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Miguel P Eckstein

Publications and source records attributed to Miguel P Eckstein.

At least 19 recordsLinked to original sources

Limited flexibility in the filter underlying saccadic targeting.

The choice of where to look in a visual scene depends on visual processing of information from potential target locations. We examined to what extent the sampling window, or filter, underlying saccadic eye movements is under flexible control and adjusted to the behavioural task demands. Observers performed a contrast discrimination task with systematic variations in the spatial scale and location of the visual signals: small (sigma=0.175 degrees ) or large (sigma=0.8 degrees ) Gaussian signals were presented 4.5 degrees , 6 degrees , or 9 degrees away from central fixation. In experiment 1, we measured the accuracy of the first saccade as a function of target contrast. The efficiency of saccadic targeting decreased with increases in both scale and eccentricity. In experiment 2, the filter underlying saccadic targeting was estimated with the classification image method. We found that the filter (1) had a center-surround organisation, even though the signal was Gaussian; (2) was much too small for the large scale items; (3) remained constant up to the largest measured eccentricity of 9 degrees . The filter underlying the decision of where to look is not fixed, and can be adjusted to the task demands. However, there are clear limits to this flexibility. These limits reflect the coding of visual information by early mechanisms, and the extent to which the neural circuitry involved in programming saccadic eye movements is able to appropriately weigh and combine the outputs from these mechanisms.

Choice Behavior↗

Classification images for detection, contrast discrimination, and identification tasks with a common ideal observer.

We consider three simple forced-choice visual tasks--detection, contrast discrimination, and identification--in Gaussian white noise. The three tasks are designed so that the difference signal in all three cases is the same difference-of-Gaussians (DOG) profile. The distribution of the image noise implies that the ideal observer uses the same DOG filter to perform all three tasks. But do human observers also use the same visual strategy to perform these tasks? We use classification image analysis to evaluate the visual strategies of human observers. We find significantly different subject classification images across the three tasks. The domain of greatest variability appears to be low spatial frequencies [<5 cycles per degree (cpd)]. In this range, we find frequency enhancement in the detection task, and frequency suppression and reversal in the contrast discrimination task. In the identification task, subject classification images agree reasonably well with the ideal observer filter. We evaluate the effect of nonlinear transducers and intrinsic spatial uncertainty to explain divergence from the ideal observer found in detection and contrast discrimination tasks.

Choice Behavior↗

The effect of nonlinear human visual system components on performance of a channelized Hotelling observer in structured backgrounds.

Linear model observers based on statistical decision theory have been used successfully to predict human visual detection of aperiodic signals in a variety of noisy backgrounds. However, some models have included nonlinearities such as a transducer or nonlinear decision rules to handle intrinsic uncertainty. In addition, masking models used to predict human visual detection of signals superimposed on one of two identical backgrounds (masks) usually include a number of nonlinear components in the channels that reflect properties of the firing of cells in the primary visual cortex (V1). The effect of these nonlinearities on the ability of linear model observers to predict human signal detection in real patient structured backgrounds is unknown. We evaluate the effect of including different nonlinear human visual system components into a linear channelized Hotelling observer (CHO) using a signal known exactly but variable (SKEV) task. In particular, we evaluate whether the rank order of two compression algorithms (JPEG versus JPEG 2000) and two compression encoder settings (JPEG 2000 default versus JPEG 2000 optimized) based on model observer signal detection performance in X-ray coronary angiograms is altered by inclusion of nonlinear components. The results show: 1) the simpler linear CHO model observer outperforms CHO model with the nonlinear components; 2) the rank order of model observer performance for the compression algorithms/parameters does not change when the nonlinear components are included. For the present task and images, the results suggest that the addition of the nonlinearities to a channelized Hotelling model may add complexity to the model observers without great impact on rank order evaluation of image processing and/or acquisition algorithms.

Algorithms↗

Attentional cues in real scenes, saccadic targeting, and Bayesian priors.

Performance finding a target improves when artificial cues direct covert attention to the target's probable location or locations, but how do predictive cues help observers search for objects in real scenes? Controlling for target detectability and retinal eccentricity, we recorded observers' first saccades during search for objects that appeared in expected and unexpected locations within real scenes. As has been found with synthetic images and cues, accuracy of first saccades was significantly higher when the target appeared at an expected location rather than an unexpected location. Observers' saccades with target-absent images make it possible to distinguish two mechanisms that might mediate this effect: limited attentional resources versus differential weighting of information (Bayesian priors). Endpoints of first saccades in target-absent images were significantly closer to the expected than the unexpected locations, a result consistent with the differential-weighting model and inconsistent with limited resources being the sole mechanism underlying the effect.

