Utility of temporally-extended signal space separation algorithm for magnetic noise from vagal nerve stimulators

ObjectiveTo evaluate the utility of a temporally-extended signal space separation algorithm (tSSS) for patients with vagal nerve stimulator (VNS).MethodsWe evaluated median nerve somatosensory evoked responses (SER) of magnetoencephalography (MEG) in 27 VNS patients (48 sides) with/without tSSS processing. We classified SER dipoles as ‘acceptable’ if: (A) the location of the dipole was in the expected location in the central sulcus, and (B) the goodness of fit value (GOF) was greater than 80%. We evaluated (1) the number of sides which produced acceptable dipoles in each dataset (i.e. with/without tSSS processing), and in cases where the both data produced reliable dipoles, (2) compared their GOFs and the 95% confidence volumes (CV) (mm3). Statistical differences in the GOF and CV between with/without tSSS conditions were determined by paired t test.ResultsOnly 11 (23%) responses had reliable dipoles without tSSS processing, while all 48 (100%) had acceptable dipoles under tSSS processing. Additionally, the latter group had significantly higher GOF (increased by 7% on average) and lower CV (mean decrease of 200 mm3) than the former (p < 0.01).ConclusionsProcessing with tSSS quantitatively improves dipole fitting of known sources in VNS patients.SignificanceThis algorithm permits satisfactory MEG testing in the relatively commonly encountered epilepsy patient with VNS.

► This is the first MEG study to test the usefulness of the temporally-extended signal space separation algorithm (tSSS) algorithm in a relatively large number of epilepsy patients with vagal nerve stimulator (VNS). ► The tSSS algorithm not only reduces noise so that otherwise undetectable somatosensory evoked responses (SERs) can be identified, but also improves dipole fitting quantitatively. ► The algorithm permits satisfactory MEG testing in the relatively commonly encountered epilepsy patient with an implanted VNS.