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The neural representation and perceptual salience of tonal signals presented in different noise maskers were investigated. The properties of the maskers and signals were varied such that they produced different amounts of either monaural masking release, binaural masking release, or a combination of both. The signals were then presented at different levels above their corresponding masked thresholds and auditory evoked potentials (AEPs) were measured. It was found that, independent of the masking condition, the amplitude of the P2 component of the AEP was similar for the same stimulus levels above masked threshold, suggesting that both monaural and binaural effects of masking release were represented at the level of the auditory pathway where P2 is generated. The perceptual salience of the signal was evaluated at equal levels above masked threshold using a rating task. In contrast to the electrophysiological findings, the subjective ratings of the perceptual signal salience were less consistent with the signal level above masked threshold and varied strongly across listeners and masking conditions. Overall, the results from the present study suggest that the P2 amplitude of the AEP represents an objective indicator of the audibility of a target signal in the presence of complex acoustic maskers. [ABSTRACT FROM AUTHOR]

Purpose: To develop a 7T simultaneous multi-slice (SMS) 2D gradient-echo sequence for susceptibility contrast imaging, and to compare its quality to 3D imaging. Methods: A frequency modulated and phase cycled RF pulse was designed to simultaneously excite multiple slices in multi-echo 2D gradient-echo imaging. The imaging parameters were chosen to generate images with susceptibility contrast, including T2*-weighted magnitude/phase images, susceptibility-weighted images and quantitative susceptibility/R2* maps. To compare their image quality with 3D gradient-echo imaging, both 2D and 3D imaging were performed on 11 healthy volunteers and 4 patients with multiple sclerosis (MS). The signal to noise ratio (SNR) in gray and white matter and their contrast to noise ratio (CNR) was simulated for the 2D and 3D magnitude images using parameters from the imaging. The experimental SNRs and CNRs were measured in gray/white matter and deep gray matter structures on magnitude, phase, R2* and QSM images from volunteers and the visibility of MS lesions on these images from patients was visually rated. All SNRs and CNRs were compared between the 2D and 3D imaging using a paired t-test. Results: Although the 3D magnitude images still had significantly higher SNRs (by 13.0~17.6%), the 2D magnitude and QSM images generated significantly higher gray/white matter or globus pallidus/putamen contrast (by 13.3~87.5%) and significantly higher MS lesion contrast (by 5.9~17.3%). Conclusion: 2D SMS gradient-echo imaging can serve as an alternative to often used 3D imaging to obtain susceptibility-contrast-weighted images, with an advantage of providing better image contrast and MS lesion sensitivity. [ABSTRACT FROM AUTHOR]

The neuroimaging of humans using 7T magnetic resonance imaging (MRI) has been conducted using phased array (PA) coils with different numbers of receiving channels. PA coils with a high number of channels may offer parallel imaging (PI) with a high reduction (R)-factor, which is enabled via under-sampling and coil geometry (g) factor, increasing the radiofrequency signal sensitivity provided by a small coil. The goals of this study were to assess and validate the coil performance of PA coils with different numbers of receiver (Rx)-channels in and to propose the coil selection guidelines by visualizing 7T brain images. The combined magnetic flux density (||B1||) distributions of four configurations of PA coils—4-, 8-, 12-, and 16-channel Rx-only mode under the local transmit (Tx) mode of birdcage coils—were evaluated using electromagnetic (EM) calculations. These four configurations of PA coils and a local Tx coil were designed and built for a 7T MRI experiment. For 7T brain imaging experiments, all PA coils with (w/) and without (w/o) R-factors were compared in terms of signal-to-noise ratio (SNR) and spatial noise variation (SNV). EM simulation results clearly demonstrated that PA coils with a high number of Rx channels showed more homogeneously distributed ||B1|| fields than a PA coils with a low number of Rx coils. The results of this study demonstrate that a collection of smaller surface coils can contribute to high RF signal sensitivity in terms of the anatomical coverage of the brain and may facilitate PI. With further improvement in coil technology, researchers and clinicians will be provided with PA coils with different numbers of channels, which can ensure the optimum SNR and PI benefits for 7T brain MR imaging. [ABSTRACT FROM AUTHOR]

DIBR-3D technology has evolved over the past few years with the demands of consumers increasing in recent times for future free-view 3D videos on their home televisions. The main issue in 3D technology is the lack of 3D content available to watch using the traditional TV systems. Although, some sophisticated devices like stereoscopic cameras have been used to fill the gap between the 3D content demand and 3D content supply. But the content generated through these sophisticated devices can not be displayed on the traditional TV systems, so there needs to be some mechanism which is inline with the traditional TV. Furthermore, the huge collection of existing 2D content should be converted to 3D using depth image-based rendering techniques. This conversion technique can highly contribute in overcoming the shortage problem of the 3D content. This paper presents a novel approach for converting 2D degraded image for DIBR 3D-TV view. This degraded or noisy/blur image is enhanced through image dehazing and Directional Filter Bank (DFB). This enhancement is necessary because of the occlusion effect or hole filling problem that occurs due to imperfect depth map. The enhanced image is then segmented into the foreground image and the background image. After the segmentation, the depth map is generated using image profiles. Moreover, Stereoscopic images are finally produced using the DIBR procedure which is based on the 2D input image and the corresponding depth map. We have verified the results of the proposed approach by comparing the results with the existing state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Noisy galvanic vestibular stimulation (nGVS) has been shown to improve dynamic walking stability, affect postural responses, enhance balance in healthy subjects, and influence motor performance in individuals with Parkinson’s disease. Although the studies to fully characterize the effect of nGVS are still ongoing, stochastic resonance theory which states that the addition of noisy signal may enhance a weak sensory input signals transmission in a non-linear system may provide a possible explanation for the observed positive effects of nGVS. This study explores the effect of nGVS on fine tracking behavior in healthy subjects. Ten healthy participants performed a computer-based visuomotor task by controlling an object with a joystick to follow an amplitude-modulated signal path while simultaneously receiving a sham or pink noise nGVS. The stimulation was generated to have a zero-mean, linearly detrended 1/f-type power spectrum, Gaussian distribution within 0.1–10 Hz range, and a standard deviation (SD) set to 90% based on each participant’s cutaneous threshold value. Results show that simultaneous nGVS delivery statistically improved the tracking performance with a decreased root-mean-squared error of 5.71±6.20% (mean±SD), a decreased time delay of 11.88±9.66% (mean±SD), and an increased signal-to-noise ratio of 2.93% (median, interquartile range (IQR) 3.31%). This study showed evidence that nGVS may be beneficial in improving sensorimotor performance during a fine motor tracking task requiring fine wrist movement in healthy subjects. Further research with a more comprehensive subset of tasks is required to fully characterize the effects of nGVS on fine motor skills. [ABSTRACT FROM AUTHOR]

Visual cortex is organized into discrete sub-regions or areas that are arranged into a hierarchy and serves different functions in the processing of visual information. In retinotopic maps of mouse cortex, there appear to be substantial mouse-to-mouse differences in visual area location, size and shape. Here we quantify the biological variation in the size, shape and locations of 11 visual areas in the mouse, after separating biological variation and measurement noise. We find that there is biological variation in the locations and sizes of visual areas. [ABSTRACT FROM AUTHOR]

Miniaturized microscopes are lightweight imaging devices that allow optical recordings from neurons in freely moving animals over the course of weeks. Despite their ubiquitous use, individual neuronal responses measured with these microscopes have not been directly compared to those obtained with established in vivo imaging techniques such as bench-top two-photon microscopes. To achieve this, we performed calcium imaging in mouse primary visual cortex while presenting animals with drifting gratings. We identified the same neurons in image stacks acquired with both microscopy methods and quantified orientation tuning of individual neurons. The response amplitude and signal-to-noise ratio of calcium transients recorded upon visual stimulation were highly correlated between both microscopy methods, although influenced by neuropil contamination in miniaturized microscopy. Tuning properties, calculated for individual orientation tuned neurons, were strongly correlated between imaging techniques. Thus, neuronal tuning features measured with a miniaturized microscope are quantitatively similar to those obtained with a two-photon microscope. [ABSTRACT FROM AUTHOR]

