Inverse modeling in magnetic source imaging: Comparison of MUSIC, SAM(g2), and sLORETA to interictal intracranial EEG

Groep, Karin de Gooijer-van de L.; Leijten, Frans S.S.; Ferrier, Cyrille H.; Huiskamp, Geertjan

doi:10.1002/hbm.22049

Cited by 38 publications

(37 citation statements)

References 32 publications

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“…MUSIC has been successfully used in the past for EEG or MEG (Gavaret et al 2009;de Gooijer-van de Groep et al 2013). In this previous study (Gavaret et al 2009), MUSIC gave similar results to single dipole analysis.…”

Section: Discussionsupporting

confidence: 62%

Magnetic Source Imaging in Posterior Cortex Epilepsies

et al. 2014

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Posterior cortex epilepsies (PCE) are characterized by less satisfying postoperative results than temporal lobe epilepsies and are thus challenging for non-invasive presurgical investigations. The objective of this study was to evaluate the performance of magnetic source imaging (MSI) in PCE, validating the results by the SEEG (stereoelectroencephalography) definition of irritative and epileptogenic zones (IZ and EZ). Fourteen PCE surgery candidates were investigated using MSI and SEEG. LCMV (Linearly Constrained Minimum Variance) and MUSIC algorithms were used. IZ was quantified using a semi-automatic detection of interictal spikes. EZ was quantified using the epileptogenicity index (EI) method that accounts for both the propensity of a brain area to generate rapid discharges and the time for this area to get involved in the seizure. EI values range from 0 (no epileptogenicity) to 1 (maximal epileptogenicity). Levels of concordance between MSI and IZ, MSI and EZ were determined as follows: A = localized on MSI and SEEG for the site of value 1 (IZ and EZ quantification), B = localized on MSI and SEEG for a part of the IZ or a structure involved in the EZ (without the maximal value 1), C = localized on MSI and not SEEG, D = localized on SEEG and not MSI, E = localized on MSI and SEEG, discordant for site. Five PCE cases were characterized by focal IZ, nine by distributed IZ between several distant brain areas. MSI allowed to determinate IZ in 4/5 focal IZ cases. In case of distributed IZ, levels of concordance were A (2 cases), B (4 cases) and D (3 cases). In most distributed cases, MSI allowed to localize only a part of the IZ. Medial temporal involvement in the IZ was frequent (9/12 cases) and not evidenced by MSI. The brain area that demonstrated the maximal value of EI was shown by MSI in four out of five (80 %) focal IZ cases, in two out of nine (22 %) distributed cases. MSI results depend on IZ characteristics. A distributed IZ organization presents difficulties for MSI and highlights the need for further methodological approaches.

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Section: Discussionsupporting

confidence: 62%

Magnetic Source Imaging in Posterior Cortex Epilepsies

et al. 2014

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“…Building on previous reports (Mosher and Leahy, 1998; Vrba and Robinson, 2001; De Gooijer-Van De Groep, 2013), the mathematic relationship between measured MEG data and source activity can be expressed as following equation:

B = L Q + N

…”

Section: Methodsmentioning

confidence: 99%

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals

Xiang

Luo

Kotecha

et al. 2014

Front. Neuroinform.

129

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Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstation's memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2–3 days and used 1–2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory.

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“…It is possible, but unlikely, that the differences between results from the two source localisation methods arises from differences in head model. The multi-sphere head model has been widely used with beamformers (e.g 193334 and comparable accuracy compared to BEM models35.…”

Section: Discussionmentioning

confidence: 99%

Localising the auditory N1m with event-related beamformers: localisation accuracy following bilateral and unilateral stimulation

Gascoyne

Furlong

Hillebrand

et al. 2016

Sci Rep

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The auditory evoked N1m-P2m response complex presents a challenging case for MEG source-modelling, because symmetrical, phase-locked activity occurs in the hemispheres both contralateral and ipsilateral to stimulation. Beamformer methods, in particular, can be susceptible to localisation bias and spurious sources under these conditions. This study explored the accuracy and efficiency of event-related beamformer source models for auditory MEG data under typical experimental conditions: monaural and diotic stimulation; and whole-head beamformer analysis compared to a half-head analysis using only sensors from the hemisphere contralateral to stimulation. Event-related beamformer localisations were also compared with more traditional single-dipole models. At the group level, the event-related beamformer performed equally well as the single-dipole models in terms of accuracy for both the N1m and the P2m, and in terms of efficiency (number of successful source models) for the N1m. The results yielded by the half-head analysis did not differ significantly from those produced by the traditional whole-head analysis. Any localisation bias caused by the presence of correlated sources is minimal in the context of the inter-individual variability in source localisations. In conclusion, event-related beamformers provide a useful alternative to equivalent-current dipole models in localisation of auditory evoked responses.

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Inverse modeling in magnetic source imaging: Comparison of MUSIC, SAM(g2), and sLORETA to interictal intracranial EEG

Cited by 38 publications

References 32 publications

Magnetic Source Imaging in Posterior Cortex Epilepsies

Magnetic Source Imaging in Posterior Cortex Epilepsies

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals

Localising the auditory N1m with event-related beamformers: localisation accuracy following bilateral and unilateral stimulation

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