Learning-induced plasticity in auditory spatial representations revealed by electrical neuroimaging.

Auditory spatial representations are likely encoded at a population level within human auditory cortices. We investigated learning-induced plasticity of spatial discrimination in healthy subjects using auditory-evoked potentials (AEPs) and electrical neuroimaging analyses. Stimuli were 100 ms white-noise bursts lateralized with varying interaural time differences. In three experiments, plasticity was induced with 40 min of discrimination training. During training, accuracy significantly improved from near-chance levels to approximately 75%. Before and after training, AEPs were recorded to stimuli presented passively with a more medial sound lateralization outnumbering a more lateral one (7:1). In experiment 1, the same lateralizations were used for training and AEP sessions. Significant AEP modulations to the different lateralizations were evident only after training, indicative of a learning-induced mismatch negativity (MMN). More precisely, this MMN at 195-250 ms after stimulus onset followed from differences in the AEP topography to each stimulus position, indicative of changes in the underlying brain network. In experiment 2, mirror-symmetric locations were used for training and AEP sessions; no training-related AEP modulations or MMN were observed. In experiment 3, the discrimination of trained plus equidistant untrained separations was tested psychophysically before and 0, 6, 24, and 48 h after training. Learning-induced plasticity lasted <6 h, did not generalize to untrained lateralizations, and was not the simple result of strengthening the representation of the trained lateralizations. Thus, learning-induced plasticity of auditory spatial discrimination relies on spatial comparisons, rather than a spatial anchor or a general comparator. Furthermore, cortical auditory representations of space are dynamic and subject to rapid reorganization.

Ambient seismic noise monitoring of a clay landslide: Toward failure prediction

Given that clay-rich landslides may become mobilized, leading to rapid mass movements (earthflows and debris flows), they pose critical problems in risk management worldwide. The most widely proposed mechanism leading to such flow-like movements is the increase in water pore pressure in the sliding mass, generating partial or complete liquefaction. This solid-to-liquid transition results in a dramatic reduction of mechanical rigidity in the liquefied zones, which could be detected by monitoring shear wave velocity variations. With this purpose in mind, the ambient seismic noise correlation technique has been applied to measure the variation in the seismic surface wave velocity in the Pont Bourquin landslide (Swiss Alps). This small but active composite earthslide-earthflow was equipped with continuously recording seismic sensors during spring and summer 2010. An earthslide of a few thousand cubic meters was triggered in mid-August 2010, after a rainy period. This article shows that the seismic velocity of the sliding material, measured from daily noise correlograms, decreased continuously and rapidly for several days prior to the catastrophic event. From a spectral analysis of the velocity decrease, it was possible to determine the location of the change at the base of the sliding layer. These results demonstrate that ambient seismic noise can be used to detect rigidity variations before failure and could potentially be used to predict landslides.

Dosimetric comparison of different treatment modalities for stereotactic radiosurgery of arteriovenous malformations and acoustic neuromas.

PURPOSE: We investigated the influence of beam modulation on treatment planning by comparing four available stereotactic radiosurgery (SRS) modalities: Gamma-Knife-Perfexion, Novalis-Tx Dynamic-Conformal-Arc (DCA) and Dynamic-Multileaf-Collimation-Intensity-Modulated-radiotherapy (DMLC-IMRT), and Cyberknife. MATERIAL AND METHODS: Patients with arteriovenous malformation (n = 10) or acoustic neuromas (n = 5) were planned with different treatment modalities. Paddick conformity index (CI), dose heterogeneity (DH), gradient index (GI) and beam-on time were used as dosimetric indices. RESULTS: Gamma-Knife-Perfexion can achieve high degree of conformity (CI = 0.77 ± 0.04) with limited low-doses (GI = 2.59 ± 0.10) surrounding the inhomogeneous dose distribution (D(H) = 0.84 ± 0.05) at the cost of treatment time (68.1 min ± 27.5). Novalis-Tx-DCA improved this inhomogeneity (D(H) = 0.30 ± 0.03) and treatment time (16.8 min ± 2.2) at the cost of conformity (CI = 0.66 ± 0.04) and Novalis-TX-DMLC-IMRT improved the DCA CI (CI = 0.68 ± 0.04) and inhomogeneity (D(H) = 0.18 ± 0.05) at the cost of low-doses (GI = 3.94 ± 0.92) and treatment time (21.7 min ± 3.4) (p<0.01). Cyberknife achieved comparable conformity (CI = 0.77 ± 0.06) at the cost of low-doses (GI = 3.48 ± 0.47) surrounding the homogeneous (D(H) = 0.22 ± 0.02) dose distribution and treatment time (28.4min±8.1) (p<0.01). CONCLUSIONS: Gamma-Knife-Perfexion will comply with all SRS constraints (high conformity while minimizing low-dose spread). Multiple focal entries (Gamma-Knife-Perfexion and Cyberknife) will achieve better conformity than High-Definition-MLC of Novalis-Tx at the cost of treatment time. Non-isocentric beams (Cyberknife) or IMRT-beams (Novalis-Tx-DMLC-IMRT) will spread more low-dose than multiple isocenters (Gamma-Knife-Perfexion) or dynamic arcs (Novalis-Tx-DCA). Inverse planning and modulated fluences (Novalis-Tx-DMLC-IMRT and CyberKnife) will deliver the most homogeneous treatment. Furthermore, Linac-based systems (Novalis and Cyberknife) can perform image verification at the time of treatment delivery.

