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SummaryTo expedite the review of semi-automated probability maps of organelles and other features from 3D electron microscopy data we have developed Probability Map Viewer, a Java-based web application that enables the computation and visualization of probability map generation results in near real-time as the data are being collected from the microscope. Probability Map Viewer allows the user to select one or more voxel classifiers, apply them on a sub-region of an active collection, and visualize the results as overlays on the raw data via any web browser using a personal computer or mobile device. Thus, Probability Map Viewer accelerates and informs the image analysis workflow by providing a tool for experimenting with and optimizing dataset-specific segmentation strategies during imaging.Availability and implementationhttps://github.com/crbs/probabilitymapviewer.Contactmellisman@ucsd.edu.Supplementary informationSupplementary data are available at Bioinformatics online.

Perimetry, or visual field test, estimates differential light sensitivity thresholds across many locations in the visual field (e.g., 54 locations in the 24–2 grid). Recent developments have shown that an entire visual field may be relatively accurately reconstructed from measurements of a subset of these locations using a linear regression model. Here, we show that incorporating a dimensionality reduction layer can improve the robustness of this reconstruction. Specifically, we propose to use principal component analysis to transform the training dataset to a lower dimensional representation and then use this representation to reconstruct the visual field. We named our new reconstruction method the transformed-target principal component regression (TTPCR). When trained on a large dataset, our new method yielded results comparable with the original linear regression method, demonstrating that there is no underfitting associated with parameter reduction. However, when trained on a small dataset, our new method used on average 22% fewer trials to reach the same error. Our results suggest that dimensionality reduction techniques can improve the robustness of visual field testing reconstruction algorithms. [ABSTRACT FROM AUTHOR]

Purpose: In this study, the authors sought to quantify the relationships between speech intelligibility (perception) and gaze patterns under different auditory-visual conditions. Method: Eleven subjects listened to low-context sentences spoken by a single talker while viewing the face of one or more talkers on a computer display. Subjects either maintained their gaze at a specific distance (0 degrees, 2.5 degrees, 5 degrees, 10 degrees, and 15 degrees) from the center of the talker's mouth (CTM) or moved their eyes freely on the computer display. Eye movements were monitored with an eye-tracking system, and speech intelligibility was evaluated by the mean percentage of correctly perceived. Results: With a single talker and a fixed point of gaze, speech intelligibility was similar for all fixations within 10 degrees of the CTM. With visual cues from two talker faces and a speech signal from one of the talkers, speech intelligibility was similar to that of a single talker for fixations within 2.5 degrees of the CTM. With natural viewing of a single talker, gaze strategy changed with speech-signal-to-noise ratio (SNR). For low speech-SNR, a strategy that brought the point of gaze directly to within 2.5 degrees of the CTM was used in approximately 80% of trials, whereas in high speech-SNR it was used in only approximately 50% of trials. Conclusions: With natural viewing of a single talker and high speech-SNR, subjects can shift their gaze between points on the talker's face without compromising speech intelligibility. With low-speech SNR, subjects change their gaze patterns to fixate primarily on points that are in close proximity to the talker's mouth. The latter strategy is essential to optimize speech intelligibility in situations where there are simultaneous visual cues from multiple talkers (i.e., when some of the visual cues are distracters). (Contains 7 figures and 1 footnote.)

The goal of this study was to quantitatively describe aspects of coronal tongue movement in different anatomical regions of the tongue. Four normal speakers and a speaker with partial glossectomy read four repetitions of a metronome-paced poem. Their tongue movement was recorded in four coronal planes using two-dimensional B-mode ultrasound imaging. Quantitative indicators of tongue function (total distance travelled and concavity) were calculated. In all participants, it was observed that the centre of the tongue travelled greater distances than the lateral free margins. The tongues of the female speakers F1 and F2 travelled greater distances than those of the males M1 and M2. The greatest distances travelled were observed in the speaker with partial glossectomy G. In three of the participants, the greatest cumulative distances were recorded for the anterior tongue (F1, M1, and G) and in the other two (F2 and M2) in the posterior tongue. The concavity measure illustrated that the posterior tongue showed consistent grooving during connected speech, in all speakers. Flatness or convexity of the tongue was mainly observed in the anterior tongue. The study provides the first quantitative description of coronal tongue movement in a complex speech passage. Future research will have to further examine the effects of gender and orofacial morphology on the coronal shape and movement of the tongue. (Contains 2 tables and 4 figures.)

