Biomedical subjects

Wim van Drongelen

Publications and source records attributed to Wim van Drongelen.

5 recordsLinked to original sources

PubMed2006

Role of persistent sodium current in bursting activity of mouse neocortical networks in vitro.

Most types of electrographic epileptiform activity can be characterized by isolated or repetitive bursts in brain electrical activity. This observation is our motivation to determine mechanisms that underlie bursting behavior of neuronal networks. Here we show that the persistent sodium (Na(P)) current in mouse neocortical slices is associated with cellular bursting and our data suggest that these cells are capable of driving networks into a bursting state. This conclusion is supported by the following observations. 1) Both low concentrations of tetrodotoxin (TTX) and riluzole reduce and eventually stop network bursting while they simultaneously abolish intrinsic bursting properties and sensitivity levels to electrical stimulation in individual intrinsically bursting cells. 2) The sensitivity levels of regular spiking neurons are not significantly affected by riluzole or TTX at the termination of network bursting. 3) Propagation of cellular bursting in a neuronal network depended on excitatory connectivity and disappeared on bath application of CNQX (20 microM) + CPP (10 microM). 4) Voltage-clamp measurements show that riluzole (20 microM) and very low concentrations of TTX (50 nM) attenuate Na(P) currents in the neural membrane within a 1-min interval after bath application of the drug. 5) Recordings of synaptic activity demonstrate that riluzole at this concentration does not affect synaptic properties. 6) Simulations with a neocortical network model including different types of pyramidal cells, inhibitory interneurons, neurons with and without Na(P) currents, and recurrent excitation confirm the essence of our experimental observations that Na(P) conductance can be a critical factor sustaining slow population bursting.

Animals↗

PubMed2006

A cortical potential imaging study from simultaneous extra- and intracranial electrical recordings by means of the finite element method.

In the present study, we have validated the cortical potential imaging (CPI) technique for estimating cortical potentials from scalp EEG using simultaneously recorded electrocorticogram (ECoG) in the presence of strong local inhomogeneity, i.e., Silastic ECoG grid(s). The finite element method (FEM) was used to model the realistic postoperative head volume conductor, which includes the scalp, skull, cerebrospinal fluid (CSF) and brain, as well as the Silastic ECoG grid(s) implanted during the surgical evaluation in epilepsy patients, from the co-registered magnetic resonance (MR) and computer tomography (CT) images. A series of computer simulations were conducted to evaluate the present FEM-based CPI technique and to assess the effect of the Silastic ECoG grid on the scalp EEG forward solutions. The present simulation results show that the Silastic ECoG grid has substantial influence on the scalp potential forward solution due to the distortion of current pathways in the presence of the extremely low conductive materials. On the other hand, its influence on the estimated cortical potential distribution is much less than that on the scalp potential distribution. With appropriate numerical modeling and inverse estimation techniques, we have demonstrated the feasibility of estimating the cortical potentials from the scalp EEG with the implanted Silastic ECoG gird(s), in both computer simulations and in human experimentation. In an epilepsy patient undergoing surgical evaluation, the cortical potentials were reconstructed from the simultaneously recorded scalp EEG, in which main features of spatial patterns during interictal spike were preserved and over 0.75 correlation coefficient value was obtained between the recorded and estimated cortical potentials. The FEM-based CPI technique provides a means of connecting the simultaneous recorded ECoG and the scalp EEG and promises to become an effective tool to evaluate and validate CPI techniques using clinic data.

Algorithms↗

PubMed2005

Emergent epileptiform activity in neural networks with weak excitatory synapses.

Brain electrical activity recorded during an epileptic seizure is frequently associated with rhythmic discharges in cortical networks. Current opinion in clinical neurophysiology is that strongly coupled networks and cellular bursting are prerequisites for the generation of epileptiform activity. Contrary to expectations, we found that weakly coupled cortical networks can create synchronized cellular activity and seizure-like bursting. Evaluation of a range of synaptic parameters in a detailed computational model revealed that seizure-like activity occurs when the excitatory synapses are weakened. Guided by this observation, we confirmed experimentally that, in mouse neocortical slices, a pharmacological reduction of excitatory synaptic transmission elicited sudden onset of repetitive network bursting. Our finding provides powerful evidence that onset of seizures can be associated with a reduction in synaptic transmission. These results open a new avenue to explore network synchrony and may ultimately lead to a rational approach to treatment of network pathology in epilepsy.

Animals↗

PubMed2004

Localization of brainstem auditory evoked potentials in primates: a comparison of localization techniques applied to deep brain sources.

The objective of this study was to evaluate the performance of source localization techniques through localization of deep brain sources. To accomplish this, two replications of a brainstem auditory evoked potential (BAEP, left ear 60 dB nHL clicks) were recorded from five normal rhesus monkeys. We analyzed waves III and IV, as this portion of the BAEP corresponds to the deepest signal. Data were analyzed using five different source localization techniques: Moving Dipoles, Fixed Dipoles, MUSIC (Multiple Signal Classification) dipole scan, LORETA (Low Resolution Tomography), and LCMV (Linearly Constrained Minimum Variance) spatial filtering. The moving dipole, fixed dipole and MUSIC solutions were found to be, on average, 25.1 mm from the brainstem generators. LORETA detected sources within the brainstem 65% of the time. However, 90% of these localization results also included false detections defined as regions of the brain that were more than 2 cm away from the auditory pathway. LCMV included the brainstem in 90% of the trials and false detections in 40% of the cases. These findings indicate that evoked electrical activity from deep brain sources can be localized with cm accuracy. The dipole methods performed better than LORETA and LCMV. Given the depth and amplitude of the sources analyzed in this study, these results can be interpreted as an upper bound on the accuracy of each technique.

Acoustic Stimulation↗

PubMed2003

Seizure anticipation in pediatric epilepsy: use of Kolmogorov entropy.

The purpose of this paper is to demonstrate feasibility of using trends in Kolmogorov entropy to anticipate seizures in pediatric patients with intractable epilepsy. Surface and intracranial recordings of preseizure and seizure activity were obtained from five patients and subjected to time series analysis using Kolmogorov entropy. This metric was compared with correlation dimension and power indices, both known to predict seizures in some adult patients. We used alarm levels and introduced regression analysis as a quantitative approach to the analysis of trends. Surrogate time series evaluated data nonlinearity, as a precondition to the use of nonlinear measures. Seizures were anticipated before clinical or electrographic seizure onset for three of the five patients from the intracranial recordings, and in two of five patients from the scalp recordings. Anticipation times varied between 2 and 40 minutes. This is the first report in which simultaneous surface and intracranial recording are used for seizure prediction in children. We conclude that the Kolmogorov entropy and power indices were as effective as the more commonly used correlation dimension in anticipating seizures. Further, regression analysis of the Kolmogorov entropy time series is feasible, making the analysis of data trends more objective.

Adolescent↗