Clinical growth rate of acoustic schwannomas: correlation with the growth fraction as defined by the monoclonal antibody ki-67.

The growth rate of acoustic tumors, although slow, varies widely. There may be a continuous spectrum or distinct groups of tumor growth rates. Clinical, audiologic, and conventional histologic tests have failed to shed any light on this problem. Modern immunohistochemical methods may stand a better chance. The Ki-67 monoclonal antibody stains proliferating cells and is used in this study to investigate the growth fraction of 13 skull base schwannomas. The acoustic tumors can be divided into two different growth groups, one with a rate five times the other. The literature is reviewed to see if this differentiation is borne out by the radiologic studies. Distinct growth rates have been reported: one very slow, taking 50 years to reach 1 cm in diameter, a second rate with a diameter increase of 0.2 cm/year, and a third rate five times the second, with a 1.0 cm increase in diameter per year. A fourth group growing at 2.5 cm/year is postulated, but these tumors cannot be followed for long radiologically, since symptoms demand surgical intervention. The clinical implications of these separate growth rates are discussed.

Auditory-somatosensory multisensory interactions are spatially modulated by stimulated body surface and acoustic spectra

Previous research has provided inconsistent results regarding the spatial modulation of auditory-somatosensory interactions. The present study reports three experiments designed to investigate the nature of these interactions in the space close to the head. Human participants made speeded detection responses to unimodal auditory, somatosensory, or simultaneous auditory-somatosensory stimuli. In Experiment 1, electrocutaneous stimuli were presented to either earlobe, while auditory stimuli were presented from the same versus opposite sides, and from one of two distances (20 vs. 70cm) from the participant's head. The results demonstrated a spatial modulation of auditory-somatosensory interactions when auditory stimuli were presented from close to the head. In Experiment 2, electrocutaneous stimuli were delivered to the hands, which were placed either close to or far from the head, while the auditory stimuli were again presented at one of two distances. The results revealed that the spatial modulation observed in Experiment 1 was specific to the particular body part stimulated (head) rather than to the region of space (i.e. around the head) where the stimuli were presented. The results of Experiment 3 demonstrate that sounds that contain high-frequency components are particularly effective in eliciting this auditory-somatosensory spatial effect. Taken together, these findings help to resolve inconsistencies in the previous literature and suggest that auditory-somatosensory multisensory integration is modulated by the stimulated body surface and acoustic spectra of the stimuli presented.

Validity of the acoustic approximation in full-waveform seismic crosshole tomography

