta synchronization was maximal over the contralateral hemisphere and localized slightly more anterior to the maximal desynchronization of the hand area mu rhythm. The post-movement beta synchronization is interpreted as a correlate of "idling" motor cortex neurons.

Adult↗
PubMed1996

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. The results demonstrate that hand dominance, handedness and type of movement influence the proportion of pre-movement mu-rhythm desynchronisation in the left and right peri-rolandic area.

Adult↗
PubMed1996

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 teaching input was provided by a medical expert in accordance with the rules of Guilleminault and Souquet. The performance of TBNN is compared with 5 other methods and the results are discussed.

Artificial Intelligence↗
PubMed1996

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. A neural network in form of a learning vector quantizertion (LVQ) with an input dimension of 16 was trained to classify EEG patterns from two electrodes and two time windows. After two training sessions on 2 different days, 4 subjects showed a classification accuracy of 89-100%. For two subjects classification was not possible. These results show that in general movement specific EEG-patterns can be found, classified in real time and used to move a cursor on a monitor to the left or right. On-line EEG classification is necessary when the EEG is used as input signal to a brain computer interface (BCI). Such a BCI can be a help for handicapped people.

Adult↗
PubMed1996

Event-related desynchronization (ERD) and the Dm effect: does alpha desynchronization during encoding predict later recall performance?

Based on previous research which has shown that event-related desynchronization (ERD) in the lower and upper alpha band reflects attentional and semantic processing respectively, the present study examines the hypothesis whether event-related shifts in the two alpha bands are capable of predicting later recall performance. In an incidental memory paradigm, subjects first had to judge the category membership for a set of 96 words. Later, without prior warning, subjects were asked to recall the words. The results show that for good performers, the extent of ERD in the lower alpha band during the semantic encoding for words is significantly larger for remembered as compared to not remembered words, whereas for bad performers the ERD in the upper alpha band is significantly more pronounced. This type of Dm effect is particularly strong over parietal recording sites in both hemispheres. In referring to the proposed interpretation of the lower and upper alpha band, the present findings seem to indicate that in contrast to good performers, bad performers are less attentive or alert during encoding. Event-related potentials (ERPs) also yielded significant Dm effects at parietal recording sites.

Adult↗