Purpose of this work was to assess feasibility of cardiac diffusion tensor imaging (cDTI) at 7 T in a set of healthy, unfixed, porcine hearts using various parallel imaging acceleration factors and to compare SNR and derived cDTI metrics to a reference measured at 3 T. Magnetic resonance imaging was performed on 7T and 3T whole body systems using a spin echo diffusion encoding sequence with echo planar imaging readout. Five reference (b = 0 s/mm2) images and 30 diffusion directions (b = 700 s/mm2) were acquired at both 7 T and 3 T using a GRAPPA acceleration factor R = 1. Scans at 7 T were repeated using R = 2, R = 3, and R = 4. SNR evaluation was based on 30 reference (b = 0 s/mm2) images of 30 slices of the left ventricle and cardiac DTI metrics were compared within AHA segmentation. The number of hearts scanned at 7 T and 3 T was n = 11. No statistically significant differences were found for evaluated helix angle, secondary eigenvector angle, fractional anisotropy and apparent diffusion coefficient at the different field strengths, given sufficiently high SNR and geometrically undistorted images. R≥3 was needed to reduce susceptibility induced geometric distortions to an acceptable amount. On average SNR in myocardium of the left ventricle was increased from 29±3 to 44±6 in the reference image (b = 0 s/mm2) when switching from 3 T to 7 T. Our study demonstrates that high resolution, ex vivo cDTI is feasible at 7 T using commercial hardware. [ABSTRACT FROM AUTHOR]

This work discusses video communications over wireless networks (IEEE 802.11ac standard). The videos are in three different resolutions: 720p, 1080p, and 2160p. It is essential to study the performance of these media in access technologies to enhance the current coding and communications techniques. This study sets out a video quality prediction model that includes the different resolutions that are based on wireless network terms and conditions, an approach that has not previously been adopted in the literature. The model involves obtaining Service and Experience Quality Metrics, such as PSNR (Peak Signal-to-Noise Ratio) and packet loss. This article outlines a methodology and mathematical model for video quality loss in the wireless network from simulated data and its accuracy is ensured through the use of performance metrics (RMSE and Standard Deviation). The methodology is based on two mathematical functions, (logarithmic and exponential), and their parameters are defined by linear regression. The model obtained RMSE values and standard deviation of 2.32 dB and 2.2 dB for the predicted values, respectively. The results should lead to a CODEC (Coder-Decoder) improvement and contribute to a better wireless networks design. [ABSTRACT FROM AUTHOR]

Diffusion MRI derives its contrast from MR signal attenuation induced by the movement of water molecules in microstructural environments. Associated with the signal attenuation is the reduction of signal-to-noise ratio (SNR). Methods based on total variation (TV) have shown superior performance in image noise reduction. However, TV denoising can result in stair-casing effects due to the inherent piecewise-constant assumption. In this paper, we propose a tight wavelet frame based approach for edge-preserving denoising of diffusion-weighted (DW) images. Specifically, we employ the unitary extension principle (UEP) to generate frames that are discrete analogues to differential operators of various orders, which will help avoid stair-casing effects. Instead of denoising each DW image separately, we collaboratively denoise groups of DW images acquired with adjacent gradient directions. In addition, we introduce a very efficient method for solving an ℓ0 denoising problem that involves only thresholding and solving a trivial inverse problem. We demonstrate the effectiveness of our method qualitatively and quantitatively using synthetic and real data. [ABSTRACT FROM AUTHOR]

The locus coeruleus is a small brainstem nucleus which contains neuromelanin cells and is involved in a number of cognitive functions such as attention, arousal and stress, as well as several neurological and psychiatric disorders. Locus coeruleus imaging in vivo is generally performed using a T1-weighted turbo spin echo MRI sequence at 3 Tesla (T). However, imaging at high magnetic field strength can increase the signal-to-noise ratio and offers the possibility of imaging at higher spatial resolution. Therefore, in the present study we explored the possibility of visualizing the locus coeruleus at 7T. To this end, twelve healthy volunteers participated in three scanning sessions: two with 3T MRI and one with 7T MRI. The volumes of the first 3T session were used to segment the locus coeruleus, whereas the volumes of the second 3T and the 7T session were used to quantify the contrast of the locus coeruleus with several reference regions across eight different structural sequences. The results indicate that several of the 7T sequences provide detectable contrast between the locus coeruleus and surrounding tissue. Of the tested sequences, a T1-weighted sequence with spectral presaturation inversion recovery (SPIR) seems the most promising method for visualizing the locus coeruleus at ultra-high field MRI. While there is insufficient evidence to prefer the 7T SPIR sequence over the 3T TSE sequence, the isotropic voxels at 7T are an important advantage when visualizing small structures such as the locus coeruleus. [ABSTRACT FROM AUTHOR]

Purpose: Objective of this study was to evaluate the effectiveness of the iterative reconstruction of high-pitch dual-source chest CT (IR-HP-CT) scanned with low radiation exposure compared with low dose chest CT (LDCT). Materials and methods: This study was approved by the institutional review board. Thirty healthy adult volunteers (mean age 44 years) were enrolled in this study. All volunteers underwent both IR-HP-CT and LDCT. IR-HP-CT was scanned with 120 kVp tube voltage, 30 mAs tube current and pitch 3.2 and reconstructed with sinogram affirmed iterative reconstruction. LDCT was scanned with 120 kVp tube voltage, 40 mAs tube current and pitch 0.8 and reconstructed with B50 filtered back projection. Image noise, and signal to noise ratio (SNR) of the infraspinatus muscle, subcutaneous fat and lung parenchyma were calculated. Cardiac motion artifact, overall image quality and artifacts was rated by two blinded readers using 4-point scale. The dose-length product (DLP) (mGy∙cm) were obtained from each CT dosimetry table. Scan length was calculated from the DLP results. The DLP parameter was a metric of radiation output, not of patient dose. Size-specific dose estimation (SSDE, mGy) was calculated using the sum of the anteroposterior and lateral dimensions and effective radiation dose (ED, mSv) were calculated using CT dosimetry index. Results: Approximately, mean 40% of SSDE (2.1 ± 0.2 mGy vs. 3.5 ± 0.3 mGy) and 34% of ED (1.0 ± 0.1 mSv vs. 1.5 ± 0.1 mSv) was reduced in IR-HP-CT compared to LDCT (P < 0.0001). Image noise was reduced in the IR-HP-CT (16.8 ± 2.8 vs. 19.8 ± 3.4, P = 0.0001). SNR of lung and aorta of IR-HP-CT showed better results compared with that of LDCT (22.2 ± 5.9 vs. 33.0 ± 7.8, 1.9 ± 0.4 vs 1.1 ± 0.3, P < 0.0001). The score of cardiac pulsation artifacts were significantly reduced on IR-HP-CT (3.8 ± 0.4, 95% confidence interval, 3.7‒4.0) compared with LDCT (1.6 ± 0.6, 95% confidence interval, 1.3‒1.8) (P < 0.0001). SNR of muscle and fat, beam hardening artifact and overall subjective image quality of the mediastinum, lung and chest wall were comparable on both scans (P ≥ 0.05). Conclusion: IR-HP-CT with 120 kVp and 30 mAs tube setting in addition to an iterative reconstruction reduced cardiac motion artifact and radiation exposure while representing similar image quality compared with LDCT. [ABSTRACT FROM AUTHOR]

The current commercial access point (AP) selection schemes are mostly based on received signal strength, but perform poorly in many situations. To address this problem, a number of alternative schemes collect and analyze the actual load of every candidate AP. However, these schemes may incur significant latency and signaling overhead in dense wireless local area networks (WLANs). To mitigate such overhead, we propose a user application-based AP selection scheme that considers historical information about AP performance. Without inducing any signaling activity, our scheme monitors the amount of network traffic used by applications and estimates the achievable throughput of APs. Our scheme employs the characteristics of application traffic with the intent of accurately predicting AP performance. Using a measurement study in dense WLAN environments, we show that our scheme achieves higher throughput and lower association latency than those of existing schemes in places highly accessible to the user. [ABSTRACT FROM AUTHOR]

In this study, we investigate the feasibility of improving the imaging quality for low-dose multislice helical computed tomography (CT) via iterative reconstruction with tensor framelet (TF) regularization. TF based algorithm is a high-order generalization of isotropic total variation regularization. It is implemented on a GPU platform for a fast parallel algorithm of X-ray forward band backward projections, with the flying focal spot into account. The solution algorithm for image reconstruction is based on the alternating direction method of multipliers or the so-called split Bregman method. The proposed method is validated using the experimental data from a Siemens SOMATOM Definition 64-slice helical CT scanner, in comparison with FDK, the Katsevich and the total variation (TV) algorithm. To test the algorithm performance with low-dose data, ACR and Rando phantoms were scanned with different dosages and the data was equally undersampled with various factors. The proposed method is robust for the low-dose data with 25% undersampling factor. Quantitative metrics have demonstrated that the proposed algorithm achieves superior results over other existing methods. [ABSTRACT FROM AUTHOR]

