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Biomedical subjects

B W van Dijk

Publications and source records attributed to B W van Dijk.

At least 19 recordsLinked to original sources
PubMed2001

The localization of spontaneous brain activity: first results in patients with cerebral tumors.

OBJECTIVE: From EEG studies, it is known that structural brain lesions are accompanied by abnormal rhythmic electric activity. With the better spatial resolution of MEG, MEG dipole analysis can extend the knowledge based on EEG power spectra. This study presents the first results of a completely automatic analysis method applied to spontaneous MEG. METHODS: Spontaneous MEG data of 5 patients with cerebral brain tumors and 4 controls were collected using a whole-head MEG system. Signals were bandpass-filtered with cut-off frequencies according to standard EEG bands. A moving dipole model was fitted to samples with at least twice the average sample power. Dipoles explaining 90% or more of the magnetic variance were projected onto a matched MR scan. RESULTS: In controls, dipole distributions are symmetrical with respect to the mid-sagittal plane whereas distributions in patients often are asymmetrical to it. Dipoles describing gamma activity were located contralateral, and dipoles describing delta and theta activity were located ipsilateral to lesions. CONCLUSIONS: The automatic method gives plausible 3-dimensional information about generator foci of abnormal slow waves and other rhythms with respect to lesion foci and thereby adds physiological knowledge to that derived from EEG power spectra.

Adult↗
PubMed2000

Self-organized dynamics in plastic neural networks: bistability and coherence.

In this paper, we study the combined dynamics of the neural activity and the synaptic efficiency changes in a fully connected network of biologically realistic neurons with simple synaptic plasticity dynamics including both potentiation and depression. Using a mean-field of technique, we analyzed the equilibrium states of neural networks with dynamic synaptic connections and found a class of bistable networks. For this class of networks, one of the stable equilibrium states shows strong connectivity and coherent responses to external input. In the other stable equilibrium, the network is loosely connected and responds non coherently to external input. Transitions between the two states can be achieved by positively or negatively correlated external inputs. Such networks can therefore switch between their phases according to the statistical properties of the external input. Non-coherent input can only "rcad" the state of the network, while a correlated one can change its state. We speculate that this property, specific for plastic neural networks, can give a clue to understand fully unsupervised learning models.

Animals↗
PubMed2000

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 Alzheimer's 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.

Aged↗
PubMed2000

The application of electrical impedance tomography to reduce systematic errors in the EEG inverse problem--a simulation study.

In this paper we propose a new method, using the principles of electrical impedance tomography (EIT), to correct for the systematic errors in the inverse problem (IP) of electroencephalography (EEG) that arise from the wrong specification of the electrical conductivities of the head compartments. By injecting known currents into pairs of electrodes and measuring the resulting potential differences recorded from the other electrodes, the equivalent conductivities of brain (sigma3), skull (sigma2) and scalp (sigma1) can be estimated. Since the geometry of the head is assumed to be known, the electrical conductivities remain as the only unknown parameters to be estimated. These conductivities can then be used in the inverse problem of EEG. The simulations performed in this study, using a three-layer sphere to model the head, prove the feasibility of the method, theoretically. Even in the presence of simulated noise with a value of signal-to-noise ratio (SNR) equal to 10, estimations of the electrical conductivities within 5% of the true values were obtained. Simulations showed the existence of a strong relation between errors in the skull thickness and the EIT estimated conductivities. If the skull thickness is wrongly specified, for example overestimated by a factor of two, the conductivity determined by EIT is also overestimated by a factor of two. Simulations showed that this compensation effect also works in the inverse problem of EEG. Application of the proposed method reduces systematic errors in the dipole localization, up to an amount of 1 cm. However it proved to be ineffective to decrease the dipole strength error.

Brain↗
PubMed1997

Coherency and connectivity in oscillating neural networks: linear partialization analysis.

This paper studies the relation between the functional synaptic connections between two artificial neural networks and the correlation of their spiking activities. The model neurons had realistic non-oscillatory dynamic properties and the networks showed oscillatory behavior as a result of their internal synaptic connectivity. We found that both excitation and inhibition cause phase locking of the oscillating activities. When the two networks excite each other the oscillations synchronize with zero phase lag, whereas mutual inhibition between the networks resulted in an anti-phase (half period phase difference) synchronization. Correlations between the activities of the two networks can also be caused by correlated external inputs driving the systems (common input). Our analysis shows that when the networks exhibit oscillatory behavior and the rate of the common input is smaller than a characteristic network oscillator frequency, the cross-correlation functions between the activities of two systems still carry information about the mutual synaptic connectivity. This information can be retrieved with linear partialization, removing the influence of the common input. We further explored the network responses to periodic external input. We found that when the input is of a frequency smaller than a certain threshold, the network responds with bursts at the same frequency as the input. Above the threshold, the network responds with a fraction of the input frequency. This frequency threshold, characterizing the oscillatory properties of the network, is also found to determine the limit to which linear partialization works.

