J.P.A. Verbunt

Altered temporal correlations in parietal alpha and prefrontal theta oscillations in early-stage Alzheimer disease

Encoding and retention of information in memory are associated with a sustained increase in the amplitude of neuronal oscillations for up to several seconds. We reasoned that coordination of oscillatory activity over time might be important for memory and, therefore, that the amplitude modulation of oscillations may be abnormal in Alzheimer disease (AD). To test this hypothesis, we measured magnetoencephalography (MEG) during eyes-closed rest in 19 patients diagnosed with early-stage AD and 16 age-matched control subjects and characterized the autocorrelation structure of ongoing oscillations using detrended fluctuation analysis and an analysis of the life- and waiting-time statistics of oscillation bursts. We found that Alzheimers patients had a strongly reduced incidence of alpha-band oscillation bursts with long life- or waiting-times (< 1 s) over temporo-parietal regions and markedly weaker autocorrelations on long time scales (1–25 seconds). Interestingly, the life- and waiting-times of theta oscillations over medial prefrontal regions were greatly increased. Whereas both temporo-parietal alpha and medial prefrontal theta oscillations are associated with retrieval and retention of information, metabolic and structural deficits in early-stage AD are observed primarily in temporo-parietal areas, suggesting that the enhanced oscillations in medial prefrontal cortex reflect a compensatory mechanism. Together, our results suggest that amplitude modulation of neuronal oscillations is important for cognition and that indices of amplitude dynamics of oscillations may prove useful as neuroimaging biomarkers of early-stage AD.

In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head

In vivo measurements of equivalent resistivities of skull (/spl rho//sub skull/) and brain (/spl rho//sub brain/) are performed for six subjects using an electric impedance tomography (EIT)-based method and realistic models for the head. The classical boundary element method (BEM) formulation for EIT is very time consuming. However, the application of the Sherman-Morrison formula reduces the computation time by a factor of 5. Using an optimal point distribution in the BEM model to optimize its accuracy, decreasing systematic errors of numerical origin, is important because cost functions are shallow. Results demonstrate that /spl rho//sub skull///spl rho//sub brain/ is more likely to be within 20 and 50 rather than equal to the commonly accepted value of 80. The variation in /spl rho//sub brain/ (average = 301 /spl Omega/ /spl middot/ cm, SD = 13%) and /spl rho//sub skull/ (average = 12230 /spl Omega/ /spl middot/ cm, SD = 18%) is decreased by half, when compared with the results using the sphere model, showing that the correction for geometry errors is essential to obtain realistic estimations. However, a factor of 2.4 may still exist between values of /spl rho//sub skull///spl rho//sub brain/ corresponding to different subjects. Earlier results show the necessity of calibrating /spl rho//sub brain/ and /spl rho//sub skull/ by measuring them in vivo for each subject, in order to decrease errors associated with the electroencephalogram inverse problem. We show that the proposed method is suited to this goal.

Magnetoencephalographic analysis of cortical activity in Alzheimer's disease: a pilot study.

OBJECTIVES In the present study, MEG was used to analyze spectral power and reference-free coherence in patients with probable Alzheimers disease (AD). METHODS Sixty-one channel MEG was recorded in 5 AD patients and 5 age-matched controls at rest with eyes open and eyes closed, as well as during the performance of two different mental tasks. Artefact-free epochs were selected for the analysis of power and coherence values in each of 5 4-Hz wide frequency bands ranging from 2 to 22 Hz. RESULTS In AD patients, the absolute low frequency magnetic power was significantly and rather diffusely increased relative to controls with a fronto-central maximum. High frequency power values were significantly decreased over the occipital and temporal areas. Reactivity to eye-opening and mental tasks was reduced in the patient group. Relative to controls, a general decrease of MEG coherence values, including all frequencies analyzed, was found in AD patients. CONCLUSIONS These observations confirm the pattern of changes in spectral power and reactivity known from EEG studies and suggest that coherence decreases in AD patients are widespread and include frequencies outside the alpha band.