Background: Spatial release of masking (SRM) is a measure of an individual’s ability to perform speech-noise segregation, which is usually quantified by the extent of improvement of the individual’s speech recognition performance when the noise is switched from a spatially co-located position (e.g., speech and noise both presented from the front) to a spatially separated position (e.g., speech presented from the front and noise presented from the right side) with reference to the target speech. SRM is a combined measure of head shadow and binaural unmasking benefits. SRM has only been investigated in young children at group level but not at individual participant level in the international literature due to the lack of reliable speech recognition test materials able to detect subtle statistically significant within-participant changes in speech-recognition-in-noise thresholds. Method: The performance to signal-to-noise ratio (P-SNR) functions of twenty-four disyllabic words were obtained from 40 native Mandarin-speaking children aged 3.6–6.2 years with reported normal speech, language and hearing. The test items’ difficulty levels were homogenized by adjusting the speech intensity level of each item so that the adjusted signal-to-noise ratio for 50% correct score (SNR-50%) point of each item would overlap at the mean SNR-50% point of all test items. In the MAPID-A, the homogenized test items were randomly presented in an adaptive testing procedure at a fixed noise intensity level, but the speech intensity level of the upcoming test item varied in 2-dB SNR steps depending on the recognition result of the previous test item. The SNR reversal point is marked by a change from a decrease to an increase in the SNR or vice versa. Two successive SNR reversal points marked the boundaries of an excursion. The mid-points from 12 excursions (in dB SNR) were averaged to produce the adaptive SNR-50% measure (aSNR-50%). Results: The aSNR-50% results were obtained from another 12 children aged 4.8–5.3 years with reported normal speech, language and hearing. The average 99% confidence interval (CI) of all participants’ mean aSNR-50% values was ±1.61 dB SNR; therefore, 3.22 dB SNR was the average critical difference required to confirm a significant difference in the scores obtained from the same participant between two test conditions. Statistically significant within-participant SRM was identified in 95% of the participants; in other words, aSNR-50% obtained from the spatially separated condition outperformed aSNR-50% obtained from the spatially co-located condition. The adaptive testing procedure was highly reliable, with an within-participant test-retest reliability of 90.6%. and significantly limited testing time to an average of 4.2 min. This research study has fulfilled its aim on detecting subtle within-participant SRM in very young children starting from 4 years of age with a reliable statistical procedure. MAPID-A offers a reliable and efficient clinical tool to investigate speech-recognition-in-noise and SRM performances in young Mandarin-speaking children. Conclusions: The narrow CIs, high test-retest reliability, and short testing time has proven that the MAPID-A is a promising sensitive, reliable and time-efficient clinical tool to detect subtle within-participant speech-recognition-in-noise changes in children as young as 4–5 years. The MAPID-A offers a clinical tool to behaviorally track young children’s development in speech-recognition-in-noise and SRM, and to potentially review the development of the auditory neural pathway and the cerebral dominance for speech-recognition-in-noise in young children. [ABSTRACT FROM AUTHOR]

To further reduce the noise and artifacts in the reconstructed image of sparse-view CT, we have modified the traditional total variation (TV) methods, which only calculate the gradient variations in x and y directions, and have proposed 8- and 26-directional (the multi-directional) gradient operators for TV calculation to improve the quality of reconstructed images. Different from traditional TV methods, the proposed 8- and 26-directional gradient operators additionally consider the diagonal directions in TV calculation. The proposed method preserves more information from original tomographic data in the step of gradient transform to obtain better reconstruction image qualities. Our algorithms were tested using two-dimensional Shepp–Logan phantom and three-dimensional clinical CT images. Results were evaluated using the root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR), and universal quality index (UQI). All the experiment results show that the sparse-view CT images reconstructed using the proposed 8- and 26-directional gradient operators are superior to those reconstructed by traditional TV methods. Qualitative and quantitative analyses indicate that the more number of directions that the gradient operator has, the better images can be reconstructed. The 8- and 26-directional gradient operators we proposed have better capability to reduce noise and artifacts than traditional TV methods, and they are applicable to be applied to and combined with existing CT reconstruction algorithms derived from CS theory to produce better image quality in sparse-view reconstruction. [ABSTRACT FROM AUTHOR]

Local field potential (LFP) recording is a very useful electrophysiological method to study brain processes. However, this method is criticized for recording low frequency activity in a large area of extracellular space potentially contaminated by distal activity. Here, we theoretically and experimentally compare ground-referenced (RR) with differential recordings (DR). We analyze electrical activity in the rat cortex with these two methods. Compared with RR, DR reveals the importance of local phasic oscillatory activities and their coherence between cortical areas. Finally, we show that DR provides a more faithful assessment of functional connectivity caused by an increase in the signal to noise ratio, and of the delay in the propagation of information between two cortical structures. [ABSTRACT FROM AUTHOR]

We investigated the feasibility of low-dose coronary computed tomography angiography (CCTA), using a prospective electrocardiogram (ECG)-triggered axial scan protocol, knowledge-based iterative model reconstruction (IMR), and fixed tube current, in overweight subjects. Forty non-overweight (group A; body-mass index [BMI] < 25 kg/m2) and 40 overweight individuals (group B; BMI = 25–30 kg/m2), who underwent CCTA for coronary artery disease screening, were retrospectively and consecutively enrolled. A 64-slice CT scanner was used at 100-kVp tube voltage and 150-mA tube current, and images were reconstructed using IMR techniques. Image noise, attenuation at the aorta, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) at the proximal right and left main coronary arteries (pRCA and LMCA) were calculated. CCTA images were qualitatively evaluated using a four-point scale (1, poor; 4, excellent) and analyzed using a non-inferiority test with a pre-defined non-inferiority margin of -0.2. The mean CCTA radiation dose (Group A: 1.33 ± 0.02 mSv; Group B: 1.35 ± 0.10 mSv; p = 0.151) and mean aortic root CT attenuation values (Group A: 447.9 ± 81.6 HU; Group B: 439.5 ± 63.6 HU; p = 0.571) did not differ significantly between the two groups. The mean noise in groups A and B was 26.0 ± 4.8 HU and 29.2 ± 4.4 HU, respectively (p = 0.005). The noise reduction ratio in the groups, compared to filtered back projection, was 65.0% and 68.1%, respectively. The mean grade of image quality did not differ significantly (3.75 ± 0.04 vs. 3.71 ± 0.04, p = 0.478). Group B CCTA image quality was non-inferior (mean difference = -0.043, 95% CI = -0.162–0.077) to that of Group A. We concluded that low-dose CCTA with prospective ECG-triggering and IMR might be applied to overweight subjects, as well as to normal-weight subjects, by using a fixed tube current without an increase in tube current based on the patient’s body size. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this work is the design, implementation and evaluation of a mechanically flexible receive-only coil array for magnetic resonance imaging (MRI) at 3 T that can be applied to various target organs and provides high parallel imaging performance. Methods: A 23-channel array was designed based on a rigid-flex printed circuit board (PCB). The flexible multi-layer part contains the copper traces forming the coil elements. The rigid part of the PCB houses the solder joints and lumped elements. The coil housing consists of rigid caps mounted above the rigid parts. Adhesive PTFE sheets cover all flexible parts. The developed array was tested on the bench as well as in phantom and in vivo MRI experiments employing parallel imaging acceleration factors up to six. Results: Efficient mutual decoupling between receive elements and detuning between receive array and body coil was achieved. An increased signal-to-noise ratio in comparison to commercial reference coils is demonstrated, especially in regions close to the developed array and for high parallel imaging acceleration factors. Exemplary in vivo images of head, ankle, knee, shoulder and hand are presented. Conclusion: Based on high sensitivity close to the array and low g-factors, this flexible coil is well suited for studies of occipital and temporal cortex, as well as musculoskeletal targets like knee, ankle, elbow and wrist. [ABSTRACT FROM AUTHOR]