Computer Simulation↗
PubMed1994

Non-linear dynamics of columns of cat visual cortex revealed by simulation and experiment.

Correlation images were derived from simultaneous recordings of 12 signals representing the synaptic activity at different layers of a column in cat visual cortex (area 18) and 12 signals representing the local average spiking activity at the same locations. Because the ongoing activity and the activity evoked by stroboscopic flashes yielded the same correlation image, ongoing activity is caused by an input to a column similar to flash-evoked activity and is thus not endogenous. Moving bar stimuli evoked bursts of oscillations (25-75 Hz band) in the correlation image. The rhythm of these oscillations was not related to any frequency component in the stimulus. In all correlation images we observed that synaptic activity in one layer resulted in simultaneous spiking activity in all layers with latency differences smaller than 2 ms (the sample interval used). Similar behaviour was observed in a simulation experiment where we 'realistically' modelled one column of visual cortex with 1000 three-compartmental neurons in 11 functional layers. When such a model column was tuned to yield a stable and excitable system with low ongoing activity, activation of any of the layers caused simultaneous activity in all 11 layers. Both the simulation and the experimental results suggest that a column can be regarded as a basic processing element sending the same information over all its outputs to other columns within the same cortical region, other visual areas and subcortical structures.

Animals↗
PubMed1993

Contour from motion processing occurs in primary visual cortex.

Relative motion is one of the most salient cues for segmentation of a visual scene into separate objects. This is illustrated by the vivid contours that are perceived when random dot patterns move in different directions. Once motion is halted in such displays the segmentation contours disappear. This makes random dot patterns ideal for the study of contour from motion processing in isolation. Contour from motion processing obviously relies on direction-selective neurons, which are found in many visual cortical areas. It is, however, largely unknown at what level of processing their signals interact to serve the global process of motion-based image segmentation. To answer this question, we recorded visually evoked potentials, both in man and in awake monkey, to a stimulus specifically designed to signal the presence of neuronal activity related to contour from motion processing. We report here that response components specific to contour from motion were elicited only when the stimulus yielded a contour percept. In awake monkey, the sources of these components were located within the supra- and infra-granular layers of primary visual cortex. We conclude that V1 is involved in image segmentation processing.

Animals↗
PubMed1993

Motion-onset visual-evoked potentials as a function of retinal eccentricity in man.

Visual-evoked potentials were elicited by the motion-onset of a black-and-white square-wave grating of 2.4 cycles/deg that drifted from right to left at a velocity of 3 deg/s. The center of the 2 x 2 deg stimulus field was binocularly viewed either foveally or at eccentricities of 6, 12, or 20 deg in the lower visual field along the vertical meridian. Peak-to-peak amplitudes P1-N2 and N2-P2 were found to decrease non-linearly as a function of eccentricity. The VEP-amplitudes were standardized by setting each foveal value to 100%, and a relative measure was derived for peripheral values given by the ratio of the peripheral to the foveal values. The decrease of the relative VEP-values with eccentricity was significantly smaller than that of the relative cortical magnification factor of striate cortex in man, whereas it agreed fairly well with that of the relative point-image size of the area MT in Macaque monkey. In this respect, the motion-onset VEP is distinct from the pattern-reversal VEP, the amplitude of which decreases much more rapidly with retinal eccentricity; hence, it may involve different generating structures of the brain.

Adolescent↗
PubMed1992

Topography of occipital EEG-reduction upon visual stimulation.

Visual stimuli were designed to drive a high proportion of the neurons in restricted parts of the human visual cortex. These stimuli were used to examine changes in the ongoing EEG during visual stimulation. The topographic organization of these changes was studied. It was found that the EEG from those parts of the cortex that are exposed to the stimulus is strongly reduced in amplitude. This stimulus dependency is indicative that cortical processing results itself in a reduction of the ongoing EEG, presumably due to desynchronization of neurons. The method shows that ongoing EEG can be used for functional mapping of cortical areas and is therefore valuable in situations where stimulus locked activity can not be measured.

Brain Mapping↗
PubMed1992

Confidence limits for the parameter estimation in the dipole localization method on the basis of spatial correlation of background EEG.

A new residual function in the inverse problem of equivalent dipole localization methods is proposed which is based on the spatial correlation of the background EEG. This residual has the advantage that it allows the calculation of confidence limits for dipole model parameters. The method was applied to VEP data, and it was studied how the localization precision depends on the recording time of the EEG. It was found that the tangential position of an equivalent dipole can be located at 99% confidence in a region of the order 7 x 7mm for a head radius of 10cm, while the 99% confidence interval of the depth estimate is approximately 1cm, with a recording time of 20 minutes. It was also observed that an EEG recording time of more than 10-15 minutes is needed to obtain stable localization precision estimates.

