The transition from mild sedation to deep anaesthesia is marked by the phenomenon of burst suppression (BS). FDG-PET studies show that the cerebral metabolic rate for glucose (CMRglc) declines dramatically with onset of BS in the adult brain. Global CMRglc increases substantially in the post-natal period and achieves its maximum in preadolescence. However, the impact of post-natal brain development on the vulnerability of CMRglc to the onset of BS has not been documented.Therefore, cerebral blood flow and metabolism were measured using a variant of the Kety–Schmidt method, in conjunction with quantitative regional estimation of brain glucose uptake by FDG-PET in groups of neonate and juvenile pigs, under a condition of light sedation or after induction of deep anaesthesia with thiopental. Quantification of simultaneous ECoG recordings was used to establish the correlation between anaesthesia-related changes in brain electrical activity and the observed cerebrometabolic changes.In the condition of light sedation the magnitude of CMRglc was approximately 20% higher in the older pigs, with the greatest developmental increase evident in the cerebral cortex and basal ganglia (P<0.05). Onset of BS was associated with 20–40% declines in CMRglc. Subtraction of the mean parametric maps for CMRglc showed the absolute reductions in CMRglc evoked by thiopental anaesthesia to be two-fold greater in the pre-adolescent pigs than in the neonates (P<0.05). Thus, the lesser suppression of brain energy demand of neonate brain during deep anaesthesia represents a reduced part of thiopental suppressing brain metabolism in neonates.

Purpose There is compelling evidence that interference of various anesthetics with synaptic functions and stress-provoking procedures during critical periods of brain maturation results in increased neuroapoptotic cell death. The hypothesis is that adverse intrauterine environmental conditions leading to intrauterine growth restriction (IUGR) with altered brain development may result in enhanced susceptibility to developmental anesthetic neurotoxicity. Methods This was a prospective, randomized, blinded animal study performed in a university laboratory involving 20 normal-weight (NW) and 19 IUGR newborn piglets. General inhalation anesthesia with isoflurane and nitrous oxide at clinically comparable dosages were administered for about 10 h. Surgical and monitoring procedures were accompanied by appropriate stage of general anesthesia. Resulting effects on developmental anesthetic and stress-induced neurotoxicity were assessed by estimation of apoptotic rates in untreated piglets and piglets after 10-h general anesthesia with MAC 1.0 isoflurane in 70 % nitrous oxide and 30 % oxygen. Results IUGR piglets exposed to different levels of isoflurane inhalation exhibited a significant increased apoptosis rate (TUNEL-positive neuronal cells) compared to NW animals of similar condition ( P < 0.05). Cardiovascular and metabolic monitorings revealed similar effects of general anesthesia together with similar effects on brain electrical activity and broadly a similar dose-dependent gradual restriction in brain oxidative metabolism in NW and IUGR piglets. Conclusions There is no indication that the increased rate in neuroapoptosis in IUGR piglets is confounded by additional adverse systemic or organ-specific impairments resulting from administered mixed inhalation anesthesia. Developmental anesthetic and stress-induced neuroapoptosis presumably originated in response to fetal adaptations to adverse conditions during prenatal life and should be considered in clinical interventions on infants having suffered from fetal growth restriction.

BACKGROUND:Newborn mammals suffering from moderate hypoxia during or after birth are able to compensate a transitory lack of oxygen by adapting their vital functions. Exposure to hypoxia leads to an increase in the sympathetic tone causing cardio-respiratory response, peripheral vasoconstriction and vasodilatation in privileged organs like the heart and brain. However, there is only limited information available about the time and intensity changes of the underlying complex processes controlled by the autonomic nervous system.METHODS:In this study an animal model involving seven piglets was used to examine an induced state of circulatory redistribution caused by moderate oxygen deficit. In addition to the main focus on the complex dynamics occurring during sustained normocapnic hypoxia, the development of autonomic regulation after induced reoxygenation had been analysed. For this purpose, we first introduced a new algorithm to prove stationary conditions in short-term time series. Then we investigated a multitude of indices from heart rate and blood pressure variability and from bivariate interactions, also analysing respiration signals, to quantify the complexity of vegetative oscillations influenced by hypoxia.RESULTS:The results demonstrated that normocapnic hypoxia causes an initial increase in cardiovascular complexity and variability, which decreases during moderate hypoxia lasting one hour (p < 0.004). After reoxygenation, cardiovascular complexity parameters returned to pre-hypoxic values (p < 0.003), however not respiratory-related complexity parameters.CONCLUSIONS:In conclusion, indices from linear and nonlinear dynamics reflect considerable temporal changes of complexity in autonomous cardio-respiratory regulation due to normocapnic hypoxia shortly after birth. These findings might be suitable for non-invasive clinical monitoring of hypoxia-induced changes of autonomic regulation in newborn humans.

