Spatio–Temporal Reconstruction of Bilateral Auditory Steady-State Responses Using MEG Beamformers

Abstract

A rapidly growing number of neuromagnetic studies focus on the analysis of auditory steady-state responses (ASSR) in relation to a diverse array of factors including age, selective attention, and presence of psychopathology. The objectives of these studies require accurate spatio-temporal estimation of the underlying neural generators, a challenging task due to the relatively low signal strength and high correlation between bilateral auditory cortical sources. This paper evaluates the performance of two beamforming schemes that can potentially overcome such difficulties: 1) the linearly constrained minimum variance beamformer with partial sensor coverage (LCMV-PSC), and 2) the multiple constrained minimum-variance beamformer with coherent source region suppression (MCMV-CSRS). Simulation experiments are conducted to assess the impact of source parameters on the reconstruction accuracy. The results indicate that the LCMV-PSC method is prone to localization errors that essentially occur along medio-lateral directions, increase with source depth, and are associated to amplitude and phase distortions of the estimated time courses of activity. Comparatively, the MCMV-CSRS method exhibits precise localization and minimal amplitude and phase distortion for a broad range of relative interferer's positions within the suppression region. The results from the numerical experiments are validated on real magnetoencephalographic (MEG) data collected from a 40-Hz ASSR paradigm.

Characterization of Brain Dynamics Using Beamformer Techniques: Advantages and Limitations

“…This approach is mainly applicable to auditory cortex sources with widely separated field patterns. However, a recent publication (Popescu et al, 2008) has shown that such a technique can result in significant localization errors due to incomplete removal of the signal from the contralateral source, in agreement with our own results (Quraan, unpublished).…”

“…Despite their advantages in terms of spatial resolution and localization accuracy, the performance of beamformers is seriously degraded in the presence of sources with high temporal correlations. This has been demonstrated for neural sources that are known to be highly correlated, such as bilateral activation of the temporal lobes during steady-state auditory stimulation (Brookes et al, 2007;Dalal et al, 2006;Popescu et al, 2008;Quraan and Cheyne, 2008;Quraan and Cheyne, 2010), and for primary visual sources (Quraan and Cheyne, 2008;Quraan and Cheyne, 2010), and is likely the case for many other sources as most brain modules are organized with bilateral symmetry. The beamformer's susceptibility to temporally correlated sources limits the beamformer's ability to accurately localize such sources, and results in significant attenuation of the source magnitude and, hence, a poor www.intechopen.com Characterization of Brain Dynamics Using Beamformer Techniques: Advantages and Limitations 69 reconstruction of the time courses.…”

Volumetric imaging of brain activity with spatial-frequency decoding of neuromagnetic signals

“…It is well known that the conventional beamformer cannot detect coherent or correlated MFBS (Dalal et al, 2006;Popescu et al, 2008), let alone weak HFBS. It is necessary to develop specialized methods to deal with coherent sources.…”

“…Since HFBS typically appear on a small group of sensors in a whole-cortex MEG system (Gummadavelli et al, 2013;Xiang and Xiao, 2009) using fewer sensors, beamformer can aid in the detection of MEG high-frequency components. In addition, previous reports (Popescu et al, 2008) have shown that partial sensor coverage (PSC) can minimize the coherent source effect at low-frequency signals. Therefore, from a methodological point of view, using fewer MEG sensors which are sensitive to a targeted source beamformer can aid in the detection of high-frequency components and at the same time reduce the coherent source effect at low-frequencies (Popescu et al, 2008).…”

Advances in Non-Invasive Brain Computer Interfaces for Control and Biometry

“…On the other hand, when the sources are correlated it is difficult to detect distinct source locations. A number of techniques have attempted to address the problem of correlated sources, such as a dual beamformer (Herdman et al, 2003) or using only half of the sensor array (Popescu et al, 2008). The idea of a multiple-source beamforming is to account for the activity from possibly correlated brain regions: the calculation contains not only the leadfield matrix of the source at the target location, but also those of possible sources whose interference is to be minimized.…”