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Background: Surgical treatment of drug-resistant temporal lobe epilepsy (TLE) depends on proper identification of the seizure onset zone (SOZ) and differentiation of mesial, temporolimbic seizure onsets from temporal neocortical seizure onsets. Noninvasive source imaging using electroencephalography (EEG) and magnetoencephalography (MEG) can provide accurate information on interictal spike localization; however, EEG and MEG have low sensitivity for epileptiform activity restricted to deep temporolimbic structures. Moreover, in mesial temporal lobe epilepsy (MTLE), interictal spikes frequently arise in neocortical foci distant from the SOZ, rendering interictal spike localization potentially misleading for presurgical planning., Methods: In this study, we used two different beamformer techniques applied to the MEG signal of ictal events acquired during EEG-MEG recordings in six patients with TLE (three neocortical, three MTLE) in whom the ictal source localization results could be compared to ground truth SOZ localizations determined from intracranial EEG and/or clinical, neuroimaging, and postsurgical outcome evidence., Results: Beamformer analysis proved to be highly accurate in all cases and was able to identify focal SOZs in mesial, temporolimbic structures. In three patients, interictal spikes were absent, too complex for dipole modeling, or localized to anterolateral temporal neocortex distant to a mesial temporal SOZ, and thus unhelpful in presurgical investigation., Conclusions: MEG beamformer source reconstruction is suitable for analysis of ictal events in TLE and can complement or supersede the traditional analysis of interictal spikes. The method outlined is applicable to any type of epileptiform event, expanding the information value of MEG and broadening its utility for presurgical recording in epilepsy.

A nasogastric tube is commonly used to pour nutrients into the stomachs of patients who have difficulty swallowing in order to provide them with the required nutrition. However, it is possible to inadvertently insert the tube into the lungs. Thus, a method of obtaining the tip position of the tube is desired. In this paper, we use predata of magnetoimpedance (MI) sensors to estimate the position of the magnet attached to the tube tip using a minimum variance beamformer. Experimental results show that the position estimation error is <10 mm even when the distance from the MI sensors is 150 mm using the predata, whereas the error exceeds 10 mm when the predata is not used. These results suggest that the proposed method is a promising method for hospital applications. [ABSTRACT FROM AUTHOR]

This letter proposes a new algorithm for solving the optimal zero-forcing beamforming problem that maximizes the user achievable rate with restriction on the per-antenna element power constraints. An accelerated gradient method with step size search is proposed for solving the problem. For each iteration of the gradient approach, a quick one dimensional search is employed to obtain the step size. The advantage of the step-size search is that it is relatively fast and requires only a few calculations of the objective function. Design examples show that the proposed algorithm converges faster than the gradient approach and the accelerated gradient approach with a constant step size while achieving a low computational complexity. [ABSTRACT FROM AUTHOR]

The Nucleus® 5 System Sound Processor (CP810, Cochlear™, Macquarie University, NSW, Australia) contains two omnidirectional microphones. They can be configured as a fixed directional microphone combination (called Zoom) or as an adaptive beamformer (called Beam), which adjusts the directivity continuously to maximally reduce the interfering noise. Initial evaluation studies with the CP810 had compared performance and usability of the new processor in comparison with the Freedom™ Sound Processor (Cochlear™) for speech in quiet and noise for a subset of the processing options. This study compares the two processing options suggested to be used in noisy environments, Zoom and Beam, for various sound field conditions using a standardized speech in noise matrix test (Oldenburg sentences test). Nine German-speaking subjects who previously had been using the Freedom speech processor and subsequently were upgraded to the CP810 device participated in this series of additional evaluation tests. The speech reception threshold (SRT for 50% speech intelligibility in noise) was determined using sentences presented via loudspeaker at 65 dB SPL in front of the listener and noise presented either via the same loudspeaker (S0N0) or at 90 degrees at either the ear with the sound processor (S0NCI+) or the opposite unaided ear (S0NCI-). The fourth noise condition consisted of three uncorrelated noise sources placed at 90, 180 and 270 degrees. The noise level was adjusted through an adaptive procedure to yield a signal to noise ratio where 50% of the words in the sentences were correctly understood. In spatially separated speech and noise conditions both Zoom and Beam could improve the SRT significantly. For single noise sources, either ipsilateral or contralateral to the cochlear implant sound processor, average improvements with Beam of 12.9 and 7.9 dB in SRT were found. The average SRT of -8 dB for Beam in the diffuse noise condition (uncorrelated noise from both sides and back) is truly remarkable and comparable to the performance of normal hearing listeners in the same test environment. The static directivity (Zoom) option in the diffuse noise condition still provides a significant benefit of 5.9 dB in comparison with the standard omnidirectional microphone setting. These results indicate that CI recipients may improve their speech recognition in noisy environments significantly using these directional microphone-processing options. [ABSTRACT FROM AUTHOR]

Functional connectivity calculated using multiple channels of electromagnetic brain signals is often over- or underestimated due to volume conduction or field spread. Considering connectivity measures, coherence is suitable for the detection of rhythmic synchronization, whereas temporal correlation is appropriate for transient synchronization. This paper presents a beamformer-based imaging method, called spatiotemporal imaging of linearly-related source component (SILSC), which is capable of estimating connectivity at the cortical level by extracting the source component with the maximum temporal correlation between the activity of each targeted region and a reference signal. The spatiotemporal correlation dynamics can be obtained by applying SILSC at every brain region and with various time latencies. The results of six simulation studies demonstrated that SILSC is sensitive to detect the source activity correlated to the specified reference signal and is accurate and robust to noise in terms of source localization. In a facial expression imitation experiment, the correlation dynamics estimated by SILSC revealed the regions with mirror properties and the regions involved in motor control network when performing the imitation and execution tasks, respectively, with the left inferior frontal gyrus specified as the reference region. [ABSTRACT FROM AUTHOR]

