Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements

By Samu Taulu, Juha Simola. Physics in Medicine and Biology, 2006

1,575 citations recorded by the source corpus.

Subfields: Radiology, Nuclear Medicine and Imaging, Signal Processing

View Paper: https://www.semanticscholar.org/paper/c407ecf09027afbd98a1ce335b48f81cca523edb

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In Radiology, Nuclear Medicine and Imaging

In Signal Processing

Citations in the corpus

MNE software for processing MEG and EEG data (2013, background): “While it is also possible to employ automatic artifact rejection procedures right from the beginning, e.g., using signal space separation (Taulu, 2006), it is a good practice to inspect the data visually at an early stage of processing.”
Removal of magnetoencephalographic artifacts with temporal signal‐space separation: Demonstration with single‐trial auditory‐evoked responses (2009, positive): “After this spatial step, the possible temporally correlated signals between the internal and intermediate parts are recognized by a subspace-intersection method [Golub and Van Loan, 1996; Taulu and Simola, 2006].”
Broadband Criticality of Human Brain Network Synchronization (2009, methodology): “The data set was corrected for the presence of internal and external noise sources and for disturbances as a result of head movements using signal space separation [40] with the spatiotemporal extension [41] via MaxFilter (Elekta Neuromag, Finland).”
Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence (2016, methodology): “To compensate for head movements and to perform noise reduction with spatiotemporal filters 48,49 we pre-processed data using Maxfilter software (Elekta, Stockholm).”
Revolutionizing Pediatric Neurophysiology With Magnetoencephalography (2026, unknown): “…recording from head position indicator coils and using tools such as signal-space separation (SSS) and tSSS (temporal SSS) to adjust signals for head movement following the recording (Taulu and Hari 2009; Taulu et al. 2004; Taulu and Simola 2006; Wehner et al. 2008; Larson and Taulu 2017).”
Cognitive interference elicits developmental sex differences in inhibitory control (2025, unknown): “Raw MEG data were corrected for head motion and extraneous noise using the signal space separation method with a temporal extension (Taulu et al., 2005; Taulu and Simola, 2006).”
Sexual dimorphism in cortical theta rhythms relates to elevated internalizing symptoms during adolescence (2024, unknown): “Each MEG dataset was individually corrected for head motion and subjected to noise reduction using the signal space separation method with a temporal extension (tSSS; MaxFilter v 2.2; correlation limit: 0.950; correlation window duration: six seconds; Taulu & Simola, 2006).”
Developmental changes in endogenous testosterone have sexually‐dimorphic effects on spontaneous cortical dynamics (2023, unknown): “2; correlation limit: 0.950; correlation window duration: 6 s; Taulu & Simola, 2006).”
Spontaneous α Brain Dynamics Track the Episodic “When” (2023, methodology): “Signal space separation (Taulu and Simola, 2006) was applied to decrease the impact of external noise.”
Interplay between preclinical indices of obesity and neural signatures of fluid intelligence in youth (2024, unknown): “MEG data were subjected to environmental noise reduction and corrected for head motion 112 .”
Inflammation-related aberrations in beta and gamma oscillatory dynamics serving attention processing in typically developing youth (2025, unknown): “42,43”