The study investigates time-variant directed interactions between brain regions during the interburst–burst EEG pattern (tracé alternant) characteristic of quiet sleep in healthy neonates. The transition from interburst to burst is of particular interest as the generation of the EEG characteristics at burst onset reflects timing and time-variant interplay between the cortical and the thalamo-cortical brain structures. To study the dynamics of the interactions, time-variant partial directed coherence (PDC), a measure of effective connectivity, was used which allows analysis in the time–frequency range. The main results of the grand mean PDC analysis are: (1) PDC time–frequency patterns are frequently associated with phase-locked oscillations. (2) Interhemispheric interactions are dominant between frontal, central and occipital electrodes and intrahemispheric interactions are much less substantial. (3) An interaction breakdown for the frequency ranges 1–4Hz (Fp1⇒Fp2) and 0.5–3Hz (Fp2⇒Fp1) exists which lasts about 2.5s and which is located at about burst onset. (4) Strong interactions in the high-frequency range 3.5–4.5Hz between the frontal electrodes can be observed for both directions at the burst onset. It can be concluded that the evolution of strong interactions in the high-frequency range, which starts shortly before or at the burst onset from frontal regions to anteroposterior directions as well as the frontal interhemispheric interactions, are associated with the burst onset generation. Additionally, the collapsing of the interactions before burst onset and after the burst are indicative of neuronal reorganisation processes.

Time-variant partial directed coherence (tvPDC) is used for the first time in a multivariate analysis of heart rate variability (HRV), respiratory movements (RMs) and (systolic) arterial blood pressure. It is shown that respiration-related HRV components which also occur at other frequencies besides the RM frequency (=respiratory sinus arrhythmia, RSA) can be identified. These additional components are known to be an effect of the 'half-the-mean-heart-rate-dilemma' ('cardiac aliasing' CA). These CA components may contaminate the entire frequency range of HRV and can lead to misinterpretation of the RSA analysis. TvPDC analysis of simulated and clinical data (full-term neonates and sedated patients) reveals these contamination effects and, in addition, the respiration-related CA components can be separated from the RSA component and the Traube-Hering-Mayer wave. It can be concluded that tvPDC can be beneficially applied to avoid misinterpretations in HRV analyses as well as to quantify partial correlative interaction properties between RM and RSA.

Objective There is still a lack of knowledge on the age-dependent relation between a reduction in cerebral perfusion pressure (CPP) and compromised brain perfusion leading to excessive transmitter release and brain damage cascades. The hypothesis is that an age-dependent lower threshold of cerebral blood flow (CBF) autoregulation determines the amount and time course of transmitter accumulation. Design and setting This was a prospective randomized, blinded animal study performed in a university laboratory involving eight newborn and 11 juvenile anesthetized pigs. Intervention Striatal dopamine, glutamate, glucose, and lactate were monitored by microdialysis. For CPP manipulation, the cisterna magna was infused with artificial cerebrospinal fluid to control intracranial pressure at the maintained arterial blood pressure (stepwise CPP decrease in 15-min stages to 50, 40, 30, and finally 0 mmHg). Measurements and main results Juvenile pigs showed a gradual decrease in CBF between 50 mmHg CPP (CPP-50) and 30 mmHg CPP (CPP-30), but a significant CBF reduction did not occur in newborn piglets until CPP-30 ( P < 0.05). At CPP-30, brain oxidative metabolism was reduced only in juveniles, concomitantly with elevations in dopamine and glutamate levels ( P < 0.05). In contrast, newborn piglets exhibited a delayed and blunted accumulated of transmitters and metabolites ( P < 0.05). Conclusions The lower limit of CBF autoregulation was associated with modifications in neurochemical parameters that clearly occurred before brain oxidative metabolism was compromised. Early indicators for mild to moderate hypoperfusion are elevated levels of lactate and dopamine, but elevated levels of glutamate appear to be an indicator of brain ischemia. The shift to the left of the lower autoregulatory threshold is mainly responsible for the postponed neurochemical response to decrements in the CPP in the immature brain.

