Effects of dipole position,orientation and noise on the accuracy of EEG source localization

Background  

The electroencephalogram (EEG) reflects the electrical activity in the brain on the surface of scalp. A major challenge in this field is the localization of sources in the brain responsible for eliciting the EEG signal measured at the scalp. In order to estimate the location of these sources, one must correctly model the sources, i.e., dipoles, as well as the volume conductor in which the resulting currents flow. In this study, we investigate the effects of dipole depth and orientation on source localization with varying sets of simulated random noise in 4 realistic head models.     

EEG and implanted sources in the brain

Localisation procedures are based on models of the EEG that are relatively simple. The models are based on assumptions and choices of parameters that can be mistaken. Thus, it is crucial to validate the localisation procedures used in EEG. One of the options is to use the data obtained with electrodes that are implanted within the brain of an epileptic patient as part of the pre-surgical evaluation. When one of two neighbouring electrodes is used as a current source and the other as a current sink this can be regarded as a current dipole. The current injected has to be below the threshold for activation of cells. The position of this dipole can be deduced from magnetic resonance or X-ray images. The current dipole gives rise to a potential distribution at the scalp that can be measured by EEG. The measurements can be compared with the potential distribution that is calculated in a forward computation. Another method is to use the measured potential at the scalp to localize the source and to compare the result with the actual position of the dipole. In this paper the measured potential distributions at the scalp due to implanted dipoles were used to evaluate different volume conductor models. Since intracerebral and subdural electrodes were introduced through trephine holes over the fronto-central areas, and the diameter of the holes was rather large, approximately 23 mm, special effort was put into modelling the skull. Two important assumptions could be validated in this study: the electric currents within the head are Ohmic and a dipole can be used to model the induced electric activity of pairs of contacts on subdural electrodes or intra cerebral electrodes.     

脑源定位技术的精度评估及其在实际中的应用

脑源定位技术旨在通过头皮表面的脑电、脑磁信号来识别大脑内的神经活动源，是研究大脑皮层神经活动、认知过程和病理功能的基础。其毫秒级的时间分辨率可以有效弥补功能核磁共振在低时间分辨率方面的不足。然而，理论分析层面中逆问题的不适定性，以及实践操作层面上不同的记录方式、电极数量和头模型构建等过程带来的误差，给脑源定位的准确性带来极大挑战，也在一定程度上限制了脑源定位方法在神经科学和心理学研究以及临床诊断治疗中的实际应用。因此，理论分析和实践操作层面中的精度评估在脑源定位方法的实际使用中至关重要。针对以上问题，本文在对现有脑源定位方法介绍的基础上，着重分析了脑源定位技术的精度评估方法以及其在基础研究和临床诊断治疗中的实际应用。具体地，本文在理论分析中总结了基于空间分辨率、基于点扩散以及串扰函数的评估方法对于不同脑源定位方法中源的重叠程度和其他源对目标源的影响；在实践操作中介绍了记录方式、电极数量和密度、头部容积传导模型等因素对源定位精度的影响；进一步介绍了脑源定位技术在时频分析、连通性分析中的应用，以及其在临床中的应用，包括癫痫、注意缺陷与多动障碍等脑部疾病。     

Electric Field Encephalography as a Tool for Functional Brain Research: A Modeling Study

We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2–3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM) head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.     

Des sources neuronales aux signaux EEG : modèle et interprétation des activités épileptiques

This work deals with the interpretation of electrophysiological patients recorded in epileptic patients candidate to surgery. This issue is addressed through a physiologically relevant model for the generation of scalp and intracerebral electroencephalographic (EEG) signals. The proposed model is based on a spatiotemporal representation of the sources of brain activity, which combines a distributed dipole source model and a model of coupled neuronal populations. Signals recorded by sensors (scalp and intracerebral) are then computed by solving the forward problem in the head volume conductor. In this paper, the EEG generation model is used to study the influence of some source-related parameters (spatial extent, position, synchronization) on simulated signals, during epileptic transient activity (interictal spikes). Results show that the model allows for studying, on the one hand, the relationship between the spatiotemporal organization of neuronal sources and the properties of the observed signals and, on the other hand, the relationship between surface and depth EEG signals.     

Application of boundary element method for more accurate localization of EEG dipole sources

The proposed modification of boundary element method (BEM) makes it possible to solve direct EEG problem taking into account individual head geometry. This modification decreases computational cost thus enabling practical usage of BEM for localization of EEG dipole sources. The method developed was applied for error estimation of dipole localization using spherical approximation with the aid of BESA software. It was shown that the localization error of BESA for real head geometry could reach 2 cm.     

