Biomedical subjects

Kensuke Sekihara

Publications and source records attributed to Kensuke Sekihara.

12 recordsLinked to original sources

PubMed2006

Controlled Support MEG imaging.

In this paper, we present a novel approach to imaging sparse and focal neural current sources from MEG (magnetoencephalography) data. Using the framework of Tikhonov regularization theory, we introduce a new stabilizer that uses the concept of controlled support to incorporate a priori assumptions about the area occupied by focal sources. The paper discusses the underlying Tikhonov theory and its relationship to a Bayesian formulation which in turn allows us to interpret and better understand other related algorithms.

Algorithms↗

PubMed2006

Modified beamformers for coherent source region suppression.

Many tomographic source localization algorithms used in biomagnetic imaging assume, explicitly or sometimes implicitly, that the source activity at different brain locations are either independent or that the correlation structure between sources is known. Among these algorithms is a class of adaptive spatial filters known as beamformers, which have superior spatiotemporal resolution abilities. The performance of beamformers is robust to weakly coherent sources. However, these algorithms are extremely sensitive to the presence of strongly coherent sources. A frequent mode of failure in beamformers occurs with reconstruction of auditory evoked fields (AEFs), in which bilateral auditory cortices are highly coherent in their activation. Here, we present a novel beamformer that suppresses activation from regions with interfering coherent sources. First, a volume containing the interfering sources is defined. The lead field matrix for this volume is computed and reduced into a few significant columns using singular value decomposition (SVD). A vector beamformer is then constructed by rejecting the contribution of sources in the suppression region while allowing for source reconstruction at other specified regions. Performance of this algorithm was first validated with simulated data. Subsequent tests of this modified beamformer were performed on bilateral AEF data. An unmodified vector beamformer using whole head coverage misplaces the source medially. After defining a suppression region containing the temporal cortex on one side, the described method consistently results in clear focal activations at expected regions of the contralateral superior temporal plane.

Adult↗

PubMed2006

A novel adaptive beamformer for MEG source reconstruction effective when large background brain activities exist.

This paper proposes a novel prewhitening eigenspace beamformer suitable for magnetoencephalogram (MEG) source reconstruction when large background brain activities exist. The prerequisite for the method is that control-state measurements, which contain only the contributions from the background interference, be available, and that the covariance matrix of the background interference can be obtained from such control-state measurements. The proposed method then uses this interference covariance matrix to remove the influence of the interference in the reconstruction obtained from the target measurements. A numerical example, as well as applications to two types of MEG data, demonstrates the effectiveness of the proposed method.

Algorithms↗

PubMed2005

A graphical model for estimating stimulus-evoked brain responses from magnetoencephalography data with large background brain activity.

This paper formulates a novel probabilistic graphical model for noisy stimulus-evoked MEG and EEG sensor data obtained in the presence of large background brain activity. The model describes the observed data in terms of unobserved evoked and background factors with additive sensor noise. We present an expectation maximization (EM) algorithm that estimates the model parameters from data. Using the model, the algorithm cleans the stimulus-evoked data by removing interference from background factors and noise artifacts and separates those data into contributions from independent factors. We demonstrate on real and simulated data that the algorithm outperforms benchmark methods for denoising and separation. We also show that the algorithm improves the performance of localization with beamforming algorithms.

Algorithms↗

PubMed2005

A simple nonparametric statistical thresholding for MEG spatial-filter source reconstruction images.

This paper proposes a simple statistical method for extracting target source activities from spatio-temporal source activities reconstructed from MEG measurements. The method requires measurements in a control condition, which contains only non-target source activities. The method derives, at each pixel location, an empirical probability distribution of the non-target source activity using the time course reconstruction obtained from the control period. The statistical threshold that can extract the target source activities is derived from the empirical distributions obtained from all pixel locations. Here, the multiple comparison problem is addressed with a two-step procedure involving standardizing these empirical distributions and deriving an empirical distribution of the maximum pseudo T value at each pixel location. The results of applying the proposed method to auditory-evoked measurements are presented to demonstrate the method's effectiveness.

Algorithms↗

PubMed2005

Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction.

This paper discusses the location bias and the spatial resolution in the reconstruction of a single dipole source by various spatial filtering techniques used for neuromagnetic imaging. We first analyze the location bias for several representative adaptive and non-adaptive spatial filters using their resolution kernels. This analysis theoretically validates previously reported empirical findings that standardized low-resolution electromagnetic tomography (sLORETA) has no location bias. We also find that the minimum-variance spatial filter does exhibit bias in the reconstructed location of a single source, but that this bias is eliminated by using the normalized lead field. We then focus on the comparison of sLORETA and the lead-field normalized minimum-variance spatial filter, and analyze the effect of noise on source location bias. We find that the signal-to-noise ratio (SNR) in the measurements determines whether the sLORETA reconstruction has source location bias, while the lead-field normalized minimum-variance spatial filter has no location bias even in the presence of noise. Finally, we compare the spatial resolution for sLORETA and the minimum-variance filter, and show that the minimum-variance filter attains much higher resolution than sLORETA does. The results of these analyses are validated by numerical experiments as well as by reconstructions based on two sets of evoked magnetic responses.

Algorithms↗

PubMed2004

Performance of an MEG adaptive-beamformer source reconstruction technique in the presence of additive low-rank interference.

The influence of external interference on neuromagnetic source reconstruction by adaptive beamformer techniques was investigated. In our analysis, we assume that the interference has the following two properties: First, it is additive and uncorrelated with brain activity. Second, its temporal behavior can be characterized by a few distinct activities, and as a result, the spatio-temporal matrix of the interference has a few distinctly large singular values. Namely, the interference can be modeled as a low-rank signal. Under these assumptions, our analysis shows that the adaptive beamformer techniques are insensitive to interference when its spatial singular vectors are so different from a lead field vector of a brain source that the generalized cosine between these two vectors is much smaller than unity. Four types of numerical examples verifying this conclusion are presented.

