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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
PubMed2006

Synchronization likelihood with explicit time-frequency priors.

Cognitive processing requires integration of information processed simultaneously in spatially distinct areas of the brain. The influence that two brain areas exert on each others activity is usually governed by an unknown function, which is likely to have nonlinear terms. If the functional relationship between activities in different areas is dominated by the nonlinear terms, linear measures of correlation may not detect the statistical interdependency satisfactorily. Therefore, algorithms for detecting nonlinear dependencies may prove invaluable for characterizing the functional coupling in certain neuronal systems, conditions or pathologies. Synchronization likelihood (SL) is a method based on the concept of generalized synchronization and detects nonlinear and linear dependencies between two signals (Stam, C.J., van Dijk, B.W., 2002. Synchronization likelihood: An unbiased measure of generalized synchronization in multivariate data sets. Physica D, 163: 236-241.). SL relies on the detection of simultaneously occurring patterns, which can be complex and widely different in the two signals. Clinical studies applying SL to electro- or magnetoencephalography (EEG/MEG) signals have shown promising results. In previous implementations of the algorithm, however, a number of parameters have lacked a rigorous definition with respect to the time-frequency characteristics of the underlying physiological processes. Here we introduce a rationale for choosing these parameters as a function of the time-frequency content of the patterns of interest. The number of parameters that can be arbitrarily chosen by the user of the SL algorithm is thereby decreased from six to two. Empirical evidence for the advantages of our proposal is given by an application to EEG data of an epileptic seizure and simulations of two unidirectionally coupled Hénon systems.

Algorithms↗
PubMed2006

Resting state oscillatory brain dynamics in Parkinson's disease: an MEG study.

OBJECTIVE: The pathophysiological mechanisms of cognitive dysfunction and dementia in Parkinson's disease (PD) are still poorly understood. Altered resting state oscillatory brain activity may reflect underlying neuropathological changes. The present study using magneto encephalography (MEG) was set up to study differences in the pattern of resting state oscillatory brain activity in groups of demented and non-demented PD patients and healthy, elderly controls. METHODS: The pattern of MEG background oscillatory activity was studied in 13 demented PD patients, 13 non-demented PD patients and 13 healthy controls. Whole head MEG recordings were obtained in the morning in an eyes closed and an eyes open, resting state condition. Relative spectral power was calculated using Fast Fourier Transformation in delta, theta, alpha, beta and gamma frequency bands. RESULTS: In the non-demented PD patients, relative theta power was diffusely increased and beta power concomitantly decreased relative to controls. gamma Power was decreased in central and parietal channels. In the demented PD patients, a diffuse increase in relative delta and to lesser extent theta power and a decrease in relative alpha, beta and to lesser extent gamma power were found in comparison to the non-demented PD group. In addition, reactivity to eye opening was much reduced in the demented PD group. CONCLUSIONS: Parkinson's disease is characterized by a slowing of resting state brain activity involving theta, beta and gamma frequency bands. Dementia in PD is associated with a further slowing of resting state brain activity, additionally involving delta and alpha bands, as well as a reduction in reactivity to eye-opening. SIGNIFICANCE: The differential patterns of slowing of resting state brain activity in demented and non-demented PD patients suggests that, in conjunction with a progression of the pathological changes already present in non-demented patients, additional mechanisms are involved in the development of dementia in PD.

Aged↗
PubMed2006

Magnetoencephalographic evaluation of resting-state functional connectivity in Alzheimer's disease.

Statistical interdependencies between magnetoencephalographic signals recorded over different brain regions may reflect the functional connectivity of the resting-state networks. We investigated topographic characteristics of disturbed resting-state networks in Alzheimer's disease patients in different frequency bands. Whole-head 151-channel MEG was recorded in 18 Alzheimer patients (mean age 72.1 years, SD 5.6; 11 males) and 18 healthy controls (mean age 69.1 years, SD 6.8; 7 males) during a no-task eyes-closed resting state. Pair-wise interdependencies of MEG signals were computed in six frequency bands (delta, theta, alpha1, alpha2, beta and gamma) with the synchronization likelihood (a nonlinear measure) and coherence and grouped into long distance (intra- and interhemispheric) and short distance interactions. In the alpha1 and beta band, Alzheimer patients showed a loss of long distance intrahemispheric interactions, with a focus on left fronto-temporal/parietal connections. Functional connectivity was increased in Alzheimer patients locally in the theta band (centro-parietal regions) and the beta and gamma band (occipito-parietal regions). In the Alzheimer group, positive correlations were found between alpha1, alpha2 and beta band synchronization likelihood and MMSE score. Resting-state functional connectivity in Alzheimer's disease is characterized by specific changes of long and short distance interactions in the theta, alpha1, beta and gamma bands. These changes may reflect loss of anatomical connections and/or reduced central cholinergic activity and could underlie part of the cognitive impairment.

Aged↗
PubMed2004

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.

Artifacts↗
PubMed2004

Detection of very high correlation in the alpha band between temporal regions of the human brain using MEG.

It is generally believed that alpha band (8-12 Hz) electric and magnetic activity in the area of the left and right temporal regions in the human brain are at best poorly correlated. There are no previous reports of very high alpha band correlation between left and right temporal regions by magnetoencephalography (MEG) or electroencephalography (EEG). We present whole head magnetoencephalography (MEG) results that demonstrate that, for temporal channels in the majority of healthy subjects tested, the alpha band signals are highly to very highly correlated and are antiparallel in direction. A correlation as high as -0.97 was found for a limited time in one subject. We suggest that the correlation found may be the consequence of strong direct or indirect coupling between homologue areas in left and right temporal regions rather than a common source. The correlation may provide a valuable index of loss of connectivity in the brain due to disease as well providing valuable insight to brain function and deserves further investigation.

Adult↗
PubMed2003

A neural complexity measure applied to MEG data in Alzheimer's disease.

OBJECTIVE: A measure of neural complexity (C(N)) (Proc. Natl Acad. Sci. USA 91 (1994) 5033) was applied to magnetoencephalography (MEG) data to test the hypothesis that C(N) decreases when information processing in the brain is impaired, as is the case in patients with Alzheimer's Disease (AD). METHODS: One hundred and fifty-one channel MEGs were recorded in 20 AD patients and 20 healthy age-matched controls in a resting condition with eyes open (EO) and eyes closed (EC). Artifact-free epochs of 117 channels were selected for analysis. C(N) and D(2) were computed in different frequency bands, and correlated with the MMSE. RESULTS: The Group x Frequency band interaction was significant for both C(N) and D(2). C(N) was higher in AD, as compared with controls, in the 2-4 and 4-8Hz bands, and D(2) was higher in AD patients in the 14-20 and 20-30Hz bands. The C(N) was higher in the EC condition compared to the EO condition, whereas the D(2) was higher in the EO condition. CONCLUSIONS: The hypothesis of Tononi et al. (Proc. Natl Acad. Sci. USA 91 (1994) 5033) that the neural complexity decreases in AD patients has to be rejected. However, both neural complexity and the correlation dimension did show differences between controls and AD patients which depended on frequency band.

Aged↗
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↗