From Oscillatory Transcranial Current Stimulation to Scalp EEG Changes: A Biophysical and Physiological Modeling Study

Both biophysical and neurophysiological aspects need to be considered to assess the impact of electric fields induced by transcranial current stimulation (tCS) on the cerebral cortex and the subsequent effects occurring on scalp EEG. The objective of this work was to elaborate a global model allowing for the simulation of scalp EEG signals under tCS. In our integrated modeling approach, realistic meshes of the head tissues and of the stimulation electrodes were first built to map the generated electric field distribution on the cortical surface. Secondly, source activities at various cortical macro-regions were generated by means of a computational model of neuronal populations. The model parameters were adjusted so that populations generated an oscillating activity around 10 Hz resembling typical EEG alpha activity. In order to account for tCS effects and following current biophysical models, the calculated component of the electric field normal to the cortex was used to locally influence the activity of neuronal populations. Lastly, EEG under both spontaneous and tACS-stimulated (transcranial sinunoidal tCS from 4 to 16 Hz) brain activity was simulated at the level of scalp electrodes by solving the forward problem in the aforementioned realistic head model. Under the 10 Hz-tACS condition, a significant increase in alpha power occurred in simulated scalp EEG signals as compared to the no-stimulation condition. This increase involved most channels bilaterally, was more pronounced on posterior electrodes and was only significant for tACS frequencies from 8 to 12 Hz. The immediate effects of tACS in the model agreed with the post-tACS results previously reported in real subjects. Moreover, additional information was also brought by the model at other electrode positions or stimulation frequency. This suggests that our modeling approach can be used to compare, interpret and predict changes occurring on EEG with respect to parameters used in specific stimulation configurations.     

The influence of conductivity changes in boundary element compartments on the forward and inverse problem in electroencephalography and magnetoencephalography.

Source localization based on magnetoencephalographic and electroencephalographic data requires knowledge of the conductivity values of the head. The aim of this paper is to examine the influence of compartment conductivity changes on the neuromagnetic field and the electric scalp potential for the widely used three compartment boundary element models. Both the analysis of measurement data and the simulations with dipoles distributed in the brain produced two significant results. First, we found the electric potentials to be approximately one order of magnitude more sensitive to conductivity changes than the magnetic fields. This was valid for the field and potential topology (and hence dipole localization), and for the amplitude (and hence dipole strength). Second, changes in brain compartment conductivity yield the lowest change in the electric potentials topology (and hence dipole localization), but a very strong change in the amplitude (and hence in the dipole strength). We conclude that for the magnetic fields the influence of compartment conductivity changes is not important in terms of dipole localization and strength estimation. For the electric potentials however, both dipole localization and strength estimation are significantly influenced by the compartment conductivity.     

Two-dimensional Fourier representation used in the bioelectric forward problem.

The objective of this paper is the application of two-dimensional discrete Fourier transformation for solving the integral equation of the bioelectric forward problem. Therefore, the potential, the source term, and the integral equation kernel are assumed to be sampled at evenly spaced intervals. Thus the continuous functions of the problem domain can be expressed by their two-dimensional discrete Fourier transform in the spatial frequency domain. The method is applied to compute the surface potential generated by an eccentric dipole in a homogeneous spherical conducting medium. The integral equation for the potential is solved in the spatial frequency domain and the value of the potential at the sampling points is obtained from inverse Fourier transformation. The solution of the presented method is compared to both, an analytic solution and a solution gained from applying the boundary element method. Isoparametric quadrilateral boundary elements are used for modeling the spherical volume conductor in the boundary element solution, while in the two-dimensional Fourier transformation method the volume conductor is represented by a parametric boundary surface approximation.     