Brain↗
PubMed1991

Visual stimulation reduces EEG activity in man.

Data are presented which show that background electric activity of the human brain is reduced by visual stimulation. Occipital EEG amplitude decreases 5-15% for all frequencies analyzed (0.2-40 Hz) upon pattern stimulation. The reduction is stimulus-specific, i.e. is the strongest for stimuli that activate a large number of visual cortical neurons.

Electroencephalography↗
PubMed1991

Color opponency in cone-driven horizontal cells in carp retina. Aspecific pathways between cones and horizontal cells.

The spectral and dynamic properties of cone-driven horizontal cells in carp retina were evaluated with silent substitution stimuli and/or saturating background illumination. The aim of this study was to describe the wiring underlying the spectral sensitivity of these cells. We will present electrophysiological data that indicate that all cone-driven horizontal cell types receive input from all spectral cone types, and we will present evidence that all cone-driven horizontal cell types feedback to all spectral cone types. These two findings are the basis for a model for the spectral and dynamic behavior of all cone-driven horizontal cells in carp retina. The model can account for the spectral as well as the dynamic behavior of the horizontal cells. It will be shown that the strength of the feedforward and feedback pathways between a horizontal cell and a particular spectral cone type are roughly proportional. This model is in sharp contrast to the Stell model, where the spectral behavior of the three horizontal cell types is explained by a cascade of feedforward and feedback pathways between cones and horizontal cells. The Stell model accounts for the spectral but not for the dynamic behavior of the horizontal cells.

Animals↗
PubMed1989

Lateral feedback from monophasic horizontal cells to cones in carp retina. I. Experiments.

The spatial and color coding of the monophasic horizontal cells were studied in light- and dark-adapted retinae. Slit displacement experiments revealed differences in integration area for the different cone inputs of the monophasic horizontal cells. The integration area measured with a 670-nm stimulus was larger than that measured with a 570-nm stimulus. Experiments in which the diameter of the test spot was varied, however, revealed at high stimulus intensities a larger summation area for 520-nm stimuli than for 670-nm stimuli. The reverse was found for low stimulus intensities. To investigate whether these differences were due to interaction between the various cone inputs to the monophasic horizontal cell, adaptation experiments were performed. It was found that the various cone inputs were not independent. Finally, some mechanisms for the spatial and color coding will be discussed.

Animals↗
PubMed1989

Lateral feedback from monophasic horizontal cells to cones in carp retina. II. A quantitative model.

About half of the monophasic horizontal cells in carp retina receive input from both red- and green-sensitive cones. Since the horizontal cells feed back to cones, the color and feedback pathways result in wavelength- and intensity-dependent changes of the dynamics and of the receptive field amplitude profile of the horizontal cell responses. In this paper we present a quantitative model that describes adequately the color and spatial coding and the dynamics of the responses from monophasic horizontal cells in carp. Lateral feedback plays a distinct role in this model.

Animals↗
PubMed1987

Spatial patterns of visual cortical fast EEG during conditioned reflex in a rhesus monkey.

A preliminary assay was made of the existence of time-space coherence patterns of fast EEG activity in the visual cortex of a Rhesus monkey. The primary intent of the present study was to evaluate the similarities and differences in relation to the olfactory bulb, where such coherences have been described and have been demonstrated to be associated with behaviour. Segments 1.5 s in duration were recorded simultaneously without averaging from 16 to 35 subdural electrodes fixed over the left occipital lobe in an array 3.6 cm X 2.8 cm. Each segment was taken during the delivery of a visual conditioned stimulus (CS) and the performance of a conditioned response (CR) by a well-trained Rhesus monkey. The EEGs appeared chaotic with irregular bursts lasting 75-200 ms, resembling those in the olfactory EEG but with lower peak frequencies. Fourier spectra showed broad distributions of power resembling '1/f noise' with multiple peaks in the range of 20-40 Hz. Time intervals were selected where coherent activity seemed to be present at a number of electrodes. A dominant component waveform that was common to all channels was extracted by principal components analysis (PCA) of each segment. The distribution of the power of this component across the electrodes (the factor loadings) was used to describe the spatial pattern of the coherent cortical activity. Statistical analyses suggested that different patterns could be associated to the CS and the CR, as has been found in the olfactory system. These patterns remained stable over a 6 week recording interval. The patterns can be better discriminated, when the factor loadings of each channel are normalized to zero mean and unit variance, to discard a basic pattern of power distribution, which may reflect anatomical and electrode positioning factors that are related to behavioral information processing by the cortex. The wide spatial distribution of the common patterns found suggests that EEG patterns that manifest differing states of the visual cortex may also be accessible with scalp electrodes.

Animals↗