Acoustic waveform inversions are an increasingly popular tool for extracting subsurface information from seismic data. They are computationally much more efficient than elastic inversions. Naturally, an inherent disadvantage is that any elastic effects present in the recorded data are ignored in acoustic inversions. We investigate the extent to which elastic effects influence seismic crosshole data. Our numerical modeling studies reveal that in the presence of high contrast interfaces, at which P-to-S conversions occur, elastic effects can dominate the seismic sections, even for experiments involving pressure sources and pressure receivers. Comparisons of waveform inversion results using a purely acoustic algorithm on synthetic data that is either acoustic or elastic, show that subsurface models comprising small low-to-medium contrast (?30%) structures can be successfully resolved in the acoustic approximation. However, in the presence of extended high-contrast anomalous bodies, P-to-S-conversions may substantially degrade the quality of the tomographic images. In particular, extended low-velocity zones are difficult to image. Likewise, relatively small low-velocity features are unresolved, even when advanced a priori information is included. One option for mitigating elastic effects is data windowing, which suppresses later arriving seismic arrivals, such as shear waves. Our tests of this approach found it to be inappropriate because elastic effects are also included in earlier arriving wavetrains. Furthermore, data windowing removes later arriving P-wave phases that may provide critical constraints on the tomograms. Finally, we investigated the extent to which acoustic inversions of elastic data are useful for time-lapse analyses of high contrast engineered structures, for which accurate reconstruction of the subsurface structure is not as critical as imaging differential changes between sequential experiments. Based on a realistic scenario for monitoring a radioactive waste repository, we demonstrated that acoustic inversions of elastic data yield substantial distortions of the tomograms and also unreliable information on trends in the velocity changes.

3D noise power spectrum applied on clinical mdct scanners: effects of reconstruction algorithms and reconstruction filters

The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters.A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed.In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements.The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.

Population receptive field estimates of human auditory cortex.

Here we describe a method for measuring tonotopic maps and estimating bandwidth for voxels in human primary auditory cortex (PAC) using a modification of the population Receptive Field (pRF) model, developed for retinotopic mapping in visual cortex by Dumoulin and Wandell (2008). The pRF method reliably estimates tonotopic maps in the presence of acoustic scanner noise, and has two advantages over phase-encoding techniques. First, the stimulus design is flexible and need not be a frequency progression, thereby reducing biases due to habituation, expectation, and estimation artifacts, as well as reducing the effects of spatio-temporal BOLD nonlinearities. Second, the pRF method can provide estimates of bandwidth as a function of frequency. We find that bandwidth estimates are narrower for voxels within the PAC than in surrounding auditory responsive regions (non-PAC).

Three-Dimensional (3D) Microarchitecture Correlations with 2D Projection Image Gray-Level Variations Assessed by Trabecular Bone Score Using High-Resolution Computed Tomographic Acquisitions: Effects of Resolution and Noise.

The aim of the present study is to determine the level of correlation between the 3-dimensional (3D) characteristics of trabecular bone microarchitecture, as evaluated using microcomputed tomography (μCT) reconstruction, and trabecular bone score (TBS), as evaluated using 2D projection images directly derived from 3D μCT reconstruction (TBSμCT). Moreover, we have evaluated the effects of image degradation (resolution and noise) and X-ray energy of projection on these correlations. Thirty human cadaveric vertebrae were acquired on a microscanner at an isotropic resolution of 93μm. The 3D microarchitecture parameters were obtained using MicroView (GE Healthcare, Wauwatosa, MI). The 2D projections of these 3D models were generated using the Beer-Lambert law at different X-ray energies. Degradation of image resolution was simulated (from 93 to 1488μm). Relationships between 3D microarchitecture parameters and TBSμCT at different resolutions were evaluated using linear regression analysis. Significant correlations were observed between TBSμCT and 3D microarchitecture parameters, regardless of the resolution. Correlations were detected that were strongly to intermediately positive for connectivity density (0.711≤r(2)≤0.752) and trabecular number (0.584≤r(2)≤0.648) and negative for trabecular space (-0.407 ≤r(2)≤-0.491), up to a pixel size of 1023μm. In addition, TBSμCT values were strongly correlated between each other (0.77≤r(2)≤0.96). Study results show that the correlations between TBSμCT at 93μm and 3D microarchitecture parameters are weakly impacted by the degradation of image resolution and the presence of noise.

Tolerance and Relative Utility: Two Proposed Indices for Comparing Change in Clinical Measurement Noise Between Different Populations (Repeatability) or Measurement Methods (Agreement).

Reaching a consensus in terms of interchangeability and utility (i.e., disease detection/monitoring) of a medical device is the eventual aim of repeatability and agreement studies. The aim of the tolerance and relative utility indices described in this report is to provide a methodology to compare change in clinical measurement noise between different populations (repeatability) or measurement methods (agreement), so as to highlight problematic areas. No longitudinal data are required to calculate these indices. Both indices establish a metric of least to most effected across all parameters to facilitate comparison. If validated, these indices may prove useful tools when combining reports and forming the consensus required in the validation process for software updates and new medical devices.

