Elsevier

Clinical Neurophysiology

Volume 123, Issue 11, November 2012, Pages 2180-2191
Clinical Neurophysiology

Validation of head movement correction and spatiotemporal signal space separation in magnetoencephalography

https://doi.org/10.1016/j.clinph.2012.03.080Get rights and content

Abstract

Objective

Our aim was to assess the effectiveness and reliability of spatiotemporal signal space separation (tSSS) and movement correction (MC) in magnetoencephalography (MEG) recordings disturbed by head movements and magnetized material on the head.

Methods

We recorded MEG from 20 healthy adults in stationary (reference) head position and during controlled head movements. Nearby magnetic interference sources were simulated by attaching magnetized particles on the subject’s head. Auditory and somatosensory stimuli were presented. MC, tSSS and averaging were performed to obtain auditory (AEF) and somatosensory (SEF) evoked fields. Neuronal sources were modeled as equivalent current dipoles. MC was also validated by reconstructing signals generated by current dipoles in a phantom.

Results

After MC, the AEF and SEF responses recorded during intermittent head movements were similar in amplitude to the reference recordings and differed by 5–7 mm in source location. The tSSS method removed artifacts due to the attached magnetized particles but did not affect the reference data.

Conclusions

The methods are able to reliably recover MEG responses contaminated by movements and magnetic artifacts on the head.

Significance

The combination of tSSS and MC methods is especially useful in clinical measurements, where movements and magnetic disturbances are commonly present.

Highlights

► We evaluated novel methods for artifact suppression and movement correction in MEG data recorded in 20 subjects with controlled magnetic artifacts and head movements. ► The results show that methods based on signal space separation can reliably suppress interference from nearby sources. ► Head movement correction recovered evoked responses of satisfactory quality in all test conditions.

Introduction

Magnetoencephalography (MEG) reveals the dynamics of cortical processing with millisecond resolution (Hämäläinen et al., 1993). It has clinical applications in pre-operative planning and localization of epileptic foci (Mäkelä et al., 2006).

Significant head movements and magnetized impurities near or on the head have traditionally been regarded as exclusion criteria for MEG recordings. The signal space separation (SSS) method (Taulu and Kajola, 2005) provides a novel approach for suppressing interference originating outside of the MEG sensor array. In addition, the SSS method can be used for head movement correction and standardization of the head position (Taulu et al., 2005).

The temporal extension of SSS, tSSS (Taulu and Simola, 2006) further improves the shielding capabilities of SSS. The tSSS method is able to suppress interference from sources very close to the sensors, e.g. from magnetic particles on the head. The method has been experimentally demonstrated by analyzing unaveraged, tSSS-processed auditory responses from a healthy volunteer with controlled interference sources, though without head movement (Taulu and Hari, 2009). Recently, tSSS has also been evaluated in clinical studies involving epileptic patients with vagus nerve stimulators (Carrette et al., 2011) and Parkinsonian patients implanted with deep brain stimulators (Airaksinen et al., 2011). Using tSSS simultaneously with head movement correction can improve data quality further. For example, Medvedovsky et al. (2007) studied averaged somatosensory responses of one healthy volunteer from a reference head position and from five distinctly differing deviant positions, i.e. the head was initially in the reference position and after few seconds shifted to a deviant position for the rest of the recording. Movement correction improved the mean localization error of magnetic N20 responses from 39 to 21 mm, while combined tSSS and movement correction improved the mean error further to 9 mm.

Another test of SSS-based movement correction was a study involving a group of 19 children of 8–12 years of age performing a cognitive task (Wehner et al., 2008). When movement correction was applied, the goodness-of-fit improved slightly, and the confidence volume of a dipole cluster shrunk by 19%. The efficiency of the SSS-based head position transformation was evaluated by (Lioumis et al., 2007).

In the present study, our aim was to systematically assess the reliability of tSSS and movement correction. To this end, we recorded MEG data from 20 volunteers in four different controlled conditions. We also recorded signals from a phantom subjected to similar conditions. The data were processed with tSSS for suppression of artifacts and with an SSS-based movement correction. The results were compared to a reference recording where the head was held as stationary as possible. The conditions included discrete movements of the head, continuous regular movement, and continuous movement with magnetic impurities on the head.

Discrete head position shifts are typical in all MEG experiments where the subject is required to keep the head still for several minutes or even longer. Such movements are difficult to detect without continuous head position tracking. Some subjects and patients are not willing or able to maintain a steady head position and may continuously move their heads. Reliable analysis of such recordings requires effective movement correction and interference suppression.

Section snippets

MEG system and head position tracking

All MEG recordings were performed with an Elekta Neuromag® system (Elekta Oy, Helsinki, Finland), which samples the magnetic field distribution by 510 coils at distinct locations directly above the cortex. The coils are configured into 306 independent channels consisting of 102 magnetometers and 204 planar gradiometers.

The location of the subject’s head relative to the MEG sensors was determined with the aid of four head position indicator (HPI) coils attached to the scalp. First, three

Phantom data

The results of phantom dipole localization are presented in Table 1 and in Fig. 1. With tSSS and MC, the dipole signals could be reliably reconstructed. For rotation speed less than 5 deg/s, single epochs were clear in the raw data and could be localized accurately. In faster rotations the finite window length (200 ms) employed in the HPI amplitude estimation reduced the accuracy of movement tracking. Still, after averaging the dipole localizations were 3 mm or less from the known locations.

Summary

After tSSS and movement correction, evoked responses sufficiently good for source modeling could be recovered in all conditions. The combined tSSS and MC method showed significantly smaller deviations in source localization than tSSS alone.

With tSSS and MC, the average localization difference compared to the reference data was reduced to the level of the intersite differences, i.e. to about 5–8 mm for most responses. The AEF conditions with continuous head movements displayed more variability

Conclusion

We have demonstrated the reliability of temporal signal-space separation and head movement correction in MEG evoked-response measurements. These methods are especially important in clinical settings, where patients may have sources of strong magnetic interference close to their heads (e.g. a brain stimulator) or they may perform involuntary movements, as in Parkinson’s disease and epilepsy. Our data also show that magnetic auditory evoked responses are more affected by continuous movement than

Acknowledgements

Lauri Parkkonen and Veikko Jousmäki were supported by the Academy of Finland (National Centers of Excellence Programme 2006–2011). Additionally, Lauri Parkkonen was supported by the aivoAALTO research project of Aalto University and Veikko Jousmäki by the European Research Council (Advanced Grant #232946). Jussi Nurminen was supported by Jenny and Antti Wihuri Foundation and the Instrumentarium Foundation.

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