Article Finite Element Method applied to extended source models in the neuromagnetic forward problem was published on January 1, 1995 in the journal Biomedical Engineering / Biomedizinische Technik (volume 40, issue s1).

Background and aim: It is not known on which time scales the nonlinear respirocardial interactions occur. This work's aim is to quantitatively assess functional respirocardial organization during quiet and active steep of healthy full-term neonates by autonomic information flow (AIF) without limitation on specific time scales. Representing respirocardial interactions on a global time scale AIF carries information on a wider scope of interdependencies than known linear and nonlinear measures described. It assesses the complexity of heart rate fluctuations (HRF) and respiratory movements (RM) and their interaction comprising both linear and nonlinear properties. Thus, we hypothesized AIF to characterize novel aspects of steep state-dependent respirocardial interaction.Methods: RM and ECG-derived HRF of six healthy full-term neonates were studied. We analyzed their power spectra, coherence, auto- and cross-correlation and complexity estimated on local ("next sample" prediction) and global time scales (an integral over AIF predicting for all time tags in HRF and RM).Results: We found the global AIF of HRF and RM to differ significantly between active and quiet steep in all neonates, whereas on a local time scale this applied to the HRF AIF only. HRF complexity was larger in quiet than in active steep. Respirocardial interaction was less complex in quiet versus active steep in the high frequency band only.Conclusion: Complex steep state-related changes of respirocardial interdependencies cannot be identified completely on the local time scale. Considering the global time scale of respirocardial, interactions allows a more complete physiological interpretation with regard to the underlying autonomic dynamics. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Few reports exist on complex functions of pigs central nervous system. A direct access to thalamic structures enables a deeper understanding of neuronal networks. Here we present an easy to implement stereotactic approach to reach both reticular and dorsolateral thalamic nuclei (RTN and LD). In thirteen pigs (7 weeks old) the correct electrode position was confirmed for 22 out of 26 thalamic electrodes (RTN: A+2, L9, V24 and LD: A-2, L5, V20, with bregma A 0, L 0). Quantitative effects of isoflurane/nitrous oxide (State 1) and fentanyl sedation (State 2) were determined by brain hemodynamics and metabolism. Neurophysiologic features were performed by spectral power, coherence and SEP analysis. Brain blood flow (by 21 +/- 13%) and oxidative brain metabolism (CMRO2 by 26 +/- 12%, CMRGlucose by 26 +/- 22%) were markedly reduced during State 1 (P

The heart rate variability (HRV) can be taken as an indicator of the coordination of the cardio-respiratory rhythms. Bispectral analysis using a direct (fast Fourier transform based) and time-invariant approach has shown the occurrence of a quadratic phase coupling (QPC) between a low-frequency (LF: 0.1 Hz) and a high-frequency (HF: 0.4-0.6 Hz) component of the HRV during quiet sleep in healthy neonates. The low-frequency component corresponds to the Mayer-Traube-Hering waves in blood pressure and the high-frequency component to the respiratory sinus arrhythmia (RSA). Time-variant, parametric estimation of the bispectrum provides the possibility of quantifying QPC in the time course. Therefore, the aim of this work was a parametric, time-variant bispectral analysis of the neonatal HRV in the same neonates used in the direct, time-invariant approach. For the first time rhythms in the time course of QPC between the HF component and the LF component could be shown in the neonatal HRV.

We propose a number of electric source models that are spatially distributed on an unknown surface for biomagnetism. These can be useful to model, e.g., patches of electrical activity on the cortex. We use a realistic head (or another organ) model and discuss the special case of a spherical head model with radial sensors resulting in more efficient computations of the estimates for magnetoencephalography. We derive forward solutions, maximum likelihood (ML) estimates, and Cramer-Rao bound (CRB) expressions for the unknown source parameters. A model selection method is applied to decide on the most appropriate model. We also present numerical examples to compare the performances and computational costs of the different models and illustrate when it is possible to distinguish between surface and focal sources or line sources. Finally, we apply our methods to real biomagnetic data of phantom human torso and demonstrate the applicability of them.