New head exposure system for use in human provocation studies with EEG recording during GSM900- and UMTS-like exposure

A new head exposure system for double blinded human provocation studies, which requires EEG recording during exposure with GSM900- and UMTS-like signals has been developed and dosimetrically evaluated. The system uses planar patch antennas fixed at 65 mm distance from the subject's head by a special headset, which provides minimum impairment of the test subjects and ensures an almost constant position of the antennas with respect to the head, even in case of head movements. Compared to exposure concepts operating small antennas in close proximity to the head, the concept of planar antennas at a certain distance from the head produces a much more homogeneous SAR distribution in the temporal and parietal lobe of the brain. At the same time the resulting uncertainty of exposure due to variations in head size, variations of the dielectric properties of tissues and unavoidable small changes of the antenna's position with respect to the head, is reduced to the order of approximately 3 dB, which is a significant improvement to comparable head exposure systems reported in literature in the past. To avoid electromagnetic interference on the EEG recording caused by the incident RF-field an appropriate double-shielded filter circuit has been developed. Furthermore, the effect of the presence of the sintered Ag/AgCl EEG electrodes and electrode wires on the SAR distribution inside the head has been investigated and was found to be minimal if the electrode wires are arranged orthogonal to the incident electric field vector. EEG electrode arrangement parallel to the incident field vector, however, might cause drastic changes in the SAR distribution inside the head.     

Investigating Social Cognition in Infants and Adults Using Dense Array Electroencephalography (dEEG)

Dense array electroencephalography (_dEEG), which provides a non-invasive window for measuring brain activity and a temporal resolution unsurpassed by any other current brain imaging technology^1,2, is being used increasingly in the study of social cognitive functioning in infants and adults. While _dEEG is enabling researchers to examine brain activity patterns with unprecedented levels of sensitivity, conventional EEG recording systems continue to face certain limitations, including 1) poor spatial resolution and source localization^3,4,2) the physical discomfort for test subjects of enduring the individual application of numerous electrodes to the surface of the scalp, and 3) the complexity for researchers of learning to use multiple software packages to collect and process data. Here we present an overview of an established methodology that represents a significant improvement on conventional methodologies for studying EEG in infants and adults. Although several analytical software techniques can be used to establish indirect indices of source localization to improve the spatial resolution of _dEEG, the HydroCel Geodesic Sensor Net (HCGSN) by Electrical Geodesics, Inc. (EGI), a dense sensory array that maintains equal distances among adjacent recording electrodes on all surfaces of the scalp, further enhances spatial resolution^4,5,6 compared to standard _dEEG systems. The sponge-based HCGSN can be applied rapidly and without scalp abrasion, making it ideal for use with adults^7,8, children^9,10,11, and infants¹², in both research and clinical^{4,5,6,13,14,15} settings. This feature allows for considerable cost and time savings by decreasing the average net application time compared to other _dEEG systems. Moreover, the HCGSN includes unified, seamless software applications for all phases of data, greatly simplifying the collection, processing, and analysis of _dEEG data.The HCGSN features a low-profile electrode pedestal, which, when filled with electrolyte solution, creates a sealed microenvironment and an electrode-scalp interface. In all Geodesic _dEEG systems, EEG sensors detect changes in voltage originating from the participant''s scalp, along with a small amount of electrical noise originating from the room environment. Electrical signals from all sensors of the Geodesic sensor net are received simultaneously by the amplifier, where they are automatically processed, packaged, and sent to the data-acquisition computer (DAC). Once received by the DAC, scalp electrical activity can be isolated from artifacts for analysis using the filtering and artifact detection tools included in the EGI software. Typically, the HCGSN can be used continuously for only up to two hours because the electrolyte solution dries out over time, gradually decreasing the quality of the scalp-electrode interface.In the Parent-Infant Research Lab at the University of Toronto, we are using _dEEG to study social cognitive processes including memory, emotion, goals, intentionality, anticipation, and executive functioning in both adult and infant participants.     

The influence of local tissue conductivity changes on the magnetoencephalogram and the electroencephalogram.

We examined the influence of local tissue conductivity changes in the vicinity of a dipolar source on the neuromagnetic field and the electric scalp potential using a high resolution finite element method model of the human head. We found that the topology of both the electric scalp potential and the neuromagnetic field (and consequently dipole localization) is influenced significantly by conductivity changes only in voxels adjacent to the source. Conductivity changes in these voxels yield a greater change in the amplitude of the magnetic field (and consequently in the dipole strength) than in the amplitude of the electric potential.     