We propose a new application of the adaptive chirplet transform that involves partitioning signals into non-overlapping sequential segments. From these segments, the local time-frequency structures of the signal are estimated by using a four-parameter chirplet decomposition. Entitled the windowed adaptive chirplet transform (windowed ACT), this approach is applied to the analysis of visual evoked potentials (VEPs). It can provide a unified and compact representation of VEPs from the transient buildup to the steady-state portion with less computational cost than its non-windowed counterpart. This paper also details a method to select the optimal window length for signal segmentation. This approach will be useful for long-term signal monitoring as well as for signal feature extraction and data compression. Index Terms--Chirplet transform, optimal window length, short-term changes, time-frequency analysis, visual evoked potentials.

An overview is presented on research conducted in our lab to quantify the underlying principles behind the recognition of temporal patterns. We have been developing a theory based upon pattern matching and time-series analysis, which allows us to model and understand how humans recognize familiar patterns evolving over time and how performance degrades with noise. While our studies are primarily scientific in nature, the work has application beyond the elucidation of psychological and physiological mechanisms. We illustrate an application of these ideas to computer-based human identification through gait analysis. This study also illustrates a novel approach to interdisciplinary research by integrating experimental psychology with that of engineering design. Resume Cet article presente un apercu des recherches effectuees dans notre laboratoire en vue de quantifier les principes fondamentaux de la reconnaissance des tendances temporelles. Nous avons elabore une theorie fondee sur l'appariement des tendances et l'analyse des series temporelles, ce qui nous permet de modeliser et de comprendre comment les humains reconnaissent les tendances familieres qui evoluent avec le temps et comment le rendement diminue en raison du bruit. Bien que nos etudes soient surtout de nature scientifique, le travail peut etre applique au-dela de l'eclaircissement des mecanismes psychologique et physiologique. Nous illustrons une application de ces idees pour l'identification genetique informatisee par l'entremise de l'analyse de la demarche. En integrant la psychologie experimentale a celle de la conception technique, cette etude jette aussi un nouvel eclairage sur la recherche multidisciplinaire.

We propose a new approach based upon the adaptive chirplet transform (ACT) to characterize the time-dependent behavior of the visual evoked potential (VEP) from its initial transient portion (tVEP) to the steady-state portion (ssVEP). This approach employs a matching pursuit (MP) algorithm to estimate the chirplets and then a maximum-likelihood estimation (MLE) algorithm to refine the results. The ACT decomposes signals into Gaussian chirplet basis functions with four adjustable parameters, i.e., time-spread, chirp rate, time-center and frequency-center. In this paper, we show how these four parameters can be used to distinguish between the transient and the steady-state phase of the response. We also show that as few as three chirplets are required to represent a VEP response. Compared to decomposition with Gabor logons, a more compact representation can be achieved by using Gaussian chirplets. Finally, we argue that the adaptive chirplet spectrogram gives a superior visualization of VEP signals' time-frequency structures when compared to the conventional spectrogram. Index Terms--Chirplet transform, time-frequency analysis, tVEP and ssVEP, unified representation, visual evoked potentials.

We investigated whether pitch-synchronous neural activity could be recorded in humans, with a natural vowel and a vowel in which the fundamental frequency was suppressed. Small variations of speech periodicity were detected in the evoked responses using a fine structure spectrograph (FSS). A significant response (P [much less than] 0.001) was measured in all seven normal subjects even when the fundamental frequency was suppressed, and it very accurately tracked the acoustic pitch contour (normalized mean absolute error < 0.57%). Small variations in speech periodicity, which humans can detect, are therefore available to the perceptual system as pitch-synchronous neural firing. These findings suggest that the measurement of pitch-evoked responses may be a viable tool for objective speech audiometry. Index Terms--Bioelectric potentials, biomedical signal processing, speech processing, time-frequency analysis.