Millimeter wave systems offer high date rate due to huge bandwidth but suffers from poor link budget. This is due to the blockage of the millimeter wave signal by the obstacles of size comparable to that of the wavelength of the signal. Various analysis in improving the signal strength is reported. One of them suggests use of directional antenna which guarantees signal delivery if line of sight communication between the transmitter and receiver exists. The other alternative scheme is Multi Input Multi Output (MIMO) beamforming that uses the channel statistics to steer the beam thereby improving the multiplexing gain and beamforming gain. In this paper, extensive research work carried out by us in MMW MIMO at 60 GHz covering aspects related to MIMO fixed-beam, adaptive beam and multibeam beamformers addressing line-of-sight and non-line-of-sight channel for MMW 60 GHz system is reviewed. [ABSTRACT FROM AUTHOR]

Objectives To compare the Naida CI UltraZoom adaptive beamformer and T-Mic settings in a real life environment. Methods Speech reception thresholds (SRTs) were measured in a moderately reverberant room, using the German Oldenburger sentence test. The speech signal was always presented from the front loudspeaker at 0° azimuth and fixed masking noise was presented either simultaneously from all eight loudspeakers around the subject at 0°, ±45°, ±90°, ±135°, and 180° azimuth or from five loudspeakers positioned at ±70°, ±135°, and 180° azimuth. In the third test setup, an additional roving noise was added to the six loudspeaker arrangement. Results There was a significant difference in mean SRTs between the Naida CI T-Mic and UltraZoom in each of the three test setups. The largest improvements were seen in the six speaker roving and fixed noise conditions. Adding ClearVoice to the Naida CI T-Mic setting significantly improved the SRT in both fixed noise conditions, but not in the roving noise condition. In each setup, the lowest SRTs were obtained with the UltraZoom plus ClearVoice setting. Discussion The degree of improvement was consistent with previous beamforming studies. In the most challenging listening situation, with noise from eight speakers and speech and noise presented coincidentally from the front, UltraZoom still provided a significant benefit. When a moving noise source was added, the improvement in SRT provided by UltraZoom was maintained. Conclusion When tested in challenging and realistic noise environments, the Naida CI UltraZoom adaptive beamformer resulted in significantly lower mean SRTs than when the T-Mic alone was used. [ABSTRACT FROM AUTHOR]

The objective of the study is to assess the hearing performance of cochlear implant users in three device microphone configurations: omni-directional, directional, and beamformer (BEAMformer two-adaptive noise reduction system), in localization and speech perception tasks in dynamically changing listening environments. Seven cochlear implant users aided with Cochlear CM-24 devices with Freedom speech processor participated in the study. For the localization test in quiet and in background noise, subjects demonstrated significant differences between different microphone settings. Confusion matrices showed that in about 70% cases cochlear implant subjects correctly localized sounds within a horizontal angle of 30-40◦ (±1◦ loudspeaker apart from signal source). However localization in noise was less accurate as shown by a large number of considerable errors in localization in the confusion matrices. Average results indicated no significant difference between three microphone configurations. For speech presented from the front 3 dB SNR improvements in speech intelligibility in three subjects can be observed for beamforming system compared to directional and omni-directional microphone settings. The benefits of using different microphone settings in cochlear implant devices in dynamically changing listening conditions depend on the particular sound environment [ABSTRACT FROM AUTHOR]

This paper proposes a new computational procedure for solving the optimal zero-forcing beamforming problem in multiple antenna channels that maximizes user achievable rate with restriction on the per-antenna element power constraints. An interior point method with optimal step size procedure is developed in which the step size for the line search in the Newton search direction is calculated exactly for each iteration. This significantly enhances the efficiency associated with the line search. Design examples show that the proposed algorithm converges rapidly to the optimal solution with low computational complexity. [ABSTRACT FROM AUTHOR]

We have explored both the benefits and detriments of providing electrical input through a cochlear implant in one ear to the auditory system of young children. A cochlear implant delivers electrical pulses to stimulate the auditory nerve, providing children who are deaf with access to sound. The goals of implantation are to restrict reorganization of the deprived immature auditory brain and promote development of hearing and spoken language. It is clear that limiting the duration of deprivation is a key factor. Additional considerations are the onset, etiology, and use of residual hearing as each of these can have unique effects on auditory development in the pre-implant period. New findings show that many children receiving unilateral cochlear implants are developing mature-like brainstem and thalamo-cortical responses to sound with long term use despite these sources of variability; however, there remain considerable abnormalities in cortical function. The most apparent, determined by implanting the other ear and measuring responses to acute stimulation, is a loss of normal cortical response from the deprived ear. Recent data reveal that this can be avoided in children by early implantation of both ears simultaneously or with limited delay. We conclude that auditory development requires input early in development and from both ears.