The number of selectable targets is one of the main factors that affect the performance of a brain-computer interface (BCI). Most existing code modulated visual evoked potential (c-VEP) based BCIs use a single pseudorandom binary sequence and its circularly shifting sequences to modulate different stimulus targets, making the number of selectable targets limited by the length of modulation codes. This paper proposes a novel paradigm for c-VEP BCIs, which divides the stimulus targets into four target groups and each group of targets are modulated by a unique pseudorandom binary code and its circularly shifting codes. Based on the paradigm, a four-group c-VEP BCI with a total of 64 stimulus targets was developed and eight subjects were recruited to participate in the BCI experiment. Based on the experimental data, the characteristics of the c-VEP BCI were explored by the analyses of auto- and cross-correlation, frequency spectrum, signal to noise ratio and correlation coefficient. On the basis, single-trial data with the length of one stimulus cycle were classified and the attended target was recognized. The averaged classification accuracy across subjects was 88.36% and the corresponding information transfer rate was as high as 184.6 bit/min. These results suggested that the c-VEP BCI paradigm is both feasible and effective, and provides a new solution for BCI study to substantially increase the number of available targets. [ABSTRACT FROM AUTHOR]

Background: Magnetic Resonance Imaging (MRI) relies on optimal scanning parameters to achieve maximal signal-to-noise ratio (SNR) and high contrast-to-noise ratio (CNR) between tissues resulting in high quality images. The optimization of such parameters is often laborious, time consuming, and user-dependent, making harmonization of imaging parameters a difficult task. In this report, we aim to develop and validate a computer simulation technique that can reliably provide “optimal in vivo scanning parameters” ready to be used for in vivo evaluation of disease models. Methods: A glioblastoma murine model was investigated using several MRI imaging methods. Such MRI methods underwent a simulated and an in vivo scanning parameter optimization in pre- and post-contrast conditions that involved the investigation of tumor, brain parenchyma and cerebrospinal fluid (CSF) CNR values in addition to the time relaxation values of the related tissues. The CNR tissues information were analyzed and the derived scanning parameters compared in order to validate the simulated methodology as a reliable technique for “optimal in vivo scanning parameters” estimation. Results: The CNRs and the related scanning parameters were better correlated when spin-echo-based sequences were used rather than the gradient-echo-based sequences due to augmented inhomogeneity artifacts affecting the latter methods. “Optimal in vivo scanning parameters” were generated successfully by the simulations after initial scanning parameter adjustments that conformed to some of the parameters derived from the in vivo experiment. Conclusion: Scanning parameter optimization using the computer simulation was shown to be a valid surrogate to the in vivo approach in a glioblastoma murine model yielding in a better delineation and differentiation of the tumor from the contralateral hemisphere. In addition to drastically reducing the time invested in choosing optimal scanning parameters when compared to an in vivo approach, this simulation program could also be used to harmonize MRI acquisition parameters across scanners from different vendors. [ABSTRACT FROM AUTHOR]

We theoretically investigate the signal-to-noise ratio (SNR) of a parallel array of leaky integrate-and-fire (LIF) neurons that receives a weak periodic signal and uses spatially nearest neighbor correlated noise. By using linear response theory, we derive the analytic expression of the SNR. The results show that the amplitude of internal noise can be increased up to an optimal value, which corresponds to a maximum SNR. Given the existence of spatially nearest neighbor correlated noise in the neural ensemble, the SNR gain of the collective ensemble response can exceed unity, especially for a negative correlation. This nonlinear collective phenomenon of SNR gain amplification may be related to the array stochastic resonance. In addition, we show that the SNR can be improved by varying the number of neurons, frequency, and amplitude of the weak periodic signal. We expect that this investigation will be useful for both controlling the collective response of neurons and enhancing weak signal transmission. [ABSTRACT FROM AUTHOR]

This study investigates quality prediction methods for synthesized speech using EEG. Training a predictive model using EEG is challenging due to a small number of training trials, a low signal-to-noise ratio, and a high correlation among independent variables. When a predictive model is trained with a machine learning algorithm, the features extracted from multi-channel EEG signals are usually organized as a vector and their structures are ignored even though they are highly structured signals. This study predicts the subjective rating scores of synthesized speeches, including their overall impression, valence, and arousal, by creating tensor structured features instead of vectorized ones to exploit the structure of the features. We extracted various features to construct a tensor feature that maintained their structure. Vectorized and tensorial features were used to predict the rating scales, and the experimental result showed that prediction with tensorial features achieved the better predictive performance. Among the features, the alpha and beta bands are particularly more effective for predictions than other features, which agrees with previous neurophysiological studies. [ABSTRACT FROM AUTHOR]

This work focuses on the experimental data analysis of electroencephalography (EEG) data, in which multiple sensors are recording oscillatory voltage time series. The EEG data analyzed in this manuscript has been acquired using a low-cost commercial headset, the Emotiv EPOC+. Our goal is to compare different techniques for the optimal estimation of collective rhythms from EEG data. To this end, a traditional method such as the principal component analysis (PCA) is compared to more recent approaches to extract a collective rhythm from phase-synchronized data. Here, we extend the work by Schwabedal and Kantz (PRL 116, 104101 (2016)) evaluating the performance of the Kosambi-Hilbert torsion (KHT) method to extract a collective rhythm from multivariate oscillatory time series and compare it to results obtained from PCA. The KHT method takes advantage of the singular value decomposition algorithm and accounts for possible phase lags among different time series and allows to focus the analysis on a specific spectral band, optimally amplifying the signal-to-noise ratio of a common rhythm. We evaluate the performance of these methods for two particular sets of data: EEG data recorded with closed eyes and EEG data recorded while observing a screen flickering at 15 Hz. We found an improvement in the signal-to-noise ratio of the collective signal for the KHT over the PCA, particularly when random temporal shifts are added to the channels. [ABSTRACT FROM AUTHOR]

Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

Over the past several years, significant efforts have been made to improve the spatial resolution of diffusion-weighted imaging (DWI), aiming at better detecting subtle lesions and more reliably resolving white-matter fiber tracts. A major concern with high-resolution DWI is the limited signal-to-noise ratio (SNR), which may significantly offset the advantages of high spatial resolution. Although the SNR of DWI data can be improved by denoising in post-processing, existing denoising procedures may potentially reduce the anatomic resolvability of high-resolution imaging data. Additionally, non-Gaussian noise induced signal bias in low-SNR DWI data may not always be corrected with existing denoising approaches. Here we report an improved denoising procedure, termed diffusion-matched principal component analysis (DM-PCA), which comprises 1) identifying a group of (not necessarily neighboring) voxels that demonstrate very similar magnitude signal variation patterns along the diffusion dimension, 2) correcting low-frequency phase variations in complex-valued DWI data, 3) performing PCA along the diffusion dimension for real- and imaginary-components (in two separate channels) of phase-corrected DWI voxels with matched diffusion properties, 4) suppressing the noisy PCA components in real- and imaginary-components, separately, of phase-corrected DWI data, and 5) combining real- and imaginary-components of denoised DWI data. Our data show that the new two-channel (i.e., for real- and imaginary-components) DM-PCA denoising procedure performs reliably without noticeably compromising anatomic resolvability. Non-Gaussian noise induced signal bias could also be reduced with the new denoising method. The DM-PCA based denoising procedure should prove highly valuable for high-resolution DWI studies in research and clinical uses. [ABSTRACT FROM AUTHOR]

The prototypes of ultra-low-field (ULF) MRI scanners developed in recent years represent new, innovative, cost-effective and safer systems, which are suitable to be integrated in multi-modal (Magnetoencephalography and MRI) devices. Integrated ULF-MRI and MEG scanners could represent an ideal solution to obtain functional (MEG) and anatomical (ULF MRI) information in the same environment, without errors that may limit source reconstruction accuracy. However, the low resolution and signal-to-noise ratio (SNR) of ULF images, as well as their limited coverage, do not generally allow for the construction of an accurate individual volume conductor model suitable for MEG localization. Thus, for practical usage, a high-field (HF) MRI image is also acquired, and the HF-MRI images are co-registered to the ULF-MRI ones. We address here this issue through an optimized pipeline (SWIM—Sliding WIndow grouping supporting Mutual information). The co-registration is performed by an affine transformation, the parameters of which are estimated using Normalized Mutual Information as the cost function, and Adaptive Simulated Annealing as the minimization algorithm. The sub-voxel resolution of the ULF images is handled by a sliding-window approach applying multiple grouping strategies to down-sample HF MRI to the ULF-MRI resolution. The pipeline has been tested on phantom and real data from different ULF-MRI devices, and comparison with well-known toolboxes for fMRI analysis has been performed. Our pipeline always outperformed the fMRI toolboxes (FSL and SPM). The HF–ULF MRI co-registration obtained by means of our pipeline could lead to an effective integration of ULF MRI with MEG, with the aim of improving localization accuracy, but also to help exploit ULF MRI in tumor imaging. [ABSTRACT FROM AUTHOR]

