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Akhtari, Massoud; Bryant, H. C.; Mamelak, Adam N.; Heller, L.; Shih, Jerry J.; Mandelkern, Mark; Matlachov, A.N.; Ranken, Doug; Best, Elaine; Sutherling, William W.

doi:10.1023/a:1007882102297

Cited by 42 publications

(15 citation statements)

References 65 publications

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“…In step 1 of Algorithm 2, we used a set of 11 different conductivity parameters in the range between 0.0016 S/m [71] and 0.033 S/m [55] (x-axis in Figure 3). In Figure 3, the differences in source reconstruction to the calibrated head models (indicated by the bar) when using other skull conductivity parameters are indicated by boxes with dashed frames: Differences are shown in source location x (top row, in mm), orientation o 2 (middle row, in degree) and strength m 2 (bottom row, in %).…”

Section: Resultsmentioning

confidence: 99%

Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

et al. 2014

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To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data.

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Section: Resultsmentioning

confidence: 99%

Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

et al. 2014

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“…For uniform materials, conductance is independent of layer thickness. However, the skull has three layers, two outer compacta layers (reported conductivity 2.25 mS/m) with an intermediate spongiform layer (7.73 mS/m) between them (Akhtari et al, 2000). These authors measured skull layer thicknesses and conductivities in four subjects and found no strong dependence between the thickness of the individual skull layers and their respective conductivities.…”

Section: Discussionmentioning

confidence: 99%

Simultaneous head tissue conductivity and EEG source location estimation

Acar

Makeig

2016

NeuroImage

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Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3 cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15 cm2-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm2-scale accurate 3-D functional cortical imaging modality.

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“…We distinguished between conductivities of cancelous and cortical bone because of the large electrical property differences between these tissues (Akhtari et al, 2000, 2002; Sadleir and Argibay, 2007). …”

Section: Methodsmentioning

confidence: 99%

Target Optimization in Transcranial Direct Current Stimulation

Sadleir¹,

Vannorsdall²,

Schretlen³

et al. 2012

Front. Psychiatry

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Transcranial direct current stimulation (tDCS) is an emerging neuromodulation therapy that has been experimentally determined to affect a wide range of behaviors and diseases ranging from motor, cognitive, and memory processes to depression and pain syndromes. The effects of tDCS may be inhibitory or excitatory, depending on the relative polarities of electrodes and their proximity to different brain structures. This distinction is believed to relate to the interaction of current flow with activation thresholds of different neural complexes. tDCS currents are typically applied via a single pair of large electrodes, with one (the active electrode) sited close to brain structures associated with targeted processes. To efficiently direct current toward the areas presumed related to these effects, we devised a method of steering current toward a selected area by reference to a 19-electrode montage applied to a high-resolution finite element model of the head. We used a non-linear optimization procedure to maximize mean current densities inside the left inferior frontal gyrus (IFG), while simultaneously restricting overall current, and median current densities within the accumbens. We found that a distributed current pattern could be found that would indeed direct current toward the IFG in this way, and compared it to other candidate 2-electrode configurations. Further, we found a combination of four anterior-posterior electrodes could direct current densities to the accumbens. We conclude that a similar method using multiple electrodes may be a useful means of directing current toward or away from specific brain regions and also of reducing tDCS side effects.

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Untitled

Cited by 42 publications

References 65 publications

Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

Simultaneous head tissue conductivity and EEG source location estimation

Target Optimization in Transcranial Direct Current Stimulation

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