Attention↗

Adaptive detection mechanisms in globally statistically nonstationary-oriented noise.

Studies have shown that human observers can adapt their detection strategies on the basis of the statistical properties of noisy backgrounds. One common property of such studies is that the backgrounds studied are (or are assumed to be) statistically stationary. Less is known about how humans detect signals in the more complex setting of nonstationary backgrounds. We investigated detection performance in the presence of a globally nonstationary oriented noise background. We controlled for noise-correlation effects by considering a stationary background with a power spectrum matched to the average spectrum of the nonstationary process. Performance of a nonadaptive linear filter that was unable to make use of differences in local statistics yielded constant performance in both the stationary and the nonstationary backgrounds. In contrast, performance of an ideal observer that uses local noise statistics yielded substantially higher (140%) detectability with the nonstationary backgrounds than the stationary ones. Human observers showed significantly higher (33%) detection performance in the nonstationary backgrounds, suggesting that they can adapt their detection mechanisms to the local orientation properties.

Journal Article↗

Spatial profiles of local and nonlocal effects upon contrast detection/discrimination from classification images.

We used classification images (A. J. Ahumada, Jr., & J. Lovell, 1971) to estimate the perceptual filter in a task designed to assess both local and nonlocal effects upon contrast detection/discrimination. Three observers performed a yes/no detection or discrimination task of a uniform circular decrement (radius = 0.68 deg) near threshold presented for 100 to 400 ms. Stimuli were presented in ring image noise that either covered the signal and an annular surrounding area (out to 1.36 deg), or only the surrounding annular area (out to 1.36 deg). Both the signal and the annular surround appeared on a uniform background. With ring noise over both the signal and surround, the amplitudes of the classification images in the signal area decreased as radial distance increased from the signal/surround border, and no effect of the surround was found. With ring noise only in the surround, classification images indicated noncontiguous effects at both the signal/surround border (local) and the surround/background border (nonlocal). The spatial extents of the nonlocal effects (< 0.07 deg) were smaller than local effects (0.25 deg), whereas the peak amplitudes of the local and nonlocal effects were comparable. These results suggest that the nonlocal effects were smaller than the local effects, and that the smaller effects would be due to smaller effective areas, as opposed to smaller amplitudes over the same area. Little or no change was found in the classification images across stimulus duration, suggesting that both the local and nonlocal processes found in this study were completed within 100 ms.

Adult↗

Task-based model/human observer evaluation of SPIHT wavelet compression with human visual system-based quantization.

RATIONALE AND OBJECTIVE: The set partitioning in hierarchical trees (SPIHT) wavelet image compression algorithm with the human visual system (HVS) quantization matrix was investigated using x-ray coronary angiograms. We tested whether the HVS quantization matrix for the SPIHT wavelet compression improved computer model/human observer performance in a detection task with variable signals compared to performance with the default quantization matrix. We also tested the hypothesis of whether evaluating the rank order of the two quantization matrices (HVS versus default) based on performance of computer model observers in a signal known exactly but variable task (SKEV) generalized to model/human performance in the more clinically realistic signal known statistically task (SKS). MATERIALS AND METHODS: Nine hundred test images were created using real x-ray coronary angiograms as backgrounds and simulated arteries with filling defects (signals). The task for the model and human observer was to detect which one of the four computer simulated arterial segments contained the signal, four alternative-forced-choice (4 AFC). We obtained performance for four model observers (nonprewhitening matched filter with an eye filter, Hotelling, Channelized Hotelling, and Laguerre Gauss Hotelling model observers) for both the SKEV and SKS tasks with images compressed with and without the HVS quantization matrix. A psychophysical study measured performance from three human observers for the same conditions and tasks as the model observers. RESULTS: Performance for all four model observers improved with the use of the HVS quantization scheme. Improvements ranged from 5% (at compression ratio 7:1) to 50% (at compression ratio 30:1) for both the SKEV and SKS tasks. Human observer performance improvement averaged across observers ranged from 6% (at compression ratio 7:1) to 35% (at compression ratio 30:1) for the SKEV task and from 2% (at compression ratio 7:1) to 38% (at compression ratio 30:1) for the SKS task. Addition of internal noise to the model observers allowed for good prediction of human performance. CONCLUSIONS: Use of the HVS quantization scheme in the SPIHT wavelet compression led to improved model and human observer performance in clinically relevant detection tasks in x-ray coronary angiograms. Model observer performance can be reliably used to predict the human observer performance for the studied tasks as a function of SPIHT wavelet image compression. Our results further confirmed that model observer performance in the computationally more tractable SKEV task can be potentially used as a figure of merit for the more clinically realistic SKS task with real anatomic backgrounds.