Typical simultaneous blood oxygenation-level dependent (BOLD) and arterial spin labeling (ASL) sequences acquire two echoes, one perfusion-sensitive and one BOLD-sensitive. However, for ASL, spatial resolution and brain coverage are limited due to the T1 decay of the labeled blood. This study applies a sequence combining a multiband acquisition with four echoes for simultaneous BOLD and pseudo-continuous ASL (pCASL) echo planar imaging (MBME ASL/BOLD) for block-design task-fMRI. A multiband acceleration of four was employed to increase brain coverage and reduce slice-timing effects on the ASL signal. Multi-echo independent component analysis (MEICA) was implemented to automatically denoise the BOLD signal by regressing non-BOLD components. This technique led to increased temporal signal-to-noise ratio (tSNR) and BOLD sensitivity. The MEICA technique was also modified to denoise the ASL signal by regressing artifact and BOLD signals from the first echo time-series. The MBME ASL/BOLD sequence was applied to a finger-tapping task functional MRI (fMRI) experiment. Signal characteristics and activation were evaluated using single echo BOLD, combined ME BOLD, combined ME BOLD after MEICA denoising, perfusion-weighted (PW), and perfusion-weighted after MEICA denoising time-series. The PW data was extracted using both surround subtraction and high-pass filtering followed by demodulation. In addition, the CBF/BOLD response ratio and CBF/BOLD coupling were analyzed. Results showed that the MEICA denoising procedure significantly improved the BOLD signal, leading to increased BOLD sensitivity, tSNR, and activation statistics compared to conventional single echo BOLD data. At the same time, the denoised PW data showed increased tSNR and activation statistics compared to the non-denoised PW data. CBF/BOLD coupling was also increased using the denoised ASL and BOLD data. Our preliminary data suggest that the MBME ASL/BOLD sequence can be employed to collect whole-brain task-fMRI with improved data quality for both BOLD and PW time series, thus improving the results of block-design task fMRI. [ABSTRACT FROM AUTHOR]

Voluntary movements and the standing of spinal cord injured patients have been facilitated using lumbosacral spinal cord epidural stimulation (scES). Identifying the appropriate stimulation parameters (intensity, frequency and anode/cathode assignment) is an arduous task and requires extensive mapping of the spinal cord using evoked potentials. Effective visualization and detection of muscle evoked potentials induced by scES from the recorded electromyography (EMG) signals is critical to identify the optimal configurations and the effects of specific scES parameters on muscle activation. The purpose of this work was to develop a novel approach to automatically detect the occurrence of evoked potentials, quantify the attributes of the signal and visualize the effects across a high number of scES parameters. This new method is designed to automate the current process for performing this task, which has been accomplished manually by data analysts through observation of raw EMG signals, a process that is laborious and time-consuming as well as prone to human errors. The proposed method provides a fast and accurate five-step algorithms framework for activation detection and visualization of the results including: conversion of the EMG signal into its 2-D representation by overlaying the located signal building blocks; de-noising the 2-D image by applying the Generalized Gaussian Markov Random Field technique; detection of the occurrence of evoked potentials using a statistically optimal decision method through the comparison of the probability density functions of each segment to the background noise utilizing log-likelihood ratio; feature extraction of detected motor units such as peak-to-peak amplitude, latency, integrated EMG and Min-max time intervals; and finally visualization of the outputs as Colormap images. In comparing the automatic method vs. manual detection on 700 EMG signals from five individuals, the new approach decreased the processing time from several hours to less than 15 seconds for each set of data, and demonstrated an average accuracy of 98.28% based on the combined false positive and false negative error rates. The sensitivity of this method to the signal-to-noise ratio (SNR) was tested using simulated EMG signals and compared to two existing methods, where the novel technique showed much lower sensitivity to the SNR. [ABSTRACT FROM AUTHOR]

Objectives: To quantitatively and qualitatively assess abdominal arterial and venous phase contrast-enhanced spectral detector computed tomography (SDCT) virtual mono-energetic (MonoE) datasets in comparison to conventional CT reconstructions provided by the same system. Materials and methods: Conventional and MonoE images at 40–120 kilo-electron volt (keV) levels with a 10 keV increment as well as 160 and 200 keV were reconstructed in abdominal SDCT datasets of 55 patients. Attenuation, image noise, and contrast- / signal-to-noise ratios (CNR, SNR) of vessels and solid organs were compared between MonoE and conventional reconstructions. Two readers assessed contrast conditions, detail visualization, overall image quality and subjective image noise with both, fixed and adjustable window settings. Results: Attenuation, CNR and SNR of vessels and solid organs showed a stepwise increase from high to low keV reconstructions in both contrast phases while image noise stayed stable at low keV MonoE reconstruction levels. Highest levels were found at 40 keV MonoE reconstruction (p<0.001), respectively. Solid abdominal organs showed a stepwise decrease from low to high energy levels in regard to attenuation, CNR and SNR with significantly higher values at 40 and 50 keV, compared to conventional images. The 70 keV MonoE was comparable to conventional poly-energetic reconstruction (p≥0.99). Subjective analysis displayed best image quality for the 70 keV MonoE reconstruction level in both phases at fixed standard window presets and at 40 keV if window settings could be adjusted. Conclusion: SDCT derived low keV MonoE showed markedly increased CNR and SNR values due to constantly low image noise values over the whole energy spectrum from 40 to 200 keV. [ABSTRACT FROM AUTHOR]

Arterial Spin Labeled (ASL) perfusion MRI enables non-invasive, quantitative measurements of tissue perfusion, and has a broad range of applications including brain functional imaging. However, ASL suffers from low signal-to-noise ratio (SNR), limiting image resolution. Acquisitions using 3D readouts are optimal for background-suppression of static signals, but can be SAR intensive and typically suffer from through-plane blurring. In this study, we investigated the use of accelerated 3D readouts to obtain whole-brain, high-SNR ASL perfusion maps and reduce SAR deposition. Parallel imaging was implemented along the partition-encoding direction in a pseudo-continuous ASL sequence with background-suppression and 3D RARE Stack-Of-Spirals readout, and its performance was evaluated in three small cohorts. First, both non-accelerated and two-fold accelerated single-shot versions of the sequence were evaluated in healthy volunteers during a motor-photic task, and the performance was compared in terms of temporal SNR, GM-WM contrast, and statistical significance of the detected activation. Secondly, single-shot 1D-accelerated imaging was compared to a two-shot accelerated version to assess benefits of SNR and spatial resolution for applications in which temporal resolution is not paramount. Third, the efficacy of this approach in clinical populations was assessed by applying the single-shot 1D-accelerated version to a larger cohort of elderly volunteers. Accelerated data demonstrated the ability to detect functional activation at the subject level, including cerebellar activity, without loss in the perfusion signal temporal stability and the statistical power of the activations. The use of acceleration also resulted in increased GM-WM contrast, likely due to reduced through-plane partial volume effects, that were further attenuated with the use of two-shot readouts. In a clinical cohort, image quality remained excellent, and expected effects of age and sex on cerebral blood flow could be detected. The sequence is freely available upon request for academic use and could benefit a broad range of cognitive and clinical neuroscience research. [ABSTRACT FROM AUTHOR]

Objectives: The present study explored tone perception ability in school age Mandarin-speaking children with otitis media with effusion (OME) in noisy listening environments. The study investigated the interaction effects of noise, tone type, age, and hearing status on monaural tone perception, and assessed the application of a hierarchical clustering algorithm for profiling hearing impairment in children with OME. Methods: Forty-one children with normal hearing and normal middle ear status and 84 children with OME with or without hearing loss participated in this study. The children with OME were further divided into two subgroups based on their severity and pattern of hearing loss using a hierarchical clustering algorithm. Monaural tone recognition was measured using a picture-identification test format incorporating six sets of monosyllabic words conveying four lexical tones under speech spectrum noise, with the signal-to-noise ratio (SNR) conditions ranging from -9 to -21 dB. Results: Linear correlation indicated tone recognition thresholds of children with OME were significantly correlated with age and pure tone hearing thresholds at every frequency tested. Children with hearing thresholds less affected by OME performed similarly to their peers with normal hearing. Tone recognition thresholds of children with auditory status more affected by OME were significantly inferior to those of children with normal hearing or with minor hearing loss. Younger children demonstrated poorer tone recognition performance than older children with OME. A mixed design repeated-measure ANCOVA showed significant main effects of listening condition, hearing status, and tone type on tone recognition. Contrast comparisons revealed that tone recognition scores were significantly better under -12 dB SNR than under -15 dB SNR conditions and tone recognition scores were significantly worse under -18 dB SNR than those obtained under -15 dB SNR conditions. Tone 1 was the easiest tone to identify and Tone 3 was the most difficult tone to identify for all participants, when considering -12, -15, and -18 dB SNR as within-subject variables. The interaction effect between hearing status and tone type indicated that children with greater levels of OME-related hearing loss had more impaired tone perception of Tone 1 and Tone 2 compared to their peers with lesser levels of OME-related hearing loss. However, tone perception of Tone 3 and Tone 4 remained similar among all three groups. Tone 2 and Tone 3 were the most perceptually difficult tones for children with or without OME-related hearing loss in all listening conditions. Conclusions: The hierarchical clustering algorithm demonstrated usefulness in risk stratification for tone perception deficiency in children with OME-related hearing loss. There was marked impairment in tone perception in noise for children with greater levels of OME-related hearing loss. Monaural lexical tone perception in younger children was more vulnerable to noise and OME-related hearing loss than that in older children. [ABSTRACT FROM AUTHOR]

