Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings.

OBJECTIVE: The present study aims to accurately estimate the in vivo brain-to-skull conductivity ratio by means of cortical imaging technique. Simultaneous extra- and intra-cranial potential recordings induced by subdural current stimulation were analyzed to get the estimation. METHODS: The effective brain-to-skull conductivity ratio was estimated in vivo for 5 epilepsy patients. The estimation was performed using multi-channel simultaneously recorded scalp and cortical electrical potentials during subdural electrical stimulation. The cortical imaging technique was used to compute the inverse cortical potential distribution from the scalp recorded potentials using a 3-shell head volume conductor model. The brain-to-skull conductivity ratio, which leads to the most consistent cortical potential estimates with respect to the direct intra-cranial measurements, is considered to be the effective brain-to-skull conductivity ratio. RESULTS: The present estimation provided consistent results in 5 human subjects studied. The in vivo effective brain-to-skull conductivity ratio ranged from 18 to 34 in the 5 epilepsy patients. CONCLUSIONS: The effective brain-to-skull conductivity ratio can be estimated from simultaneous intra- and extra-cranial potential recordings and the averaged value/standard deviation is 25+/-7. SIGNIFICANCE: The present results provide important experimental data on the brain-to-skull conductivity ratio, which is of significance for accurate brain source localization using piece-wise homogeneous head models.

High-resolution EEG: cortical potential imaging of interictal spikes.

BACKGROUND: It is of clinical importance to localize pathologic brain tissue in epilepsy. Noninvasive localization of cortical areas associated with interictal epileptiform spikes may provide important information to facilitate presurgical planning for intractable epilepsy patients. METHODS: A cortical potential imaging (CPI) technique was used to deconvolve the smeared scalp potentials into the cortical potentials. A 3-spheres inhomogeneous head model was used to approximately represent the head volume conductor. Five pediatric epilepsy patients were studied. The estimated cortical potential distributions of interictal spikes were compared with the subsequent surgical resections of these same patients. RESULTS: The areas of negativity in the reconstructed cortical potentials of interictal spikes in 5 patients were consistent with the areas of surgical resections for these patients. CONCLUSIONS: The CPI technique may become a useful alternative for noninvasive mapping of cortical regions displaying epileptiform activity from scalp electroencephalogram recordings.

Localization of brain electrical activity via linearly constrained minimum variance spatial filtering.

A spatial filtering method for localizing sources of brain electrical activity from surface recordings is described and analyzed. The spatial filters are implemented as a weighted sum of the data recorded at different sites. The weights are chosen to minimize the filter output power subject to a linear constraint. The linear constraint forces the filter to pass brain electrical activity from a specified location, while the power minimization attenuates activity originating at other locations. The estimated output power as a function of location is normalized by the estimated noise power as a function of location to obtain a neural activity index map. Locations of source activity correspond to maxima in the neural activity index map. The method does not require any prior assumptions about the number of active sources of their geometry because it exploits the spatial covariance of the source electrical activity. This paper presents a development and analysis of the method and explores its sensitivity to deviations between actual and assumed data models. The effect on the algorithm of covariance matrix estimation, correlation between sources, and choice of reference is discussed. Simulated and measured data is used to illustrate the efficacy of the approach.

Identification of epileptogenic foci from causal analysis of ECoG interictal spike activity.

OBJECTIVE: In patients with intractable epilepsy, the use of interictal spikes as surrogate markers of the epileptogenic cortex has generated significant interest. Previous studies have suggested that the cortical generators of the interictal spikes are correlated with the epileptogenic cortex as identified from the ictal recordings. We hypothesize that causal analysis of the functional brain networks during interictal spikes are correlated with the clinically-defined epileptogenic zone. METHODS: We employed a time-varying causality measure, the adaptive directed transfer function (ADTF), to identify the cortical sources of the interictal spike activity in eight patients with medically intractable neocortical-onset epilepsy. The results were then compared to the foci identified by the epileptologists. RESULTS: In all eight patients, the majority of the ADTF-calculated source activity was observed within the clinically-defined SOZs. Furthermore, in three of the five patients with two separate epileptogenic foci, the calculated source activity was correlated with both cortical sites. CONCLUSIONS: The ADTF method identified the cortical sources of the interictal spike activity as originating from the same cortical locations as the recorded ictal activity. SIGNIFICANCE: Evaluation of the sources of the cortical networks obtained during interictal spikes may provide information as to the generators underlying the ictal activity.

The feeding apparatus of Caiman crocodilus; a functional-morphological study.

A functional morphological study on the cranio-facial region of Caiman crocodilus was carried out. The anatomy of the skull, mandible, cartilaginous structures and the muscles of the jaw was described. Myography experiments, an X-ray study and observations of behaviour gave insight into the sequence of actions during food-intake. Evidence has been obtained that the cartilago transiliens, attached to the medial side of the mandible, is used to block the jaws relative to each other. For each food-intake action, the amount of material necessary to resist muscle force was calculated. Integration of these figures, together with a consideration on the lines of stress, resulted in a paradigm for the mandible.

Developing a petascale neural simulation.

Simulations of large neural networks have the potential to contribute uniquely to the study of epilepsy, from the effects of extremely local changes in neuron environment and behavior, to the effects of large scale wiring anomalies. Currently, simulations with sufficient detail in the neuron model, however, are limited to cell counts that are far smaller than scales measured by typical probes. Furthermore, it is likely that future simulations will follow the path that large-scale simulations in other fields have and include hierarchically interacting components covering different scales and different biophysics. The resources needed for problem solving in this domain call for petascale computing--computing with supercomputers capable of 10(15) operations a second and holding datasets of 10(15) bytes in memory. We will lay out the structure of our simulation of epileptiform electrical activity in the neocortex, describe experiments and models of its scaling behavior in large cluster supercomputers, identify tight spots in this behavior, and project the performance onto a candidate next generation computing platform.

Interaction between cellular voltage-sensitive conductance and network parameters in a model of neocortex can generate epileptiform bursting.

We examined the effects of both intrinsic neuronal membrane properties and network parameters on oscillatory activity in a model of neocortex. A scalable network model with six different cell types was built with the pGENESIS neural simulator. The neocortical network consisted of two types of pyramidal cells and four types of inhibitory interneurons. All cell types contained both fast sodium and delayed rectifier potassium channels for generation of action potentials. A subset of the pyramidal neurons contained an additional slow inactivating (persistent) sodium current (NaP). The neurons with the NaP current showed spontaneous bursting activity in the absence of external stimulation. The model also included a routine to calculate a simulated electroencephalogram (EEG) trace from the population activity. This revealed emergent network behavior which ranged from desynchronized activity to different types of seizure-like bursting patterns. At settings with weaker excitatory network effects, the propensity to generate seizure-like behavior increased. Strong excitatory network connectivity destroyed oscillatory behavior, whereas weak connectivity enhanced the relative importance of the spontaneously bursting cells. Our findings are in contradiction with the general opinion that strong excitatory synaptic and/or insufficient inhibition effects are associated with seizure initiation, but are in agreement with previously reported behavior in neocortex.