Three-dimensional brain current source reconstruction from intra-cranial ECoG recordings

Electrical Source Imaging of Somatosensory Evoked Potentials from Intracranial EEG Signals

Stereoelectroencephalography (SEEG) records electrical brain activity with intracerebral electrodes. However, it has an inherently limited spatial coverage. Electrical source imaging (ESI) infers the position of the neural generators from the recorded electric potentials, and thus, could overcome this spatial undersampling problem. Here, we aimed to quantify the accuracy of SEEG ESI under clinical conditions. We measured the somatosensory evoked potential (SEP) in SEEG and in high-density EEG (HD-EEG) in 20 epilepsy surgery patients. To localize the source of the SEP, we employed standardized low resolution brain electromagnetic tomography (sLORETA) and equivalent current dipole (ECD) algorithms. Both sLORETA and ECD converged to similar solutions. Reflecting the large differences in the SEEG implantations, the localization error also varied in a wide range from 0.4 to 10 cm. The SEEG ESI localization error was linearly correlated with the distance from the putative neural source to the most activated contact. We show that it is possible to obtain reliable source reconstructions from SEEG under realistic clinical conditions, provided that the high signal fidelity recording contacts are sufficiently close to the source of the brain activity.

Source localization of ictal SEEG to predict postoperative seizure outcome

OBJECTIVE

Stereo-electroencephalography (SEEG) is inherently-three-dimensional and can be modeled using source localization. This study aimed to assess the validity of ictal SEEG source localization.

METHODS

The dominant frequency at ictal onset was used for source localization in the time and frequency domains using rotating dipoles and current density maps. Validity was assessed by concordance with the epileptologist-defined seizure onset zone (conventional SOZ) and the surgical treatment volume (TV) of seizure-free versus non-seizure-free patients.

RESULTS

Source localization was performed on 68 seizures from 27 patients. Median distance to nearest contact in the conventional SOZ was 7 (IQR 6-12) mm for time-domain dipoles. Current density predicted ictal activity with up to 86 % (60-87 %) accuracy. Distance from time-domain dipoles to the TV was smaller (P = 0.045) in seizure-free (2 [0-4] mm) versus non-seizure-free (12 [2-17] mm) patients, and predicted surgical outcome with 91 % sensitivity and 63 % specificity. Removing near-field data from contacts within the TV negated outcome prediction (P = 0.51).

CONCLUSIONS

Source localization of SEEG accurately mapped ictal onset compared with conventional interpretation. Proximity of dipoles to the TV predicted seizure outcome when near-field recordings were analyzed.

SIGNIFICANCE

Ictal SEEG source localization is useful in corroborating the epileptogenic zone, assuming near-field recordings are obtained.

SEEG in 3D: Interictal Source Localization From Intracerebral Recordings

BACKGROUND

Stereo-electroencephalography (SEEG) uses a three-dimensional configuration of depth electrodes to localize epileptiform activity, but traditional analysis of SEEG is spatially restricted to the point locations of the electrode contacts. Interpolation of brain activity between contacts might allow for three-dimensional representation of epileptiform activity and avoid pitfalls of SEEG interpretation.

OBJECTIVE

The goal of this study was to validate SEEG-based interictal source localization and assess the ability of this technique to monitor far-field activity in non-implanted brain regions.

METHODS

Interictal epileptiform discharges were identified on SEEG in 26 patients who underwent resection, ablation, or disconnection of the suspected epileptogenic zone. Dipoles without (free) and with (scan) gray matter restriction, and current density (sLORETA and SWARM methods), were calculated using a finite element head model. Source localization results were compared to the conventional irritative zone (IZ) and the surgical treatment volumes (TV) of seizure-free vs. non-seizure-free patients.

RESULTS

The median distance from dipole solutions to the nearest contact in the conventional IZ was 7 mm (interquartile range 4-15 mm for free dipoles and 4-14 mm for scan dipoles). The IZ modeled with SWARM predicted contacts within the conventional IZ with 83% (75-100%) sensitivity and 94% (88-100%) specificity. The proportion of current within the TV was greater in seizure-free patients (P = 0.04) and predicted surgical outcome with 45% sensitivity and 93% specificity. Dipole solutions and sLORETA results did not correlate with seizure outcome. Addition of scalp EEG led to more superficial modeled sources (P = 0.03) and negated the ability to predict seizure outcome (P = 0.23). Removal of near-field data from contacts within the TV resulted in smearing of the current distribution (P = 0.007) and precluded prediction of seizure freedom (P = 0.20).

CONCLUSIONS

Source localization accurately represented interictal discharges from SEEG. The proportion of current within the TV distinguished between seizure-free and non-seizure-free patients when near-field recordings were obtained from the surgical target. The high prevalence of deep sources in this cohort likely obscured any benefit of concurrent scalp EEG. SEEG-based interictal source localization is useful in illustrating and corroborating the epileptogenic zone. Additional techniques are needed to localize far-field epileptiform activity from non-implanted brain regions.

Multimodal Neuroimaging Using Concurrent EEG/fNIRS for Poststroke Recovery Assessment: An Exploratory Study

Background

Persistent motor deficits are very common in poststroke survivors and often lead to disability. Current clinical measures for profiling motor impairment and assessing poststroke recovery are largely subjective and lack precision.

Objective

A multimodal neuroimaging approach was developed based on concurrent functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) to identify biomarkers associated with motor function recovery and document the poststroke cortical reorganization.

Methods

EEG and fNIRS data were simultaneously recorded from 9 healthy controls and 18 stroke patients during a hand-clenching task. A novel fNIRS-informed EEG source imaging approach was developed to estimate cortical activity and functional connectivity. Subsequently, graph theory analysis was performed to identify network features for monitoring and predicting motor function recovery during a 4-week intervention.

Results

The task-evoked strength at ipsilesional primary somatosensory cortex was significantly lower in stroke patients compared with healthy controls ( P < .001). In addition, across the 4-week rehabilitation intervention, the strength at ipsilesional premotor cortex (PMC) ( R = 0.895, P = .006) and the connectivity between bilateral primary motor cortices (M1) ( R = 0.9, P = .007) increased in parallel with the improvement of motor function. Furthermore, a higher baseline strength at ipsilesional PMC was associated with a better motor function recovery ( R = 0.768, P = .007), while a higher baseline connectivity between ipsilesional supplementary motor cortex (SMA)–M1 implied a worse motor function recovery ( R = −0.745, P = .009).