Summary Objectives: Electroencephalographic burst activity characteristic of burst-suppression pattern (BSP) in sedated patients and of burst-interburst pattern (BIP) in the quiet sleep of healthy neonates have similar linear and non-linear signal properties. Strong interrelations between a slow frequency component and rhythmic, spindle-like activities with higher frequencies have been identified in previous studies. Time-varying characteristics of BSP and BIP prevent a definite pattern-related analysis. A continuous estimation of the bispectrum is essential to analyze these patterns. Parametric bispectral approaches provide this opportunity. Methods: The adaptation of an AR model leads to a parametric bispectrum by using the transfer function of the estimated AR filter. Time-variant parametric bispectral approaches require an estimation of AR parameters which consider higher order moments to preserve phase information. Accordingly, a time-variant parametric estimation of the bispectrum was introduced. Data driven simulations were performed to provide optimal parameters. BSP (12 patients) and BIP (6 neonates) were analyzed using this novel approach. Results: Significant differences in the time course of burst pattern during BSP and burst-like pattern before the onset of BSP could be shown. A rhythmic quadratic phase coupling (period 10 sec) was identified during BIP in all neonates. Conclusion: Quadratic phase couplings during BSP increases in the time course depending on depth of sedation. The visually detected burst activity in BIP is only the temporarily observable EEG correlate of a hidden neural process. Time-variant bispectral approaches offer the possibility of a better characterization of underlying neural processes leading to improved diagnostic tools used in clinical routine.

Objective: Interpretation of Electroencephalography (EEG) signals from newborns is in some cases difficult because the fontanels and open sutures produce inhomogeneity in skull conductivity. We experimentally determined how EEG is influenced by a hole mimicking the anterior fontanel since distortion of EEG signals is important in neurological examinations during the perinatal period.Methods: Experiments were carried out on 10 anesthetized farm swine. The fontanel was mimicked by a hole (12 X 12 mm) in the skull. The hole was filled with 3 types of medium differing in conductivity (air, 0 S/m; sucrose-agar, 0.017 S/m; saline-agar, 1.28 S/m). Three positions of the snout were stimulated with a concentric bipolar electrode to activate cortical areas near the middle, the edge, and the outside of the hole. The somatic-evoked potential (SEP) was recorded by a 4 X 4 electrode array with a 4 mm grid spacing. It was placed on the 4 quadrants of a 28 X 28 mm measurement area on a saline-soaked filter paper over the skull, which served as artificial scalp.Results: The SEP over the hole was clearly stronger when the hole was filled with sucrose- or saline-agar as compared to air, although paradoxically the leakage current was stronger for the sucrose- than saline-agar. The current leaking from the hole was strongly related to position of the active tissue. It was nearly negligible for sources 6-10 mm away from the border of the hole. The distortion was different for 3 components of the SEP elicited by each stimulus, probably indicating effects of source distance relative to the hole.Conclusions: EEG is strongly distorted by the presence of a hole/fontanel with the distortion specifically dependent on both conductivity of the hole and source location.Significance: The distortion of the EEG is in contrast to the lack of distortion of magnetoencephalography (MEG) signals shown by previous studies. In studying brain development with EEG, the infant's head and sources should be modeled accurately in order to relate the signals to the underlying activity. MEG may be particularly advantageous over EEG for studying brain functions in infants since it is relatively insensitive to skull defects. (c) 2005 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

The aim of this study was to quantify the influence of the inclusion of anisotropic conductivity on EEG source reconstruction. We applied high-resolution finite element modeling and performed forward and inverse simulation with over 4000 single dipoles placed around an anisotropic volume block (with an anisotropic ratio of 1:10) in a rabbit brain. We investigated three different orientation of the dipoles with respect to the anisotropy in the white matter block. We found a weak influence of the anisotropy in the forward simulation on the electric potential. The relative difference measure (RDM) between the potentials simulated with and without taking into account anisotropy was less than 0.009. The changes in magnitude (MAG) ranged from 0.944 to 1.036. Using the potentials of the forward simulation derived with the anisotropic model and performing source reconstruction by employing the isotropic model led to dipole shifts of up to 2 mm, however the mean shift over all dipoles and orientations of 0.05 mm was smaller than the grid size of the FEM model (0.6 mm). However, we found the source strength estimation to be more influenced by the anisotropy (up to 7-times magnified dipole strength). Keywords—anisotropy, conductivity, FEM, animal model, simulation, EEG

