Passive functional mapping guides electrical cortical stimulation for efficient determination of eloquent cortex in epilepsy patients.

Electrical cortical stimulation (ECS) is often used in presurgical evaluation procedures for patients suffering from pharmacoresistant epilepsy. Real-time functional mapping (RTFM) is an alternative brain mapping methodology that can accompany traditional functional mapping approaches like ECS. In this paper, we present a combined RTFM/ECS system that aims to exploit the common ground and the advantages of the two procedures for improved time/effort effectiveness, patients' experience and safety. Using the RTFM and ECS data from four patients who suffer epilepsy, we demonstrate that the RTFM-guided ECS procedure hypothetically reduces the number of electrical stimulations necessary for eloquent cortex detection by 40%.

3-Heptanone as a potential new marker for valproic acid therapy.

Breath gas samples from 27 patients with epilepsy (17 male and 10 female patients; mean age: 9.7 years, median age: 8.2 years, SD: ±4.2 years) were screened via proton transfer reaction mass spectrometry. The patients were treated with valproic acid (VPA) therapy, and blood samples for determination of VPA concentrations were surveyed. All patients showed significantly elevated concentrations of 3-heptanone (C(7)H(14)O) in exhaled breath gas (mean: 14.7 ppb, median: 13.8 ppb SD: ±5.7 ppb). In human breath, several hundred different volatile organic compounds can be detected. In breath of patients with valproic acid monotherapy, an increased concentration of 3-heptanone was measured. The objective of this study was to investigate if serum VPA concentrations correlate with 3-heptanone concentrations in exhaled breath. In conclusion, 3-heptanone in breath gas is significantly elevated in patients treated with the valproic acid, but does not correlate significantly with the VPA concentrations in serum or the daily dose of this drug.

Laboratory PC and Mobile Pocket PC Brain-Computer Interface Architectures.

EEG-based brain-computer interface (BCI) systems convert brain activity into control signals and have been developed for people with severe disabilities to improve their quality of life. A BCI system has to satisfy different demands depending on the application area. A laboratory PC based system allows the flexible design of multiple/single channel feature extraction, classification methods and experimental paradigms. The key advantage of a Pocket PC based BCI approach is its small dimension and battery supply. Hence a mobile BCI system e.g. mounted on a wheelchair can be realized. This study compares and discusses thoroughly the two mentioned approaches.

Correlation Changes of EEG and ECG After Fast Cable CAR Ascents.

In the Eastern Alps in Europe, the Dachstein. massif with a height of almost 3000 m is an ideal location for investigating the effects of changes in altitude on the human body. Within a few minutes, a cable car facilitates an ascent from 1702 m to 2700 m above sea level, where the partial pressure of oxygen is about 550 mmHg (as compared to 760 mmHg at sea level). In this study ten healthy subjects performed a reaction time task at 990 m and 2700 m in altitude. The subjects were instructed to perform a right hand index finger movement as fast as possible after a green light flashed (repeated 50 times). The corresponding electrocardiogram (ECG) and the electroencephalogram (EEG) were recorded. From the ECG heart rate and heart rate variability measures in the time and frequency domain were calculated. An event-related desynchronization/synchronization (ERD/ERS) analysis was performed with the EEG data. Finally, the EEG activity and the ECG parameters were correlated.

How many people are able to operate an EEG-based brain-computer interface (BCI)?

Ninety-nine healthy people participated in a brain-computer interface (BCI) field study conducted at an exposition held in Graz, Austria. Each subject spent 20-30 min on a two-session BCI investigation. The first session consisted of 40 trials conducted without feedback. Then, a subject-specific classifier was set up to provide the subject with feedback, and the second session--40 trials in which the subject had to control a horizontal bar on a computer screen--was conducted. Subjects were instructed to imagine a right-hand movement or a foot movement after a cue stimulus depending on the direction of an arrow. Bipolar electrodes were mounted over the right-hand representation area and over the foot representation area. Classification results achieved with 1) an adaptive autoregressive model (39 subjects) and 2) band power estimation (60 subjects) are presented. Roughly 93% of the subjects were able to achieve classification accuracy above 60% after two sessions of training.

Source localization of induced cortical oscillations during tactile finger stimulation.

We investigated the EEG beta event-related synchronization (ERS) after tactile finger stimulation in three subjects. Prior studies from our group using electrical stimulation and self-paced movement showed a beta rebound within one second after stimulation respectively movement offset. As the tactile-stimulation-data showed a similar ERS behaviour, we extracted the cortical sources for this beta rebound by the linear estimation method in order to see whether the representation areas of different fingers were distinguishable (as is possible with MEG data). Although realistic head models of two subjects were used for the calculations the fingers could not be spatially distinguished. However, regarding the whole spatio-temporal pattern of the ERS for different fingers clear differences can be observed.

Do brain oscillations of different frequencies indicate interaction between cortical areas in humans?

Oscillatory cortical activity in the beta frequency range (14-32 Hz) was investigated in a voluntary movement task using closely-spaced electroencephalogram recordings over the sensorimotor cortex. According to recent studies, short-lasting beta oscillations were observed within the first second after termination of a self-paced finger movement. In this study we show, moreover, that finger movement creates beta bursts not only overlying the hand representation area, but also, at a higher frequency, over neighboring cortical areas representing the foot. The results indicate that, related to the same event, distinct cortical areas can display increased synchronized activity at different frequencies, providing evidence for interaction between the corresponding neuronal networks.

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. The surface laplacian estimates were calculated using spherical splines and cortical current distributions were constructed using the linear estimation method. Both methods yield similar results and reveal a maximal event-related synchronisation over the left sensorimotor area approximately 500-750 ms after termination of movement.

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. It is possible to transfer the potential field given on the outer surface of a spherically shaped volume conductor to an arbitrary inner surface (e.g., to the cortical surface) under consideration of the electrical and geometrical properties of the model. For the application of the proposed method to real-world problems, the coefficients of the series expansion describing the cortical potential distribution are determined by minimizing the squared curvature of the scalp potential field integrated over the scalp surface. Simulation results for distributed sources show that the proposed method is superior to the surface Laplacian method for interelectrode distances below 2.5 cm.

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.

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. (ii) Another beta component started to desynchronize about 1 s prior to movement, recovered very fast and displayed a pronounced post-movement beta synchronization (PMBS) within the first second after movement-offset. This PMBS was found in the frequency band between 12 and 26 Hz. The average percentage power increase at contralateral sensorimotor area was 232% (SD = 82%) for brisk and 265% (SD = 102%) for slow movements. The PMBS was of contralateral dominance and is interpreted as a correlate of active inhibition or idling of the primary motor area following movement execution.

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.

Analysis of cardiorespiratory signals--methodology and applications in infants.

Heart rate variability and thoracal respiratory movements were examined in two babies aged six months during eight hour polysomnographic recordings. Computer-assisted analysis in the time and frequency domain were performed to investigate the mechanisms underlying cardiorespiratory control. Coherence and phase relation between cardiac cycles and respiration were investigated in detail. Both methods demonstrated that during quiet sleep (stage 3/4), the cardiorespiratory coupling was significantly increased as compared to active sleep (REM sleep).