Conclusion

The proposed multimodal EEG/fNIRS technique demonstrates a preliminary potential for monitoring and predicting poststroke motor recovery. We expect such findings can be further validated in future study.

Localization of deep brain activity with scalp and subdural EEG

To what extent electrocorticography (ECoG) and electroencephalography (scalp EEG) differ in their capability to locate sources of deep brain activity is far from evident. Compared to EEG, the spatial resolution and signal-to-noise ratio of ECoG is superior but its spatial coverage is more restricted, as is arguably the volume of tissue activity effectively measured from. Moreover, scalp EEG studies are providing evidence of locating activity from deep sources such as the hippocampus using high-density setups during quiet wakefulness. To address this question, we recorded a multimodal dataset from 4 patients with refractory epilepsy during quiet wakefulness. This data comprises simultaneous scalp, subdural and depth EEG electrode recordings. The latter was located in the hippocampus or insula and provided us with our "ground truth" for source localization of deep activity. We applied independent component analysis (ICA) for the purpose of separating the independent sources in theta, alpha and beta frequency band activity. In all patients subdural- and scalp EEG components were observed which had a significant zero-lag correlation with one or more contacts of the depth electrodes. Subsequent dipole modeling of the correlating components revealed dipole locations that were significantly closer to the depth electrodes compared to the dipole location of non-correlating components. These findings support the idea that components found in both recording modalities originate from neural activity in close proximity to the depth electrodes. Sources localized with subdural electrodes were ~70% closer to the depth electrode than sources localized with EEG with an absolute improvement of around ~2cm. In our opinion, this is not a considerable improvement in source localization accuracy given that, for clinical purposes, ECoG electrodes were implanted in close proximity to the depth electrodes. Furthermore, the ECoG grid attenuates the scalp EEG, due to the electrically isolating silastic sheets in which the ECoG electrodes are embedded. Our results on dipole modeling show that the deep source localization accuracy of scalp EEG is comparable to that of ECoG. SIGNIFICANCE STATEMENT: Deep and subcortical regions play an important role in brain function. However, as joint recordings at multiple spatial scales to study brain function in humans are still scarce, it is still unresolved to what extent ECoG and EEG differ in their capability to locate sources of deep brain activity. To the best of our knowledge, this is the first study presenting a dataset of simultaneously recorded EEG, ECoG and depth electrodes in the hippocampus or insula, with a focus on non-epileptiform activity (quiet wakefulness). Furthermore, we are the first study to provide experimental findings on the comparison of source localization of deep cortical structures between invasive and non-invasive brain activity measured from the cortical surface.

Clinical Relevance of Interictal Spikes in Tumor-Related Epilepsy: An Electrocorticographic Study

Background and Purpose

Although some surgeons utilize interictal spikes recorded via electrocorticography (ECoG) when planning extensive peritumoral resection in patients with tumor-related epilepsy, the association between interictal spikes and epileptogenesis has not been fully described. We investigated whether the resection of interictal spikes recorded by ECoG is associated with more favorable surgical outcomes in tumor-related epilepsy.

Methods

Of 132 patients who underwent epilepsy surgery for tumor-related epilepsy from 2006 to 2013, seven patients who underwent extraoperative ECoG were included in this study. In each patient, ECoG interictal spike sources were localized using standardized low-resolution brain electromagnetic tomography and were co-registered into a reconstructed brain model. Correspondence to the resection volume was estimated by calculating the percentage of interictal spike sources in the resection volume.

Results

All patients achieved gross total resection without oncological recurrence. Five patients achieved favorable surgical outcomes, whereas the surgical outcomes of two patients were unfavorable. Correspondence rates to the resection volume in the favorable and unfavorable surgical outcome groups were 44.6%±27.8% and 43.5%±22.8%, respectively (p=0.96). All patients had interictal spike source clusters outside the resection volume regardless of seizure outcome.

Conclusions

In these cases of tumor-related epilepsy, the extent of the resection of ECoG interictal spikes was not associated with postoperative seizure outcomes. Furthermore, the presence of interictal spike sources outside of the resection area was not related to seizure outcomes. Instead, concentrating more on the complete removal of the brain tumor appears to be a rational approach.

Decoding Movement From Electrocorticographic Activity: A Review

Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.

Characterizing the role of the structural connectome in seizure dynamics

How does the human brain's structural scaffold give rise to its intricate functional dynamics? This is a central question in translational neuroscience that is particularly relevant to epilepsy, a disorder affecting over 50 million subjects worldwide. Treatment for medication-resistant focal epilepsy is often structural-through surgery or laser ablation-but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG. Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structure-function coupling, specifically between white matter connections and intracranial EEG, across pre-ictal and ictal periods in 45 seizures from nine patients with unilateral drug-resistant focal epilepsy. We use high angular resolution diffusion imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequency-specific functional networks derived from coregistered intracranial EEG. Across all frequency bands, we find significant increases in structure-function coupling from pre-ictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are highly stereotyped for each patient. These results suggest that seizures harness the underlying structural connectome as they propagate. Mapping the relationship between structural and functional connectivity in epilepsy may inform new therapies to halt seizure spread, and pave the way for targeted patient-specific interventions.

Global Innervation Zone Identification With High-Density Surface Electromyography

OBJECTIVE

The aim of this study is to compare the performance of three strategies in determining the global innervation zone (IZ) distribution.

METHODS

High-density surface electromyography was recorded from the biceps brachii muscle of seven healthy subjects under isometric voluntary contractions at 20%, 50%, and 100% of the maximal voluntary contraction and supramaximal musculocutaneous nerve stimulations. IZs were detected: first, by visual identification in a column-specific manner (IZ-1D); second, based on decomposed bipolar mapping of motor unit action potentials (IZ-2D); and third, by source imaging in the three-dimensional muscle space (IZ-3D).

RESULTS

All three IZ detection approaches have exhibited excellent trial-to-trial repeatability. Consistent IZ results were found in the axial direction of the arm across all three approaches, yet a difference was observed in the mediolateral direction.

CONCLUSIONS

Among all three approaches, IZ-3D is capable of providing the most comprehensive information regarding the global IZ distribution, while maintaining high consistency with IZ-1D and IZ-2D results.

SIGNIFICANCE

IZ-3D approach can be a potential tool for global IZ imaging, which is critical to the clinical diagnosis and treatment of neuromuscular disorders.