Noninvasive studies to predict regions of seizure onset are important to choose grid locations for subsequent invasive cortical recordings prior to resective surgery for patients with medically intractable epilepsy. The neurosurgeon needs to know both the seizure onset zone (SOZ) and the region of immediate cortical spread to determine the epileptogenic zone (EZ) to be resected. The immediate zone of spread may be immediately adjacent, on a nearby gyrus, in a different lobe, and sometimes even in the contralateral cerebral hemisphere. We reviewed consecutive simultaneous EEG/MEG recordings on 162 children with medically intractable epilepsy. We analyzed the MEG signals in the bandwidth 20-70 Hz with a beamformer algorithm, synthetic aperture magnetometry (SAM), at a 2.5 mm voxel spacing throughout the brain (virtual sensor locations) with the kurtosis statistic (g2) to determine presence of excess kurtosis ( ) consistent with intermittent increased high frequency spikiness of the background. The MEG time series was reconstructed (virtual sensor signals) at each of these virtual sensor locations (VSLs). The VS signals were further examined with a relative peak amplitude spike detection algorithm. The time of VS spike detection was compared to the simultaneous EEG and MEG sensor signals for the presence of conventional epileptiform spike morphology in the latter signals. The time of VS spike detection was compared across VSLs to determine earliest and last VSL to show a VS spike. Seven subjects showed delay in activation across VS locations detectable on visual examination. We compared the VS locations that showed earliest and later VS spikes with the locations on intracranial grid locations by electrocorticography (ECoG) that showed spikes and both onset and spread of seizures. We compared completeness of resection of VS locations to postoperative outcome. The VS locations for spike onset and spread were similar to locations for ictal onset and spread by ECoG.

A dual-circular polarized dielectric lens-loaded cavity-backed four-arm sinuous antenna operating in the frequency range from 600 MHz to 2.5 GHz is proposed. The antenna is built without lossy absorber with several design aspects discussed, including substrate/lens loadings, effects of backing, and impedance match to 50 \Omega. Fabricated prototype is integrated with a dual-CP beamformer network. The complete configuration is unidirectional, flush-mountable, has input \VSWR < \1.5, isolation> 7 dB, boresight realized gain> 3.9 dBic, boresight axial ratio< 2.3 dB, and Wobble of Wave (WoW) at the 3-dB elevation cut< 2 dB. Through a high power test, the antenna is shown to be capable of transmitting 200 W of CW power with a maximum temperature rise of 60~^\circ\!C without any external cooling in the operating frequency range. Average overall efficiency of 70% is demonstrated. Two other high-power capable ferrite-tile-backed sinuous antennas are also fabricated to fully showcase unique benefits of the proposed antenna. Presented results should pave the way for the use of sinuous as a transmit antenna in many nontraditional applications requiring higher radiated powers and efficient high-quality dual-polarized patterns over wide frequency ranges. [ABSTRACT FROM PUBLISHER]

Increasing evidence from invasive intracranial recordings suggests that the matured brain generates both physiological and pathological high-frequency signals. The present study was designed to detect high-frequency brain signals in the developing brain using newly developed magnetoencephalography (MEG) methods. Twenty healthy children were studied with a high-sampling rate MEG system. Functional high-frequency brain signals were evoked by electrical stimulation applied to the index fingers. To determine if the highfrequency neuromagnetic signals are true brain responses in high-frequency range, we analyzed the MEG data using the conventional averaging as well as newly developed timefrequency analysis along with beamforming.The data of healthy children showed that very high-frequency brain signals (>1000 Hz) in the somatosensory cortex in the developing brain could be detected and localized using MEG. The amplitude of very high-frequency brain signals was significantly weaker than that of the low-frequency brain signals. Very high-frequency brain signals showed a much earlier latency than those of a low-frequency. Magnetic source imaging (MSI) revealed that a portion of the high-frequency signals was from the somatosensory cortex, another portion of the high-frequency signals was probably from the thalamus. Our results provide evidence that the developing brain generates high-frequency signals that can be detected with the non-invasive technique of MEG. MEG detection of high-frequency brain signals may open a new window for the study of developing brain function. [ABSTRACT FROM AUTHOR]

We propose source-space independent component analysis (ICA) for separation, tomography, and time-course reconstruction of EEG and MEG source signals. Source-space ICA is based on the application of singular value decomposition and ICA on the neuroelectrical signals from all brain voxels obtained post minimum-variance beamforming of sensor-space EEG or MEG. We describe the theoretical background and equations, then evaluate the performance of this technique in several different situations, including weak sources, bilateral correlated sources, multiple sources, and cluster sources. In this approach, tomographic maps of sources are obtained by back-projection of the ICA mixing coefficients into the source-space (3-D brain template). The advantages of source-space ICA over the popular alternative approaches of sensor-space ICA together with dipole fitting and power mapping via minimum-variance beamforming are demonstrated. Simulated EEG data were produced by forward head modeling to project the simulated sources onto scalp sensors, then superimposed on real EEG background. To illustrate the application of source-space ICA to real EEG source reconstruction, we show the localization and time-course reconstruction of visual evoked potentials. Source-space ICA is superior to the minimum-variance beamforming in the reconstruction of multiple weak and strong sources, as ICA allows weak sources to be identified and reconstructed in the presence of stronger sources. Source-space ICA is also superior to sensor-space ICA on accuracy of localization of sources, as source-space ICA applies ICA to the time-courses of voxels reconstructed from minimum-variance beamforming on a 3D scanning grid and these time-courses are optimally unmixed via the beamformer. Each component identified by source-space ICA has its own tomographic map which shows the extent to which each voxel has contributed to that component. [ABSTRACT FROM AUTHOR]