This study proposes a method for classifying event-related fMRI responses in a specialized setting of many known but few unknown stimuli presented in a rapid event-related design. Compared to block design fMRI signals, classification of the response to a single or a few stimulus trial(s) is not a trivial problem due to contamination by preceding events as well as the low signal-to-noise ratio. To overcome such problems, we proposed a single trial-based classification method of rapid event-related fMRI signals utilizing sparse multivariate Bayesian decoding of spatio-temporal fMRI responses. We applied the proposed method to classification of memory retrieval processes for two different classes of episodic memories: a voluntarily conducted experience and a passive experience induced by watching a video of others’ actions. A cross-validation showed higher classification performance of the proposed method compared to that of a support vector machine or of a classifier based on the general linear model. Evaluation of classification performances for one, two, and three stimuli from the same class and a correlation analysis between classification accuracy and target stimulus positions among trials suggest that presenting two target stimuli at longer inter-stimulus intervals is optimal in the design of classification experiments to identify the target stimuli. The proposed method for decoding subject-specific memory retrieval of voluntary behavior using fMRI would be useful in forensic applications in a natural environment, where many known trials can be extracted from a simulation of everyday tasks and few target stimuli from a crime scene. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to explore the efficacy of Ultra-high field [UHF] 7 Tesla [T] MRI as compared to 3T MRI in non-contrast enhanced [nCE] imaging of structural anatomy in the elbow, forearm, and hand [upper extremity]. Materials and method: A wide range of sequences including T1 weighted [T1] volumetric interpolate breath-hold exam [VIBE], T2 weighted [T2] double-echo steady state [DESS], susceptibility weighted imaging [SWI], time-of-flight [TOF], diffusion tensor imaging [DTI], and diffusion spectrum imaging [DSI] were optimized and incorporated with a radiofrequency [RF] coil system composed of a transverse electromagnetic [TEM] transmit coil combined with an 8-channel receive-only array for 7T upper extremity [UE] imaging. In addition, Siemens optimized protocol/sequences were used on a 3T scanner and the resulting images from T1 VIBE and T2 DESS were compared to that obtained at 7T qualitatively and quantitatively [SWI was only qualitatively compared]. DSI studio was utilized to identify nerves based on analysis of diffusion weighted derived fractional anisotropy images. Images of forearm vasculature were extracted using a paint grow manual segmentation method based on MIPAV [Medical Image Processing, Analysis, and Visualization]. Results: High resolution and high quality signal-to-noise ratio [SNR] and contrast-to-noise ratio [CNR]—images of the hand, forearm, and elbow were acquired with nearly homogeneous 7T excitation. Measured [performed on the T1 VIBE and T2 DESS sequences] SNR and CNR values were almost doubled at 7T vs. 3T. Cartilage, synovial fluid and tendon structures could be seen with higher clarity in the 7T T1 and T2 weighted images. SWI allowed high resolution and better quality imaging of large and medium sized arteries and veins, capillary networks and arteriovenous anastomoses at 7T when compared to 3T. 7T diffusion weighted sequence [not performed at 3T] demonstrates that the forearm nerves are clearly delineated by fiber tractography. The proper digital palmar arteries and superficial palmar arch could also be clearly visualized using TOF nCE 7T MRI. Conclusion: Ultra-high resolution neurovascular imaging in upper extremities is possible at 7T without use of renal toxic intravenous contrast. 7T MRI can provide superior peripheral nerve [based on fiber anisotropy and diffusion coefficient parameters derived from diffusion tensor/spectrum imaging] and vascular [nCE MRA and vessel segmentation] imaging. [ABSTRACT FROM AUTHOR]

Optical “virtual biopsy” is an attractive way to improve disease diagnosis and surgical guidance. Many optical microscopy techniques have been developed to provide diagnostic information without the need for tissue sectioning or staining. Among these techniques, label-free chemical imaging is the most desirable. Recently, it has been shown that narrowband, picosecond stimulated Raman scattering (SRS) can achieve comparable morphological contrast to hematoxylin and eosin staining (H&E staining), the ‘gold standard’ of pathology. However, to translate the technique from the bench to the bedside, optimal laser sources and parameters have yet to be identified. Here we describe an improvement to the narrowband SRS microscopy techniques for label-free tissue imaging. Through spectral slicing of broadband, femtosecond pulses, we are able to maintain the same protein/lipid contrast as narrowband SRS while achieving a higher signal-to-noise ratio (SNR). Our method draws upon the benefits of femtosecond pulses (e.g. higher peak power) while preserving those of picosecond pulses (e.g. adequate spectral resolution). We demonstrate this achievement through protein/lipid signal and contrast quantification of mouse brain tissue as a function of bandwidth, and comparison with numerical simulations. Further method validation is provided through imaging of additional mouse tissues: liver, kidney, and skin. [ABSTRACT FROM AUTHOR]

Purpose: Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. Materials and methods: The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18–70 years) and 13 patients with epilepsy (8 males, age range 21–67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients). Results: RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG recorded during high-speed fMRI and during conventional EPI (p = 0.78). Residual ballistocardiographic artifacts resulted in 58% of EEG data being rated as poor quality. Conclusion: This study demonstrates that high-density EEG can be safely implemented in conjunction with high-speed fMRI and that high-speed fMRI does not adversely affect EEG data quality. However, the deterioration of the EEG quality due to residual ballistocardiographic artifacts remains a significant constraint for routine clinical applications of concurrent EEG-fMRI. [ABSTRACT FROM AUTHOR]

Artificial, anisotropic fibre phantoms are nowadays increasingly used in the field of diffusion-weighted MRI. Such phantoms represent useful tools for, among others, the calibration of pulse sequences and validation of diffusion models since they can mimic well-known structural features of brain tissue on the one hand, but exhibit a reduced complexity, on the other. Among all materials, polyethylene fibres have been widely used due to their excellent properties regarding the restriction of water diffusion and surface relaxation properties. Yet the magnetic susceptibility of polyethylene can be distinctly lower than that of distilled water. This difference produces strong microscopic, background field gradients in the vicinity of fibre bundles which are not parallel to the static magnetic field. This, in turn, modulates the MRI signal behaviour. In the present work we investigate an approach to reduce the susceptibility-induced background gradients via reducing the heterogeneity in the internal magnetic susceptibility. An aqueous solution of magnesium chloride hexahydrate (MgCl2·6H2O) is used for this purpose. Its performance is demonstrated in dedicated anisotropic fibre phantoms with different geometrical configurations. [ABSTRACT FROM AUTHOR]

Background: To study dose reduction using iterative reconstruction (IR) for pediatric great vessel stent computed tomography (CT). Methods: Five different great vessel stents were separately placed in a gel-containing plastic holder within an anthropomorphic chest phantom. The stent lumen was filled with diluted contrast gel. CT acquisitions were performed at routine dose, 52% and 81% reduced dose and reconstructed with filtered back projection (FBP) and IR. Objective image quality in terms of noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as subjective image quality were evaluated. Results: Noise, SNR and CNR were improved with IR at routine and 52% reduced dose, compared to FBP at routine dose. The lowest dose level resulted in decreased objective image quality with both FBP and IR. Subjective image quality was excellent at all dose levels. Conclusion: IR resulted in improved objective image quality at routine dose and 52% reduced dose, while objective image quality deteriorated at 81% reduced dose. Subjective image quality was not affected by dose reduction. [ABSTRACT FROM AUTHOR]