Algorithms↗

Perceptual learning through optimization of attentional weighting: human versus optimal Bayesian learner.

Human performance in visual detection, discrimination, identification, and search tasks typically improves with practice. Psychophysical studies suggest that perceptual learning is mediated by an enhancement in the coding of the signal, and physiological studies suggest that it might be related to the plasticity in the weighting or selection of sensory units coding task relevant information (learning through attention optimization). We propose an experimental paradigm (optimal perceptual learning paradigm) to systematically study the dynamics of perceptual learning in humans by allowing comparisons to that of an optimal Bayesian algorithm and a number of suboptimal learning models. We measured improvement in human localization (eight-alternative forced-choice with feedback) performance of a target randomly sampled from four elongated Gaussian targets with different orientations and polarities and kept as a target for a block of four trials. The results suggest that the human perceptual learning can occur within a lapse of four trials (<1 min) but that human learning is slower and incomplete with respect to the optimal algorithm (23.3% reduction in human efficiency from the 1st-to-4th learning trials). The greatest improvement in human performance, occurring from the 1st-to-2nd learning trial, was also present in the optimal observer, and, thus reflects a property inherent to the visual task and not a property particular to the human perceptual learning mechanism. One notable source of human inefficiency is that, unlike the ideal observer, human learning relies more heavily on previous decisions than on the provided feedback, resulting in no human learning on trials following a previous incorrect localization decision. Finally, the proposed theory and paradigm provide a flexible framework for future studies to evaluate the optimality of human learning of other visual cues and/or sensory modalities.

Adult↗

The time course of visual information accrual guiding eye movement decisions.

Saccadic eye movements are the result of neural decisions about where to move the eyes. These decisions are based on visual information accumulated before the saccade; however, during an approximately 100-ms interval immediately before the initiation of an eye movement, new visual information cannot influence the decision. Does the brain simply ignore information presented during this brief interval or is the information used for the subsequent saccade? Our study examines how and when the brain integrates visual information through time to drive saccades during visual search. We introduce a new technique, saccade-contingent reverse correlation, that measures the time course of visual information accrual driving the first and second saccades. Observers searched for a contrast-defined target among distractors. Independent contrast noise was added to the target and distractors every 25 ms. Only noise presented in the time interval in which the brain accumulates information will influence the saccadic decisions. Therefore, we can retrieve the time course of saccadic information accrual by averaging the time course of the noise, aligned to saccade initiation, across all trials with saccades to distractors. Results show that before the first saccade, visual information is being accumulated simultaneously for the first and second saccades. Furthermore, information presented immediately before the first saccade is not used in making the first saccadic decision but instead is stored and used by the neural processes driving the second saccade.

Humans↗

The footprints of visual attention during search with 100% valid and 100% invalid cues.

Human performance during visual search typically improves when spatial cues indicate the possible target locations. In many instances, the performance improvement is quantitatively predicted by a Bayesian or quasi-Bayesian observer in which visual attention simply selects the information at the cued locations without changing the quality of processing or sensitivity and ignores the information at the uncued locations. Aside from the general good agreement between the effect of the cue on model and human performance, there has been little independent confirmation that humans are effectively selecting the relevant information. In this study, we used the classification image technique to assess the effectiveness of spatial cues in the attentional selection of relevant locations and suppression of irrelevant locations indicated by spatial cues. Observers searched for a bright target among dimmer distractors that might appear (with 50% probability) in one of eight locations in visual white noise. The possible target location was indicated using a 100% valid box cue or seven 100% invalid box cues in which the only potential target locations was uncued. For both conditions, we found statistically significant perceptual templates shaped as differences of Gaussians at the relevant locations with no perceptual templates at the irrelevant locations. We did not find statistical significant differences between the shapes of the inferred perceptual templates for the 100% valid and 100% invalid cues conditions. The results confirm the idea that during search visual attention allows the observer to effectively select relevant information and ignore irrelevant information. The results for the 100% invalid cues condition suggests that the selection process is not drawn automatically to the cue but can be under the observers' voluntary control.