Recently, several new beamformers have been introduced for reconstruction and localization of neural sources from EEG and MEG. Although studies have compared the accuracy of beamformers for localization of strong sources in the brain, a comparison of new and conventional beamformers for time-course reconstruction of a desired source has not been previously undertaken. In this study, 8 beamformers were examined with respect to several parameters, including variations in depth, orientation, magnitude, and frequency of the simulated source to determine their (i) effectiveness at time-course reconstruction of the sources, and (ii) stability of their performances with respect to the input changes. The spatial and directional pass-bands of the beamformers were estimated via simulated and real EEG sources to determine spatial resolution. White-noise spatial maps of the beamformers were calculated to show which beamformers have a location bias. Simulated EEG data were produced by projection via forward head modelling of simulated sources onto scalp electrodes, then superimposed on real background EEG. Real EEG was recorded from a patient with essential tremor and deep brain implanted electrodes. Gain – the ratio of SNR of the reconstructed time-course to the input SNR – was the primary measure of performance of the beamformers. Overall, minimum-variance beamformers had higher Gains and superior spatial resolution to those of the minimum-norm beamformers, although their performance was more sensitive to changes in magnitude, depth, and frequency of the simulated source. White-noise spatial maps showed that several, but not all, beamformers have an undesirable location bias. [ABSTRACT FROM AUTHOR]

A high resolution optical true-time delay (OTTD) beamformer constructed by fiber Bragg grating (FBG) and highly dispersive fiber (HDF) is presented. It can produce the true time delay with the resolution of 1ps. Besides the proposed system has compact structure and light weight even when a large number of antenna elements are present in a practical antenna array, this is because the used FBG fibers and HDFs are short and independent of the antenna element number. Theoretical analysis and numerical simulations are made. Proof-of-concept experiment results that demonstrate the feasibility of the system are presented. [ABSTRACT FROM AUTHOR]

In electroencephalography (EEG) and magnetoencephalography signal processing, scalar beamformers are a popular technique for reconstruction of the time-course of a brain source in a single time-series. A prerequisite for scalar beamformers, however, is that the orientation of the source must be known or estimated, whereas in reality the orientation of a brain source is often not known in advance and current techniques for estimation of brain source orientation are effective only for high signal-to-noise ratio (SNR) brain sources. As a result, vector beamformers are applied which do not need the orientation of the source and reconstruct the source time-course in three orthogonal (x, y, and z) directions. To obtain a single time-course, the vector magnitude of the three orthogonal outputs of the beamformer can be calculated at each time point (often called neural activity index, NAI). The NAI, however, is different from the actual time-course of a source since it contains only positive values. Moreover, in estimating the magnitude of the desired source, the background activity (undesired signals) in the beamformer outputs also become all positive values, which, when added to each other, leads to a drop in the SNR. This becomes a serious problem when the desired source is weak. We propose applying independent component analysis (ICA) to the orthogonal time-courses of a brain voxel, as reconstructed by a vector beamformer, to reconstruct the time-course of a desired source in a single time-series. This approach also provides a good estimation of dipole orientation. Simulated and real EEG data were used to demonstrate the performance of voxel-ICA and were compared with a scalar beamformer and the magnitude time-series of a vector beamformer. This approach is especially helpful when the desired source is weak and the orientation of the source cannot be estimated by other means. [ABSTRACT FROM AUTHOR]

Frontal midline theta rhythm (Fmθ) appears widely distributed over medial prefrontal areas in EEG recordings, indicating focused attention. Although mental calculation is often used as an attention-demanding task, little has been reported on calculation-related activation in Fmθ experiments. In this study we used spatially filtered MEG and permutation analysis to precisely localize cortical generators of the magnetic counterpart of Fmθ, as well as other sources of oscillatory activity associated with mental calculation processing (i.e., arithmetic subtraction). Our results confirmed and extended earlier EEG/MEG studies indicating that Fmθ during mental calculation is generated in the dorsal anterior cingulate and adjacent medial prefrontal cortex. Mental subtraction was also associated with gamma event-related synchronization, as an index of activation, in right parietal regions subserving basic numerical processing and number-based spatial attention. Gamma event-related desynchronization appeared in the right lateral prefrontal cortex, likely representing a mechanism to interrupt neural activity that can interfere with the ongoing cognitive task. [ABSTRACT FROM AUTHOR]

Inaccuracy of EEG electrode coordinates forms an error term in forward model generation and ultimate source reconstruction performance. This error arises from the combination of both intrinsic measurement noise of the digitization apparatus and manual coregistration error when selecting corresponding points on anatomical MRI volumes. A common assumption is that such an error would lead only to displacement of localized sources. Here, we measured electrode positions on a 3D-printed full-scale replica head, using three different techniques: a fringe projection 3D scanner, a novel “Flying Triangulation” 3D sensor, and a traditional electromagnetic digitizer. Using highly accurate fringe projection data as ground truth, the Flying Triangulation sensor had a mean error of 1.5 mm while the electromagnetic digitizer had a mean error of 6.8 mm. Then, again using the fringe projection as ground truth, individual EEG simulations were generated, with source locations across the brain space and a range of sensor noise levels. The simulated datasets were then processed using a beamformer in conjunction with the electrode coordinates registered with the Flying Triangulation and electromagnetic digitizer methods. The beamformer’s output SNR was severely degraded with the digitizer-based positions but less severely with the Flying Triangulation coordinates. Therefore, the seemingly innocuous error in electrode registration may result in substantial degradation of beamformer performance, with output SNR penalties up to several decibels. In the case of low-SNR signals such as deeper brain structures or gamma band sources, this implies that sensor coregistration accuracy could make the difference between successful detection of such activity or complete failure to resolve the source. [ABSTRACT FROM AUTHOR]