Electrophysiological Brain Connectivity: Theory and Implementation

We review the theory and algorithms of electrophysiological brain connectivity analysis. This tutorial is aimed at providing an introduction to brain functional connectivity from electrophysiological signals, including electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG), stereoelectroencephalography (SEEG). Various connectivity estimators are discussed, and algorithms introduced. Important issues for estimating and mapping brain functional connectivity with electrophysiology are discussed.

Three dimensional innervation zone imaging in spastic muscles of stroke survivors

OBJECTIVE

The outcome of botulinum toxin (BTX) therapy of post-stroke spasticity relies largely on accuracy of BTX injection to the proximity of innervation zones (IZs). Recently developed three-dimensional IZ imaging (3DIZI) is the only technique currently available to provide 3D distributions of IZs in vivo, yet its performance has not been validated under pathological conditions.

APPROACH

The performance of 3DIZI was evaluated in the spastic biceps brachii muscles of four chronic stroke subjects. High-density surface electromyography (sEMG) and intramuscular electromyography (iEMG) were simultaneously recorded. The IZ location in the 3D space of the spastic biceps calculated using the 3DIZI technique from sEMG recordings were compared against the IZ location detected using intramuscular wires.

MAIN RESULTS

3DIZI successfully reconstructed the IZs in the 3D space of the spastic biceps of all four stroke subjects, with a localization error of 4.7  ±  2.7 mm, and specifically a depth error of 1.8  ±  0.4 mm.

SIGNIFICANCE

Results have demonstrated the robust performance of 3DIZI under pathological conditions, laying a solid foundation for clinical application of 3D source imaging in leading precise BTX injections for spasticity management.

Electromagnetic Brain Source Imaging by Means of a Robust Minimum Variance Beamformer

OBJECTIVE

Adaptive beamformer methods that have been extensively used for functional brain imaging using EEG/MEG (magnetoencephalography) signals are sensitive to model mismatches. We propose a robust minimum variance beamformer (RMVB) technique, which explicitly incorporates the uncertainty of the lead field matrix into the estimation of spatial-filter weights that are subsequently used to perform the imaging.

METHODS

The uncertainty of the lead field is modeled by ellipsoids in the RMVB method; these hyperellipsoids (ellipsoids in higher dimensions) define regions of uncertainty for a given nominal lead field vector. These ellipsoids are estimated empirically by sampling lead field vectors surrounding each point of the source space, or more generally by building several forward models for the source space. Once these uncertainty regions (ellipsoids) are estimated, they are used to perform the source-imaging task. Computer simulations are conducted to evaluate the performance of the proposed RMVB technique.

RESULTS

Our results show that robust beamformers can outperform conventional beamformers in terms of localization error, recovering source dynamics, and estimation of the underlying source extents when uncertainty in the lead field matrix is properly determined and modeled.

CONCLUSION

The RMVB can be substituted for conventional beamformers, especially in applications where source imaging is performed off-line, and computational speed and complexity are not of major concern.

SIGNIFICANCE

A high-quality source imaging can be utilized in various applications, such as determining the epileptogenic zone in medically intractable epilepsy patients or estimating the time course of activity, which is a required step for computing the functional connectivity of brain networks.

Source-reconstruction of the sensorimotor network from resting-state macaque electrocorticography

The discovery of hemodynamic (BOLD-fMRI) resting-state networks (RSNs) has brought about a fundamental shift in our thinking about the role of intrinsic brain activity. The electrophysiological underpinnings of RSNs remain largely elusive and it has been shown only recently that electric cortical rhythms are organized into the same RSNs as hemodynamic signals. Most electrophysiological studies into RSNs use magnetoencephalography (MEG) or scalp electroencephalography (EEG), which limits the spatial resolution with which electrophysiological RSNs can be observed. Due to their close proximity to the cortical surface, electrocorticographic (ECoG) recordings can potentially provide a more detailed picture of the functional organization of resting-state cortical rhythms, albeit at the expense of spatial coverage. In this study we propose using source-space spatial independent component analysis (spatial ICA) for identifying generators of resting-state cortical rhythms as recorded with ECoG and for reconstructing their functional connectivity. Network structure is assessed by two kinds of connectivity measures: instantaneous correlations between band-limited amplitude envelopes and oscillatory phase-locking. By simulating rhythmic cortical generators, we find that the reconstruction of oscillatory phase-locking is more challenging than that of amplitude correlations, particularly for low signal-to-noise levels. Specifically, phase-lags can both be over- and underestimated, which troubles the interpretation of lag-based connectivity measures. We illustrate the methodology on somatosensory beta rhythms recorded from a macaque monkey using ECoG. The methodology decomposes the resting-state sensorimotor network into three cortical generators, distributed across primary somatosensory and primary and higher-order motor areas. The generators display significant and reproducible amplitude correlations and phase-locking values with non-zero lags. Our findings illustrate the level of spatial detail attainable with source-projected ECoG and motivates wider use of the methodology for studying resting-state as well as event-related cortical dynamics in macaque and human.

Mapping Brain Activity with Electrocorticography: Resolution Properties and Robustness of Inverse Solutions

Electrocorticography (ECoG) is an electrophysiological technique that records brain activity directly from the cortical surface with high temporal (ms) and spatial (mm) resolution. Its major limitations are in the high invasiveness and in the restricted field-of-view of the electrode grid, which partially covers the cortex. To infer brain activity at locations different from just below the electrodes, it is necessary to solve the electromagnetic inverse problem. Limitations in the performance of source reconstruction algorithms from ECoG have been, to date, only partially addressed in the literature, and a systematic evaluation is still lacking. The main goal of this study is to provide a quantitative evaluation of resolution properties of widely used inverse methods (eLORETA and MNE) for various ECoG grid sizes, in terms of localization error, spatial dispersion, and overall amplitude. Additionally, this study aims at evaluating how the use of simultaneous electroencephalography (EEG) affects the above properties. For these purposes, we take advantage of a unique dataset in which a monkey underwent a simultaneous recording with a 128 channel ECoG grid and an 18 channel EEG grid. Our results show that, in general conditions, the reconstruction of cortical activity located more than 1 cm away from the ECoG grid is not accurate, since the localization error increases linearly with the distance from the electrodes. This problem can be partially overcome by recording simultaneously ECoG and EEG. However, this analysis enlightens the necessity to design inverse algorithms specifically targeted at taking into account the limited field-of-view of the ECoG grid.