Seizure source localization using a hybrid second order blind identification and extended rival penalized competitive learning algorithm

Localization of seizure sources prior to neurosurgery is crucial. In this paper, a new method is proposed to localize the seizure sources from multi-channel electroencephalogram (EEG) signals. Blind source separation based on second order blind identification (SOBI) is primarily applied to estimate the brain source signals in each window of the EEG signals. A new clustering method based on rival penalized competitive learning (RPCL) is then developed to cluster the rows of the estimated unmixing matrices in all the windows. The algorithm also includes pre and post-processing stages. By multiplying each cluster center to the EEG signals, the brain signal sources are approximated. According to a complexity value measure, the main seizure source signal is separated from the others. This signal is projected back to the electrodes’ space and is subjected to the dipole source localization using a single dipole model. The simulation results verify the accuracy of the system. In addition, correct localization of the seizure source is consistent with the clinical tests derived using the simultaneous intracranial recordings.     

Modelling and detecting deep brain activity with MEG and EEG

We introduce an anatomical and electrophysiological model of deep brain structures dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) source imaging. So far, most imaging inverse models considered that MEG/EEG surface signals were predominantly produced by cortical, hence superficial, neural currents. Here we question whether crucial deep brain structures such as the basal ganglia and the hippocampus may also contribute to distant, scalp MEG and EEG measurements. We first design a realistic anatomical and electrophysiological model of these structures and subsequently run Monte-Carlo experiments to evaluate the respective sensitivity of the MEG and EEG to signals from deeper origins. Results indicate that MEG/EEG may indeed localize these deeper generators, which is confirmed here from experimental MEG data reporting on the modulation of alpha (10–12 Hz) brain waves.     

Wave III of brain-stem auditory evoked potentials analysed both with 3-channel Lissajous' trajectory and dipole localization method

Wave III of the BAEP was analysed both with 3-channel Lissajous' trajectory (3-CLT) and a dipole localization method. The experiments were performed on 5 normally hearing subjects. The dipole analysis used an iterative algorithm assuming a spherical head model and homogeneous media. 3-CLT planar analysis was performed with a laboratory system. The parameters of plane C (azimuth and elevation) corresponding to wave III and those of the equivalent dipole showed a similar orientation of the plane and the dipole. This result is in agreement with previous investigations and confirms the interest of 3-CLT in far-field analysis and, at the same time, validates the dipole localization model used in this study, at least for BAEP analysis.     

Analysis of parametric estimation of head tissue conductivities using Electrical Impedance Tomography

We study the theoretical performance of using Electrical Impedance Tomography (EIT) to measure the conductivity of the main tissues of the head. The governing equations are solved using the Finite Element Method for realistically shaped head models with isotropic and anisotropic electrical conductivities. We focus on the Electroencephalography (EEG) signal frequency range since EEG source localization is the assumed application. We obtain the Cramér-Rao Lower Bound (CRLB) to find the minimum conductivity estimation error expected with EIT measurements. The more convenient electrode pairs selected for current injection from a typical EEG array are determined from the CRLB. Moreover, using simulated data, the Maximum Likelihood Estimator of the conductivity parameters is shown to be close to the CRLB for a relatively low number of measurements. The results support the idea of using EIT as a low-cost and practical tool for individually measure the conductivity of the head tissues, and to use them when solving the EEG source localization. Even when the conductivity of the soft tissues of the head is available from Diffusion Tensor Imaging, EIT can complement the electrical model with the estimation of the skull and scalp conductivities.     

Experimental model for civilian ballistic brain injury biomechanics quantification

Biomechanical quantification of projectile penetration using experimental head models can enhance the understanding of civilian ballistic brain injury and advance treatment. Two of the most commonly used handgun projectiles (25-cal, 275 m/s and 9 mm, 395 m/s) were discharged to spherical head models with gelatin and Sylgard simulants. Four ballistic pressure transducers recorded temporal pressure distributions at 308kHz, and temporal cavity dynamics were captured at 20,000 frames/second (fps) using high-speed digital video images. Pressures ranged from 644.6 to -92.8 kPa. Entry pressures in gelatin models were higher than exit pressures, whereas in Sylgard models entry pressures were lower or equivalent to exit pressures. Gelatin responded with brittle-type failure, while Sylgard demonstrated a ductile pattern through formation of micro-bubbles along projectile path. Temporary cavities in Sylgard models were 1.5-2x larger than gelatin models. Pressures in Sylgard models were more sensitive to projectile velocity and diameter increase, indicating Sylgard was more rate sensitive than gelatin. Based on failure patterns and brain tissue rate-sensitive characteristics, Sylgard was found to be an appropriate simulant. Compared with spherical projectile data, full-metal jacket (FMJ) projectiles produced different temporary cavity and pressures, demonstrating shape effects. Models using Sylgard gel and FMJ projectiles are appropriate to enhance understanding and mechanisms of ballistic brain injury.     