Abstract: There is strong evidence to suggest that data recorded from magnetoencephalography (MEG) follows a non-Gaussian distribution. However, existing standard methods for source localisation model the data using only second order statistics, and therefore use the inherent assumption of a Gaussian distribution. In this paper, we present a new general method for non-Gaussian source estimation of stationary signals for localising brain activity from MEG data. By providing a Bayesian formulation for MEG source localisation, we show that the source probability density function (pdf), which is not necessarily Gaussian, can be estimated using multivariate kernel density estimators. In the case of Gaussian data, the solution of the method is equivalent to that of widely used linearly constrained minimum variance (LCMV) beamformer. The method is also extended to handle data with highly correlated sources using the marginal distribution of the estimated joint distribution, which, in the case of Gaussian measurements, corresponds to the null-beamformer. The proposed non-Gaussian source localisation approach is shown to give better spatial estimates than the LCMV beamformer, both in simulations incorporating non-Gaussian signals, and in real MEG measurements of auditory and visual evoked responses, where the highly correlated sources are known to be difficult to estimate. [Copyright &y& Elsevier]

This work focuses on the relationship between real and synthetic aperture radiometers giving a general and common mathematical framework for both of them. It will be demonstrated that a real aperture radiometer array can be understood as a synthetic aperture one, with a high level of redundancy. Therefore, all the recent results from synthetic aperture radiometry can be translated to real aperture radiometer arrays. This fact can be used to create beamforming arrays in a new way. To do this, the beamforming array equation will be written in terms of cross-correlations between all pair of antenna signals (visibility samples). By properly combining the visibility samples, a new type of digital beamforming radiometer can be implemented, which will benefit from the high calibration accuracy achieved in synthetic aperture radiometers (e.g., The Y-shaped MIRAS radiometer used in the Soil Moisture and Ocean Salinity mission of the European Space Agency) and the flexibility to electronically steer the beam. [ABSTRACT FROM AUTHOR]

Objective. High-frequency oscillations (HFOs) are promising biomarkers for localizing epileptogenic brain tissue. Previous studies have revealed that HFOs that present concurrence with interictal epileptic discharges (IEDs) better delineate epileptogenic brain tissue, particularly for epilepsy patients with multitype interictal discharges. However, the analysis of noninvasively recorded epileptic HFOs involves many complex procedures, such as data preprocessing, detection and source localization, impeding the translation of this approach to clinical practice. Approach. To address these problems, we developed a graphical user interface (GUI)-based pipeline called EMHapp, which can be used for the automatic detection, source localization and visualization of HFO events concurring with IEDs in magnetoencephalography (MEG) signals by using a beamformer-based virtual sensor (VS) technique. An improved VS reconstruction method was developed to enhance the amplitudes of both HFO and IED VS signals. To test the capability of our pipeline, we collected MEG data from 11 complex focal epilepsy patients with surgical resections or seizure onset zones (SOZs) that were identified by intracranial electroencephalography. Main results. Our results showed that the HFO sources of eight patients were concordant with their resection margins or SOZs. Our proposed VS signal reconstruction approach achieved an 83.2% improvement regarding the number of detected HFO events and a 17.3% improvement in terms of the spatial overlaps between the HFO sources and the resection margins or SOZs in comparison with conventional VS reconstruction approaches. Significance. EMHapp is the first GUI-based pipeline for the analysis of epileptic magnetoencephalographic HFOs, which conveniently obtains HFO source locations using clinical data and enables direct translation to clinical applications., (© 2022 IOP Publishing Ltd.)

• Binaural weighted subtraction is effective in attenuating the contralateral sound field. • Subtraction weights are best when calculated using head-related transfer functions. • Binaural weighted subtraction is simple to implement in bilateral hearing devices. • Binaural weighted subtraction can improve speech intelligibility in complex, free-field listening scenarios. Understanding speech presented in competition with other sounds can be challenging. Here, we reason that in free-field settings, this task can be facilitated by attenuating the sound field contralateral to each ear and propose to achieve this by linear subtraction of the weighted contralateral stimulus. We mathematically justify setting the weight equal to the ratio of ipsilateral to contralateral head-related transfer functions (HRTFs) averaged over an appropriate azimuth range. The algorithm is implemented in the frequency domain and evaluated technically and experimentally for normal-hearing listeners in simulated free-field conditions. Results show that (1) it can substantially improve the signal-to-noise ratio (up to 30 dB) and the short-term objective intelligibility in the ear ipsilateral to the target source, particularly for maskers with speech-like spectra; (2) it can improve speech reception thresholds (SRTs) for sentences in competition with speech-shaped noise by up to 8.5 dB in bilateral listening and 10.0 dB in unilateral listening; (3) for sentences in competition with speech maskers and in bilateral listening, it can improve SRTs by 2 to 5 dB, depending on the number and location of the masker sources; (4) it hardly affects virtual sound-source lateralization; and (5) the improvements, and the algorithm's directivity pattern depend on the azimuth range used to calculate the weights. Contralateral HRTF-weighted subtraction may prove valuable for users of binaural hearing devices. [ABSTRACT FROM AUTHOR]