Objective: The time courses of quadratic phase-coupling (QPC) of electroencephalographic burst and interburst patterns of the 'trace alternant' (TA) in full-term newborns have been quantified.Methods: Using the Gabor expansion, a fast Fourier transformation based method, biamplitude, bicoherence and phase-bicoherence time courses of both burst and interburst patterns have been determined (common average reference EEG recordings). With a frequency resolution of 0.25 Hz and a frequency grid of 1-1.5 double left right arrow 3.5-4.5 Hz (region-of-interest), a number of 15 frequency pairs result. These pairs have been investigated.Results: The burst and the interburst patterns are characterized by temporally and topographically different QPC profiles. All differences are dominant at the electrode Fp1 followed by Fp2. There is a significant difference (combined multiple and global test strategy) in the QPC characteristics between both patterns within the time period from 0.75 to 1.5 s after the pattern onset at electrode Fp1. The maximal QPC in burst patterns (especially at Fp1) can be observed during this time period. In contrast to this finding, maximal QPC in interburst patterns (at Fp1) are reached immediately after the onset and at 3 s. Summarising all findings, a QPC-rhythm of 0.1 Hz during TA can be assumed.Conclusions: It can be assumed that the QPC rhythm of the TA is generated by a pattern-spanning time-variant phase-locking process and there are indications for a possible correspondence between the QPC rhythm and vegetative rhythms.Significance: This study showed that advanced, time-variant analysis methods quantifying QPC rhythms are able to add new scientific information to the understanding of nature, characteristics and significance of TA in the neonatal EEG. (C) 2004 Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

The complexity of heart rate fluctuations (HRF) is based on several interacting physiological mechanisms operating on different time scales. No prominent time scale for HRF complexity analysis is given a priori. The aim of this work is to discriminate the active and quiet sleep of healthy full-term neonates by quantitatively assessing respirocardial coordination dynamics using the recently introduced complexity parameter mutual information function (MIF). Representing the different time scales of information flow in autonomic nervous system, MIF carries information on a wider scope of complex interdependencies than complexity estimators previously known. Our hypothesis was therefore that MIF discriminates sleep states by comprehensively characterizing complex coordinations of HRF and respiratory movements (RM). RM and ECG-derived HRF of 6 healthy full-term neonates (4±1 days of life) were studied. As standard measures characterizing sleep states linear parameters were calculated (power spectra, coherence, auto- and cross-correlation functions). As non-linear parameters of HRF and RM, auto- and cross-MIF were analyzed. All results were statistically tested for their discriminatory power and non-linearity. Confirming our hypothesis we were able to discriminate active and quiet sleep states in all individual cases using one single global time scale parameter of HRF total auto-MIF. We assume that the vagal influence in healthy human neonates mediates mostly complex (linear and non-linear) HRF properties, whereas the sympathetic effect is mainly responsible for linear HRF properties. With the character of the MIF parameters deployed in mind, this finding would explain our success in discriminating the sleep states. Remarkably, HRF complexity was larger in quiet than in active sleep. Complex respirocardial interdependencies cannot be identified completely by the local time scale MIF parameters alone. New information is gained when total MIF values are also considered. This result confirms the relevance of global measures of information flow for a comprehensive discrimination of complex systems. Sleep state-related changes of MIF parameters extend the possibilities of interpreting the underlying physiological processes of complex respirocardial coordination dynamics.

