A new dynamical approach to auditory evoked magnetic field by blind identification.
← Research streamThe authors propose a blind signal separation and blind identification approach to analyze MEG time series for auditory evoked magnetic fields. They report that changes in impulse responses between right and left hemispheres decay within about 40 ms and that …
Study snapshot
Abstract
A new approach to understand neural dynamics underlying the generation of auditory evoked magnetic field is proposed. MEG time series data are temporally decorrelated by using a blind signal separation method. Two components are selected from their periodical property and a remixing matrix is applied to the two selected components to retrieve MEG signals of auditory evoked magnetic field. After principal component data for each sensor pairs are calculated, a minimum phase innovation model is identified from the viewpoint of statistical inverse problem. By using a blind identification method based on feedback system theory transfer functions can be evaluated to get a dynamical understanding of brain auditory functions. It is reported that all changes of their impulse responses between right and left hemisphere decay within about 40 ms, and that directional differences in transfer functions can be found.
AI evidence extraction
Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.
Main findings
The authors propose a blind signal separation and blind identification approach to analyze MEG time series for auditory evoked magnetic fields. They report that changes in impulse responses between right and left hemispheres decay within about 40 ms and that directional differences in transfer functions can be found.
Outcomes measured
- auditory evoked magnetic field (MEG) signal components
- impulse response differences between hemispheres
- directional differences in transfer functions (feedback system theory)
Limitations
- No EMF exposure is described; the study concerns measurement/analysis of MEG signals rather than environmental or device-related EMF exposure.
- Population characteristics and sample size are not provided in the abstract.
View raw extracted JSON
{
"study_type": "other",
"exposure": {
"band": null,
"source": null,
"frequency_mhz": null,
"sar_wkg": null,
"duration": null
},
"population": null,
"sample_size": null,
"outcomes": [
"auditory evoked magnetic field (MEG) signal components",
"impulse response differences between hemispheres",
"directional differences in transfer functions (feedback system theory)"
],
"main_findings": "The authors propose a blind signal separation and blind identification approach to analyze MEG time series for auditory evoked magnetic fields. They report that changes in impulse responses between right and left hemispheres decay within about 40 ms and that directional differences in transfer functions can be found.",
"effect_direction": "unclear",
"limitations": [
"No EMF exposure is described; the study concerns measurement/analysis of MEG signals rather than environmental or device-related EMF exposure.",
"Population characteristics and sample size are not provided in the abstract."
],
"evidence_strength": "insufficient",
"confidence": 0.74,
"peer_reviewed_likely": "yes",
"keywords": [
"MEG",
"auditory evoked magnetic field",
"blind signal separation",
"blind identification",
"principal component",
"minimum phase innovation model",
"transfer function",
"hemispheric differences"
],
"suggested_hubs": []
}AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.
Identifiers and source
DOI: Not supplied
PubMed: 16012699
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