MEG’s ability to localise accurately weak transient neural sources

Papadelis, Christos; Poghosyan, Vahe; Fenwick, Peter B.C.; Ioannides, Andreas A.

doi:10.1016/j.clinph.2009.08.018

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Volume 120, Issue 11 , Pages 1958-1970, November 2009

MEG’s ability to localise accurately weak transient neural sources

Christos Papadelis
- Laboratory for Human Brain Dynamics, Brain Science Institute (BSI), RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
- Laboratory of Functional Neuroimaging, Center for Mind/Brain Sciences (CIMeC), University of Trento, Via delle Regole 101, 38060 Mattarello (TN), Italy
- Corresponding author. Address: Laboratory of Functional Neuroimaging, Center for Mind/Brain Sciences (CIMeC), University of Trento, Via delle Regole 101, 38060 Mattarello (TN), Italy. Tel.: +39 0461 88 2779; fax: +39 0461 88 3066.
Vahe Poghosyan
- Laboratory for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Office 501, Galaxias Building Block A, 33 Arch. Makarios III Avenue, 1065, Nicosia, Cyprus
- Laboratory for Human Brain Dynamics, Brain Science Institute (BSI), RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
Peter B.C. Fenwick
- Laboratory for Human Brain Dynamics, Brain Science Institute (BSI), RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
Andreas A. Ioannides
- Laboratory for Human Brain Dynamics, Brain Science Institute (BSI), RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
- Laboratory for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Office 501, Galaxias Building Block A, 33 Arch. Makarios III Avenue, 1065, Nicosia, Cyprus

Accepted 31 August 2009.

Abstract

Objective

To investigate the accurate localisation of weak, transient, neural sources under conditions of varying difficulty.

Methods

Multiple dipolar sources placed within a head-shaped phantom at superficial and deep locations were driven separately or simultaneously by a short-lasting current with varied amplitudes. Artificial MEG signals that were very similar to the human High Frequency Oscillations (HFO) were produced. MEG signals of HFO were also recorded from median nerve stimulation. Different inverse techniques were used to localise the phantom dipoles and the human HFO generators.

Results

The human HFO were measured around 200 and 600Hz by using only 120 trials. The 200Hz HFO were localised to BA3b. The superficial phantom’s source was localised with an accuracy of 2–3mm by all inverse techniques (120 trials). The ‘subcortical’ source was localised with an error of ∼5mm. Localisation of deeper ‘thalamic’ sources required more trials.

Conclusion

MEG can detect and localise weak transient activations and the human HFO with an accuracy of a few mm at cortical and subcortical regions even when a small number of trials are used.

Significance

Localizing HFO to specific anatomical structures has high clinical utility, for example in epilepsy, where discrete HFO appears to be generated just before focal epileptic activity.

Keywords: MEG, High Frequency Oscillations, Localisation, Phantom, ECD, MUSIC, SAM, MFT

Abbreviations: Av-ECD, Equivalent Current Dipole on averages, ECD, Equivalent Current Dipole, ECG, electrocardiogram, EEG, electroencephalography, EOG, electro-oculogram, GOF, goodness of fit, HFO, high frequency oscillation, ICA, independent component analysis, ITS, intertrial synchronization index, LE, localisation error, LGN, lateral geniculate nucleus, MEG, magnetoencephalography, MFT, Magnetic Field Tomography, MLS, multiple local spheres, MTH, motor threshold, MUSIC, MUltiple SIgnal Classification, NP, noise power, S1, primary somatosensory area, SAM, Synthetic Aperture Magnetometry, SEF, somatosensory-evoked field, SMA, supplementary motor area, SNR, signal-noise-ratio, SP, signal power, SPM, statistical parametric map, SS, single sphere, ST, single trial, STH, sensory threshold