Electromagnetic source imaging using simultaneous scalp EEG and intracranial EEG: An emerging tool for interacting with pathological brain networks

OBJECTIVE

The goal of this study is to investigate the performance, merits and limitations of source imaging using intracranial EEG (iEEG) recordings and to compare its accuracy to the results of EEG source imaging. Accuracy in this study, is measured both by determining the location and inter-nodal connectivity of underlying brain networks.

METHODS

Systematic computer simulation studies are conducted to evaluate iEEG-based source imaging vs. EEG-based source imaging, and source imaging using both EEG and iEEG. To test the source imaging models, networks of inter-connected nodes (in terms of activity) are simulated. The location of the network nodes is randomly selected within a realistic geometry head model and a connectivity link is created among these nodes based on a multi-variate auto-regressive (MVAR) model. Then the forward problem is solved to calculate the potentials at the electrodes and noise (white and correlated) is added to these simulated potentials to simulate realistic measurements. Subsequently, the inverse problem is solved and an algorithm based on principle component analysis is performed on the estimated source activities to determine the location of the simulated network nodes. The activity of these nodes (over time), is then extracted, and used to estimate the connectivity links among the mentioned nodes using Granger causality analysis.

RESULTS

Source imaging based on iEEG recordings may or may not improve the accuracy in localization, depending on the number and location of active nodes relative to iEEG electrodes and to other nodes within the network. However, our simulation results suggest that combining EEG and iEEG modalities (simultaneous scalp and intracranial recordings) can improve the imaging accuracy significantly.

CONCLUSIONS

While iEEG source imaging is useful in estimating the exact location of sources near the iEEG electrodes, combining EEG and iEEG recordings can achieve a more accurate imaging due to the high spatial coverage of the scalp electrodes and the added near field information provided by the iEEG electrodes.

SIGNIFICANCE

The present results suggest the feasibility of localizing brain electrical sources from iEEG recordings and improving EEG source localization using simultaneous EEG and iEEG recordings to cover the whole brain. The hybrid EEG and iEEG source imaging can assist the clinicians when unequivocal decisions about determining the epileptogenic zone cannot be reached using a single modality.

Imaging three-dimensional innervation zone distribution in muscles from M-wave recordings

OBJECTIVE

To localize neuromuscular junctions in skeletal muscles in vivo which is of great importance in understanding, diagnosing and managing of neuromuscular disorders.

APPROACH

A three-dimensional global innervation zone imaging technique was developed to characterize the global distribution of innervation zones, as an indication of the location and features of neuromuscular junctions, using electrically evoked high-density surface electromyogram recordings.

MAIN RESULTS

The performance of the technique was evaluated in the biceps brachii of six intact human subjects. The geometric centers of the distributions of the reconstructed innervation zones were determined with a mean distance of 9.4  ±  1.4 cm from the reference plane, situated at the medial epicondyle of the humerus. A mean depth was calculated as 1.5  ±  0.3 cm from the geometric centers to the closed points over the skin. The results are consistent with those reported in previous histology studies. It was also found that the volumes and distributions of the reconstructed innervation zones changed as the stimulation intensities increased until the supramaximal muscle response was achieved.

SIGNIFICANCE

Results have demonstrated the high performance of the proposed imaging technique in noninvasively imaging global distributions of the innervation zones in the three-dimensional muscle space in vivo, and the feasibility of its clinical applications, such as guiding botulinum toxin injections in spasticity management, or in early diagnosis of neurodegenerative progression of amyotrophic lateral sclerosis.

Spatial characterization of innervation zones under electrically elicited M-wave

The three dimensional (3D) innervation zone (IZ) imaging approach (3DIZI) has been developed in our group to localize the IZ of a particular motor unit (MU) from its motor unit action potentials decomposed from high-density surface electromyography (EMG) recordings. In this study, the developed 3DIZI approach was combined with electrical stimulation to investigate global distributions of IZs in muscles from electrically elicited M-wave recordings. Electrical stimulations were applied to the musculocutaneous nerve to activate supramaximal muscle response of the biceps brachii in one healthy subject, and high-density (128 channels) surface EMG signals of the biceps brachii muscles were recorded. The 3DIZI approach was then employed to image the IZ distribution of IZs in the 3D space of the biceps brachii. The performance of the M-wave based 3DIZI approach was evaluated with different stimulation intensities. Results show that the reconstructed IZs under supramaximal stimulation are spatially distributed in the center region of muscle belly which is consistent with previous studies. With sub-maximal stimulation intensity, the imaged IZ centers became more proximally and deeply located. The proposed M-wave based 3DIZI approach demonstrated its capability of imaging global distribution of IZs in muscles, which provide valuable information for clinical applications such as guiding botulinum toxin injection in treating muscle spasticity.

Polarity detection in ultrasound current source density imaging

Modulating the electric dipole field with ultrasound pulse, ultrasound current source density imaging (UCSDI) can detect current direction and form spatial 3D imaging of dipole changing in one period of treatment. As ultrasound pulse passes through the conductive media, it convolves/correlates with the inner product of the electric field of a dipole and lead field of a pair of detectors, making the shifting frequency of polarity lower than the center frequency of the ultrasound pulse. After acoustoelectric (AE) signal is shifted to base band, the AE voltage is positive at anode and negative at cathode. In the simulation, the lead fields of detectors and electric field of dipole were calculated by the finite element (FE) method; the convolution and correlation in the computation of AE signal were accelerated using 3-D fast Fourier transforms. The current direction and amplitude are encoded in the phase and amplitude of the AE signal. Based on the analysis of polarity algorithms on the simulated and in-vitro ultrasound current source density images, it is concluded that the cross-correlation method is significantly better than the autocorrelation method to extract the frequency shift for high pulse bandwidth.

Discrepancies between Multi-Electrode LFP and CSD Phase-Patterns: A Forward Modeling Study

Multi-electrode recordings of local field potentials (LFPs) provide the opportunity to investigate the spatiotemporal organization of neural activity on the scale of several millimeters. In particular, the phases of oscillatory LFPs allow studying the coordination of neural oscillations in time and space and to tie it to cognitive processing. Given the computational roles of LFP phases, it is important to know how they relate to the phases of the underlying current source densities (CSDs) that generate them. Although CSDs and LFPs are distinct physical quantities, they are often (implicitly) identified when interpreting experimental observations. That this identification is problematic is clear from the fact that LFP phases change when switching to different electrode montages, while the underlying CSD phases remain unchanged. In this study we use a volume-conductor model to characterize discrepancies between LFP and CSD phase-patterns, to identify the contributing factors, and to assess the effect of different electrode montages. Although we focus on cortical LFPs recorded with two-dimensional (Utah) arrays, our findings are also relevant for other electrode configurations. We found that the main factors that determine the discrepancy between CSD and LFP phase-patterns are the frequency of the neural oscillations and the extent to which the laminar CSD profile is balanced. Furthermore, the presence of laminar phase-differences in cortical oscillations, as commonly observed in experiments, precludes identifying LFP phases with those of the CSD oscillations at a given cortical depth. This observation potentially complicates the interpretation of spike-LFP coherence and spike-triggered LFP averages. With respect to reference strategies, we found that the average-reference montage leads to larger discrepancies between LFP and CSD phases as compared with the referential montage, while the Laplacian montage reduces these discrepancies. We therefore advice to conduct analysis of two-dimensional LFP recordings using the Laplacian montage.

