Background: Magnetoencephalography (MEG) provides a direct measure of brain activity with high combined spatiotemporal resolution. Preprocessing is necessary to reduce contributions from environmental interference and biological noise.
New Method: The effect on the signal-to-noise ratio of different preprocessing techniques is evaluated. The signal-to-noise ratio (SNR) was defined as the ratio between the mean signal amplitude (evoked field) and the standard error of the mean over trials.
Results: Recordings from 26 subjects obtained during and event-related visual paradigm with an Elekta MEG scanner were employed. Two methods were considered as first-step noise reduction: Signal Space Separation and temporal Signal Space Separation, which decompose the signal into components with origin inside and outside the head. Both algorithm increased the SNR by approximately 100%. Epoch-based methods, aimed at identifying and rejecting epochs containing eye blinks, muscular artifacts and sensor jumps provided an SNR improvement of 5-10%. Decomposition methods evaluated were independent component analysis (ICA) and second-order blind identification (SOBI). The increase in SNR was of about 36% with ICA and 33% with SOBI.
Comparison With Existing Methods: No previous systematic evaluation of the effect of the typical preprocessing steps in the SNR of the MEG signal has been performed.
Conclusions: The application of either SSS or tSSS is mandatory in Elekta systems. No significant differences were found between the two. While epoch-based methods have been routinely applied the less often considered decomposition methods were clearly superior and therefore their use seems advisable.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jneumeth.2013.10.019 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Noise reduction in brain magnetic resonance imaging using adaptive wavelet thresholding based on linear prediction factor.
Front Neurosci
January 2025
Graduate Program in Electrical Engineering, Federal University of Pará - UFPA, Belém, Brazil.
Introduction: Wavelet thresholding techniques are crucial in mitigating noise in data communication and storage systems. In image processing, particularly in medical imaging like MRI, noise reduction is vital for improving visual quality and accurate analysis. While existing methods offer noise reduction, they often suffer from limitations like edge and texture loss, poor smoothness, and the need for manual parameter tuning.
View Article and Find Full Text PDFQuantitative assessment of the generalizability of a brain tumor Raman spectroscopy machine learning model to various tumor types including astrocytoma and oligodendroglioma.
J Biomed Opt
January 2025
McGill University, Montreal Neurological Institute-Hospital, Montreal, Quebec, Canada.
Significance: Maximal safe resection of brain tumors can be performed by neurosurgeons through the use of accurate and practical guidance tools that provide real-time information during surgery. Current established adjuvant intraoperative technologies include neuronavigation guidance, intraoperative imaging (MRI and ultrasound), and 5-ALA for fluorescence-guided surgery.
Aim: We have developed intraoperative Raman spectroscopy as a real-time decision support system for neurosurgical guidance in brain tumors.
Evaluation of charge summing correction in CdTe-based photon-counting detectors for breast CT: performance metrics and image quality.
J Med Imaging (Bellingham)
January 2025
U.S. Food and Drug Administration, Office of Science and Engineering Labs, Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, Maryland, United States.
Purpose: We evaluate the impact of charge summing correction on a cadmium telluride (CdTe)-based photon-counting detector in breast computed tomography (CT).
Approach: We employ a custom-built laboratory benchtop system using the X-THOR FX30 0.75-mm CdTe detector (Varex Imaging, Salt Lake City, Utah, United States) with a pixel pitch of 0.
One-Step Synthesis of Carboxylated Polyethylene Glycol-Modified Polystyrene Microspheres and Their Application in the Luminescent Oxygen Channel Immunoassay.
Langmuir
January 2025
School of Chemistry and Chemical Engineering, Southeast University, Nanjing 211189, China.
As one of the key diagnostic methods for detecting biomarkers and antigen-antibody interactions, the luminescent oxygen channel immunoassay (LOCI) has been widely applied in bioanalysis and other fields. In the context of LOCI, the performance of the prepared donor polystyrene (PS) microspheres significantly impacts the detection signal values. In this study, an attempt was made to synthesize PS microspheres via one-step polymerization of styrene with an amphiphilic monomer (PEOOH), followed by swelling the silicon phthalocyanine photosensitizer into the PS microspheres, resulting in the functionalization of the PS microspheres with polyethylene glycol segments.
View Article and Find Full Text PDFNeural-WDRC: A Deep Learning Wide Dynamic Range Compression Method Combined With Controllable Noise Reduction for Hearing Aids.
Trends Hear
January 2025
Key Laboratory of Noise and Vibration Research, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China.
Wide dynamic range compression (WDRC) and noise reduction both play important roles in hearing aids. WDRC provides level-dependent amplification so that the level of sound produced by the hearing aid falls between the hearing threshold and the highest comfortable level of the listener, while noise reduction reduces ambient noise with the goal of improving intelligibility and listening comfort and reducing effort. In most current hearing aids, noise reduction and WDRC are implemented sequentially, but this may lead to distortion of the amplitude modulation patterns of both the speech and the noise.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!