Experience-based Auditory Predictions Modulate Brain Activity to Silence as Do Real Sounds.

Interactions between stimuli's acoustic features and experience-based internal models of the environment enable listeners to compensate for the disruptions in auditory streams that are regularly encountered in noisy environments. However, whether auditory gaps are filled in predictively or restored a posteriori remains unclear. The current lack of positive statistical evidence that internal models can actually shape brain activity as would real sounds precludes accepting predictive accounts of filling-in phenomenon. We investigated the neurophysiological effects of internal models by testing whether single-trial electrophysiological responses to omitted sounds in a rule-based sequence of tones with varying pitch could be decoded from the responses to real sounds and by analyzing the ERPs to the omissions with data-driven electrical neuroimaging methods. The decoding of the brain responses to different expected, but omitted, tones in both passive and active listening conditions was above chance based on the responses to the real sound in active listening conditions. Topographic ERP analyses and electrical source estimations revealed that, in the absence of any stimulation, experience-based internal models elicit an electrophysiological activity different from noise and that the temporal dynamics of this activity depend on attention. We further found that the expected change in pitch direction of omitted tones modulated the activity of left posterior temporal areas 140-200 msec after the onset of omissions. Collectively, our results indicate that, even in the absence of any stimulation, internal models modulate brain activity as do real sounds, indicating that auditory filling in can be accounted for by predictive activity.

Physiological noise in human cerebellar fMRI.

OBJECTIVES: To compare physiological noise contributions in cerebellar and cerebral regions of interest in high-resolution functional magnetic resonance imaging (fMRI) data acquired at 7T, to estimate the need for physiological noise removal in cerebellar fMRI. MATERIALS AND METHODS: Signal fluctuations in high resolution (1 mm isotropic) 7T fMRI data were attributed to one of the following categories: task-induced BOLD changes, slow drift, signal changes correlated with the cardiac and respiratory cycles, signal changes related to the cardiac rate and respiratory volume per unit of time or other. [Formula: see text] values for all categories were compared across regions of interest. RESULTS: In this high-resolution data, signal fluctuations related to the phase of the cardiac cycle and cardiac rate were shown to be significant, but comparable between cerebellar and cerebral regions of interest. However, respiratory related signal fluctuations were increased in the cerebellar regions, with explained variances that were up to 80 % higher than for the primary motor cortex region. CONCLUSION: Even at a millimetre spatial resolution, significant correlations with both cardiac and respiratory RETROICOR components were found in all healthy volunteer data. Therefore, physiological noise correction is highly likely to improve the temporal signal-to-noise ratio (SNR) for cerebellar fMRI at 7T, even at high spatial resolution.

A comprehensive model for quantum noise characterization in digital mammography.

NlmCategory="UNASSIGNED">A version of cascaded systems analysis was developed specifically with the aim of studying quantum noise propagation in x-ray detectors. Signal and quantum noise propagation was then modelled in four types of x-ray detectors used for digital mammography: four flat panel systems, one computed radiography and one slot-scan silicon wafer based photon counting device. As required inputs to the model, the two dimensional (2D) modulation transfer function (MTF), noise power spectra (NPS) and detective quantum efficiency (DQE) were measured for six mammography systems that utilized these different detectors. A new method to reconstruct anisotropic 2D presampling MTF matrices from 1D radial MTFs measured along different angular directions across the detector is described; an image of a sharp, circular disc was used for this purpose. The effective pixel fill factor for the FP systems was determined from the axial 1D presampling MTFs measured with a square sharp edge along the two orthogonal directions of the pixel lattice. Expectation MTFs were then calculated by averaging the radial MTFs over all possible phases and the 2D EMTF formed with the same reconstruction technique used for the 2D presampling MTF. The quantum NPS was then established by noise decomposition from homogenous images acquired as a function of detector air kerma. This was further decomposed into the correlated and uncorrelated quantum components by fitting the radially averaged quantum NPS with the radially averaged EMTF(2). This whole procedure allowed a detailed analysis of the influence of aliasing, signal and noise decorrelation, x-ray capture efficiency and global secondary gain on NPS and detector DQE. The influence of noise statistics, pixel fill factor and additional electronic and fixed pattern noises on the DQE was also studied. The 2D cascaded model and decompositions performed on the acquired images also enlightened the observed quantum NPS and DQE anisotropy.