Three-Dimensional Innervation Zone Imaging from Multi-Channel Surface EMG Recordings

There is an unmet need to accurately identify the locations of innervation zones (IZs) of spastic muscles, so as to guide botulinum toxin (BTX) injections for the best clinical outcome. A novel 3D IZ imaging (3DIZI) approach was developed by combining the bioelectrical source imaging and surface electromyogram (EMG) decomposition methods to image the 3D distribution of IZs in the target muscles. Surface IZ locations of motor units (MUs), identified from the bipolar map of their MU action potentials (MUAPs) were employed as a prior knowledge in the 3DIZI approach to improve its imaging accuracy. The performance of the 3DIZI approach was first optimized and evaluated via a series of designed computer simulations, and then validated with the intramuscular EMG data, together with simultaneously recorded 128-channel surface EMG data from the biceps of two subjects. Both simulation and experimental validation results demonstrate the high performance of the 3DIZI approach in accurately reconstructing the distributions of IZs and the dynamic propagation of internal muscle activities in the biceps from high-density surface EMG recordings.

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc.

In vivo imaging of epileptic foci in rats using a miniature probe integrating diffuse optical tomography and electroencephalographic source localization

OBJECTIVE

The goal of this work is to establish a new dual-modal brain-mapping technique based on diffuse optical tomography (DOT) and electroencephalographic source localization (ESL) that can chronically/intracranially record optical/electroencephalography (EEG) data to precisely map seizures and localize the seizure-onset zone and associated epileptic brain network.

METHODS

The dual-modal imaging system was employed to image seizures in an experimental acute bicuculline methiodide rat model of focal epilepsy. Depth information derived from DOT was used as constraint in ESL to enhance the image reconstruction. Groups of animals were compared based on localization of seizure foci, either at different positions or at different depths.

RESULTS

This novel imaging technique successfully localized the seizure-onset zone in rat induced by bicuculline methiodide injected at a depth of 1, 2, and 3 mm, respectively. The results demonstrated that the incorporation of the depth information from DOT into the ESL image reconstruction resulted in more accurate and reliable ESL images. Although the ESL images showed a horizontal shift of the source localization, the DOT identified the seizure focus accurately. In one case, when the bicuculline methiodide (BMI) was injected at a site outside the field of view (FOV) of the DOT/ESL interface, ESL gave false-positive detection of the focus, while DOT showed negative detection.

SIGNIFICANCE

This study represents the first to identify seizure-onset zone using implantable DOT. In addition, the combination of DOT/ESL has never been documented in neuroscience and epilepsy imaging. This technology will enable us to precisely measure the neural activity and hemodynamic response at exactly the same tissue site and at both cortical and subcortical levels.

Evaluating dipolar source localization feasibility from intracerebral SEEG recordings

Stereo-electroencephalography (SEEG) is considered as the golden standard for exploring targeted structures during pre-surgical evaluation in drug-resistant partial epilepsy. The depth electrodes, inserted in the brain, consist of several collinear measuring contacts (sensors). Clinical routine analysis of SEEG signals is performed on bipolar montage, providing a focal view of the explored structures, thus eliminating activities of distant sources that propagate through the brain volume. We propose in this paper to exploit the common reference SEEG signals. In this case, the volume propagation information is preserved and electrical source localization (ESL) approaches can be proposed. Current ESL approaches used to localize and estimate the activity of the neural generators are mainly based on surface EEG/MEG signals, but very few studies exist on real SEEG recordings, and the case of equivalent current dipole source localization has not been explored yet in this context. In this study, we investigate the influence of volume conduction model, spatial configuration of SEEG sensors and level of noise on the ESL accuracy, using a realistic simulation setup. Localizations on real SEEG signals recorded during intracerebral electrical stimulations (ICS, known sources) as well as on epileptic interictal spikes are carried out. Our results show that, under certain conditions, a straightforward approach based on an equivalent current dipole model for the source and on simple analytical volume conduction models yields sufficiently precise solutions (below 10mm) of the localization problem. Thus, electrical source imaging using SEEG signals is a promising tool for distant brain source investigation and might be used as a complement to routine visual interpretations.

Simulation-based validation for four- dimensional multi-channel ultrasound current source density imaging

Ultrasound current source density imaging (UCSDI), which has application to the heart and brain, exploits the acoustoelectric (AE) effect and Ohm's law to detect and map an electrical current distribution. In this study, we describe 4-D UCSDI simulations of a dipole field for comparison and validation with bench-top experiments. The simulations consider the properties of the ultrasound pulse as it passes through a conductive medium, the electric field of the injected dipole, and the lead field of the detectors. In the simulation, the lead fields of detectors and electric field of the dipole were calculated by the finite element (FE) method, and the convolution and correlation in the computation of the detected AE voltage signal were accelerated using 3-D fast Fourier transforms. In the bench-top experiment, an electric dipole was produced in a bath of 0.9% NaCl solution containing two electrodes, which injected an ac pulse (200 Hz, 3 cycles) ranging from 0 to 140 mA. Stimulating and recording electrodes were placed in a custom electrode chamber made on a rapid prototype printer. Each electrode could be positioned anywhere on an x-y grid (5 mm spacing) and individually adjusted in the depth direction for precise control of the geometry of the current sources and detecting electrodes. A 1-MHz ultrasound beam was pulsed and focused through a plastic film to modulate the current distribution inside the saline-filled tank. AE signals were simultaneously detected at a sampling frequency of 15 MHz on multiple recording electrodes. A single recording electrode is sufficient to form volume images of the current flow and electric potentials. The AE potential is sensitive to the distance from the dipole, but is less sensitive to the angle between the detector and the dipole. Multi-channel UCSDI potentially improves 4-D mapping of bioelectric sources in the body at high spatial resolution, which is especially important for diagnosing and guiding treatment of cardiac and neurologic disorders, including arrhythmia and epilepsy.