Spike cluster analysis in neocortical localization related epilepsy yields clinically significant equivalent source localization results in magnetoencephalogram (MEG)

OBJECTIVE In magnetoencephalogram (MEG) recordings of patients with epilepsy several types of sharp transients with different spatiotemporal distributions are commonly present. Our objective was to develop a computer based method to identify and classify groups of epileptiform spikes, as well as other transients, in order to improve the characterization of irritative areas in the brain of epileptic patients. METHODS MEG data centered on selected spikes were stored in signal matrices of C channels by T time samples. The matrices were normalized and euclidean distances between spike representations in vector space R(CxT) were input to a Wards hierarchical clustering algorithm. RESULTS The method was applied to MEG data from 4 patients with localization-related epilepsy. For each patient, distinct spike subpopulations were found with clearly different topographical field maps. Inverse computations to selected spike subaverages yielded source solutions in agreement with seizure classification and location of structural lesions, if present, on magnetic resonance images. CONCLUSIONS With the proposed method a reliable categorization of epileptiform spikes is obtained, that can be applied in an automatic way. Computation of subaverages of similar spikes enhances the signal-to-noise ratio of spike field maps and allows for more accurate reconstruction of sources generating the epileptiform discharges.

A whole head MEG study of the amplitude-modulation-following response: phase coherence, group delay and dipole source analysis

OBJECTIVE The amplitude-modulation-following response (AMFR) is the frequency component detectable in the electroencephalogram (EEG) or magnetoencephalography (MEG) corresponding to the modulation frequency of an amplitude modulated tone used as a continuous acoustic stimulus. Various properties of the AMFR depend on modulation frequency, suggesting that different generators along the auditory pathway are involved. The present study addresses these issues on the basis of a whole head MEG experiment. METHODS AM tones with modulators in the 40 Hz and 80 Hz range were presented unilaterally to 10 normal hearing subjects. Biomagnetic responses were recorded with a 151 channel MEG system. The data analysis concentrated on the phase coherence of the responses, group delays and the estimated location of underlying equivalent dipole sources. RESULTS MEG AMFR is more reliably detected in the 40 Hz than in the 80 Hz range. Both response amplitude and phase coherence indicate clear bilateral activation over the parietal/temporal region. Dipole source analysis confirms that sources are located in or near the auditory cortex. Group delays at 80 Hz are shorter than at 40 Hz. CONCLUSIONS In both modulation frequency ranges MEG responses are dominated by activity in the auditory cortex, in apparent contrast with EEG data in the literature, pointing to dominant contributions of thalamic sources to the 80 Hz AMFR.

MEG-compatible force sensor

By use of an insulating material we constructed a strain gauge based sensor to measure isometric forces in parallel with magneto-encephalographic recordings (i.e. without interference). The sensor can be used in different geometries to measure force production in different dimensions. Furthermore, it can easily be adapted or modified for specific experimental applications. Finally, on-line processing of the recorded forces, e.g., for the purpose of feedback, can be realized using standard MEG equipment.

The localization of energized coils using MEG sensors: theory and applications

An algorithm is described that localizes a set of simultaneously energized coils using MEG detectors. The algorithm is based on a mathematical model which describes the coils as stationary magnetic dipoles, of which the source time functions are known. It is assumed that the source time functions are orthogonal. It is shown how this a priori knowledge can be used to improve the efficiency of the algorithm. Furthermore, a method is presented to detect bad channels, automatically. The method is useful for continuous or intermittent head position registration during long MEG sessions, to registrate MR and MEG data, and to localize EEG electrodes attached to the head, when EEG and MEG are recorded simultaneously. Experimental data shows that the localization error can smaller than 2 mm.

A theoretical model of the spatial distribution of EEG/MEG for correlated and uncorrelated sources

In this paper a study is made of the relationship between the correlation of EEG and MEG signals and the coherence of brain activity. The quantification of this relationship is complicated by the fact that electrical activity of a current source spreads out in space before it is measured with EEG electrodes or MEG sensors. In this paper a mathematical model is derived which expresses the covariance of the EEG/MEG sensors into the statistics of the sources. When both the volume conductor and the distribution of the sources are spherically symmetric, the spatial covariance can be expressed as a simple series of Legendre polynomials. For the EEG the variance is studied as a function of electrode distance, for several source correlation distances. Due to the large amount of smearing of the skull these functions are hardly different showing that the EEG is not a very sensitive instrument to distinguish between correlated and uncorrelated sources. For the MEG the model is tested experimentally by plotting the coherence as a function of gradiometer distance. It appears that these data are in good agreement with the model.