Attention↗

Automated optimization of JPEG 2000 encoder options based on model observer performance for detecting variable signals in X-ray coronary angiograms.

Image compression is indispensable in medical applications where inherently large volumes of digitized images are presented. JPEG 2000 has recently been proposed as a new image compression standard. The present recommendations on the choice of JPEG 2000 encoder options were based on nontask-based metrics of image quality applied to nonmedical images. We used the performance of a model observer [non-prewhitening matched filter with an eye filter (NPWE)] in a visual detection task of varying signals [signal known exactly but variable (SKEV)] in X-ray coronary angiograms to optimize JPEG 2000 encoder options through a genetic algorithm procedure. We also obtained the performance of other model observers (Hotelling, Laguerre-Gauss Hotelling, channelized-Hotelling) and human observers to evaluate the validity of the NPWE optimized JPEG 2000 encoder settings. Compared to the default JPEG 2000 encoder settings, the NPWE-optimized encoder settings improved the detection performance of humans and the other three model observers for an SKEV task. In addition, the performance also was improved for a more clinically realistic task where the signal varied from image to image but was not known a priori to observers [signal known statistically (SKS)]. The highest performance improvement for humans was at a high compression ratio (e.g., 30:1) which resulted in approximately a 75% improvement for both the SKEV and SKS tasks.

Algorithms↗

Evaluation of JPEG 2000 encoder options: human and model observer detection of variable signals in X-ray coronary angiograms.

Previous studies have evaluated the effect of the new still image compression standard JPEG 2000 using nontask based image quality metrics, i.e., peak-signal-to-noise-ratio (PSNR) for nonmedical images. In this paper, the effect of JPEG 2000 encoder options was investigated using the performance of human and model observers (nonprewhitening matched filter with an eye filter, square-window Hotelling, Laguerre-Gauss Hotelling and channelized Hotelling model observer) for clinically relevant visual tasks. Two tasks were investigated: the signal known exactly but variable task (SKEV) and the signal known statistically task (SKS). Test images consisted of real X-ray coronary angiograms with simulated filling defects (signals) inserted in one of the four simulated arteries. The signals varied in size and shape. Experimental results indicated that the dependence of task performance on the JPEG 2000 encoder options was similar for all model and human observers. Model observer performance in the more tractable and computationally economic SKEV task can be used to reliably estimate performance in the complex but clinically more realistic SKS task. JPEG 2000 encoder settings different from the default ones resulted in greatly improved model and human observer performance in the studied clinically relevant visual tasks using real angiography backgrounds.

Algorithms↗

Search for lesions in mammograms: statistical characterization of observer responses.

We investigate human performance for visually detecting simulated microcalcifications and tumors embedded in x-ray mammograms as a function of signal contrast and the number of possible signal locations. Our results show that performance degradation with an increasing number of locations is well approximated by signal detection theory (SDT) with the usual Gaussian assumption. However, more stringent statistical analysis finds a departure from Gaussian assumptions for the detection of microcalcifications. We investigated whether these departures from the SDT Gaussian model could be accounted for by an increase in human internal response correlations arising from the image-pixel correlations present in 1/f spectrum backgrounds and/or observer internal response distributions that departed from the Gaussian assumption. Results were consistent with a departure from the Gaussian response distributions and suggested that the human observer internal responses were more compact than the Gaussian distribution. Finally, we conducted a free search experiment where the signal could appear anywhere within the image. Results show that human performance in a multiple-alternative forced-choice experiment can be used to predict performance in the clinically realistic free search experiment when the investigator takes into account the search area and the observers' inherent spatial imprecision to localize the targets.

Female↗

Signal detection theory applied to three visual search tasks--identification, yes/no detection and localization.

Adding distracters to a display impairs performance on visual tasks (i.e. the set-size effect). While keeping the display characteristics constant, we investigated this effect in three tasks: 2 target identification, yes-no detection with 2 targets, and 8-alternative localization. A Signal Detection Theory (SDT) model, tailored for each task, accounts for the set-size effects observed in identification and localization tasks, and slightly under-predicts the set-size effect in a detection task. Given that sensitivity varies as a function of spatial frequency (SF), we measured performance in each of these three tasks in neutral and peripheral precue conditions for each of six spatial frequencies (0.5-12 cpd). For all spatial frequencies tested, performance on the three tasks decreased as set size increased in the neutral precue condition, and the peripheral precue reduced the effect. Larger set-size effects were observed at low SFs in the identification and localization tasks. This effect can be described using the SDT model, but was not predicted by it. For each of these tasks we also established the extent to which covert attention modulates performance across a range of set sizes. A peripheral precue substantially diminished the set-size effect and improved performance, even at set size 1. These results provide support for distracter exclusion, and suggest that signal enhancement may also be a mechanism by which covert attention can impose its effect.