Usefulness of interictal spike source localization in temporal lobe epilepsy: electrocorticographic study

The success of epilepsy surgery depends on delineation of the suspected epileptogenic zone. The gold standard to delineate it is to use the ictal onset zone from an electrocorticography (ECoG). Although interictal spikes are also associated with the epileptogenic zone, their clinical significance has been under-evaluated. The aim of this study was to evaluate the source localization of interictal spikes in terms of the association with epileptogenic zone in surgical temporal lobe epilepsy patients. The proposition is that the resection volume in patients with favorable outcomes includes the epileptogenic zone. The association with the epileptogenic zone was assessed as follows: (1) how many of the interictal spike sources are within the resection volume in patients with favorable outcomes and (2) how many of the interictal spike sources are outside the resection volume in patients with unfavorable outcomes. Thirty-eight temporal lobe epilepsy (TLE) patients who underwent both ECoG monitoring and epilepsy surgery were recruited and their 10min of ECoG recordings were analyzed. Six tumor-related TLE patients were excluded in the analysis. Of the remaining 32 patients, 20 patients achieved favorable surgical outcomes (Engel I and II), while the surgical outcomes of 12 patients were unfavorable (Engel III and IV). In each patient, interictal spike sources were localized using sLORETA and co-registered into a reconstructed brain model. The correspondence rate with the resection volume was estimated by counting the percentage of interictal spike sources in the resection volume. The correspondence rate in patients with favorable outcomes was 72.8±22.1, which was significantly higher than that (41.2±28.8) of the patients with unfavorable outcomes (p=0.002). Nine out of twelve patients (75%) with unfavorable outcomes had multiple interictal spike source clusters both interior and exterior to the resection volume, while 4 of the 20 patients with favorable outcomes (20%) had such multiple clusters (p=0.021). In conclusion, interictal spike sources are highly associated with the epileptogenic zone. ECoG interictal spike source localization could help in the delineation of the potential resection volume.

A novel spatiotemporal muscle activity imaging approach based on the Extended Kalman Filter

A novel spatiotemporal muscle activity imaging (sMAI) approach has been developed using the Extended Kalman Filter (EKF) to reconstruct internal muscle activities from non-invasive multi-channel surface electromyogram (sEMG) recordings. A distributed bioelectric dipole source model is employed to describe the internal muscle activity space, and a linear relationship between the muscle activity space and the sEMG measurement space is then established. The EKF is employed to recursively solve the ill-posed inverse problem in the sMAI approach, in which the weighted minimum norm (WMN) method is utilized to calculate the initial state and a new nonlinear method is developed based on the propagating features of muscle activities to predict the recursive state. A series of computer simulations was conducted to test the performance of the proposed sMAI approach. Results show that the localization error rapidly decreases over 35% and the overlap ratio rapidly increases over 45% compared to the results achieved using the WMN method only. The present promising results demonstrate the feasibility of utilizing the proposed EKF-based sMAI approach to accurately reconstruct internal muscle activities from non-invasive sEMG recordings.

Noninvasive imaging of internal muscle activities from multi-channel surface EMG recordings

Surface Electromyogram (sEMG) technology provides a non-invasive way for rapid monitoring muscle activities, but its poor spatial resolution and specificity limit its application in clinic. To overcome these limitations, a noninvasive muscle activity imaging (MAI) approach has been developed and used to reconstruct internal muscle activities from multi-channel sEMG recordings. A realistic geometric hand model is developed from high-resolution MR images and a distributed bioelectric dipole source model is employed to describe the internal muscle activity space of the muscles. The finite element method and weighted minimum norm method are utilized solve the forward and inverse problems respectively involved in the proposed MAI technique. A series of computer simulations was conducted to test the performance of the proposed MAI approach. Results show that reconstruction results achieved by the MAI technique indeed provide us more detailed and dynamic information of internal muscle activities, which enhance our understanding of the mechanisms underlying the surface EMG recordings.

Co-localizing linguistic and musical syntax with intracranial EEG

Despite general agreement on shared syntactic resources in music and language, the neuroanatomical underpinnings of this overlap remain largely unexplored. While previous studies mainly considered frontal areas as supramodal grammar processors, the domain-general syntactic role of temporal areas has been so far neglected. Here we capitalized on the excellent spatial and temporal resolution of subdural EEG recordings to co-localize low-level syntactic processes in music and language in the temporal lobe in a within-subject design. We used Brain Surface Current Density mapping to localize and compare neural generators of the early negativities evoked by violations of phrase structure grammar in both music and spoken language. The results show that the processing of syntactic violations relies in both domains on bilateral temporo-fronto-parietal neural networks. We found considerable overlap of these networks in the superior temporal lobe, but also differences in the hemispheric timing and relative weighting of their fronto-temporal constituents. While alluding to the dissimilarity in how shared neural resources may be configured depending on the musical or linguistic nature of the perceived stimulus, the combined data lend support for a co-localization of early musical and linguistic syntax processing in the temporal lobe.

EEG source imaging in epilepsy--practicalities and pitfalls

EEG source imaging (ESI) is a model-based imaging technique that integrates temporal and spatial components of EEG to identify the generating source of electrical potentials recorded on the scalp. Recent advances in computer technologies have made the analysis of ESI data less time-consuming, and have rekindled interest in this technique as a clinical diagnostic tool. On the basis of the available body of evidence, ESI seems to be a promising tool for epilepsy evaluation; however, the precise clinical value of ESI in presurgical evaluation of epilepsy and in localization of eloquent cortex remains to be investigated. In this Review, we describe two fundamental issues in ESI; namely, the forward and inverse problems, and their solutions. The clinical application of ESI in surgical planning for patients with medically refractory focal epilepsy, and its use in source reconstruction together with invasive recordings, is also discussed. As ESI can be used to map evoked responses, we discuss the clinical utility of this technique in cortical mapping-an essential process when planning resective surgery for brain regions that are in close proximity to eloquent cortex.