[Display omitted] • A more robust beamformer than the reference implementation of DAS and DMAS. • The algorithm complexity is of a similar order to DAS. • The DMAS-D4 achieves higher contrast and finer resolution. • The improved performance is achieved with minimal additional computational load. • The iterative implementation makes it suitable even for large MIMO imaging volumes. Confocal microwave imaging (CMI) has the potential to be an alternative or complementary method for mammography in breast cancer screening. Data acquisition in CMI is very fast, safe, and comfortable for patients, but the reconstructed images are not always of high quality. High level of artifacts and poor resolution cause impaired quality. In this work, a novel, fast and robust beamformer, DMAS-D4 is presented. Delay-multiply-and-sum-degree-4 (DMAS-D4) is a next generation beamformer that expands the two-dimensional summations in delay-multiply-and-sum (DMAS) to four-dimensional summations in which all possible fourth degree terms are summed to increase robustness and resolution. A computationally-efficient implementation is presented which mitigates the additional computation required by DMAS. Furthermore, the proposed method can run iteratively which makes the ability to update the result using new observations. An idealized simulation compares basic performance of the proposed method with two other beamformers: (1) DAS, which is the gold standard, and (2) DMAS, which has been reported as the best beamformer so far. The results demonstrate that the DMAS-D4 achieves higher contrast and finer resolution. The proposed method increased the signal-to-max-ratio (SMXR) from 3.1 dB using DMAS to 5.7 dB in the heterogeneous breast mimicking phantom which illustrates the higher tumor detectability using the proposed method. Similarly, the Signal-to-Clutter Ratio (SCR) is 23.9 dB higher using the proposed method. By exploiting DMAS-D4 these benefits and potentially enhancing clinical decisions are attainable by the same computational load order as DAS. These results may be useful to inform future microwave breast imaging beamformer design. [ABSTRACT FROM AUTHOR]

Abstract: A joint use of pseudo-noise resampling technique and a conventional beamformer is proposed to mitigate the effect of outliers in Root-MUSIC estimator. After resampling of Root-MUSIC via pseudo-randomly generated noise we combine it with a conventional beamformer (in the sense that identification of the signal roots is based on the power of the conventional beamformer response). The resulting estimator can be referred to as modified resampled Root-MUSIC. The estimator bank is formed from a number of modified resampled Root-MUSIC. Censored selection of the results of modified pseudo-randomly resampled Root-MUSIC estimators is exploited based on an appropriate local performance test. [Copyright &y& Elsevier]

Abstract: We present a source localization method for electroencephalographic (EEG) and magnetoencephalographic (MEG) data which is based on an estimate of the sparsity obtained through the eigencanceler (EIG), which is a spatial filter whose weights are constrained to lie in the noise subspace. The EIG provides rejection of directional interferences while minimizing noise contributions and maintaining specified beam pattern constraints. In our case, the EIG is used to estimate the sparsity of the signal as a function of the position, then we use this information to spatially restrict the neural sources to locations out of the sparsity maxima. As proof of the concept, we incorporate this restriction in the “classical” linearly constrained minimum variance (LCMV) source localization approach in order to enhance its performance. We present numerical examples to evaluate the proposed method using realistically simulated EEG/MEG data for different signal-to-noise (SNR) conditions and various levels of correlation between sources, as well as real EEG/MEG measurements of median nerve stimulation. Our results show that the proposed method has the potential of reducing the bias on the search of neural sources in the classical approach, as well as making it more effective in localizing correlated sources. [Copyright &y& Elsevier]

Over the past decade, various techniques have been proposed for localization of cerebral sources of oscillatory activity on the basis of magnetoencephalography (MEG) or electroencephalography recordings. Beamformers in the frequency domain, in particular, have proved useful in this endeavor. However, the localization accuracy and efficacy of such spatial filters can be markedly limited by bias from correlation between cerebral sources and short duration of source activity, both essential issues in the localization of brain data. Here, we evaluate a method for frequency-domain localization of oscillatory neural activity based on the relevance vector machine (RVM). RVM is a Bayesian algorithm for learning sparse models from possibly overcomplete data sets. The performance of our frequency-domain RVM method (fdRVM) was compared with that of dynamic imaging of coherent sources (DICS), a frequency-domain spatial filter that employs a minimum variance adaptive beamformer (MVAB) approach. The methods were tested both on simulated and real data. Two types of simulated MEG data sets were generated, one with continuous source activity and the other with transiently active sources. The real data sets were from slow finger movements and resting state. Results from simulations show comparable performance for DICS and fdRVM at high signal-to-noise ratios and low correlation. At low SNR or in conditions of high correlation between sources, fdRVM performs markedly better. fdRVM was successful on real data as well, indicating salient focal activations in the sensorimotor area. The resulting high spatial resolution of fdRVM and its sensitivity to low-SNR transient signals could be particularly beneficial when mapping event-related changes of oscillatory activity. [ABSTRACT FROM AUTHOR]

Simultaneous magnetoencephalography (MEG) and electroencephalography (EEG) analysis is known generally to yield better localization performance than a single modality only. For simultaneous analysis, MEG and EEG data should be combined to maximize synergistic effects. Recently, beamformer for simultaneous MEG/EEG analysis was proposed to localize both radial and tangential components well, while single modality analyses could not detect them, or had relatively higher location bias. In practice, most interesting brain sources are likely to be activated coherently; however, conventional beamformer may not work properly for such coherent sources. To overcome this difficulty, a linearly constrained minimum variance (LCMV) beamformer may be used with a source suppression strategy. In this work, simultaneous MEG/EEG LCMV beamformer using source suppression was formulated firstly to investigate its capability over various suppression strategies. The localization performance of our proposed approach was examined mainly for coherent sources and compared thoroughly with the conventional simultaneous and single modality approaches, over various suppression strategies. For this purpose, we used numerous simulated data, as well as empirical auditory stimulation data. In addition, some strategic issues of simultaneous MEG/EEG analysis were discussed. Overall, we found that our simultaneous MEG/EEG LCMV beamformer using a source suppression strategy is greatly beneficial in localizing coherent sources. [ABSTRACT FROM AUTHOR]

