Biomedical subjects

B W Van Dijk

Publications and source records attributed to B W Van Dijk.

6 recordsLinked to original sources

PubMed2001

The use of an MEG device as 3D digitizer and motion monitoring system.

An algorithm is described that localizes a set of simultaneously activated coils using MEG detectors. These coil positions are used for continuous or intermittent head position registration during long MEG sessions, to coregistrate MR and MEG data and to localize EEG electrodes attached to the scalp, when EEG and MEG are recorded simultaneously. The algorithm is based on a mathematical model in which the coils are described as stationary magnetic dipoles with known source time functions. This knowledge makes it possible to detect and remove bad channels automatically. It is also assumed that the source time functions are orthogonal. Therefore, the localization problem splits into independent localization problems. for each coil. The method is validated in a phantom experiment, where the relative coil positions were known. From this experiment it is found that the average error is 0.25 cm. An error of 0.23 cm was found in an experiment where 64 electrode positions were measured four times independently. Examples of the applications of the method are presented. Our method eliminates the use of an external 3D digitizer and maps the MEG directly onto other modalities. This is not only a practical advantage, but it also reduces the gross registration error. Furthermore, head motions can be monitored and MEG data can be corrected for these motions.

Algorithms↗

PubMed2001

The localization of spontaneous brain activity: an efficient way to analyze large data sets.

An efficient solution is presented of the problem to localize the electric generators of spontaneous magnetoencephalography (MEG) and electroencephalography (EEG) data for large data sets. When a data set contains more than 100,000 samples standard methods fail or become impractical. The method presented here is useful, for example, for the localization of (pathological) brain rhythms or the analysis of single-trial data. The problem is defined as finding the good fitting dipoles using the single-dipole model applied on each time sample. First, the data is bandpass filtered to select the rhythm of interest. Next, the empirical relationship between data power and probability of a dipole with a high goodness of fit (g.o.f.) is used to preselect data points. Then a global search algorithm is applied, based on precomputed lead fields on a fixed grid, to obtain a good initial guess for the nonlinear dipole search. Finally, the dipole search is applied on those samples that have a low initial guess error. In a group of five patients, it is found that 50% of the dipoles with a g.o.f. of at least 90% can be found by disregarding 90% of the data samples. Those dipoles can be found efficiently by disregarding all sample points with an initial guess relative residual error of 15% or lower. Finally, a simple empirical expression is found for the optimal mesh size of the global search grid. The method is completely automatic and makes it possible to study simple generators of large MEG and EEG data sets on a routine basis.

Algorithms↗

PubMed1998

The accuracy of localizing equivalent dipoles and the spatio-temporal correlations of background EEG.

For the inverse problem of equivalent dipole localization, a new residual function was proposed which is based on spatio-temporal correlation of background electroencephalogram (EEG). This residual has the advantage that it allows the calculation of a confidence region for estimated dipole parameters. This method was applied to two sets of visual evoked potential (VEP) data. The localization was compared by using the volume of the confidence region. The outcome of the equivalent dipole localization was compared for three different residual functions: 1) least square; 2) based on spatial correlations in the background EEG; and 3) the proposed new function which is based on spatial and temporal correlations in the background EEG. It was found that the proposed residual function leads us to the highest accuracy and the fastest convergence in the equivalent dipole localization and that even for two-dipole localization, the present method yields more accurate solutions with less iterations than the conventional methods.

Algorithms↗

PubMed1994

Organization of contour from motion processing in primate visual cortex.

A major objective of visual processing is the segmentation of the scene into separate objects. Relative motion is one of the most salient segmentation cues. In man and monkey, we recorded visually evoked potentials to a stimulus, designed to signal the presence of relative motion processing. Relative motion specific response components were only elicited when human observers perceive contours from relative motion. Equivalent dipole source localization of the responses indicated the involvement of primary visual cortex in man. This was corroborated by intracortical recordings in awake monkey, where sources of the specific components are located within the supra- and infragranular layers of primary visual cortex. It is concluded that V1 does not merely provide an input stage to contour from motion processing, but that segmentation information, based on relative motion, is present at this early cortical level.

Animals↗

PubMed1992

Texture segregation is processed by primary visual cortex in man and monkey. Evidence from VEP experiments.

We investigated whether the process of texture segregation can be allocated to a specific visual cortical area. We designed a stimulus to reveal the presence of a mechanism, which is specifically sensitive to a checkerboard, that is solely defined by textures segregating due to orientation differences of the constituting line segments. We recorded evoked potentials to this stimulus in man and awake monkey. A difference component, signalling texture segregation sensitivity, could be recorded from both types of subjects. Its presence depended on the spatial extent of the textures, in a manner correlating with the perceptibility of the checkerboard. This difference response could be localized in primary visual cortex by means of equivalent dipole estimations.

Animals↗

PubMed1990

Interaction between the soma and the axon terminal of horizontal cells in carp retina.

In teleost retina, the receptive fields of horizontal cell axon terminals have a larger space constant than the receptive fields of the horizontal cell somata. Generally this difference in receptive field size is attributed to the cell coupling which is assumed to be stronger in the horizontal axon terminal network than in the horizontal cell soma network. The axon terminals are displaced with respect to the cell bodies. In this paper we show, using a simple simulated horizontal cell (HC) network that under the condition that the displacements are randomly distributed the difference in receptive field size between the somata and the axon terminals may be a direct consequence of this displacement. We also show that in that case it should be expected that dopamine has different actions on the somata than on the axon terminals.

Animals↗