Source cancellation profiles of electroencephalography and magnetoencephalography

Recorded electric potentials and magnetic fields due to cortical electrical activity have spatial spread even if their underlying brain sources are focal. Consequently, as a result of source cancellation, loss in signal amplitude and reduction in the effective signal-to-noise ratio can be expected when distributed sources are active simultaneously. Here we investigate the cancellation effects of EEG and MEG through the use of an anatomically correct forward model based on structural MRI acquired from 7 healthy adults. A boundary element model (BEM) with four compartments (brain, cerebrospinal fluid, skull and scalp) and highly accurate cortical meshes (~300,000 vertices) were generated. Distributed source activations were simulated using contiguous patches of active dipoles. To investigate cancellation effects in both EEG and MEG, quantitative indices were defined (source enhancement, cortical orientation disparity) and computed for varying values of the patch radius as well as for automatically parcellated gyri and sulci. Results were calculated for each cortical location, averaged over all subjects using a probabilistic atlas, and quantitatively compared between MEG and EEG. As expected, MEG sensors were found to be maximally sensitive to signals due to sources tangential to the scalp, and minimally sensitive to radial sources. Compared to EEG, however, MEG was found to be much more sensitive to signals generated antero-medially, notably in the anterior cingulate gyrus. Given that sources of activation cancel each other according to the orientation disparity of the cortex, this study provides useful methods and results for quantifying the effect of source orientation disparity upon source cancellation.

Inverse current source density method in two dimensions: inferring neural activation from multielectrode recordings

The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets.

Source connectivity analysis from MEG and its application to epilepsy source localization

We report an approach to perform source connectivity analysis from MEG, and initially evaluate this approach to interictal MEG to localize epileptogenic foci and analyze interictal discharge propagations in patients with medically intractable epilepsy. Cortical activities were reconstructed from MEG using individual realistic geometry boundary element method head models. Directional connectivity among cortical regions of interest was then estimated using directed transfer function. The MEG source connectivity analysis method was implemented in the eConnectome software, which is open-source and freely available at http://econnectome.umn.edu . As an initial evaluation, the method was applied to study MEG interictal spikes from five epilepsy patients. Estimated primary epileptiform sources were consistent with surgically resected regions, suggesting the feasibility of using cortical source connectivity analysis from interictal MEG for potential localization of epileptiform activities.

Kernel current source density method

Local field potentials (LFP), the low-frequency part of extracellular electrical recordings, are a measure of the neural activity reflecting dendritic processing of synaptic inputs to neuronal populations. To localize synaptic dynamics, it is convenient, whenever possible, to estimate the density of transmembrane current sources (CSD) generating the LFP. In this work, we propose a new framework, the kernel current source density method (kCSD), for nonparametric estimation of CSD from LFP recorded from arbitrarily distributed electrodes using kernel methods. We test specific implementations of this framework on model data measured with one-, two-, and three-dimensional multielectrode setups. We compare these methods with the traditional approach through numerical approximation of the Laplacian and with the recently developed inverse current source density methods (iCSD). We show that iCSD is a special case of kCSD. The proposed method opens up new experimental possibilities for CSD analysis from existing or new recordings on arbitrarily distributed electrodes (not necessarily on a grid), which can be obtained in extracellular recordings of single unit activity with multiple electrodes.

Three-dimensional visualization of subdural electrodes for presurgical planning

BACKGROUND

Accurate localization and visualization of subdural electrodes implanted for intracranial electroencephalography in cases of medically refractory epilepsy remains a challenging clinical problem.

OBJECTIVE

We introduce a technique for creating accurate 3-dimensional (3D) brain models with electrode overlays, ideal for resective surgical planning.

METHODS

Our procedure uses postimplantation magnetic resonance imaging (MRI) and computed tomographic (CT) imaging to create 3D models of compression-affected brain combined with intensity-thresholded CT-derived electrode models using freely available software. Footprints, or "shadows," beneath electrodes are also described for better visualization of sulcus-straddling electrodes. Electrode models were compared with intraoperative photography for validation.

RESULTS

Realistic representations of intracranial electrode positions on patient-specific postimplantation MRI brain renderings were reliably created and proved accurate when compared with photographs. Electrodes placed interhemispherically were also visible with our rendering technique. Electrode shadows were useful in locating electrodes that straddle sulci.

CONCLUSION

We present an accurate method for visualizing subdural electrodes on brain compression effected 3D models that serves as an ideal platform for surgical planning.

Computed basis functions for finite element analysis based on tomographic data

In bioelectromagnetics, the structures in which the electromagnetic field is to be computed are sometimes defined by a fine grid of voxels (3-D cells) whose tissue types are obtained by tomography. A novel finite element method is proposed for such cases. A simple, regular mesh of cube elements is constructed, each containing the same, integer number of voxels. There may be several different tissues present within an element, but this is accommodated by computing element basis functions that approximately respect the interface conditions between different tissues. Results are presented for a test model of 128 (3) voxels, consisting of nested dielectric cubes, driven by specified charges. The electrostatic potential computed with the new method agrees well with that of a conventional finite element code: the rms difference along the sample line is 1.5% of the highest voltage. Results are also presented for the potential due to a current dipole placed in a brain model of 181 × 217 × 181 voxels, derived from MRI data. The new method gives potentials that are different to those obtained by treating each voxel as an element by 1% of the peak voltage, yet the global finite element matrix has a dimension which is more than 50 times smaller.

sLORETA allows reliable distributed source reconstruction based on subdural strip and grid recordings

Source localization based on invasive recordings by subdural strip and grid electrodes is a topic of increasing interest. This simulation study addresses the question, which factors are relevant for reliable source reconstruction based on sLORETA. MRI and electrode positions of a patient undergoing invasive presurgical epilepsy diagnostics were the basis of sLORETA simulations. A boundary element head model derived from the MRI was used for the simulation of electrical potentials and source reconstruction. Focal dipolar sources distributed on a regular three-dimensional lattice and spatiotemporal distributed patches served as input for simulation. In addition to the distance between original and reconstructed source maxima, the activation volume of the reconstruction and the correlation of time courses between the original and reconstructed sources were investigated. Simulations were supplemented by the localization of the patient's spike activity. For noise-free simulated data, sLORETA achieved results with zero localization error. Added noise diminished the percentage of reliable source localizations with a localization error ≤15 mm to 67.8%. Only for source positions close to the electrode contacts the activation volume correctly represented focal generators. Time-courses of original and reconstructed sources were significantly correlated. The case study results showed accurate localization. sLORETA is a distributed source model, which can be applied for reliable grid and strip based source localization. For distant source positions, overestimation of the extent of the generator has to be taken into account. sLORETA-based source reconstruction has the potential to improve the localization of distributed generators in presurgical epilepsy diagnostics and cognitive neuroscience.