Attention↗

Comparison of two weighted integration models for the cueing task: linear and likelihood.

In a task in which the observer must detect a signal at two locations, presenting a precue that predicts the location of a signal leads to improved performance with a valid cue (signal location matches the cue), compared to an invalid cue (signal location does not match the cue). The cue validity effect has often been explained with a limited capacity attentional mechanism improving the perceptual quality at the cued location. Alternatively, the cueing effect can also be explained by unlimited capacity models that assume a weighted combination of noisy responses across the two locations. We compare two weighted integration models, a linear model and a sum of weighted likelihoods model based on a Bayesian observer. While qualitatively these models are similar, quantitatively they predict different cue validity effects as the signal-to-noise ratios (SNR) increase. To test these models, 3 observers performed in a cued discrimination task of Gaussian targets with an 80% valid precue across a broad range of SNR's. Analysis of a limited capacity attentional switching model was also included and rejected. The sum of weighted likelihoods model best described the psychophysical results, suggesting that human observers approximate a weighted combination of likelihoods, and not a weighted linear combination.

Adult↗

Saccadic and perceptual performance in visual search tasks. I. Contrast detection and discrimination.

Humans use saccadic eye movements when they search for visual targets. We investigated the relationship between the visual processing used by saccades and perception during search by comparing saccadic and perceptual decisions under conditions in which each had access to equal visual information. We measured the accuracy of perceptual judgments and of the first search saccade over a wide range of target saliences [signal-to-noise ratios (SNRs)] in both a contrast-detection and a contrast-discrimination task. We found that saccadic and perceptual performances (1) were similar across SNRs, (2) showed similar task-dependent differences, and (3) were well described by a model based on signal detection theory that explicitly includes observer uncertainty [M. P. Eckstein et al., J. Opt. Soc. Am. A 14, 2406 (1997)1]. Our results demonstrate that the accuracy of the first saccade provides much information about the observer's perceptual state at the time of the saccadic decision and provide evidence that saccades and perception use similar visual processing mechanisms for contrast detection and discrimination.

Adult↗

Saccadic and perceptual performance in visual search tasks. II. Letter discrimination.

Can the oculomotor system use shape cues to guide search saccades? Observers searched for target letters (D, U, or X) among distractors (the letter O in the discrimination task and blank locations in the detection task) in Gaussian white noise. We measured the accuracy of first saccadic responses on each trial and perceptual (i.e., button-press) responses in separate trials with the stimulus duration chosen so that the saccadic and perceptual processing times were matched. We calculated the relative efficiency of saccadic decisions compared with perceptual decisions, eta(rel) = (d'(sac)/d'(per))2. Relative efficiency was low but consistently greater than zero in discrimination tasks (15% +/- 6%) and high in detection tasks (60% +/- 10%). We conclude that the saccadic targeting system can use shape cues, but less efficiently than the perceptual system can.

Adult↗

An ideal observer with channels versus feature-independent processing of spatial frequency and orientation in visual search performance.

An influential assumption for the front end of models in vision, visual search, and object recognition is an analysis of independent features that correspond to basic image properties, such as motion, shape, and color. Empirically, one common test of independent features (a cue-summation study) measures performance with increasing available cues or features, with improving performance leading to conclusions of summation across independent features. In a study by Shimozaki et al. [J. Vision 2, 354-370 (2002)], both ideal and human observers showed no summation with large stimulus differences, in contrast to independent-feature models and suggesting that stimulus information (as assessed by an ideal observer) might affect cue-summation studies. Extending the previous summation study, observers performed a visual search of four Gabors differing in only orientation, only spatial frequency, or both orientation and spatial frequency, across a range of target-distractor differences. An ideal observer underpredicted human summation for small differences, whereas the independent-orientation and spatial-frequency feature models overpredicted human summation for large differences. An ideal observer with channels jointly tuned to spatial frequency and orientation predicted human performance across both small and large target-distractor differences.

Cues↗