Improving the SNR of EEG generated by deep sources with weighted multielectrode leads

We have developed a multielectrode lead technique to improve the signal-to-noise ratio (SNR) of scalp-recorded electroencephalography (EEG) signals generated deep in the brain. The basis of the method lies in optimization of the measurement sensitivity distribution of the multielectrode lead. We claim that two factors improve the SNR in a multielectrode lead: (1) the sensitivity distribution of a multielectrode lead is more specific in measuring signals generated deep in the brain and (2) spatial averaging of noise occurs when several electrodes are applied in the synthesis of a multielectrode lead. We showed theoretically that within a three-layer spherical head model the sensitivity distributions of multielectrode leads are more specific for deep sources than those of traditional bipolar leads. We also estimated with simulations and with preliminary measurements the total improvement in SNR achieved by both the more specific lead field and spatial averaging. Results obtained with simulations and with experimental measurements show an apparent improvement in SNR obtained with multielectrode leads. This encourages for future development of the method.     

PTFOS: Flexible and Absorbable Intracranial Electrodes for Magnetic Resonance Imaging

Intracranial electrocortical recording and stimulation can provide unique knowledge about functional brain anatomy in patients undergoing brain surgery. This approach is commonly used in the treatment of medically refractory epilepsy. However, it can be very difficult to integrate the results of cortical recordings with other brain mapping modalities, particularly functional magnetic resonance imaging (fMRI). The ability to integrate imaging and electrophysiological information with simultaneous subdural electrocortical recording/stimulation and fMRI could offer significant insight for cognitive and systems neuroscience as well as for clinical neurology, particularly for patients with epilepsy or functional disorders. However, standard subdural electrodes cause significant artifact in MRI images, and concerns about risks such as cortical heating have generally precluded obtaining MRI in patients with implanted electrodes. We propose an electrode set based on polymer thick film organic substrate (PTFOS), an organic absorbable, flexible and stretchable electrode grid for intracranial use. These new types of MRI transparent intracranial electrodes are based on nano-particle ink technology that builds on our earlier development of an EEG/fMRI electrode set for scalp recording. The development of MRI-compatible recording/stimulation electrodes with a very thin profile could allow functional mapping at the individual subject level of the underlying feedback and feed forward networks. The thin flexible substrate would allow the electrodes to optimally contact the convoluted brain surface. Performance properties of the PTFOS were assessed by MRI measurements, finite difference time domain (FDTD) simulations, micro-volt recording, and injecting currents using standard electrocortical stimulation in phantoms. In contrast to the large artifacts exhibited with standard electrode sets, the PTFOS exhibited no artifact due to the reduced amount of metal and conductivity of the electrode/trace ink and had similar electrical properties to a standard subdural electrode set. The enhanced image quality could enable routine MRI exams of patients with intracranial electrode implantation and could also lead to chronic implantation solutions.     

Concurrent Electroencephalography Recording During Transcranial Alternating Current Stimulation (tACS)

Oscillatory brain activities are considered to reflect the basis of rhythmic changes in transmission efficacy across brain networks and are assumed to integrate cognitive neural processes. Transcranial alternating current stimulation (tACS) holds the promise to elucidate the causal link between specific frequencies of oscillatory brain activity and cognitive processes. Simultaneous electroencephalography (EEG) recording during tACS would offer an opportunity to directly explore immediate neurophysiological effects of tACS. However, it is not trivial to measure EEG signals during tACS, as tACS creates a huge artifact in EEG data. Here we explain how to set up concurrent tACS-EEG experiments. Two necessary considerations for successful EEG recording while applying tACS are highlighted. First, bridging of the tACS and EEG electrodes via leaking EEG gel immediately saturates the EEG amplifier. To avoid bridging via gel, the viscosity of the EEG gel is the most important parameter. The EEG gel must be viscous to avoid bridging, but at the same time sufficiently fluid to create contact between the tACS electrode and the scalp. Second, due to the large amplitude of the tACS artifact, it is important to consider using an EEG system with a high resolution analog-to-digital (A/D) converter. In particular, the magnitude of the tACS artifact can exceed 100 mV at the vicinity of a stimulation electrode when 1 mA tACS is applied. The resolution of the A/D converter is of importance to measure good quality EEG data from the vicinity of the stimulation site. By following these guidelines for the procedures and technical considerations, successful concurrent EEG recording during tACS will be realized.