MEG/EEG source reconstruction, statistical evaluation, and visualization with NUTMEG

NUTMEG is a source analysis toolbox geared towards cognitive neuroscience researchers using MEG and EEG, including intracranial recordings. Evoked and unaveraged data can be imported to the toolbox for source analysis in either the time or time-frequency domains. NUTMEG offers several variants of adaptive beamformers, probabilistic reconstruction algorithms, as well as minimum-norm techniques to generate functional maps of spatiotemporal neural source activity. Lead fields can be calculated from single and overlapping sphere head models or imported from other software. Group averages and statistics can be calculated as well. In addition to data analysis tools, NUTMEG provides a unique and intuitive graphical interface for visualization of results. Source analyses can be superimposed onto a structural MRI or headshape to provide a convenient visual correspondence to anatomy. These results can also be navigated interactively, with the spatial maps and source time series or spectrogram linked accordingly. Animations can be generated to view the evolution of neural activity over time. NUTMEG can also display brain renderings and perform spatial normalization of functional maps using SPM's engine. As a MATLAB package, the end user may easily link with other toolboxes or add customized functions.

3D visualization of subdural electrode shift as measured at craniotomy reopening

PURPOSE

Subdural electrodes are implanted for recording intracranial EEG (iEEG) in cases of medically refractory epilepsy as a means to locate cortical regions of seizure onset amenable to surgical resection. Without the aid of imaging-derived 3D electrode models for surgical planning, surgeons have relied on electrodes remaining stationary from the time between placement and follow-up resection. This study quantifies electrode shift with respect to the cortical surface occurring between electrode placement and subsequent reopening.

METHODS

CT and structural MRI data were gathered following electrode placement on 10 patients undergoing surgical epilepsy treatment. MRI data were used to create patient specific post-grid 3D reconstructions of cortex, while CT data were co-registered to the MRI and thresholded to reveal electrodes only. At the time of resective surgery, the craniotomy was reopened and electrode positions were determined using intraoperative navigational equipment. Changes in position were then calculated between CT coordinates and intraoperative electrode coordinates.

RESULTS

Five out of ten patients showed statistically significant overall magnitude differences in electrode positions (mean: 7.2mm), while 4 exhibited significant decompression based shift (mean: 4.7mm), and 3 showed significant shear displacement along the surface of the brain (mean: 7.1mm).

DISCUSSION

Shift in electrode position with respect to the cortical surface has never been precisely measured. We show that in 50% of our cases statistically significant shift occurred. These observations demonstrate the potential utility of complimenting electrode position measures at the reopening of the craniotomy with 3D electrode and brain surface models derived from post-implantation CT and MR imaging for better definition of surgical boundaries.

Dipole source analyses of early median nerve SEP components obtained from subdural grid recordings

The median nerve N20 and P22 SEP components constitute the initial response of the primary somatosensory cortex to somatosensory stimulation of the upper extremity. Knowledge of the underlying generators is important both for basic understanding of the initial sequence of cortical activation and to identify landmarks for eloquent areas to spare in resection planning of cortex in epilepsy surgery. We now set out to localize the N20 and P22 using subdural grid recording with special emphasis on the question of the origin of P22: Brodmann area 4 versus area 1. Electroencephalographic dipole source analysis of the N20 and P22 responses obtained from subdural grids over the primary somatosensory cortex after median nerve stimulation was performed in four patients undergoing epilepsy surgery. Based on anatomical landmarks, equivalent current dipoles of N20 and P22 were localized posterior to (n = 2) or on the central sulcus (n = 2). In three patients, the P22 dipole was located posterior to the N20 dipole, whereas in one patient, the P22 dipole was located on the same coordinate in anterior-posterior direction. On average, P22 sources were found to be 6.6 mm posterior [and 1 mm more superficial] compared with the N20 sources. These data strongly suggest a postcentral origin of the P22 SEP component in Brodmann area 1 and render a major precentral contribution to the earliest stages of processing from the primary motor cortex less likely.

Improved EEG source analysis using low-resolution conductivity estimation in a four-compartment finite element head model

Bioelectric source analysis in the human brain from scalp electroencephalography (EEG) signals is sensitive to geometry and conductivity properties of the different head tissues. We propose a low-resolution conductivity estimation (LRCE) method using simulated annealing optimization on high-resolution finite element models that individually optimizes a realistically shaped four-layer volume conductor with regard to the brain and skull compartment conductivities. As input data, the method needs T1- and PD-weighted magnetic resonance images for an improved modeling of the skull and the cerebrospinal fluid compartment and evoked potential data with high signal-to-noise ratio (SNR). Our simulation studies showed that for EEG data with realistic SNR, the LRCE method was able to simultaneously reconstruct both the brain and the skull conductivity together with the underlying dipole source and provided an improved source analysis result. We have also demonstrated the feasibility and applicability of the new method to simultaneously estimate brain and skull conductivity and a somatosensory source from measured tactile somatosensory-evoked potentials of a human subject. Our results show the viability of an approach that computes its own conductivity values and thus reduces the dependence on assigning values from the literature and likely produces a more robust estimate of current sources. Using the LRCE method, the individually optimized four-compartment volume conductor model can, in a second step, be used for the analysis of clinical or cognitive data acquired from the same subject.

Influence of white matter anisotropic conductivity on EEG source localization: comparison to fMRI in human primary visual cortex

OBJECTIVE

The goal of this study was to experimentally investigate the influence of the anisotropy of white matter (WM) conductivity on EEG source localization.

METHODS

Visual evoked potentials (VEP) and fMRI data were recorded from three human subjects presented with identical visual stimuli. A finite element method was used to solve the EEG forward problems based on both anisotropic and isotropic head models, and single-dipole source localization was subsequently performed to localize the source underlying the N75 VEP component.

RESULTS

The averaged distances of the localized N75 dipole locations in V1 between the isotropic and anisotropic head models ranged from 0 to 6.22+/-2.83mm. The distances between the localized dipole positions and the centers of the fMRI V1 activations were slightly smaller when using an anisotropic model (7.49+/-1.35-15.70+/-8.60mm) than when using an isotropic model (7.65+/-1.30-15.31+/-9.18mm).

CONCLUSIONS

Anisotropic models incorporating realistic WM anisotropic conductivity distributions do not substantially improve the accuracy of EEG dipole localization in the primary visual cortex using experimental data obtained using visual stimulation.

SIGNIFICANCE

The present study represents the first attempt using a human experimental approach to assess the effects of WM anisotropy on EEG source analysis.