Literature DB >> 15214546

Noise-free magnetoencephalography recordings of brain function.

P Volegov1, A Matlachov, J Mosher, M A Espy, R H Kraus.   

Abstract

Perhaps the greatest impediment to acquiring high-quality magnetoencephalography (MEG) recordings is the ubiquitous ambient magnetic field noise. We have designed and built a whole-head MEG system using a helmet-like superconducting imaging surface (SIS) surrounding the array of superconducting quantum interference device (SQUID) magnetometers used to measure the MEG signal. We previously demonstrated that the SIS passively shields the SQUID array from ambient magnetic field noise, independent of frequency, by 25-60 dB depending on sensor location. SQUID 'reference sensors' located on the outside of the SIS helmet measure ambient magnetic fields in very close proximity to the MEG magnetometers while being nearly perfectly shielded from all sources in the brain. The fact that the reference sensors measure no brain signal yet are located in close proximity to the MEG sensors enables very accurate estimation and subtraction of the ambient field noise contribution to the MEG sensors using an adaptive algorithm. We have demonstrated total ambient noise reduction factors in excess of 10(6) (> 120 dB). The residual noise for most MEG SQUID channels is at or near the intrinsic SQUID noise floor, typically 2-3 fT Hz-1/2. We are recording MEG signals with greater signal-to-noise than equivalent EEG measurements.

Mesh:

Year:  2004        PMID: 15214546     DOI: 10.1088/0031-9155/49/10/020

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  4 in total

1.  GENERALIZED SIDELOBE CANCELLER FOR MAGNETOENCEPHALOGRAPHY ARRAYS.

Authors:  John C Mosher; Matti S Hämäläinen; Dimitrios Pantazis; Hua Brian Hui; Richard C Burgess; Richard M Leahy
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2009-08-07

2.  Sensor noise suppression.

Authors:  Alain de Cheveigné; Jonathan Z Simon
Journal:  J Neurosci Methods       Date:  2007-09-19       Impact factor: 2.390

3.  Denoising based on time-shift PCA.

Authors:  Alain de Cheveigné; Jonathan Z Simon
Journal:  J Neurosci Methods       Date:  2007-06-08       Impact factor: 2.390

4.  Denoising based on spatial filtering.

Authors:  Alain de Cheveigné; Jonathan Z Simon
Journal:  J Neurosci Methods       Date:  2008-04-08       Impact factor: 2.390

  4 in total

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