The P300 Speller is a common brain-computer interface communication system. There are many parallel lines of research underway to overcome the system’s low signal to noise ratio and thereby improve performance, including using famous face stimuli and integrating language information into the classifier. While both have been shown separately to provide significant improvements, the two methods have not yet been implemented together to demonstrate that the improvements are complimentary. The goal of this study is therefore twofold. First, we aim to compare the famous faces stimulus paradigm with an existing alternative stimulus paradigm currently used in commercial systems (i.e., character inversion). Second, we test these methods with language model integration to assess whether different optimization approaches can be combined to further improve BCI communication. In offline analysis using a previously published particle filter method, famous faces stimuli yielded superior results to both standard and inverting stimuli. In online trials using the particle filter method, all 10 subjects achieved a higher selection rate when using the famous faces flashing paradigm than when using inverting flashes. The improvements achieved by these methods are therefore complementary and a combination yields superior results to either method implemented individually when tested in healthy subjects. [ABSTRACT FROM AUTHOR]

Applicability of intravoxel incoherent motion (IVIM) imaging in the clinical setting is hampered by the limited reliability in particular of the perfusion-related parameter estimates. To alleviate this problem, various advanced postprocessing methods have been introduced. However, the underlying algorithms are not readily available and generally suffer from an increased computational burden. Contrary, several computationally fast image denoising methods have recently been proposed which are accessible online and may improve reliability of IVIM parameter estimates. The objective of the present work is to investigate the impact of image denoising on accuracy and precision of IVIM parameter estimates using comprehensive in-silico and in-vivo experiments. Image denoising is performed with four different algorithms that work on magnitude data: two algorithms which are based on nonlocal means (NLM) filtering, one algorithm that relies on local principal component analysis (LPCA) of the diffusion-weighted images, and another algorithms that exploits joint rank and edge constraints (JREC). Accuracy and precision of IVIM parameter estimates is investigated in an in-silico brain phantom and an in-vivo ground truth as a function of the signal-to-noise ratio for spatially homogenous and inhomogenous levels of Rician noise. Moreover, precision is evaluated using bootstrap analysis of in-vivo measurements. In the experiments, IVIM parameters are computed a) by using a segmented fit method and b) by performing a biexponential fit of the entire attenuation curve based on nonlinear least squares estimates. Irrespective of the fit method, the results demonstrate that reliability of IVIM parameter estimates is substantially improved by image denoising. The experiments show that the LPCA and the JREC algorithms perform in a similar manner and outperform the NLM-related methods. Relative to noisy data, accuracy of the IVIM parameters in the in-silico phantom improves after image denoising by 76–79%, 79–81%, 84–99% and precision by 74–80%, 80–83%, 84–95% for the perfusion fraction, the diffusion coefficient, and the pseudodiffusion coefficient, respectively, when the segmented fit method is used. Beyond that, the simulations reveal that denoising performance is not impeded by spatially inhomogeneous levels of Rician noise in the image. Since all investigated algorithms are freely available and work on magnitude data they can be readily applied in the clinical setting which may foster transition of IVIM imaging into clinical practice. [ABSTRACT FROM AUTHOR]

Purpose: Continuous and rapid eye movement causes significant intraframe distortion in adaptive optics high resolution retinal imaging. To minimize this artifact, we developed a high speed adaptive optics line scan confocal retinal imaging system. Methods: A high speed line camera was employed to acquire retinal image and custom adaptive optics was developed to compensate the wave aberration of the human eye’s optics. The spatial resolution and signal to noise ratio were assessed in model eye and in living human eye. The improvement of imaging fidelity was estimated by reduction of intra-frame distortion of retinal images acquired in the living human eyes with frame rates at 30 frames/second (FPS), 100 FPS, and 200 FPS. Results: The device produced retinal image with cellular level resolution at 200 FPS with a digitization of 512×512 pixels/frame in the living human eye. Cone photoreceptors in the central fovea and rod photoreceptors near the fovea were resolved in three human subjects in normal chorioretinal health. Compared with retinal images acquired at 30 FPS, the intra-frame distortion in images taken at 200 FPS was reduced by 50.9% to 79.7%. Conclusions: We demonstrated the feasibility of acquiring high resolution retinal images in the living human eye at a speed that minimizes retinal motion artifact. This device may facilitate research involving subjects with nystagmus or unsteady fixation due to central vision loss. [ABSTRACT FROM AUTHOR]

Recently, brain-computer interfaces (BCIs) based on visual evoked potentials (VEPs) have been shown to achieve remarkable communication speeds. As they use electroencephalography (EEG) as non-invasive method for recording neural signals, the application of gel-based EEG is time-consuming and cumbersome. In order to achieve a more user-friendly system, this work explores the usability of dry EEG electrodes with a VEP-based BCI. While the results show a high variability between subjects, they also show that communication speeds of more than 100 bit/min are possible using dry EEG electrodes. To reduce performance variability and deal with the lower signal-to-noise ratio of the dry EEG electrodes, an averaging method and a dynamic stopping method were introduced to the BCI system. Those changes were shown to improve performance significantly, leading to an average classification accuracy of 76% with an average communication speed of 46 bit/min, which is equivalent to a writing speed of 8.8 error-free letters per minute. Although the BCI system works substantially better with gel-based EEG, dry EEG electrodes are more user-friendly and still allow high-speed BCI communication. [ABSTRACT FROM AUTHOR]

Magnetic Particle Imaging (MPI) is able to provide high temporal and good spatial resolution, high signal-to-noise ratio and sensitivity. Furthermore, it is a truly quantitative method as its signal strength is proportional to the concentration of its tracer, superparamagnetic iron oxide nanoparticles (SPIOs). Because of that, MPI is proposed to be a promising future method for cardiovascular imaging. Here, an interesting application may be the quantification of vascular pathologies like stenosis by utilizing the proportionality of the SPIO concentration and the MPI signal strength. In this study, the feasibility of MPI based stenosis quantification is evaluated based on this application scenario. Nine different stenosis phantoms with a normal diameter of 10 mm each and different stenoses of 1–9 mm and ten reference phantoms with a straight diameter of 1–10 mm were filled with a 1% Resovist dilution and measured in a preclinical MPI-demonstrator. The MPI signal intensities of the reference phantoms were compared to each other and the change of signal intensity within each stenosis phantom was used to calculate the degree of stenosis. These values were then compared to the known diameters of each phantom. As a second measurement, the 5 mm stenosis phantom was used for a serial dilution measurement down to a Resovist dilution of 1:3200 (0.031%), which is lower than a first pass blood concentration of a Resovist bolus in the peripheral arteries of an average adult human of at least about 1:1000. The correlation of the stenosis values based on MPI signal intensity measurements and based on the known diameters showed a very good agreement, proving the high precision of quantitative MPI in this regard. [ABSTRACT FROM AUTHOR]

Recognizing speech in adverse listening conditions is a significant cognitive, perceptual, and linguistic challenge, especially for children. Prior studies have yielded mixed results on the impact of bilingualism on speech perception in noise. Methodological variations across studies make it difficult to converge on a conclusion regarding the effect of bilingualism on speech-in-noise performance. Moreover, there is a dearth of speech-in-noise evidence for bilingual children who learn two languages simultaneously. The aim of the present study was to examine the extent to which various adverse listening conditions modulate differences in speech-in-noise performance between monolingual and simultaneous bilingual children. To that end, sentence recognition was assessed in twenty-four school-aged children (12 monolinguals; 12 simultaneous bilinguals, age of English acquisition ≤ 3 yrs.). We implemented a comprehensive speech-in-noise battery to examine recognition of English sentences across different modalities (audio-only, audiovisual), masker types (steady-state pink noise, two-talker babble), and a range of signal-to-noise ratios (SNRs; 0 to -16 dB). Results revealed no difference in performance between monolingual and simultaneous bilingual children across each combination of modality, masker, and SNR. Our findings suggest that when English age of acquisition and socioeconomic status is similar between groups, monolingual and bilingual children exhibit comparable speech-in-noise performance across a range of conditions analogous to everyday listening environments. [ABSTRACT FROM AUTHOR]