This paper shows that among frequency independent (FI) conformal antennas, the modulated arm width (MAW) spiral has the simplest architecture for measuring both polarization and angle-of-arrival (AOA) instantaneously if frequency is known. The theory, design and performance of equiangular four-arm MAW spiral antennas when utilizing both sum modes (\pm 1) and difference mode (+2) for direction-finding applications are discussed. It is shown that simultaneous dual-polarization and multi-mode capability is not achievable in more commonly-used four-arm spiral and sinuous antennas. While the co-polarized modes 1, 2 and 3 are well-researched with single-polarized four-arm equiangular spirals, they have not been utilized or controlled on a four-arm MAW spiral. Effects of modulation period on cross-polarization, pattern symmetry, gain, and impedance for all three pattern modes are investigated. The studies are carried out using full-wave modeling and a prototype MAW geometry is built and evaluated with a beamformer to demonstrate its wideband, dual-polarized, multi-mode capability. [ABSTRACT FROM PUBLISHER]

Highlights: [•] Timing of brain activity during absence seizures is unclear. [•] MEG was used to determine corticothalamic brain activity during absence seizures. [•] Before absence seizure onset most activity was seen in frontal cortex and thalamus. [•] MEG can be used to measure corticothalamic activity with high temporal resolution. [•] Focal ictal activity occurs during “generalized” childhood absence seizures. [Copyright &y& Elsevier]

A Ku-, K-, and Ka-band phase shifter for beamforming applications is presented in this paper. An analysis showing the effect of loading conditions on quadrature phase accuracy in a simple poly-phase filter is carried out. Based on the analysis, a novel quadrature phase shifter (QPS) with inductive load is proposed. Sign-selection and vector addition is performed in two stages to lower supply voltage. The proposed phase shifter is fabricated in a 0.18-\mu\ m SiGe BiCMOS process and occupies an area of \520\ \mu\ m\times \370\ \mu\ m. The proposed QPS has a maximum phase error of 6.38^\circ over 15–35 GHz while maintaining an amplitude imbalance less than 2 dB. When combined into a 4-bit phase shifter, the root mean square (rms) gain error is less than 2.2 dB and the rms phase error is less than 13^\circ over 15–35 GHz. The phase shifter thus achieves a full 360^\circ phase-shift range with 22.5^\circ phase resolution. The total power consumption is 14 mA from a 1.8-V power supply. The phase shifter achieves an input P1dB of -6.25 dBm. The measured phase-shifting fractional bandwidth of 87% is the highest reported thus far in the literature for SiGe BiCMOS implementation. [ABSTRACT FROM PUBLISHER]

Unilateral hearing in childhood restricts input along the bilateral auditory pathways, possibly causing permanent reorganization. In this study we asked: (i) do the auditory pathways develop abnormally in children who are bilaterally deaf and hear with a unilateral cochlear implant? and (ii) can such differences be reversed by restoring input to the deprived ear? We measured multichannel electroencephalography in 34 children using cochlear implants and seven normal hearing peers. Dipole moments of activity became abnormally high in the auditory cortex contralateral to the first implant as unilateral cochlear implant use exceeded 1.5 years. This resulted in increased lateralization of activity to the auditory cortex contralateral to the stimulated ear and a decline in normal contralateral activity in response to stimulation from the newly implanted ear, corresponding to poorer speech perception. These results reflect an abnormal strengthening of pathways from the stimulated ear in consequence to the loss of contralateral activity including inhibitory processes normally involved in bilateral hearing. Although this reorganization occurred within a fairly short period (∼1.5 years of unilateral hearing), it was not reversed by long-term (3–4 years) bilateral cochlear implant stimulation. In bilateral listeners, effects of side of stimulation were assessed; children with long periods of unilateral cochlear implant use prior to bilateral implantation showed a reduction in normal dominance of contralateral input in the auditory cortex ipsilateral to the stimulated ear, further confirming an abnormal strengthening of pathways from the stimulated ear. By contrast, cortical activity in children using bilateral cochlear implants after limited or no unilateral cochlear implant exposure normally lateralized to the hemisphere contralateral to side of stimulation and retained normal contralateral dominance of auditory input in both hemispheres. Results demonstrate that the immature human auditory cortex reorganizes, potentially permanently, with unilateral stimulation and that bilateral auditory input provided with limited delay can protect the brain from such changes. These results indicate for the first time that there is a sensitive period for bilateral auditory input in human development with implications for functional hearing. [ABSTRACT FROM AUTHOR]

We propose a mechanism to form hole-like shapes with each of several sensor nodes equipped with a directional antenna called CS-DOA. In the system, we use an adaptive beamformer that can receive useful signals and adjust receiving angles through direction-of-arrival (DOA) estimations. We analyze single sources and links with sensor nodes to form a path around a given hole's margins. This work's proposed mechanism uses different receiving angles to detect a single source, and through the source message, we can detect and determine the given hole's margins. We use cognitive radio to estimate the energy of sensor nodes. We also propose energy consumption control via a game scheme to prolong sensor nodes' lifetime. This innovative mechanism increases performance and convenience, and improves our ability to make rigorous calculations regarding environmental topography. [ABSTRACT FROM AUTHOR]