Algorithms↗

PubMed2004

Asymptotic SNR of scalar and vector minimum-variance beamformers for neuromagnetic source reconstruction.

To reconstruct neuromagnetic sources, the minimum-variance beamformer has been extended to incorporate the three-dimensional vector nature of the sources, and two types of extensions-the scalar- and vector-type extensions-have been proposed. This paper discusses the asymptotic signal-to-noise ratio (SNR) of the outputs of these two types of beamformers. We first show that these two types of beamformers give exactly the same output power and output SNR if the beamformer pointing direction is optimized. We then compare the output SNR of the beamformer with optimum direction to that of the conventional vector beamformer formulation where the beamformer pointing direction is not optimized. The comparison shows that the beamformer with optimum direction gives an output SNR superior to that of the conventional vector beamformer. Numerical examples validating the results of the analysis are presented.

Action Potentials↗

PubMed2003

Muscle afferent inputs from the hand activate human cerebellum sequentially through parallel and climbing fiber systems.

OBJECTIVE: Spatio-temporal response characteristics of the human cerebellum to median nerve stimulation (MNS) were studied with the use of a whole-head magnetoencephalographic (MEG) system covering the cerebellum and upper cervical spine. METHODS: Neuromagnetic responses from the cerebellum were recorded following electric stimulation of the right median nerve in 12 subjects. In 6 out of 12 subjects, the responses to the left median nerve and to the right index or middle finger stimulation were also recorded. RESULTS: The medial part of the cerebellum (spinocerebellum) was activated by MNS. In contrast, there were no responses from the cerebellum to the finger stimulation, suggesting that muscle afferent inputs are the source of cerebellar activation for MNS. The cerebellar responses consisted of 3 or 4 components of alternating polarity within 90 ms post-stimulus: the current direction for the first component was from the depth to the surface of the anterior lobe. CONCLUSIONS: From the timing and current direction, we speculate that the 4 components reflect, respectively, (1) excitatory postsynaptic potentials (EPSPs) of granule cells, (2) Purkinje cell EPSPs at the distal dendrites driven by parallel fibers, (3) Purkinje cell EPSPs at the soma and the proximal dendrites mediated by climbing fibers and (4) second Purkinje cell EPSPs at the distal dendrites driven by parallel fibers. SIGNIFICANCE: We first visualized serial activation of the human spinocerebellum following MNS noninvasively with MEG.

Adult↗

PubMed2002

Modulation of the auditory cortex during speech: an MEG study.

Several behavioral and brain imaging studies have demonstrated a significant interaction between speech perception and speech production. In this study, auditory cortical responses to speech were examined during self-production and feedback alteration. Magnetic field recordings were obtained from both hemispheres in subjects who spoke while hearing controlled acoustic versions of their speech feedback via earphones. These responses were compared to recordings made while subjects listened to a tape playback of their production. The amplitude of tape playback was adjusted to match the amplitude of self-produced speech. Recordings of evoked responses to both self-produced and tape-recorded speech were obtained free of movement-related artifacts. Responses to self-produced speech were weaker than were responses to tape-recorded speech. Responses to tones were also weaker during speech production, when compared with responses to tones recorded in the presence of speech from tape playback. However, responses evoked by gated noise stimuli did not differ for recordings made during self-produced speech versus recordings made during tape-recorded speech playback. These data suggest that during speech production, the auditory cortex (1) attenuates its sensitivity and (2) modulates its activity as a function of the expected acoustic feedback.

Adult↗

PubMed2002

Application of an MEG eigenspace beamformer to reconstructing spatio-temporal activities of neural sources.

We have applied the eigenspace-based beamformer to reconstruct spatio-temporal activities of neural sources from MEG data. The weight vector of the eigenspace-based beamformer is obtained by projecting the weight vector of the minimum-variance beamformer onto the signal subspace of a measurement covariance matrix. This projection removes the residual noise-subspace component that considerably degrades the signal-to-noise ratio (SNR) of the beamformer output when errors in estimating the sensor lead field exist. Therefore, the eigenspace-based beamformer produces a SNR considerably higher than that of the minimum-variance beamformer in practical situations. The effectiveness of the eigenspace-based beamformer was validated in our numerical experiments and experiments using auditory responses. We further extended the eigenspace-based beamformer so that it incorporates the information regarding the noise covariance matrix. Such a prewhitened eigenspace beamformer was experimentally demonstrated to be useful when large background activity exists.

Evoked Potentials, Auditory↗

PubMed2002

Performance of an MEG adaptive-beamformer technique in the presence of correlated neural activities: effects on signal intensity and time-course estimates.

The influence of temporarily correlated source activities on neuromagnetic reconstruction by adaptive beamformer techniques was investigated. It is known that the spatial filter weight of an adaptive beamformer cannot perfectly block correlated signals. This causes two major influences on the reconstruction results: time course distortions and reductions in reconstructed signal intensities. Our theoretical analysis and numerical experiments both showed that the reduction in signal intensity for sources with a medium degree of correlation is small. The time-course distortion for such sources, however, may be discernible. Our analysis also showed that the magnitude correlation coefficient between two correlated sources can be accurately estimated by using the beamformer outputs. A method of retrieving the original time courses using estimated correlation coefficients was developed. Our numerical experiments demonstrated that reasonably accurate time courses can be retrieved from considerably distorted time courses even when the signal-to-noise ratio is low.

Algorithms↗