Purpose: To design, construct and validate radiofrequency (RF) transmit and receive phased array coils for high-resolution visual cortex imaging at 7 Tesla. Methods: A 4 channel transmit and 16 channel receive array was constructed on a conformal polycarbonate former. Transmit field efficiency and homogeneity were simulated and validated, along with the Specific Absorption Rate, using mapping techniques and electromagnetic simulations. Receiver signal-to-noise ratio (SNR), temporal SNR (tSNR) across EPI time series, g-factors for accelerated imaging and noise correlations were evaluated and compared with a commercial 32 channel whole head coil. The performance of the coil was further evaluated with human subjects through functional MRI (fMRI) studies at standard and submillimeter resolutions of upto 0.8mm isotropic. Results: The transmit and receive sections were characterized using bench tests and showed good interelement decoupling, preamplifier decoupling and sample loading. SNR for the 16 channel coil was ∼ 1.5 times that of the commercial coil in the human occipital lobe, and showed better g-factor values for accelerated imaging. fMRI tests conducted showed better response to Blood Oxygen Level Dependent (BOLD) activation, at resolutions of 1.2mm and 0.8mm isotropic. Conclusion: The 4 channel phased array transmit coil provides homogeneous excitation across the visual cortex, which, in combination with the dual row 16 channel receive array, makes for a valuable research tool for high resolution anatomical and functional imaging of the visual cortex at 7T. [ABSTRACT FROM AUTHOR]

Purpose: There is an increasing need for small animal in vivo imaging in murine orthotopic glioma models. Because dedicated small animal scanners are not available ubiquitously, the applicability of a clinical CT scanner for visualization and measurement of intracerebrally growing glioma xenografts in living mice was validated. Materials and Methods: 2.5x106 U87MG cells were orthotopically implanted in NOD/SCID/ᵞc-/- mice (n = 9). Mice underwent contrast-enhanced (300 μl Iomeprol i.v.) imaging using a micro-CT (80 kV, 75 μAs, 360° rotation, 1,000 projections, scan time 33 s, resolution 40 x 40 x 53 μm) and a clinical CT scanner (4-row multislice detector; 120 kV, 150 mAs, slice thickness 0.5 mm, feed rotation 0.5 mm, resolution 98 x 98 x 500 μm). Mice were sacrificed and the brain was worked up histologically. In all modalities tumor volume was measured by two independent readers. Contrast-to-noise ratio (CNR) and Signal-to-noise ratio (SNR) were measured from reconstructed CT-scans (0.5 mm slice thickness; n = 18). Results: Tumor volumes (mean±SD mm3) were similar between both CT-modalities (micro-CT: 19.8±19.0, clinical CT: 19.8±18.8; Wilcoxon signed-rank test p = 0.813). Moreover, between reader analyses for each modality showed excellent agreement as demonstrated by correlation analysis (Spearman-Rho >0.9; p<0.01 for all correlations). Histologically measured tumor volumes (11.0±11.2) were significantly smaller due to shrinkage artifacts (p<0.05). CNR and SNR were 2.1±1.0 and 1.1±0.04 for micro-CT and 23.1±24.0 and 1.9±0.7 for the clinical CTscanner, respectively. Conclusion: Clinical CT scanners may reliably be used for in vivo imaging and volumetric analysis of brain tumor growth in mice. [ABSTRACT FROM AUTHOR]

The aims of this study were to compare the image noise and quality of coronary computed tomographic angiography (CCTA) at 80 kVp with knowledge-based iterative model reconstruction (IMR) to those of CCTA at 100 kVp with hybrid iterative reconstruction (IR), and to evaluate the feasibility of a low-dose radiation protocol with IMR. Thirty subjects who underwent prospective electrocardiogram-gating CCTA at 80 kVp, 150 mAs, and IMR (Group A), and 30 subjects with 100 kVp, 150 mAs, and hybrid IR (Group B) were retrospectively enrolled after sample-size calculation. A BMI of less than 25 kg/m2 was required for inclusion. The attenuation value and image noise of CCTA were measured and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated at the proximal right coronary artery and left main coronary artery. The image noise was analyzed using a non-inferiority test. The CCTA images were qualitatively evaluated using a four-point scale. The radiation dose was significantly lower in Group A than Group B (0.69 ± 0.08 mSv vs. 1.39 ± 0.15 mSv, p < 0.001). The attenuation values were higher in Group A than Group B (p < 0.001). The SNR and CNR in Group A were higher than those of Group B. The image noise of Group A was non-inferior to that of Group B. Qualitative image quality of Group A was better than that of Group B (3.6 vs. 3.4, p = 0.017). CCTA at 80 kVp with IMR could reduce the radiation dose by about 50%, with non-inferior image noise and image quality than those of CCTA at 100 kVp with hybrid IR. [ABSTRACT FROM AUTHOR]

Magnetoencephalography (MEG) is a sophisticated tool which yields rich information on the spatial, spectral and temporal signatures of human brain function. Despite unique potential, MEG is limited by a low signal-to-noise ratio (SNR) which is caused by both the inherently small magnetic fields generated by the brain, and the scalp-to-sensor distance. The latter is limited in current systems due to a requirement for pickup coils to be cryogenically cooled. Recent work suggests that optically-pumped magnetometers (OPMs) might be a viable alternative to superconducting detectors for MEG measurement. They have the advantage that sensors can be brought to within ~4 mm of the scalp, thus offering increased sensitivity. Here, using simulations, we quantify the advantages of hypothetical OPM systems in terms of sensitivity, reconstruction accuracy and spatial resolution. Our results show that a multi-channel whole-head OPM system offers (on average) a fivefold improvement in sensitivity for an adult brain, as well as clear improvements in reconstruction accuracy and spatial resolution. However, we also show that such improvements depend critically on accurate forward models; indeed, the reconstruction accuracy of our simulated OPM system only outperformed that of a simulated superconducting system in cases where forward field error was less than 5%. Overall, our results imply that the realisation of a viable whole-head multi-channel OPM system could generate a step change in the utility of MEG as a means to assess brain electrophysiological activity in health and disease. However in practice, this will require both improved hardware and modelling algorithms. [ABSTRACT FROM AUTHOR]

Diffusion-weighted Magnetic Resonance Imaging (dMRI) has relevant applications in the microstructural characterization of the spinal cord, especially in neurodegenerative diseases. Animal models have a pivotal role in the study of such diseases; however, in vivo spinal dMRI of small animals entails additional challenges that require a systematical investigation of acquisition parameters. The purpose of this study is to compare three acquisition protocols and identify the scanning parameters allowing a robust estimation of the main diffusion quantities and a good sensitivity to neurodegeneration in the mouse spinal cord. For all the protocols, the signal-to-noise and contrast-to noise ratios and the mean value and variability of Diffusion Tensor metrics were evaluated in healthy controls. For the estimation of fractional anisotropy less variability was provided by protocols with more diffusion directions, for the estimation of mean, axial and radial diffusivity by protocols with fewer diffusion directions and higher diffusion weighting. Intermediate features (12 directions, b = 1200 s/mm2) provided the overall minimum inter- and intra-subject variability in most cases. In order to test the diagnostic sensitivity of the protocols, 7 G93A-SOD1 mice (model of amyotrophic lateral sclerosis) at 10 and 17 weeks of age were scanned and the derived diffusion parameters compared with those estimated in age-matched healthy animals. The protocols with an intermediate or high number of diffusion directions provided the best differentiation between the two groups at week 17, whereas only few local significant differences were highlighted at week 10. According to our results, a dMRI protocol with an intermediate number of diffusion gradient directions and a relatively high diffusion weighting is optimal for spinal cord imaging. Further work is needed to confirm these results and for a finer tuning of acquisition parameters. Nevertheless, our findings could be important for the optimization of acquisition protocols for preclinical and clinical dMRI studies on the spinal cord. [ABSTRACT FROM AUTHOR]

Functional multineuron calcium imaging (fMCI) provides a useful experimental platform to simultaneously capture the spatiotemporal patterns of neuronal activity from a large cell population in situ. However, fMCI often suffers from low signal-to-noise ratios (S/N). The main factor that causes the low S/N is shot noise that arises from photon detectors. Here, we propose a new denoising procedure, termed the Okada filter, which is designed to reduce shot noise under low S/N conditions, such as fMCI. The core idea of the Okada filter is to replace the fluorescence intensity value of a given frame time with the average of two values at the preceding and following frames unless the focused value is the median among these three values. This process is iterated serially throughout a time-series vector. In fMCI data of hippocampal neurons, the Okada filter rapidly reduces background noise and significantly improves the S/N. The Okada filter is also applicable for reducing shot noise in electrophysiological data and photographs. Finally, the Okada filter can be described using a single continuous differentiable equation based on the logistic function and is thus mathematically tractable. [ABSTRACT FROM AUTHOR]