Abstract: The use of magnetoencephalography (MEG) to assess long range functional connectivity across large scale distributed brain networks is gaining popularity. Recent work has shown that electrodynamic networks can be assessed using both seed based correlation or independent component analysis (ICA) applied to MEG data and further that such metrics agree with fMRI studies. To date, techniques for MEG connectivity assessment have typically used a variance normalised approach, either through the use of Pearson correlation coefficients or via variance normalisation of envelope timecourses prior to ICA. Here, we show that the use of variance information (i.e. data that have not been variance normalised) in source space projected Hilbert envelope time series yields important spatial information, and is of significant functional relevance. Further, we show that employing this information in functional connectivity analyses improves the spatial delineation of network nodes using both seed based and ICA approaches. The use of variance is particularly important in MEG since the non-independence of source space voxels (brought about by the ill-posed MEG inverse problem) means that spurious signals can exist in areas of low signal variance. We therefore suggest that this approach be incorporated into future studies. [Copyright &y& Elsevier]

Abstract: A compact high frequency true time delay (TTD) beamformer using bidirectional reflectance of the fiber gratings (FGs) is proposed. The FGs can be a set of fiber Bragg gratings (FBGs) or chirped fiber gratings (CFGs). The number and the length of the time delay lines are greatly reduced compared to the previous systems. A phase array antennas system using this TTD beamformer has many advantages including being compact, low requirement on the bandwidth of the tunable laser source and working at high microwave frequency. The proof-of-concept experiment results demonstrated the feasibility of the proposed scheme. [Copyright &y& Elsevier]

What are the functional neuroimaging measurements required for more fully characterizing the events and locations of neocortical activity? A prime assumption has been that modulation of cortical activity will inevitably be reflected in changes in energy utilization (for the most part) changes of glucose and oxygen consumption. Are such a measures complete and sufficient? More direct measures of cortical electrophysiological activity show event or task-related modulation of amplitude or band-limited oscillatory power. Using magnetoencephalography (MEG), these measures have been shown to correlate well with energy utilization sensitive BOLD fMRI. In this paper, we explore the existence of state changes in electrophysiological cortical activity that can occur independently of changes in averaged amplitude, source power or indices of metabolic rates. In addition, we demonstrate that such state changes can be described by applying a new measure of complexity, rank vector entropy (RVE), to source waveform estimates from beamformer-processed MEG. RVE is a non-parametric symbolic dynamic informational entropy measure that accommodates the wide dynamic range of measured brain signals while resolving its temporal variations. By representing the measurements by their rank values, RVE overcomes the problem of defining embedding space partitions without resorting to signal compression. This renders RVE-independent of absolute signal amplitude. In addition, this approach is robust, being relatively free of tunable parameters. We present examples of task-free and task-dependent MEG demonstrating that RVE provides new information by uncovering hidden dynamical structure in the apparent turbulent (or chaotic) dynamics of spontaneous cortical activity. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a new beamformer which combines the eigenspace-based minimum variance (ESBMV) beamformer with the Wiener postfilter is proposed for medical ultrasound imaging. The primary goal of this work is to further improve the medical ultrasound imaging quality on the basis of the ESBMV beamformer. In this method, we optimize the ESBMV weights with a Wiener postfilter. With the optimization of the Wiener postfilter, the output power of the new beamformer becomes closer to the actual signal power at the imaging point than the ESBMV beamformer. Different from the ordinary Wiener postfilter, the output signal and noise power needed in calculating the Wiener postfilter are estimated respectively by the orthogonal signal subspace and noise subspace constructed from the eigenstructure of the sample covariance matrix. We demonstrate the performance of the new beamformer when resolving point scatterers and cyst phantom using both simulated data and experimental data and compare it with the delay-and-sum (DAS), the minimum variance (MV) and the ESBMV beamformer. We use the full width at half maximum (FWHM) and the peak-side-lobe level (PSL) to quantify the performance of imaging resolution and the contrast ratio (CR) to quantify the performance of imaging contrast. The FWHM of the new beamformer is only 15%, 50% and 50% of those of the DAS, MV and ESBMV beamformer, while the PSL is 127.2dB, 115dB and 60dB lower. What is more, an improvement of 239.8%, 232.5% and 32.9% in CR using simulated data and an improvement of 814%, 1410.7% and 86.7% in CR using experimental data are achieved compared to the DAS, MV and ESBMV beamformer respectively. In addition, the effect of the sound speed error is investigated by artificially overestimating the speed used in calculating the propagation delay and the results show that the new beamformer provides better robustness against the sound speed errors. Therefore, the proposed beamformer offers a better performance than the DAS, MV and ESBMV beamformer, showing its potential in medical ultrasound imaging. [Copyright &y& Elsevier]

For over two decades, speech control mechanisms have been widely applied in manufacturing systems such as factory automation, warehouse automation, and industrial robotic control for over two decades. To implement speech controls, a commercial speech recognizer is used as the interface between users and the automation system. However, users' commands are often contaminated by environmental noise which degrades the performance of speech recognition for controlling automation systems. This paper presents a multichannel signal enhancement methodology to improve the performance of commercial speech recognizers. The proposed methodology aims to optimize speech recognition accuracy of a commercial speech recognizer in a noisy environment based on a beamformer, which is developed by an intelligent particle swarm optimization. It overcomes the limitation of the existing signal enhancement approaches whereby the parameters inside commercial speech recognizers are required to be tuned, which is impossible in a real-world situation. Also, it overcomes the limitation of the existing optimization algorithm including gradient descent methods, genetic algorithms and classical particle swarm optimization that are unlikely to develop optimal beamformers for maximizing speech recognition accuracy. The performance of the proposed methodology was evaluated by developing beamformers for a commercial speech recognizer, which was implemented on warehouse automation. Results indicate a significant improvement regarding speech recognition accuracy. [ABSTRACT FROM PUBLISHER]