The knowledge about the origin and the spatio-temporal pattern of propagation of spreading depolarization (SD) after focal ischemic brain infarction is limited. Using the information of the simultaneously recorded ECoG and MEG it seems possible to describe the localization of underlying neurophysiological processes. We investigated in 8 rats 32 periinfarct depolarizations by simultaneously recorded ECoG and MEG. The ECoG was recorded by a grid of 4×4 electrodes with a spatial distance of 1.25mm between adjacent electrodes. The MEG was recorded by a 16-channel Micro-SQUID system built at the Biomagnetic Center (1st order asymmetric gradiometers, 6.7mm pick-up-coil diameter, 30mm baselength, covering an area of 3.2×3.2cm2). Infarction was initiated via occlusion of the right middle cerebral artery. From the ECoG the moment and location of the first detected negative deflection, the sequence of the involvement of cortical regions and the spatial distribution of the amplitude of depolarization were determined. From MEG the temporal pattern of main intracortical current was estimated. The frequency of SD was 5/hr (=12±6min). Negative deflection of electric potential could be detected at first over rostro-medial regions. The location of the maximal depolarization amplitude varied intra- and interindividually. In most cases SD waves propagated from rostro-medial to caudal regions. In 26 of 32 electric SD, magnetic field changes were detected. Often (n=12) long-lasting magnetic field changes started before electric changes. The mean duration of these changes varied considerably (205±163s). We suppose that the origin of periinfarct depolarization is frequently located in frontal cortical regions and that subcortical depolarization may contribute to the MEG signal.

The perinatal period in human beings is characterized by rapid developmental changes of the CNS. Results from animal experiments indicate that spontaneous activity may be of essential importance for this development. Insights into the functional organization can be provided by EEG, but up to now only limited information is available. We hypothesize that highly organized functional patterns are generated in newborn brains in spite of their immaturity. We investigated healthy full-term newborns by multichannel EEG during quiet sleep. Part of the EEG is characterized by the recurrent appearance of high voltage periods (burst) and low voltage periods (interburst). Pattern-related analysis of this EEG was performed by calculating instantaneous spectral power, adaptive inter- and intrahemispheric coherence and the coupling between different frequency bands by bicoherence analysis. Burst periods reappeared during discontinuous EEG with a dominant frequency of about 0.1Hz. During bursts mean spectral power reached a maximum within frequency bands >2.8–14.8Hz during the first part of this period. Spectral power within the other frequency bands and during interburst periods was distributed equally. The highest coherence level was observed during burst periods in comparison to interburst periods. Maximal coherence was reached at different moments during bursts – late in the low frequency bands (0.5–1.5Hz; about 3s after the burst started) and earlier in higher frequency bands (>2Hz; about 2s). The interhemispheric coherence was highest in all frequency bands over the frontal region as compared to the central region during bursts. Mainly in frontal regions phase coupling between high and low frequency components could be described with a temporal dynamic of about 0.1Hz. It can be shown that during the early period of neurodevelopment, characteristic changes of electric potential occur, functional coupling between hemispheres exists and that the EEG expresses highly organized topographic and temporal patterns. Thus, using pattern-related investigations with high temporal resolution the newborn EEG provides evidence of early integrative cortical functions.

Purpose: Source localization based on EEG/MEG data is a widely used technique to investigate neuronal activity. It tries to localize focal sources (dipoles) in order to represent the external measured signal (EEG/MEG) solving an inverse problem. Thereby the accuracy of the results depends on the given volume conductor model. Volume conductor modeling using the Finite Element Method (FEM) opens the possibility of taking into account the anisotropic conductivity of, e.g., the white matter tracts. In our study we investigated the influence of this anisotropy on solving the forward and inverse problem using an animal model. Material: Using a T1-weighted MR image, we segmented the head of a rabbit into four different tissue layers (skin, skull, grey and white matter). Additionally, we performed diffusion-tensors imaging to obtain the anisotropy of the white matter tissue. The orientation of the diffusion tensors was used to model anisotropic conductivity tensors in the white matter of the rabbit brain employing an adopted anisotropic ratio of 1:10. 650 dipoles in the cortical region in intervals of 1mm and radial orientation served as sources. Using the anisotropic model we performed EEG simulation to asses EEG potentials at 100 electrodes placed on the rabbit head. With the computed potentials we performed source localization using the same model but with isotropic conductivity tensors. This corresponds to the assumption of a source localization with an isotropic model and realistic measurement data, which include effects of anisotropic conductivity. Results: All dipoles were shifted in their location and changed in their orientation due to the isotropic model with data derived from the anisotropic model. The shift was up to 2mm with a mean of 0.69mm. The averaged orientation deviation was 23.7 degrees and the mean magnitude change of the dipole was determined with a value of 24.2 percent. Conclusion: In this study we have shown the influence of conductivity anisotropy on EEG source simulation and localization with the help of an FEM model of a rabbit head. Volume conductor modeling in EEG source localization procedures including anisotropy will improve accuracy of the localization results.