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Biomedical subjects

G Pfurtscheller

Publications and source records attributed to G Pfurtscheller.

At least 109 records · Page 6Linked to original sources
PubMed1996

Event-related synchronization (ERS) in the alpha band--an electrophysiological correlate of cortical idling: a review.

EEG desynchronization is a reliable correlate of excited neural structures of activated cortical areas. EEG synchronization within the alpha band may be an electrophysiological correlate of deactivated cortical areas. Such areas are not processing sensory information or motor output and can be considered to be in an idling state. One example of such an idling cortical area is the enhancement of mu rhythms in the primary hand area during visual processing or during foot movement. In both circumstances, the neurons in the hand area are not needed for visual processing or preparation for foot movement. As a result of this, an enhanced hand area mu rhythm can be observed.

Alpha Rhythm↗
PubMed1996

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 < 0.21 s) and 80 slow (movement time 1.3-2.1 s) self-paced extensions of their left or right index finger. Beta-band power attenuation in the preparatory period (2.0-0.5 s before movement onset) was larger in the contralateral hemisphere in both types of movement and similar for both fingers. In the 0.4-s period before the onset of extensor muscle contraction, right-finger movements only showed a significant contralateral preponderance of beta-ERD. During movement an anterior ERD predominance in the right sensorimotor hand area and a widespread ERD in the left sensorimotor area was found for both fingers. The recovery and rebound of beta-rhythms showed contralateral preponderance which was expressed more in the right hemisphere, especially after left-finger movements. The results suggest that the dynamics of premovement desynchronisation and postmovement synchronisation of central beta-rhythms is related to hand dominance.

Adult↗
PubMed1996

Brainstem auditory evoked potentials in respiratory insufficiency following encephalitis.

Brainstem auditory evoked potentials (BAEPs) were recorded in 14 artificially ventilated patients (12 males, 2 females; mean age 33.3 +/- 16.3 years, range 18-67) with respiratory insufficiency resulting from severe inflammatory encephalopathies. The results were compared with those of 17 healthy volunteers (13 males, 4 females; mean age 27.4 +/- 5.3 years, range 21-45). BAEPs in the study patients showed prolonged interpeak latencies (I-III, I-V, III-V, IV-V) and delayed absolute latencies of waves I, II, III, and V at least on one side. Because the auditory pathways are in the near vicinity of the respiratory control centers in the brainstem, the electrophysiologic abnormalities of wave III and the IV/V complex may be a reflection of the disturbed central control of ventilation.

Acoustic Stimulation↗
PubMed1995

Desynchronization and recovery of beta rhythms during brisk and slow self-paced finger movements in man.

Event-related desynchronization (ERD) and recovery of EEG beta rhythms (15-26 Hz) were studied during slow and brisk self-paced index finger extension and flexion. beta rhythms started to recover earlier in brisk movements. Brisk movements showed no correlation between duration of EMG burst in the extensor muscle and the latency of recovery whereas slow movements did. In contrast to beta-ERD which was widespread, the recovery and rebound of beta rhythms occurred in a circumscribed focus close to the hand MI area.

Adult↗
PubMed1995

Application of the correlation integral to respiratory data of infants during REM sleep.

Non-linear time sequence analysis has been performed on infant sleep measurement data in order to obtain more information about the respiratory processes. As a first step, respiration data during REM sleep were analysed with methods from non-linear dynamics, especially, the correlation integral and the slope of its log-log plot, representing the correlation dimension. Before calculation of the correlation integral, a special kind of filtering has to be applied to the data. This filtering algorithm is a state space and singular value decomposition-based noise reduction method, and it is used to separate the noise and signal subspaces. The dynamics of a signal (in our case data from the respiratory process) and its degrees of freedom can be characterised by the correlation integral and by the correlation dimension, respectively. The main result of this study is that the highly irregular-looking breathing patterns during REM sleep could be described by a deterministic system, and finally the physiological significance of this finding is discussed.

Electroencephalography↗
PubMed1995

Discrimination between phase-locked and non-phase-locked event-related EEG activity.

Differentiation between phase-locked and non-phase-locked event-related EEG activity is an important task in the evaluation of event-related EEG activity. Event-related changes of EEG activity such as event-related desynchronization (ERD) or event-related synchronization (ERS) can be quantified by either instantaneous band power or intertrial variance calculations. In the former case the ERD or ERS can be masked by an event-related potential while in the latter it is not. Examples from sensory stimulation and movement experiments, where the ERD (ERS) is calculated by both methods, are shown and discussed.

Alpha Rhythm↗
PubMed1995

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. Besides investigating the evolution of power spectra, time courses of peak frequency, bandwidth and power of alpha (mu) and beta rhythms are traced. The method is applied to EEG recorded over the primary motor area during self-paced finger movements.

Electroencephalography↗
PubMed1995

The impact of jejunal transplant peristalsis on enteric flora.

The importance of phase III of the migrating myoelectric complex (MMC) for homeostasis of enteric flora is well documented. The goal of this study was to evaluate in an isogeneic rat model the effect of MMC changes on the self-purging capacity of the jejunal graft. The proximal 25% of the entire jejunoileum of Lewis rats was transplanted orthotopically. Electrodes were then fixed to the graft. Native bowel of five rats and five rats with analogue jejunal segmentation served as controls. Myoelectric recordings were carried out until day 21, when animals were killed for bacteriologic analysis of the segments analyzed myoelectrically and the of neighboring gut. MMCs were observed in all animals during all recordings. Phase III was irregular in transplants because of long-lasting periods of phase III absence alternating with phase III occurring more frequently. The variation coefficient of phase III periodicity calculated for grafts was 48.74, for native bowel 14.79, and for segmented jejunum 22.9. Enteric flora found in all specimens consisted of colonic-like microorganisms. Titers of microorganisms in grafts did not differ from control segments. These findings show that phase III periodicity is severely altered in jejunal grafts. Homeostasis of enteric flora, however, is not influenced by the transplant procedure.

Animals↗
PubMed1995

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.

Brain Mapping↗
PubMed1994

Visualization of sensorimotor areas involved in preparation for hand movement based on classification of mu and central beta rhythms in single EEG trials in man.

It is well known that mu and central beta rhythms start to desynchronize > 1 s before active hand or finger movement. To investigate whether the same cortical areas are involved in desynchronization of mu and central beta rhythms, 56-channel EEG recordings were made during right- and left-finger flexions in three normal subjects. The event-related desynchronization (ERD) was quantified in single EEG trials and classified by the Distinction Sensitive Learning Vector Quantization (DSLVQ) algorithm. This DSLVQ selects the most relevant features (electrode positions) for discrimination between the preparatory state for left- and right-finger movements. It was found that the most important electrode positions were close to the primary hand area. However, in all three subjects the focus of the central beta ERD was slightly anterior to the focus of mu desynchronization. This can be interpreted that different neural networks are involved in the generation of mu and central beta rhythms.

Electroencephalography↗
PubMed1994

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. This phasic synchronization of mu waves was circumscribed and found at electrodes overlying both cortical hand areas. It is speculated, that this ERS represents a short lasting 'idling state' of hand area neurons when other body parts are moved.

Adult↗
PubMed1994

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.

Artificial Intelligence↗
PubMed1994

Calculation of event-related coherence--a new method to study short-lasting coupling between brain areas.

This article deals with the estimation of event-related coherence (ERCoh) and its application to the planning and execution of self-paced index finger movement. ERCoh estimation complements the event-related desynchronization (ERD) measurements of rhythms within the alpha band. ERCoh yields information of the functional relationships between different brain areas as a function of time. The time resolution is 125 msec. Before movement onset a contralateral ERCoh increase was found between premotor and motor areas. This coherence increase was accompanied by an ERCoh decrease in parallel to the ERD over the contralateral centro-temporal areas. During movement, the ERD became bilaterally symmetrical. Simultaneously, interhemispheric coherence between contralateral and ipsilateral sensori-motor areas increased.

Brain↗
PubMed1994

Source localization using event-related desynchronization (ERD) within the alpha band.

Voluntary finger movements result in a maximal ERD in the 10-12 Hz band close to electrodes C3 and C4, overlying the sensorimotor hand areas. This ERD focus is not very pronounced with EEG data recorded against a common reference electrode (monopolar recording). After transformation of the raw data using common average, local average and weighted average reference and the Hjorth method, respectively, the ERD becomes enhanced over electrodes C3 or C4. Movement-related EEG data were studied with 17, 19, 30 and 56 electrode montages using large and small interelectrode distances. The best focused ERD was obtained with a 56 electrode montage with small interelectrode distances and local average reference data.

Alpha Rhythm↗
PubMed1994

Myoelectric activity during small bowel allograft rejection.

The effect of rejection on myoelectric activity of an orthotopically transplanted small intestinal segment (group I, N = 14) was studied. Electrodes were placed on grafts and recipient small bowel. Isografts (group II, N = 5) and native bowel (group III, N = 5) served as controls. The first morphological signs of rejection were seen on day 6 and steadily progressed until day 11, when the cellular infiltrate involved all layers of the bowel wall. Slow-wave frequencies remained unchanged throughout the observation period. No difference was detectable between grafts (group I: 31.9 +/- 1.65; group II: 31.36 +/- 0.7) and native bowel after transection (group I: 32.16 +/- 1.78; group II: 31.50 +/- 1.01), which was different (P = 0.0001) from intact bowel of group III animals (38.4 +/- 0.81). Irregular MMCs were detectable in grafts from day 5 on and replaced after food intake by random spiking activities. At day 8, spiking activities disappeared in allografts, which showed a still preserved mucosal architecture, while slow-wave activities continued. These findings demonstrate that intestinal allografts during rejection develop paralysis before mucosal destruction is established, which might be of clinical relevance.

Action Potentials↗
PubMed1994

Neural network based classification of non-averaged event-related EEG responses.

Classification of non-averaged task-related EEG responses with different types of classifier, including self-organising feature map and learning vector quantiser, K-mean, back-propagation and a combination of the last two, is reported. EEG data are collected from approximately one second periods prior to movement of the right or left index finger. A cue stimulus indicating which hand to use is employed. Feature vectors are formed by concatenating spatial information from different EEG electrodes and temporal information from different time incidents during the planning of hand movement. Power values of the most reactive frequencies within the extended alpha-band (5-16 Hz) are used as features. The features are derived from an autoregressive model fitted to the EEG signals. The performance of the classifiers and their ability to learn and generalise is tested with 200 arbitrarily selected event-related EEG data from a normal subject. Classification accuracies as high as 85-90% are achieved with the methods described here. A comparison of the classifiers is made.

Algorithms↗
PubMed1994

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. Single-trial data from 8 electrodes, 3 frequency bands and 4 time points within a 1 sec window were subject to a classification task. It was found that, based on single EEG trials, the data from the 4 movements could be differentiated with an accuracy of 70% when alpha and gamma band activity were used but only with 58% in the case of the alpha band activity alone. This shows that the gamma band activity or 40 Hz EEG is strongly related to planning of a specific movement and therefore, improves the accuracy of classification significantly.

Brain↗